Computing multiple-output regression quantile regions

Czech Academy of Sciences Publication Activity Database

Paindaveine, D.; Šiman, Miroslav

2012-01-01

Roč. 56, č. 4 (2012), s. 840-853 ISSN 0167-9473 R&D Projects: GA MŠk(CZ) 1M06047 Institutional research plan: CEZ:AV0Z10750506 Keywords : halfspace depth * multiple-output regression * parametric linear programming * quantile regression Subject RIV: BA - General Mathematics Impact factor: 1.304, year: 2012 http://library.utia.cas.cz/separaty/2012/SI/siman-0376413.pdf

Quantile regression theory and applications

CERN Document Server

Davino, Cristina; Vistocco, Domenico

2013-01-01

A guide to the implementation and interpretation of Quantile Regression models This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods. The main focus of this book is to provide the reader with a comprehensivedescription of the main issues concerning quantile regression; these include basic modeling, geometrical interpretation, estimation and inference for quantile regression, as well as issues on validity of the model, diagnostic tools. Each methodological aspect is explored and

Nonuniform sampling by quantiles

Science.gov (United States)

Craft, D. Levi; Sonstrom, Reilly E.; Rovnyak, Virginia G.; Rovnyak, David

2018-03-01

A flexible strategy for choosing samples nonuniformly from a Nyquist grid using the concept of statistical quantiles is presented for broad classes of NMR experimentation. Quantile-directed scheduling is intuitive and flexible for any weighting function, promotes reproducibility and seed independence, and is generalizable to multiple dimensions. In brief, weighting functions are divided into regions of equal probability, which define the samples to be acquired. Quantile scheduling therefore achieves close adherence to a probability distribution function, thereby minimizing gaps for any given degree of subsampling of the Nyquist grid. A characteristic of quantile scheduling is that one-dimensional, weighted NUS schedules are deterministic, however higher dimensional schedules are similar within a user-specified jittering parameter. To develop unweighted sampling, we investigated the minimum jitter needed to disrupt subharmonic tracts, and show that this criterion can be met in many cases by jittering within 25-50% of the subharmonic gap. For nD-NUS, three supplemental components to choosing samples by quantiles are proposed in this work: (i) forcing the corner samples to ensure sampling to specified maximum values in indirect evolution times, (ii) providing an option to triangular backfill sampling schedules to promote dense/uniform tracts at the beginning of signal evolution periods, and (iii) providing an option to force the edges of nD-NUS schedules to be identical to the 1D quantiles. Quantile-directed scheduling meets the diverse needs of current NUS experimentation, but can also be used for future NUS implementations such as off-grid NUS and more. A computer program implementing these principles (a.k.a. QSched) in 1D- and 2D-NUS is available under the general public license.

Boosting structured additive quantile regression for longitudinal childhood obesity data.

Science.gov (United States)

Fenske, Nora; Fahrmeir, Ludwig; Hothorn, Torsten; Rzehak, Peter; Höhle, Michael

2013-07-25

Childhood obesity and the investigation of its risk factors has become an important public health issue. Our work is based on and motivated by a German longitudinal study including 2,226 children with up to ten measurements on their body mass index (BMI) and risk factors from birth to the age of 10 years. We introduce boosting of structured additive quantile regression as a novel distribution-free approach for longitudinal quantile regression. The quantile-specific predictors of our model include conventional linear population effects, smooth nonlinear functional effects, varying-coefficient terms, and individual-specific effects, such as intercepts and slopes. Estimation is based on boosting, a computer intensive inference method for highly complex models. We propose a component-wise functional gradient descent boosting algorithm that allows for penalized estimation of the large variety of different effects, particularly leading to individual-specific effects shrunken toward zero. This concept allows us to flexibly estimate the nonlinear age curves of upper quantiles of the BMI distribution, both on population and on individual-specific level, adjusted for further risk factors and to detect age-varying effects of categorical risk factors. Our model approach can be regarded as the quantile regression analog of Gaussian additive mixed models (or structured additive mean regression models), and we compare both model classes with respect to our obesity data.

Statistical modelling with quantile functions

CERN Document Server

Gilchrist, Warren

2000-01-01

Galton used quantiles more than a hundred years ago in describing data. Tukey and Parzen used them in the 60s and 70s in describing populations. Since then, the authors of many papers, both theoretical and practical, have used various aspects of quantiles in their work. Until now, however, no one put all the ideas together to form what turns out to be a general approach to statistics.Statistical Modelling with Quantile Functions does just that. It systematically examines the entire process of statistical modelling, starting with using the quantile function to define continuous distributions. The author shows that by using this approach, it becomes possible to develop complex distributional models from simple components. A modelling kit can be developed that applies to the whole model - deterministic and stochastic components - and this kit operates by adding, multiplying, and transforming distributions rather than data.Statistical Modelling with Quantile Functions adds a new dimension to the practice of stati...

A Hybrid MCMC Sampler for Unconditional Quantile Based on Influence Function

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El Moctar Laghlal

2018-05-01

Full Text Available In this study, we provide a Bayesian estimation method for the unconditional quantile regression model based on the Re-centered Influence Function (RIF. The method makes use of the dichotomous structure of the RIF and estimates a non-linear probability model by a logistic regression using a Gibbs within a Metropolis-Hastings sampler. This approach performs better in the presence of heavy-tailed distributions. Applied to a nationally-representative household survey, the Senegal Poverty Monitoring Report (2005, the results show that the change in the rate of returns to education across quantiles is substantially lower at the primary level.

Model-based Quantile Regression for Discrete Data

KAUST Repository

Padellini, Tullia; Rue, Haavard

2018-01-01

Quantile regression is a class of methods voted to the modelling of conditional quantiles. In a Bayesian framework quantile regression has typically been carried out exploiting the Asymmetric Laplace Distribution as a working likelihood. Despite

Focused information criterion and model averaging based on weighted composite quantile regression

KAUST Repository

Xu, Ganggang; Wang, Suojin; Huang, Jianhua Z.

2013-01-01

We study the focused information criterion and frequentist model averaging and their application to post-model-selection inference for weighted composite quantile regression (WCQR) in the context of the additive partial linear models. With the non

Flood quantile estimation at ungauged sites by Bayesian networks

Science.gov (United States)

Mediero, L.; Santillán, D.; Garrote, L.

2012-04-01

Estimating flood quantiles at a site for which no observed measurements are available is essential for water resources planning and management. Ungauged sites have no observations about the magnitude of floods, but some site and basin characteristics are known. The most common technique used is the multiple regression analysis, which relates physical and climatic basin characteristic to flood quantiles. Regression equations are fitted from flood frequency data and basin characteristics at gauged sites. Regression equations are a rigid technique that assumes linear relationships between variables and cannot take the measurement errors into account. In addition, the prediction intervals are estimated in a very simplistic way from the variance of the residuals in the estimated model. Bayesian networks are a probabilistic computational structure taken from the field of Artificial Intelligence, which have been widely and successfully applied to many scientific fields like medicine and informatics, but application to the field of hydrology is recent. Bayesian networks infer the joint probability distribution of several related variables from observations through nodes, which represent random variables, and links, which represent causal dependencies between them. A Bayesian network is more flexible than regression equations, as they capture non-linear relationships between variables. In addition, the probabilistic nature of Bayesian networks allows taking the different sources of estimation uncertainty into account, as they give a probability distribution as result. A homogeneous region in the Tagus Basin was selected as case study. A regression equation was fitted taking the basin area, the annual maximum 24-hour rainfall for a given recurrence interval and the mean height as explanatory variables. Flood quantiles at ungauged sites were estimated by Bayesian networks. Bayesian networks need to be learnt from a huge enough data set. As observational data are reduced, a

QRank: a novel quantile regression tool for eQTL discovery.

Science.gov (United States)

Song, Xiaoyu; Li, Gen; Zhou, Zhenwei; Wang, Xianling; Ionita-Laza, Iuliana; Wei, Ying

2017-07-15

Over the past decade, there has been a remarkable improvement in our understanding of the role of genetic variation in complex human diseases, especially via genome-wide association studies. However, the underlying molecular mechanisms are still poorly characterized, impending the development of therapeutic interventions. Identifying genetic variants that influence the expression level of a gene, i.e. expression quantitative trait loci (eQTLs), can help us understand how genetic variants influence traits at the molecular level. While most eQTL studies focus on identifying mean effects on gene expression using linear regression, evidence suggests that genetic variation can impact the entire distribution of the expression level. Motivated by the potential higher order associations, several studies investigated variance eQTLs. In this paper, we develop a Quantile Rank-score based test (QRank), which provides an easy way to identify eQTLs that are associated with the conditional quantile functions of gene expression. We have applied the proposed QRank to the Genotype-Tissue Expression project, an international tissue bank for studying the relationship between genetic variation and gene expression in human tissues, and found that the proposed QRank complements the existing methods, and identifies new eQTLs with heterogeneous effects across different quantile levels. Notably, we show that the eQTLs identified by QRank but missed by linear regression are associated with greater enrichment in genome-wide significant SNPs from the GWAS catalog, and are also more likely to be tissue specific than eQTLs identified by linear regression. An R package is available on R CRAN at https://cran.r-project.org/web/packages/QRank . xs2148@cumc.columbia.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Functional data analysis of generalized regression quantiles

KAUST Repository

Guo, Mengmeng; Zhou, Lan; Huang, Jianhua Z.; Hä rdle, Wolfgang Karl

2013-01-01

Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.

Functional data analysis of generalized regression quantiles

KAUST Repository

Guo, Mengmeng

2013-11-05

Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.

Does the Magnitude of the Link between Unemployment and Crime Depend on the Crime Level? A Quantile Regression Approach

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Horst Entorf

2015-07-01

Full Text Available Two alternative hypotheses – referred to as opportunity- and stigma-based behavior – suggest that the magnitude of the link between unemployment and crime also depends on preexisting local crime levels. In order to analyze conjectured nonlinearities between both variables, we use quantile regressions applied to German district panel data. While both conventional OLS and quantile regressions confirm the positive link between unemployment and crime for property crimes, results for assault differ with respect to the method of estimation. Whereas conventional mean regressions do not show any significant effect (which would confirm the usual result found for violent crimes in the literature, quantile regression reveals that size and importance of the relationship are conditional on the crime rate. The partial effect is significantly positive for moderately low and median quantiles of local assault rates.

Bayesian quantitative precipitation forecasts in terms of quantiles

Science.gov (United States)

Bentzien, Sabrina; Friederichs, Petra

2014-05-01

Ensemble prediction systems (EPS) for numerical weather predictions on the mesoscale are particularly developed to obtain probabilistic guidance for high impact weather. An EPS not only issues a deterministic future state of the atmosphere but a sample of possible future states. Ensemble postprocessing then translates such a sample of forecasts into probabilistic measures. This study focus on probabilistic quantitative precipitation forecasts in terms of quantiles. Quantiles are particular suitable to describe precipitation at various locations, since no assumption is required on the distribution of precipitation. The focus is on the prediction during high-impact events and related to the Volkswagen Stiftung funded project WEX-MOP (Mesoscale Weather Extremes - Theory, Spatial Modeling and Prediction). Quantile forecasts are derived from the raw ensemble and via quantile regression. Neighborhood method and time-lagging are effective tools to inexpensively increase the ensemble spread, which results in more reliable forecasts especially for extreme precipitation events. Since an EPS provides a large amount of potentially informative predictors, a variable selection is required in order to obtain a stable statistical model. A Bayesian formulation of quantile regression allows for inference about the selection of predictive covariates by the use of appropriate prior distributions. Moreover, the implementation of an additional process layer for the regression parameters accounts for spatial variations of the parameters. Bayesian quantile regression and its spatially adaptive extension is illustrated for the German-focused mesoscale weather prediction ensemble COSMO-DE-EPS, which runs (pre)operationally since December 2010 at the German Meteorological Service (DWD). Objective out-of-sample verification uses the quantile score (QS), a weighted absolute error between quantile forecasts and observations. The QS is a proper scoring function and can be decomposed into

Understanding child stunting in India: a comprehensive analysis of socio-economic, nutritional and environmental determinants using additive quantile regression.

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Nora Fenske

Full Text Available BACKGROUND: Most attempts to address undernutrition, responsible for one third of global child deaths, have fallen behind expectations. This suggests that the assumptions underlying current modelling and intervention practices should be revisited. OBJECTIVE: We undertook a comprehensive analysis of the determinants of child stunting in India, and explored whether the established focus on linear effects of single risks is appropriate. DESIGN: Using cross-sectional data for children aged 0-24 months from the Indian National Family Health Survey for 2005/2006, we populated an evidence-based diagram of immediate, intermediate and underlying determinants of stunting. We modelled linear, non-linear, spatial and age-varying effects of these determinants using additive quantile regression for four quantiles of the Z-score of standardized height-for-age and logistic regression for stunting and severe stunting. RESULTS: At least one variable within each of eleven groups of determinants was significantly associated with height-for-age in the 35% Z-score quantile regression. The non-modifiable risk factors child age and sex, and the protective factors household wealth, maternal education and BMI showed the largest effects. Being a twin or multiple birth was associated with dramatically decreased height-for-age. Maternal age, maternal BMI, birth order and number of antenatal visits influenced child stunting in non-linear ways. Findings across the four quantile and two logistic regression models were largely comparable. CONCLUSIONS: Our analysis confirms the multifactorial nature of child stunting. It emphasizes the need to pursue a systems-based approach and to consider non-linear effects, and suggests that differential effects across the height-for-age distribution do not play a major role.

Understanding child stunting in India: a comprehensive analysis of socio-economic, nutritional and environmental determinants using additive quantile regression.

Science.gov (United States)

Fenske, Nora; Burns, Jacob; Hothorn, Torsten; Rehfuess, Eva A

2013-01-01

Most attempts to address undernutrition, responsible for one third of global child deaths, have fallen behind expectations. This suggests that the assumptions underlying current modelling and intervention practices should be revisited. We undertook a comprehensive analysis of the determinants of child stunting in India, and explored whether the established focus on linear effects of single risks is appropriate. Using cross-sectional data for children aged 0-24 months from the Indian National Family Health Survey for 2005/2006, we populated an evidence-based diagram of immediate, intermediate and underlying determinants of stunting. We modelled linear, non-linear, spatial and age-varying effects of these determinants using additive quantile regression for four quantiles of the Z-score of standardized height-for-age and logistic regression for stunting and severe stunting. At least one variable within each of eleven groups of determinants was significantly associated with height-for-age in the 35% Z-score quantile regression. The non-modifiable risk factors child age and sex, and the protective factors household wealth, maternal education and BMI showed the largest effects. Being a twin or multiple birth was associated with dramatically decreased height-for-age. Maternal age, maternal BMI, birth order and number of antenatal visits influenced child stunting in non-linear ways. Findings across the four quantile and two logistic regression models were largely comparable. Our analysis confirms the multifactorial nature of child stunting. It emphasizes the need to pursue a systems-based approach and to consider non-linear effects, and suggests that differential effects across the height-for-age distribution do not play a major role.

Directional quantile regression in R

Czech Academy of Sciences Publication Activity Database

Boček, Pavel; Šiman, Miroslav

2017-01-01

Roč. 53, č. 3 (2017), s. 480-492 ISSN 0023-5954 R&D Projects: GA ČR GA14-07234S Institutional support: RVO:67985556 Keywords : multivariate quantile * regression quantile * halfspace depth * depth contour Subject RIV: BD - Theory of Information OBOR OECD: Applied mathematics Impact factor: 0.379, year: 2016 http://library.utia.cas.cz/separaty/2017/SI/bocek-0476587.pdf

A Quantile Regression Approach to Estimating the Distribution of Anesthetic Procedure Time during Induction.

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Hsin-Lun Wu

Full Text Available Although procedure time analyses are important for operating room management, it is not easy to extract useful information from clinical procedure time data. A novel approach was proposed to analyze procedure time during anesthetic induction. A two-step regression analysis was performed to explore influential factors of anesthetic induction time (AIT. Linear regression with stepwise model selection was used to select significant correlates of AIT and then quantile regression was employed to illustrate the dynamic relationships between AIT and selected variables at distinct quantiles. A total of 1,060 patients were analyzed. The first and second-year residents (R1-R2 required longer AIT than the third and fourth-year residents and attending anesthesiologists (p = 0.006. Factors prolonging AIT included American Society of Anesthesiologist physical status ≧ III, arterial, central venous and epidural catheterization, and use of bronchoscopy. Presence of surgeon before induction would decrease AIT (p < 0.001. Types of surgery also had significant influence on AIT. Quantile regression satisfactorily estimated extra time needed to complete induction for each influential factor at distinct quantiles. Our analysis on AIT demonstrated the benefit of quantile regression analysis to provide more comprehensive view of the relationships between procedure time and related factors. This novel two-step regression approach has potential applications to procedure time analysis in operating room management.

Quantile regression for the statistical analysis of immunological data with many non-detects.

Science.gov (United States)

Eilers, Paul H C; Röder, Esther; Savelkoul, Huub F J; van Wijk, Roy Gerth

2012-07-07

Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced statistical techniques currently available for the analysis of datasets with non-detects can only be used if a small percentage of the data are non-detects. Quantile regression, a generalization of percentiles to regression models, models the median or higher percentiles and tolerates very high numbers of non-detects. We present a non-technical introduction and illustrate it with an implementation to real data from a clinical trial. We show that by using quantile regression, groups can be compared and that meaningful linear trends can be computed, even if more than half of the data consists of non-detects. Quantile regression is a valuable addition to the statistical methods that can be used for the analysis of immunological datasets with non-detects.

Effects of environmental variables on invasive amphibian activity: Using model selection on quantiles for counts

Science.gov (United States)

Muller, Benjamin J.; Cade, Brian S.; Schwarzkoph, Lin

2018-01-01

Many different factors influence animal activity. Often, the value of an environmental variable may influence significantly the upper or lower tails of the activity distribution. For describing relationships with heterogeneous boundaries, quantile regressions predict a quantile of the conditional distribution of the dependent variable. A quantile count model extends linear quantile regression methods to discrete response variables, and is useful if activity is quantified by trapping, where there may be many tied (equal) values in the activity distribution, over a small range of discrete values. Additionally, different environmental variables in combination may have synergistic or antagonistic effects on activity, so examining their effects together, in a modeling framework, is a useful approach. Thus, model selection on quantile counts can be used to determine the relative importance of different variables in determining activity, across the entire distribution of capture results. We conducted model selection on quantile count models to describe the factors affecting activity (numbers of captures) of cane toads (Rhinella marina) in response to several environmental variables (humidity, temperature, rainfall, wind speed, and moon luminosity) over eleven months of trapping. Environmental effects on activity are understudied in this pest animal. In the dry season, model selection on quantile count models suggested that rainfall positively affected activity, especially near the lower tails of the activity distribution. In the wet season, wind speed limited activity near the maximum of the distribution, while minimum activity increased with minimum temperature. This statistical methodology allowed us to explore, in depth, how environmental factors influenced activity across the entire distribution, and is applicable to any survey or trapping regime, in which environmental variables affect activity.

bayesQR: A Bayesian Approach to Quantile Regression

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Dries F. Benoit

2017-01-01

Full Text Available After its introduction by Koenker and Basset (1978, quantile regression has become an important and popular tool to investigate the conditional response distribution in regression. The R package bayesQR contains a number of routines to estimate quantile regression parameters using a Bayesian approach based on the asymmetric Laplace distribution. The package contains functions for the typical quantile regression with continuous dependent variable, but also supports quantile regression for binary dependent variables. For both types of dependent variables, an approach to variable selection using the adaptive lasso approach is provided. For the binary quantile regression model, the package also contains a routine that calculates the fitted probabilities for each vector of predictors. In addition, functions for summarizing the results, creating traceplots, posterior histograms and drawing quantile plots are included. This paper starts with a brief overview of the theoretical background of the models used in the bayesQR package. The main part of this paper discusses the computational problems that arise in the implementation of the procedure and illustrates the usefulness of the package through selected examples.

Elliptical multiple-output quantile regression and convex optimization

Czech Academy of Sciences Publication Activity Database

Hallin, M.; Šiman, Miroslav

2016-01-01

Roč. 109, č. 1 (2016), s. 232-237 ISSN 0167-7152 R&D Projects: GA ČR GA14-07234S Institutional support: RVO:67985556 Keywords : quantile regression * elliptical quantile * multivariate quantile * multiple-output regression Subject RIV: BA - General Mathematics Impact factor: 0.540, year: 2016 http://library.utia.cas.cz/separaty/2016/SI/siman-0458243.pdf

Application of quantile functions for the analysis and comparison of gas pressure balance uncertainties

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Ramnath Vishal

2017-01-01

Full Text Available Traditionally in the field of pressure metrology uncertainty quantification was performed with the use of the Guide to the Uncertainty in Measurement (GUM; however, with the introduction of the GUM Supplement 1 (GS1 the use of Monte Carlo simulations has become an accepted practice for uncertainty analysis in metrology for mathematical models in which the underlying assumptions of the GUM are not valid. Consequently the use of quantile functions was developed as a means to easily summarize and report on uncertainty numerical results that were based on Monte Carlo simulations. In this paper, we considered the case of a piston–cylinder operated pressure balance where the effective area is modelled in terms of a combination of explicit/implicit and linear/non-linear models, and how quantile functions may be applied to analyse results and compare uncertainties from a mixture of GUM and GS1 methodologies.

Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity

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Isao Ishida

2015-01-01

Full Text Available We introduce and investigate some properties of a class of nonlinear time series models based on the moving sample quantiles in the autoregressive data generating process. We derive a test fit to detect this type of nonlinearity. Using the daily realized volatility data of Standard & Poor’s 500 (S&P 500 and several other indices, we obtained good performance using these models in an out-of-sample forecasting exercise compared with the forecasts obtained based on the usual linear heterogeneous autoregressive and other models of realized volatility.

Stock Returns and Risk: Evidence from Quantile

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Thomas C. Chiang

2012-12-01

Full Text Available This paper employs weighted least squares to examine the risk-return relation by applying high-frequency data from four major stock indexes in the US market and finds some evidence in favor of a positive relation between the mean of the excess returns and expected risk. However, by using quantile regressions, we find that the risk-return relation moves from negative to positive as the returns’ quantile increases. A positive risk-return relation is valid only in the upper quantiles. The evidence also suggests that intraday skewness plays a dominant role in explaining the variations of excess returns.

Regionalisation of a distributed method for flood quantiles estimation: Revaluation of local calibration hypothesis to enhance the spatial structure of the optimised parameter

Science.gov (United States)

Odry, Jean; Arnaud, Patrick

2016-04-01

here is to develop a SHYREG evaluation scheme focusing on both local and regional performances. Indeed, it is necessary to maintain the accuracy of at site flood quantiles estimation while identifying a configuration leading to a satisfactory spatial pattern of the calibrated parameter. This ability to be regionalised can be appraised by the association of common regionalisation techniques and split sample validation tests on a set of around 1,500 catchments representing the whole diversity of France physiography. Also, the presence of many nested catchments and a size-based split sample validation make possible to assess the relevance of the calibrated parameter spatial structure inside the largest catchments. The application of this multi-objective evaluation leads to the selection of a version of SHYREG more suitable for regionalisation. References: Arnaud, P., Cantet, P., Aubert, Y., 2015. Relevance of an at-site flood frequency analysis method for extreme events based on stochastic simulation of hourly rainfall. Hydrological Sciences Journal: on press. DOI:10.1080/02626667.2014.965174 Aubert, Y., Arnaud, P., Ribstein, P., Fine, J.A., 2014. The SHYREG flow method-application to 1605 basins in metropolitan France. Hydrological Sciences Journal, 59(5): 993-1005. DOI:10.1080/02626667.2014.902061

Limits theorems for tail processes with applications tointermediate quantile estimation

NARCIS (Netherlands)

Einmahl, J.H.J.

1992-01-01

A description of the weak and strong limiting behaviour of weighted uniform tail empirical and tail quantile processes is given. The results for the tail quantile process are applied to obtain weak and strong functional limit theorems for a weighted non-uniform tail-quantile-type process based on a

Smooth quantile normalization.

Science.gov (United States)

Hicks, Stephanie C; Okrah, Kwame; Paulson, Joseph N; Quackenbush, John; Irizarry, Rafael A; Bravo, Héctor Corrada

2018-04-01

Between-sample normalization is a critical step in genomic data analysis to remove systematic bias and unwanted technical variation in high-throughput data. Global normalization methods are based on the assumption that observed variability in global properties is due to technical reasons and are unrelated to the biology of interest. For example, some methods correct for differences in sequencing read counts by scaling features to have similar median values across samples, but these fail to reduce other forms of unwanted technical variation. Methods such as quantile normalization transform the statistical distributions across samples to be the same and assume global differences in the distribution are induced by only technical variation. However, it remains unclear how to proceed with normalization if these assumptions are violated, for example, if there are global differences in the statistical distributions between biological conditions or groups, and external information, such as negative or control features, is not available. Here, we introduce a generalization of quantile normalization, referred to as smooth quantile normalization (qsmooth), which is based on the assumption that the statistical distribution of each sample should be the same (or have the same distributional shape) within biological groups or conditions, but allowing that they may differ between groups. We illustrate the advantages of our method on several high-throughput datasets with global differences in distributions corresponding to different biological conditions. We also perform a Monte Carlo simulation study to illustrate the bias-variance tradeoff and root mean squared error of qsmooth compared to other global normalization methods. A software implementation is available from https://github.com/stephaniehicks/qsmooth.

Directional quantile regression in Octave (and MATLAB)

Czech Academy of Sciences Publication Activity Database

Boček, Pavel; Šiman, Miroslav

2016-01-01

Roč. 52, č. 1 (2016), s. 28-51 ISSN 0023-5954 R&D Projects: GA ČR GA14-07234S Institutional support: RVO:67985556 Keywords : quantile regression * multivariate quantile * depth contour * Matlab Subject RIV: IN - Informatics, Computer Science Impact factor: 0.379, year: 2016 http://library.utia.cas.cz/separaty/2016/SI/bocek-0458380.pdf

On directional multiple-output quantile regression

Czech Academy of Sciences Publication Activity Database

Paindaveine, D.; Šiman, Miroslav

2011-01-01

Roč. 102, č. 2 (2011), s. 193-212 ISSN 0047-259X R&D Projects: GA MŠk(CZ) 1M06047 Grant - others:Commision EC(BE) Fonds National de la Recherche Scientifique Institutional research plan: CEZ:AV0Z10750506 Keywords : multivariate quantile * quantile regression * multiple-output regression * halfspace depth * portfolio optimization * value-at risk Subject RIV: BA - General Mathematics Impact factor: 0.879, year: 2011 http://library.utia.cas.cz/separaty/2011/SI/siman-0364128.pdf

Technical note: Combining quantile forecasts and predictive distributions of streamflows

Science.gov (United States)

Bogner, Konrad; Liechti, Katharina; Zappa, Massimiliano

2017-11-01

The enhanced availability of many different hydro-meteorological modelling and forecasting systems raises the issue of how to optimally combine this great deal of information. Especially the usage of deterministic and probabilistic forecasts with sometimes widely divergent predicted future streamflow values makes it even more complicated for decision makers to sift out the relevant information. In this study multiple streamflow forecast information will be aggregated based on several different predictive distributions, and quantile forecasts. For this combination the Bayesian model averaging (BMA) approach, the non-homogeneous Gaussian regression (NGR), also known as the ensemble model output statistic (EMOS) techniques, and a novel method called Beta-transformed linear pooling (BLP) will be applied. By the help of the quantile score (QS) and the continuous ranked probability score (CRPS), the combination results for the Sihl River in Switzerland with about 5 years of forecast data will be compared and the differences between the raw and optimally combined forecasts will be highlighted. The results demonstrate the importance of applying proper forecast combination methods for decision makers in the field of flood and water resource management.

Regional trends in short-duration precipitation extremes: a flexible multivariate monotone quantile regression approach

Science.gov (United States)

Cannon, Alex

2017-04-01

Estimating historical trends in short-duration rainfall extremes at regional and local scales is challenging due to low signal-to-noise ratios and the limited availability of homogenized observational data. In addition to being of scientific interest, trends in rainfall extremes are of practical importance, as their presence calls into question the stationarity assumptions that underpin traditional engineering and infrastructure design practice. Even with these fundamental challenges, increasingly complex questions are being asked about time series of extremes. For instance, users may not only want to know whether or not rainfall extremes have changed over time, they may also want information on the modulation of trends by large-scale climate modes or on the nonstationarity of trends (e.g., identifying hiatus periods or periods of accelerating positive trends). Efforts have thus been devoted to the development and application of more robust and powerful statistical estimators for regional and local scale trends. While a standard nonparametric method like the regional Mann-Kendall test, which tests for the presence of monotonic trends (i.e., strictly non-decreasing or non-increasing changes), makes fewer assumptions than parametric methods and pools information from stations within a region, it is not designed to visualize detected trends, include information from covariates, or answer questions about the rate of change in trends. As a remedy, monotone quantile regression (MQR) has been developed as a nonparametric alternative that can be used to estimate a common monotonic trend in extremes at multiple stations. Quantile regression makes efficient use of data by directly estimating conditional quantiles based on information from all rainfall data in a region, i.e., without having to precompute the sample quantiles. The MQR method is also flexible and can be used to visualize and analyze the nonlinearity of the detected trend. However, it is fundamentally a

Predicting Word Reading Ability: A Quantile Regression Study

Science.gov (United States)

McIlraith, Autumn L.

2018-01-01

Predictors of early word reading are well established. However, it is unclear if these predictors hold for readers across a range of word reading abilities. This study used quantile regression to investigate predictive relationships at different points in the distribution of word reading. Quantile regression analyses used preschool and…

Optimal Tracking of Distributed Heavy Hitters and Quantiles

DEFF Research Database (Denmark)

Yi, Ke; Zhang, Qin

2013-01-01

We consider the problem of tracking heavy hitters and quantiles in the distributed streaming model. The heavy hitters and quantiles are two important statistics for characterizing a data distribution. Let A be a multiset of elements, drawn from the universe U={1,…,u}. For a given 0≤ϕ≤1, the ϕ...... of the sites has a two-way communication channel to a designated coordinator, whose goal is to track the set of ϕ-heavy hitters and the ϕ-quantile of A approximately at all times with minimum communication. We give tracking algorithms with worst-case communication cost O(k/ϵ⋅logn) for both problems, where n...

On-line quantile regression in the RKHS (Reproducing Kernel Hilbert Space) for operational probabilistic forecasting of wind power

International Nuclear Information System (INIS)

Gallego-Castillo, Cristobal; Bessa, Ricardo; Cavalcante, Laura; Lopez-Garcia, Oscar

2016-01-01

Wind power probabilistic forecast is being used as input in several decision-making problems, such as stochastic unit commitment, operating reserve setting and electricity market bidding. This work introduces a new on-line quantile regression model based on the Reproducing Kernel Hilbert Space (RKHS) framework. Its application to the field of wind power forecasting involves a discussion on the choice of the bias term of the quantile models, and the consideration of the operational framework in order to mimic real conditions. Benchmark against linear and splines quantile regression models was performed for a real case study during a 18 months period. Model parameter selection was based on k-fold crossvalidation. Results showed a noticeable improvement in terms of calibration, a key criterion for the wind power industry. Modest improvements in terms of Continuous Ranked Probability Score (CRPS) were also observed for prediction horizons between 6 and 20 h ahead. - Highlights: • New online quantile regression model based on the Reproducing Kernel Hilbert Space. • First application to operational probabilistic wind power forecasting. • Modest improvements of CRPS for prediction horizons between 6 and 20 h ahead. • Noticeable improvements in terms of Calibration due to online learning.

Quantile uncertainty and value-at-risk model risk.

Science.gov (United States)

Alexander, Carol; Sarabia, José María

2012-08-01

This article develops a methodology for quantifying model risk in quantile risk estimates. The application of quantile estimates to risk assessment has become common practice in many disciplines, including hydrology, climate change, statistical process control, insurance and actuarial science, and the uncertainty surrounding these estimates has long been recognized. Our work is particularly important in finance, where quantile estimates (called Value-at-Risk) have been the cornerstone of banking risk management since the mid 1980s. A recent amendment to the Basel II Accord recommends additional market risk capital to cover all sources of "model risk" in the estimation of these quantiles. We provide a novel and elegant framework whereby quantile estimates are adjusted for model risk, relative to a benchmark which represents the state of knowledge of the authority that is responsible for model risk. A simulation experiment in which the degree of model risk is controlled illustrates how to quantify Value-at-Risk model risk and compute the required regulatory capital add-on for banks. An empirical example based on real data shows how the methodology can be put into practice, using only two time series (daily Value-at-Risk and daily profit and loss) from a large bank. We conclude with a discussion of potential applications to nonfinancial risks. © 2012 Society for Risk Analysis.

Testing for Stock Market Contagion: A Quantile Regression Approach

NARCIS (Netherlands)

S.Y. Park (Sung); W. Wang (Wendun); N. Huang (Naijing)

2015-01-01

markdownabstract__Abstract__ Regarding the asymmetric and leptokurtic behavior of financial data, we propose a new contagion test in the quantile regression framework that is robust to model misspecification. Unlike conventional correlation-based tests, the proposed quantile contagion test

The Effectiveness of Drinking and Driving Policies for Different Alcohol-Related Fatalities: A Quantile Regression Analysis

Directory of Open Access Journals (Sweden)

Koyin Chang

2013-09-01

Full Text Available To understand the impact of drinking and driving laws on drinking and driving fatality rates, this study explored the different effects these laws have on areas with varying severity rates for drinking and driving. Unlike previous studies, this study employed quantile regression analysis. Empirical results showed that policies based on local conditions must be used to effectively reduce drinking and driving fatality rates; that is, different measures should be adopted to target the specific conditions in various regions. For areas with low fatality rates (low quantiles, people’s habits and attitudes toward alcohol should be emphasized instead of transportation safety laws because “preemptive regulations” are more effective. For areas with high fatality rates (or high quantiles, “ex-post regulations” are more effective, and impact these areas approximately 0.01% to 0.05% more than they do areas with low fatality rates.

A measure-valued differentiation approach to sensitivities of quantiles

NARCIS (Netherlands)

Heidergott, B.F.; Volk-Makarewicz, W.

2016-01-01

Quantiles play an important role in modelling quality of service in the service industry and in modelling risk in the financial industry. The recent discovery that efficient simulation-based estimators can be obtained for quantile sensitivities has led to an intensive search for sample-path

Linear independence of localized magnon states

International Nuclear Information System (INIS)

Schmidt, Heinz-Juergen; Richter, Johannes; Moessner, Roderich

2006-01-01

At the magnetic saturation field, certain frustrated lattices have a class of states known as 'localized multi-magnon states' as exact ground states. The number of these states scales exponentially with the number N of spins and hence they have a finite entropy also in the thermodynamic limit N → ∞ provided they are sufficiently linearly independent. In this paper, we present rigorous results concerning the linear dependence or independence of localized magnon states and investigate special examples. For large classes of spin lattices, including what we call the orthogonal type and the isolated type, as well as the kagome, the checkerboard and the star lattice, we have proven linear independence of all localized multi-magnon states. On the other hand, the pyrochlore lattice provides an example of a spin lattice having localized multi-magnon states with considerable linear dependence

Composite marginal quantile regression analysis for longitudinal adolescent body mass index data.

Science.gov (United States)

Yang, Chi-Chuan; Chen, Yi-Hau; Chang, Hsing-Yi

2017-09-20

Childhood and adolescenthood overweight or obesity, which may be quantified through the body mass index (BMI), is strongly associated with adult obesity and other health problems. Motivated by the child and adolescent behaviors in long-term evolution (CABLE) study, we are interested in individual, family, and school factors associated with marginal quantiles of longitudinal adolescent BMI values. We propose a new method for composite marginal quantile regression analysis for longitudinal outcome data, which performs marginal quantile regressions at multiple quantile levels simultaneously. The proposed method extends the quantile regression coefficient modeling method introduced by Frumento and Bottai (Biometrics 2016; 72:74-84) to longitudinal data accounting suitably for the correlation structure in longitudinal observations. A goodness-of-fit test for the proposed modeling is also developed. Simulation results show that the proposed method can be much more efficient than the analysis without taking correlation into account and the analysis performing separate quantile regressions at different quantile levels. The application to the longitudinal adolescent BMI data from the CABLE study demonstrates the practical utility of our proposal. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Sign and Quantiles of the Realized Stock-Bond Correlation

DEFF Research Database (Denmark)

Aslanidis, Nektarios; Christiansen, Charlotte

over its economic determinants. We document that the correlation behaves di¤erently when it is large negative (0.10 quantile) as opposed to when it is large positive (0.90 quantile). Nevertheless, the empirical findings are only partially robust to using other, possibly less precise, measures...

Diagnostics for Linear Models With Functional Responses

OpenAIRE

Xu, Hongquan; Shen, Qing

2005-01-01

Linear models where the response is a function and the predictors are vectors are useful in analyzing data from designed experiments and other situations with functional observations. Residual analysis and diagnostics are considered for such models. Studentized residuals are defined and their properties are studied. Chi-square quantile-quantile plots are proposed to check the assumption of Gaussian error process and outliers. Jackknife residuals and an associated test are proposed to det...

Fused Adaptive Lasso for Spatial and Temporal Quantile Function Estimation

KAUST Repository

Sun, Ying

2015-09-01

Quantile functions are important in characterizing the entire probability distribution of a random variable, especially when the tail of a skewed distribution is of interest. This article introduces new quantile function estimators for spatial and temporal data with a fused adaptive Lasso penalty to accommodate the dependence in space and time. This method penalizes the difference among neighboring quantiles, hence it is desirable for applications with features ordered in time or space without replicated observations. The theoretical properties are investigated and the performances of the proposed methods are evaluated by simulations. The proposed method is applied to particulate matter (PM) data from the Community Multiscale Air Quality (CMAQ) model to characterize the upper quantiles, which are crucial for studying spatial association between PM concentrations and adverse human health effects. © 2016 American Statistical Association and the American Society for Quality.

Influences of spatial and temporal variation on fish-habitat relationships defined by regression quantiles

Science.gov (United States)

Dunham, J.B.; Cade, B.S.; Terrell, J.W.

2002-01-01

We used regression quantiles to model potentially limiting relationships between the standing crop of cutthroat trout Oncorhynchus clarki and measures of stream channel morphology. Regression quantile models indicated that variation in fish density was inversely related to the width:depth ratio of streams but not to stream width or depth alone. The spatial and temporal stability of model predictions were examined across years and streams, respectively. Variation in fish density with width:depth ratio (10th-90th regression quantiles) modeled for streams sampled in 1993-1997 predicted the variation observed in 1998-1999, indicating similar habitat relationships across years. Both linear and nonlinear models described the limiting relationships well, the latter performing slightly better. Although estimated relationships were transferable in time, results were strongly dependent on the influence of spatial variation in fish density among streams. Density changes with width:depth ratio in a single stream were responsible for the significant (P 80th). This suggests that stream-scale factors other than width:depth ratio play a more direct role in determining population density. Much of the variation in densities of cutthroat trout among streams was attributed to the occurrence of nonnative brook trout Salvelinus fontinalis (a possible competitor) or connectivity to migratory habitats. Regression quantiles can be useful for estimating the effects of limiting factors when ecological responses are highly variable, but our results indicate that spatiotemporal variability in the data should be explicitly considered. In this study, data from individual streams and stream-specific characteristics (e.g., the occurrence of nonnative species and habitat connectivity) strongly affected our interpretation of the relationship between width:depth ratio and fish density.

Choosing put option parameters based on quantiles from the distribution of portfolio value

OpenAIRE

Bell, Peter Newton

2014-01-01

This paper explores how a put option changes the probability distribution of portfolio value. The paper extends the model introduced in Bell (2014) by allowing both the quantity and strike price to vary. I use the 5% quantile from the portfolio distribution to measure riskiness and compare different put options. I report a so-called ‘quantile surface’ that shows the quantile across different combinations of quantity and strike price. I find that it is possible to maximize the quantile by ...

Assessing the impact of local meteorological variables on surface ozone in Hong Kong during 2000-2015 using quantile and multiple line regression models

Science.gov (United States)

Zhao, Wei; Fan, Shaojia; Guo, Hai; Gao, Bo; Sun, Jiaren; Chen, Laiguo

2016-11-01

The quantile regression (QR) method has been increasingly introduced to atmospheric environmental studies to explore the non-linear relationship between local meteorological conditions and ozone mixing ratios. In this study, we applied QR for the first time, together with multiple linear regression (MLR), to analyze the dominant meteorological parameters influencing the mean, 10th percentile, 90th percentile and 99th percentile of maximum daily 8-h average (MDA8) ozone concentrations in 2000-2015 in Hong Kong. The dominance analysis (DA) was used to assess the relative importance of meteorological variables in the regression models. Results showed that the MLR models worked better at suburban and rural sites than at urban sites, and worked better in winter than in summer. QR models performed better in summer for 99th and 90th percentiles and performed better in autumn and winter for 10th percentile. And QR models also performed better in suburban and rural areas for 10th percentile. The top 3 dominant variables associated with MDA8 ozone concentrations, changing with seasons and regions, were frequently associated with the six meteorological parameters: boundary layer height, humidity, wind direction, surface solar radiation, total cloud cover and sea level pressure. Temperature rarely became a significant variable in any season, which could partly explain the peak of monthly average ozone concentrations in October in Hong Kong. And we found the effect of solar radiation would be enhanced during extremely ozone pollution episodes (i.e., the 99th percentile). Finally, meteorological effects on MDA8 ozone had no significant changes before and after the 2010 Asian Games.

"A Quantile Regression Analysis of Wages in Panama."

OpenAIRE

Evangelos M. Falaris

2004-01-01

I investigate differences in the effects of worker characteristics on wages in Panama at different points of the conditional wage distribution. Public sector employment increases wages of men and of women relatively more at lower quantiles. Public sector employment increases wages of the median worker in that sector and reduces wage inequality within the sector. The existence of a labor union at a worker’s workplace increases relatively more wages of men at lower quantiles. Labor unions reduc...

Estimation of Conditional Quantile using Neural Networks

DEFF Research Database (Denmark)

Kulczycki, P.; Schiøler, Henrik

1999-01-01

The problem of estimating conditional quantiles using neural networks is investigated here. A basic structure is developed using the methodology of kernel estimation, and a theory guaranteeing con-sistency on a mild set of assumptions is provided. The constructed structure constitutes a basis...... for the design of a variety of different neural networks, some of which are considered in detail. The task of estimating conditional quantiles is related to Bayes point estimation whereby a broad range of applications within engineering, economics and management can be suggested. Numerical results illustrating...... the capabilities of the elaborated neural network are also given....

Quantile Acoustic Vectors vs. MFCC Applied to Speaker Verification

Directory of Open Access Journals (Sweden)

Mayorga-Ortiz Pedro

2014-02-01

Full Text Available In this paper we describe speaker and command recognition related experiments, through quantile vectors and Gaussian Mixture Modelling (GMM. Over the past several years GMM and MFCC have become two of the dominant approaches for modelling speaker and speech recognition applications. However, memory and computational costs are important drawbacks, because autonomous systems suffer processing and power consumption constraints; thus, having a good trade-off between accuracy and computational requirements is mandatory. We decided to explore another approach (quantile vectors in several tasks and a comparison with MFCC was made. Quantile acoustic vectors are proposed for speaker verification and command recognition tasks and the results showed very good recognition efficiency. This method offered a good trade-off between computation times, characteristics vector complexity and overall achieved efficiency.

A quantile regression analysis of China's provincial CO_2 emissions: Where does the difference lie?

International Nuclear Information System (INIS)

Xu, Bin; Lin, Boqiang

2016-01-01

China is already the largest carbon dioxide emitter in the world. This paper adopts provincial panel data from 1990 to 2014 and employs quantile regression model to investigate the influencing factors of China's CO_2 emissions. The results show that economic growth plays a dominant role in the growth of CO_2 emissions due to massive fixed–asset investment and export trade. The influences of energy intensity on the lower 10th and upper 90th quantile provinces are stronger than those in the 25th–50th quantile provinces because of big differences in R&D expenditure and human resources distribution. The impact of urbanization increases continuously from the lower 10th quantile provinces to the 10th–25th, 25th–50th, 50th–75th, 75th–90th and upper 90th quantile provinces, owing to the differences in R&D personnel, real estate development and motor–vehicle ownership. The effect of industrialization on the upper 90th quantile provinces is greater than those on other quantile provinces on account of the differences in the industrial scale and the development of the building industry. Thus, the heterogeneity effects of influencing factors on different quantile provinces should be taken into consideration when discussing the mitigation of CO_2 emissions in China. - Highlights: • The driving forces of China's CO_2 emissions are investigated. • Economic growth plays a dominant role in the growth of CO_2 emissions. • The impact of urbanization increases from the lower 10th quantiles to the upper 90th quantiles.

An Analysis of Bank Service Satisfaction Based on Quantile Regression and Grey Relational Analysis

Directory of Open Access Journals (Sweden)

Wen-Tsao Pan

2016-01-01

Full Text Available Bank service satisfaction is vital to the success of a bank. In this paper, we propose to use the grey relational analysis to gauge the levels of service satisfaction of the banks. With the grey relational analysis, we compared the effects of different variables on service satisfaction. We gave ranks to the banks according to their levels of service satisfaction. We further used the quantile regression model to find the variables that affected the satisfaction of a customer at a specific quantile of satisfaction level. The result of the quantile regression analysis provided a bank manager with information to formulate policies to further promote satisfaction of the customers at different quantiles of satisfaction level. We also compared the prediction accuracies of the regression models at different quantiles. The experiment result showed that, among the seven quantile regression models, the median regression model has the best performance in terms of RMSE, RTIC, and CE performance measures.

Estimation of peak discharge quantiles for selected annual exceedance probabilities in northeastern Illinois

Science.gov (United States)

Over, Thomas M.; Saito, Riki J.; Veilleux, Andrea G.; Sharpe, Jennifer B.; Soong, David T.; Ishii, Audrey L.

2016-06-28

This report provides two sets of equations for estimating peak discharge quantiles at annual exceedance probabilities (AEPs) of 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively) for watersheds in Illinois based on annual maximum peak discharge data from 117 watersheds in and near northeastern Illinois. One set of equations was developed through a temporal analysis with a two-step least squares-quantile regression technique that measures the average effect of changes in the urbanization of the watersheds used in the study. The resulting equations can be used to adjust rural peak discharge quantiles for the effect of urbanization, and in this study the equations also were used to adjust the annual maximum peak discharges from the study watersheds to 2010 urbanization conditions.The other set of equations was developed by a spatial analysis. This analysis used generalized least-squares regression to fit the peak discharge quantiles computed from the urbanization-adjusted annual maximum peak discharges from the study watersheds to drainage-basin characteristics. The peak discharge quantiles were computed by using the Expected Moments Algorithm following the removal of potentially influential low floods defined by a multiple Grubbs-Beck test. To improve the quantile estimates, regional skew coefficients were obtained from a newly developed regional skew model in which the skew increases with the urbanized land use fraction. The drainage-basin characteristics used as explanatory variables in the spatial analysis include drainage area, the fraction of developed land, the fraction of land with poorly drained soils or likely water, and the basin slope estimated as the ratio of the basin relief to basin perimeter.This report also provides the following: (1) examples to illustrate the use of the spatial and urbanization-adjustment equations for estimating peak discharge quantiles at ungaged

Extreme quantile estimation for dependent data with applications to finance

OpenAIRE

Drees, Holger

2002-01-01

The asymptotic normality of a class of estimators for extreme quantiles is established under mild structural conditions on the observed stationary \\beta-mixing time series. Consistent estimators of the asymptotic variance are introduced, which render possible the construction of asymptotic confidence intervals for the extreme quantiles. Moreover, it is shown that many well-known time series models satisfy our conditions. Then the theory is applied to a time series of returns of a stock in...

Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility

Czech Academy of Sciences Publication Activity Database

Žikeš, F.; Baruník, Jozef

2016-01-01

Roč. 14, č. 1 (2016), s. 185-226 ISSN 1479-8409 R&D Projects: GA ČR GA13-32263S EU Projects: European Commission 612955 - FINMAP Institutional support: RVO:67985556 Keywords : conditional quantiles * quantile regression * realized measures * value-at-risk Subject RIV: AH - Economics Impact factor: 1.800, year: 2016 http://library.utia.cas.cz/separaty/2014/E/barunik-0434200.pdf

Construction of local and non-local conservation laws for non-linear field equations

International Nuclear Information System (INIS)

Vladimirov, V.S.; Volovich, I.V.

1984-08-01

A method of constructing conserved currents for non-linear field equations is presented. More explicitly for non-linear equations, which can be derived from compatibility conditions of some linear system with a parameter, a procedure of obtaining explicit expressions for local and non-local currents is developed. Some examples such as the classical Heisenberg spin chain and supersymmetric Yang-Mills theory are considered. (author)

Local linear viscoelasticity of confined fluids.

Science.gov (United States)

Hansen, J S; Daivis, P J; Todd, B D

2007-04-14

In this paper the authors propose a novel method to study the local linear viscoelasticity of fluids confined between two walls. The method is based on the linear constitutive equation and provides details about the real and imaginary parts of the local complex viscosity. They apply the method to a simple atomic fluid undergoing zero mean oscillatory flow using nonequilibrium molecular dynamics simulations. The method shows that the viscoelastic properties of the fluid exhibit dramatic spatial changes near the wall-fluid boundary due to the high density in this region. It is also shown that the real part of the viscosity converges to the frequency dependent local shear viscosity sufficiently far away from the wall. This also provides valuable information about the transport properties in the fluid, in general. The viscosity is compared with predictions from the local average density model. The two methods disagree in that the local average density model predicts larger viscosity variations near the wall-fluid boundary than what is observed through the method presented here.

Quantile arithmetic methodology for uncertainty propagation in fault trees

International Nuclear Information System (INIS)

Abdelhai, M.; Ragheb, M.

1986-01-01

A methodology based on quantile arithmetic, the probabilistic analog to interval analysis, is proposed for the computation of uncertainties propagation in fault tree analysis. The basic events' continuous probability density functions (pdf's) are represented by equivalent discrete distributions by dividing them into a number of quantiles N. Quantile arithmetic is then used to performthe binary arithmetical operations corresponding to the logical gates in the Boolean expression of the top event expression of a given fault tree. The computational advantage of the present methodology as compared with the widely used Monte Carlo method was demonstrated for the cases of summation of M normal variables through the efficiency ratio defined as the product of the labor and error ratios. The efficiency ratio values obtained by the suggested methodology for M = 2 were 2279 for N = 5, 445 for N = 25, and 66 for N = 45 when compared with the results for 19,200 Monte Carlo samples at the 40th percentile point. Another advantage of the approach is that the exact analytical value of the median is always obtained for the top event

Removing Batch Effects from Longitudinal Gene Expression - Quantile Normalization Plus ComBat as Best Approach for Microarray Transcriptome Data.

Directory of Open Access Journals (Sweden)

Christian Müller

Full Text Available Technical variation plays an important role in microarray-based gene expression studies, and batch effects explain a large proportion of this noise. It is therefore mandatory to eliminate technical variation while maintaining biological variability. Several strategies have been proposed for the removal of batch effects, although they have not been evaluated in large-scale longitudinal gene expression data. In this study, we aimed at identifying a suitable method for batch effect removal in a large study of microarray-based longitudinal gene expression. Monocytic gene expression was measured in 1092 participants of the Gutenberg Health Study at baseline and 5-year follow up. Replicates of selected samples were measured at both time points to identify technical variability. Deming regression, Passing-Bablok regression, linear mixed models, non-linear models as well as ReplicateRUV and ComBat were applied to eliminate batch effects between replicates. In a second step, quantile normalization prior to batch effect correction was performed for each method. Technical variation between batches was evaluated by principal component analysis. Associations between body mass index and transcriptomes were calculated before and after batch removal. Results from association analyses were compared to evaluate maintenance of biological variability. Quantile normalization, separately performed in each batch, combined with ComBat successfully reduced batch effects and maintained biological variability. ReplicateRUV performed perfectly in the replicate data subset of the study, but failed when applied to all samples. All other methods did not substantially reduce batch effects in the replicate data subset. Quantile normalization plus ComBat appears to be a valuable approach for batch correction in longitudinal gene expression data.

Estimating conditional quantiles with the help of the pinball loss

International Nuclear Information System (INIS)

Steinwart, Ingo

2008-01-01

Using the so-called pinball loss for estimating conditional quantiles is a well-known tool in both statistics and machine learning. So far, however, only little work has been done to quantify the efficiency of this tool for non-parametric (modified) empirical risk minimization approaches. The goal of this work is to fill this gap by establishing inequalities that describe how close approximate pinball risk minimizers are to the corresponding conditional quantile. These inequalities, which hold under mild assumptions on the data-generating distribution, are then used to establish so-called variance bounds which recently turned out to play an important role in the statistical analysis of (modified) empirical risk minimization approaches. To illustrate the use of the established inequalities, we then use them to establish an oracle inequality for support vector machines that use the pinball loss. Here, it turns out that we obtain learning rates which are optimal in a min-max sense under some standard assumptions on the regularity of the conditional quantile function

Is the local linearity of space-time inherited from the linearity of probabilities?

Science.gov (United States)

Müller, Markus P.; Carrozza, Sylvain; Höhn, Philipp A.

2017-02-01

The appearance of linear spaces, describing physical quantities by vectors and tensors, is ubiquitous in all of physics, from classical mechanics to the modern notion of local Lorentz invariance. However, as natural as this seems to the physicist, most computer scientists would argue that something like a ‘local linear tangent space’ is not very typical and in fact a quite surprising property of any conceivable world or algorithm. In this paper, we take the perspective of the computer scientist seriously, and ask whether there could be any inherently information-theoretic reason to expect this notion of linearity to appear in physics. We give a series of simple arguments, spanning quantum information theory, group representation theory, and renormalization in quantum gravity, that supports a surprising thesis: namely, that the local linearity of space-time might ultimately be a consequence of the linearity of probabilities. While our arguments involve a fair amount of speculation, they have the virtue of being independent of any detailed assumptions on quantum gravity, and they are in harmony with several independent recent ideas on emergent space-time in high-energy physics.

Is the local linearity of space-time inherited from the linearity of probabilities?

International Nuclear Information System (INIS)

Müller, Markus P; Carrozza, Sylvain; Höhn, Philipp A

2017-01-01

The appearance of linear spaces, describing physical quantities by vectors and tensors, is ubiquitous in all of physics, from classical mechanics to the modern notion of local Lorentz invariance. However, as natural as this seems to the physicist, most computer scientists would argue that something like a ‘local linear tangent space’ is not very typical and in fact a quite surprising property of any conceivable world or algorithm. In this paper, we take the perspective of the computer scientist seriously, and ask whether there could be any inherently information-theoretic reason to expect this notion of linearity to appear in physics. We give a series of simple arguments, spanning quantum information theory, group representation theory, and renormalization in quantum gravity, that supports a surprising thesis: namely, that the local linearity of space-time might ultimately be a consequence of the linearity of probabilities. While our arguments involve a fair amount of speculation, they have the virtue of being independent of any detailed assumptions on quantum gravity, and they are in harmony with several independent recent ideas on emergent space-time in high-energy physics. (paper)

Logistic quantile regression provides improved estimates for bounded avian counts: A case study of California Spotted Owl fledgling production

Science.gov (United States)

Cade, Brian S.; Noon, Barry R.; Scherer, Rick D.; Keane, John J.

2017-01-01

Counts of avian fledglings, nestlings, or clutch size that are bounded below by zero and above by some small integer form a discrete random variable distribution that is not approximated well by conventional parametric count distributions such as the Poisson or negative binomial. We developed a logistic quantile regression model to provide estimates of the empirical conditional distribution of a bounded discrete random variable. The logistic quantile regression model requires that counts are randomly jittered to a continuous random variable, logit transformed to bound them between specified lower and upper values, then estimated in conventional linear quantile regression, repeating the 3 steps and averaging estimates. Back-transformation to the original discrete scale relies on the fact that quantiles are equivariant to monotonic transformations. We demonstrate this statistical procedure by modeling 20 years of California Spotted Owl fledgling production (0−3 per territory) on the Lassen National Forest, California, USA, as related to climate, demographic, and landscape habitat characteristics at territories. Spotted Owl fledgling counts increased nonlinearly with decreasing precipitation in the early nesting period, in the winter prior to nesting, and in the prior growing season; with increasing minimum temperatures in the early nesting period; with adult compared to subadult parents; when there was no fledgling production in the prior year; and when percentage of the landscape surrounding nesting sites (202 ha) with trees ≥25 m height increased. Changes in production were primarily driven by changes in the proportion of territories with 2 or 3 fledglings. Average variances of the discrete cumulative distributions of the estimated fledgling counts indicated that temporal changes in climate and parent age class explained 18% of the annual variance in owl fledgling production, which was 34% of the total variance. Prior fledgling production explained as much of

Focused information criterion and model averaging based on weighted composite quantile regression

KAUST Repository

Xu, Ganggang

2013-08-13

We study the focused information criterion and frequentist model averaging and their application to post-model-selection inference for weighted composite quantile regression (WCQR) in the context of the additive partial linear models. With the non-parametric functions approximated by polynomial splines, we show that, under certain conditions, the asymptotic distribution of the frequentist model averaging WCQR-estimator of a focused parameter is a non-linear mixture of normal distributions. This asymptotic distribution is used to construct confidence intervals that achieve the nominal coverage probability. With properly chosen weights, the focused information criterion based WCQR estimators are not only robust to outliers and non-normal residuals but also can achieve efficiency close to the maximum likelihood estimator, without assuming the true error distribution. Simulation studies and a real data analysis are used to illustrate the effectiveness of the proposed procedure. © 2013 Board of the Foundation of the Scandinavian Journal of Statistics..

Robust small area estimation of poverty indicators using M-quantile approach (Case study: Sub-district level in Bogor district)

Science.gov (United States)

Girinoto, Sadik, Kusman; Indahwati

2017-03-01

The National Socio-Economic Survey samples are designed to produce estimates of parameters of planned domains (provinces and districts). The estimation of unplanned domains (sub-districts and villages) has its limitation to obtain reliable direct estimates. One of the possible solutions to overcome this problem is employing small area estimation techniques. The popular choice of small area estimation is based on linear mixed models. However, such models need strong distributional assumptions and do not easy allow for outlier-robust estimation. As an alternative approach for this purpose, M-quantile regression approach to small area estimation based on modeling specific M-quantile coefficients of conditional distribution of study variable given auxiliary covariates. It obtained outlier-robust estimation from influence function of M-estimator type and also no need strong distributional assumptions. In this paper, the aim of study is to estimate the poverty indicator at sub-district level in Bogor District-West Java using M-quantile models for small area estimation. Using data taken from National Socioeconomic Survey and Villages Potential Statistics, the results provide a detailed description of pattern of incidence and intensity of poverty within Bogor district. We also compare the results with direct estimates. The results showed the framework may be preferable when direct estimate having no incidence of poverty at all in the small area.

The Applicability of Confidence Intervals of Quantiles for the Generalized Logistic Distribution

Science.gov (United States)

Shin, H.; Heo, J.; Kim, T.; Jung, Y.

2007-12-01

The generalized logistic (GL) distribution has been widely used for frequency analysis. However, there is a little study related to the confidence intervals that indicate the prediction accuracy of distribution for the GL distribution. In this paper, the estimation of the confidence intervals of quantiles for the GL distribution is presented based on the method of moments (MOM), maximum likelihood (ML), and probability weighted moments (PWM) and the asymptotic variances of each quantile estimator are derived as functions of the sample sizes, return periods, and parameters. Monte Carlo simulation experiments are also performed to verify the applicability of the derived confidence intervals of quantile. As the results, the relative bias (RBIAS) and relative root mean square error (RRMSE) of the confidence intervals generally increase as return period increases and reverse as sample size increases. And PWM for estimating the confidence intervals performs better than the other methods in terms of RRMSE when the data is almost symmetric while ML shows the smallest RBIAS and RRMSE when the data is more skewed and sample size is moderately large. The GL model was applied to fit the distribution of annual maximum rainfall data. The results show that there are little differences in the estimated quantiles between ML and PWM while distinct differences in MOM.

A local homology theory for linearly compact modules

International Nuclear Information System (INIS)

Nguyen Tu Cuong; Tran Tuan Nam

2004-11-01

We introduce a local homology theory for linearly modules which is in some sense dual to the local cohomology theory of A. Grothendieck. Some basic properties of local homology modules are shown such as: the vanishing and non-vanishing, the noetherianness of local homology modules. By using duality, we extend some well-known results in theory of local cohomology of A. Grothendieck. (author)

Spatial Quantile Regression In Analysis Of Healthy Life Years In The European Union Countries

Directory of Open Access Journals (Sweden)

Trzpiot Grażyna

2016-12-01

Full Text Available The paper investigates the impact of the selected factors on the healthy life years of men and women in the EU countries. The multiple quantile spatial autoregression models are used in order to account for substantial differences in the healthy life years and life quality across the EU members. Quantile regression allows studying dependencies between variables in different quantiles of the response distribution. Moreover, this statistical tool is robust against violations of the classical regression assumption about the distribution of the error term. Parameters of the models were estimated using instrumental variable method (Kim, Muller 2004, whereas the confidence intervals and p-values were bootstrapped.

Vortices, semi-local vortices in gauged linear sigma model

International Nuclear Information System (INIS)

Kim, Namkwon

1998-11-01

We consider the static (2+1)D gauged linear sigma model. By analyzing the governing system of partial differential equations, we investigate various aspects of the model. We show the existence of energy finite vortices under a partially broken symmetry on R 2 with the necessary condition suggested by Y. Yang. We also introduce generalized semi-local vortices and show the existence of energy finite semi-local vortices under a certain condition. The vacuum manifold for the semi-local vortices turns out to be graded. Besides, with a special choice of a representation, we show that the O(3) sigma model of which target space is nonlinear is a singular limit of the gauged linear sigma model of which target space is linear. (author)

Generalized local homology and cohomology for linearly compact modules

International Nuclear Information System (INIS)

Tran Tuan Nam

2006-07-01

We study generalized local homology for linearly compact modules. By duality, we get some properties of generalized local cohomology modules and extend well-known properties of local cohomology of A. Grothendieck. (author)

Principles of Quantile Regression and an Application

Science.gov (United States)

Chen, Fang; Chalhoub-Deville, Micheline

2014-01-01

Newer statistical procedures are typically introduced to help address the limitations of those already in practice or to deal with emerging research needs. Quantile regression (QR) is introduced in this paper as a relatively new methodology, which is intended to overcome some of the limitations of least squares mean regression (LMR). QR is more…

Non-local quasi-linear parabolic equations

International Nuclear Information System (INIS)

Amann, H

2005-01-01

This is a survey of the most common approaches to quasi-linear parabolic evolution equations, a discussion of their advantages and drawbacks, and a presentation of an entirely new approach based on maximal L p regularity. The general results here apply, above all, to parabolic initial-boundary value problems that are non-local in time. This is illustrated by indicating their relevance for quasi-linear parabolic equations with memory and, in particular, for time-regularized versions of the Perona-Malik equation of image processing

Local hyperspectral data multisharpening based on linear/linear-quadratic nonnegative matrix factorization by integrating lidar data

Science.gov (United States)

Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2015-10-01

In this paper, a new Spectral-Unmixing-based approach, using Nonnegative Matrix Factorization (NMF), is proposed to locally multi-sharpen hyperspectral data by integrating a Digital Surface Model (DSM) obtained from LIDAR data. In this new approach, the nature of the local mixing model is detected by using the local variance of the object elevations. The hyper/multispectral images are explored using small zones. In each zone, the variance of the object elevations is calculated from the DSM data in this zone. This variance is compared to a threshold value and the adequate linear/linearquadratic spectral unmixing technique is used in the considered zone to independently unmix hyperspectral and multispectral data, using an adequate linear/linear-quadratic NMF-based approach. The obtained spectral and spatial information thus respectively extracted from the hyper/multispectral images are then recombined in the considered zone, according to the selected mixing model. Experiments based on synthetic hyper/multispectral data are carried out to evaluate the performance of the proposed multi-sharpening approach and literature linear/linear-quadratic approaches used on the whole hyper/multispectral data. In these experiments, real DSM data are used to generate synthetic data containing linear and linear-quadratic mixed pixel zones. The DSM data are also used for locally detecting the nature of the mixing model in the proposed approach. Globally, the proposed approach yields good spatial and spectral fidelities for the multi-sharpened data and significantly outperforms the used literature methods.

Multitask Quantile Regression under the Transnormal Model.

Science.gov (United States)

Fan, Jianqing; Xue, Lingzhou; Zou, Hui

2016-01-01

We consider estimating multi-task quantile regression under the transnormal model, with focus on high-dimensional setting. We derive a surprisingly simple closed-form solution through rank-based covariance regularization. In particular, we propose the rank-based ℓ 1 penalization with positive definite constraints for estimating sparse covariance matrices, and the rank-based banded Cholesky decomposition regularization for estimating banded precision matrices. By taking advantage of alternating direction method of multipliers, nearest correlation matrix projection is introduced that inherits sampling properties of the unprojected one. Our work combines strengths of quantile regression and rank-based covariance regularization to simultaneously deal with nonlinearity and nonnormality for high-dimensional regression. Furthermore, the proposed method strikes a good balance between robustness and efficiency, achieves the "oracle"-like convergence rate, and provides the provable prediction interval under the high-dimensional setting. The finite-sample performance of the proposed method is also examined. The performance of our proposed rank-based method is demonstrated in a real application to analyze the protein mass spectroscopy data.

Growth curves of preschool children in the northeast of iran: a population based study using quantile regression approach.

Science.gov (United States)

Payande, Abolfazl; Tabesh, Hamed; Shakeri, Mohammad Taghi; Saki, Azadeh; Safarian, Mohammad

2013-01-14

Growth charts are widely used to assess children's growth status and can provide a trajectory of growth during early important months of life. The objectives of this study are going to construct growth charts and normal values of weight-for-age for children aged 0 to 5 years using a powerful and applicable methodology. The results compare with the World Health Organization (WHO) references and semi-parametric LMS method of Cole and Green. A total of 70737 apparently healthy boys and girls aged 0 to 5 years were recruited in July 2004 for 20 days from those attending community clinics for routine health checks as a part of a national survey. Anthropometric measurements were done by trained health staff using WHO methodology. The nonparametric quantile regression method obtained by local constant kernel estimation of conditional quantiles curves using for estimation of curves and normal values. The weight-for-age growth curves for boys and girls aged from 0 to 5 years were derived utilizing a population of children living in the northeast of Iran. The results were similar to the ones obtained by the semi-parametric LMS method in the same data. Among all age groups from 0 to 5 years, the median values of children's weight living in the northeast of Iran were lower than the corresponding values in WHO reference data. The weight curves of boys were higher than those of girls in all age groups. The differences between growth patterns of children living in the northeast of Iran versus international ones necessitate using local and regional growth charts. International normal values may not properly recognize the populations at risk for growth problems in Iranian children. Quantile regression (QR) as a flexible method which doesn't require restricted assumptions, proposed for estimation reference curves and normal values.

Efficient estimation of an additive quantile regression model

NARCIS (Netherlands)

Cheng, Y.; de Gooijer, J.G.; Zerom, D.

2011-01-01

In this paper, two non-parametric estimators are proposed for estimating the components of an additive quantile regression model. The first estimator is a computationally convenient approach which can be viewed as a more viable alternative to existing kernel-based approaches. The second estimator

What Affects The Ability To Accumulate The Best Applicants By Russian Universities? The Application Of Quantile Regression Model

Directory of Open Access Journals (Sweden)

Łaszkiewicz Edyta

2016-12-01

Full Text Available The aim of this paper is to evaluate which university’s characteristics have the greatest impact on the competitiveness of universities in their ability to attract better students in Russia. We examined the impact of three groups of factors,related to teaching, research and entrepreneurial activities of universities. The quantile regression model was applied for the subsample of public and private higher education institutions localized in Russia.

Time signal filtering by relative neighborhood graph localized linear approximation

DEFF Research Database (Denmark)

Sørensen, John Aasted

1994-01-01

A time signal filtering algorithm based on the relative neighborhood graph (RNG) used for localization of linear filters is proposed. The filter is constructed from a training signal during two stages. During the first stage an RNG is constructed. During the second stage, localized linear filters...

Efficient estimation of an additive quantile regression model

NARCIS (Netherlands)

Cheng, Y.; de Gooijer, J.G.; Zerom, D.

2009-01-01

In this paper two kernel-based nonparametric estimators are proposed for estimating the components of an additive quantile regression model. The first estimator is a computationally convenient approach which can be viewed as a viable alternative to the method of De Gooijer and Zerom (2003). By

Efficient estimation of an additive quantile regression model

NARCIS (Netherlands)

Cheng, Y.; de Gooijer, J.G.; Zerom, D.

2010-01-01

In this paper two kernel-based nonparametric estimators are proposed for estimating the components of an additive quantile regression model. The first estimator is a computationally convenient approach which can be viewed as a viable alternative to the method of De Gooijer and Zerom (2003). By

A Bayesian nonparametric estimation of distributions and quantiles

International Nuclear Information System (INIS)

Poern, K.

1988-11-01

The report describes a Bayesian, nonparametric method for the estimation of a distribution function and its quantiles. The method, presupposing random sampling, is nonparametric, so the user has to specify a prior distribution on a space of distributions (and not on a parameter space). In the current application, where the method is used to estimate the uncertainty of a parametric calculational model, the Dirichlet prior distribution is to a large extent determined by the first batch of Monte Carlo-realizations. In this case the results of the estimation technique is very similar to the conventional empirical distribution function. The resulting posterior distribution is also Dirichlet, and thus facilitates the determination of probability (confidence) intervals at any given point in the space of interest. Another advantage is that also the posterior distribution of a specified quantitle can be derived and utilized to determine a probability interval for that quantile. The method was devised for use in the PROPER code package for uncertainty and sensitivity analysis. (orig.)

[Spatial heterogeneity in body condition of small yellow croaker in Yellow Sea and East China Sea based on mixed-effects model and quantile regression analysis].

Science.gov (United States)

Liu, Zun-Lei; Yuan, Xing-Wei; Yan, Li-Ping; Yang, Lin-Lin; Cheng, Jia-Hua

2013-09-01

By using the 2008-2010 investigation data about the body condition of small yellow croaker in the offshore waters of southern Yellow Sea (SYS), open waters of northern East China Sea (NECS), and offshore waters of middle East China Sea (MECS), this paper analyzed the spatial heterogeneity of body length-body mass of juvenile and adult small yellow croakers by the statistical approaches of mean regression model and quantile regression model. The results showed that the residual standard errors from the analysis of covariance (ANCOVA) and the linear mixed-effects model were similar, and those from the simple linear regression were the highest. For the juvenile small yellow croakers, their mean body mass in SYS and NECS estimated by the mixed-effects mean regression model was higher than the overall average mass across the three regions, while the mean body mass in MECS was below the overall average. For the adult small yellow croakers, their mean body mass in NECS was higher than the overall average, while the mean body mass in SYS and MECS was below the overall average. The results from quantile regression indicated the substantial differences in the allometric relationships of juvenile small yellow croakers between SYS, NECS, and MECS, with the estimated mean exponent of the allometric relationship in SYS being 2.85, and the interquartile range being from 2.63 to 2.96, which indicated the heterogeneity of body form. The results from ANCOVA showed that the allometric body length-body mass relationships were significantly different between the 25th and 75th percentile exponent values (F=6.38, df=1737, P<0.01) and the 25th percentile and median exponent values (F=2.35, df=1737, P=0.039). The relationship was marginally different between the median and 75th percentile exponent values (F=2.21, df=1737, P=0.051). The estimated body length-body mass exponent of adult small yellow croakers in SYS was 3.01 (10th and 95th percentiles = 2.77 and 3.1, respectively). The

Analysis of the influence of quantile regression model on mainland tourists' service satisfaction performance.

Science.gov (United States)

Wang, Wen-Cheng; Cho, Wen-Chien; Chen, Yin-Jen

2014-01-01

It is estimated that mainland Chinese tourists travelling to Taiwan can bring annual revenues of 400 billion NTD to the Taiwan economy. Thus, how the Taiwanese Government formulates relevant measures to satisfy both sides is the focus of most concern. Taiwan must improve the facilities and service quality of its tourism industry so as to attract more mainland tourists. This paper conducted a questionnaire survey of mainland tourists and used grey relational analysis in grey mathematics to analyze the satisfaction performance of all satisfaction question items. The first eight satisfaction items were used as independent variables, and the overall satisfaction performance was used as a dependent variable for quantile regression model analysis to discuss the relationship between the dependent variable under different quantiles and independent variables. Finally, this study further discussed the predictive accuracy of the least mean regression model and each quantile regression model, as a reference for research personnel. The analysis results showed that other variables could also affect the overall satisfaction performance of mainland tourists, in addition to occupation and age. The overall predictive accuracy of quantile regression model Q0.25 was higher than that of the other three models.

Analysis of the Influence of Quantile Regression Model on Mainland Tourists' Service Satisfaction Performance

Science.gov (United States)

Wang, Wen-Cheng; Cho, Wen-Chien; Chen, Yin-Jen

2014-01-01

It is estimated that mainland Chinese tourists travelling to Taiwan can bring annual revenues of 400 billion NTD to the Taiwan economy. Thus, how the Taiwanese Government formulates relevant measures to satisfy both sides is the focus of most concern. Taiwan must improve the facilities and service quality of its tourism industry so as to attract more mainland tourists. This paper conducted a questionnaire survey of mainland tourists and used grey relational analysis in grey mathematics to analyze the satisfaction performance of all satisfaction question items. The first eight satisfaction items were used as independent variables, and the overall satisfaction performance was used as a dependent variable for quantile regression model analysis to discuss the relationship between the dependent variable under different quantiles and independent variables. Finally, this study further discussed the predictive accuracy of the least mean regression model and each quantile regression model, as a reference for research personnel. The analysis results showed that other variables could also affect the overall satisfaction performance of mainland tourists, in addition to occupation and age. The overall predictive accuracy of quantile regression model Q0.25 was higher than that of the other three models. PMID:24574916

Analysis of the Influence of Quantile Regression Model on Mainland Tourists’ Service Satisfaction Performance

Directory of Open Access Journals (Sweden)

Wen-Cheng Wang

2014-01-01

Full Text Available It is estimated that mainland Chinese tourists travelling to Taiwan can bring annual revenues of 400 billion NTD to the Taiwan economy. Thus, how the Taiwanese Government formulates relevant measures to satisfy both sides is the focus of most concern. Taiwan must improve the facilities and service quality of its tourism industry so as to attract more mainland tourists. This paper conducted a questionnaire survey of mainland tourists and used grey relational analysis in grey mathematics to analyze the satisfaction performance of all satisfaction question items. The first eight satisfaction items were used as independent variables, and the overall satisfaction performance was used as a dependent variable for quantile regression model analysis to discuss the relationship between the dependent variable under different quantiles and independent variables. Finally, this study further discussed the predictive accuracy of the least mean regression model and each quantile regression model, as a reference for research personnel. The analysis results showed that other variables could also affect the overall satisfaction performance of mainland tourists, in addition to occupation and age. The overall predictive accuracy of quantile regression model Q0.25 was higher than that of the other three models.

Single image super-resolution using locally adaptive multiple linear regression.

Science.gov (United States)

Yu, Soohwan; Kang, Wonseok; Ko, Seungyong; Paik, Joonki

2015-12-01

This paper presents a regularized superresolution (SR) reconstruction method using locally adaptive multiple linear regression to overcome the limitation of spatial resolution of digital images. In order to make the SR problem better-posed, the proposed method incorporates the locally adaptive multiple linear regression into the regularization process as a local prior. The local regularization prior assumes that the target high-resolution (HR) pixel is generated by a linear combination of similar pixels in differently scaled patches and optimum weight parameters. In addition, we adapt a modified version of the nonlocal means filter as a smoothness prior to utilize the patch redundancy. Experimental results show that the proposed algorithm better restores HR images than existing state-of-the-art methods in the sense of the most objective measures in the literature.

Quantiles of the Realized Stock-Bond Correlation and Links to the Macroeconomy

DEFF Research Database (Denmark)

Aslanidis, Nektarios; Christiansen, Charlotte

2014-01-01

This paper adopts quantile regressions to scrutinize the realized stock–bond correlation based upon high frequency returns. The paper provides in-sample and out-of-sample analysis and considers factors constructed from a large number of macro-finance predictors well-known from the return predicta......This paper adopts quantile regressions to scrutinize the realized stock–bond correlation based upon high frequency returns. The paper provides in-sample and out-of-sample analysis and considers factors constructed from a large number of macro-finance predictors well-known from the return...

Predictive densities for day-ahead electricity prices using time-adaptive quantile regression

DEFF Research Database (Denmark)

Jónsson, Tryggvi; Pinson, Pierre; Madsen, Henrik

2014-01-01

A large part of the decision-making problems actors of the power system are facing on a daily basis requires scenarios for day-ahead electricity market prices. These scenarios are most likely to be generated based on marginal predictive densities for such prices, then enhanced with a temporal...... dependence structure. A semi-parametric methodology for generating such densities is presented: it includes: (i) a time-adaptive quantile regression model for the 5%–95% quantiles; and (ii) a description of the distribution tails with exponential distributions. The forecasting skill of the proposed model...

Simulating Quantile Models with Applications to Economics and Management

Science.gov (United States)

Machado, José A. F.

2010-05-01

The massive increase in the speed of computers over the past forty years changed the way that social scientists, applied economists and statisticians approach their trades and also the very nature of the problems that they could feasibly tackle. The new methods that use intensively computer power go by the names of "computer-intensive" or "simulation". My lecture will start with bird's eye view of the uses of simulation in Economics and Statistics. Then I will turn out to my own research on uses of computer- intensive methods. From a methodological point of view the question I address is how to infer marginal distributions having estimated a conditional quantile process, (Counterfactual Decomposition of Changes in Wage Distributions using Quantile Regression," Journal of Applied Econometrics 20, 2005). Illustrations will be provided of the use of the method to perform counterfactual analysis in several different areas of knowledge.

Tightness of M-estimators for multiple linear regression in time series

DEFF Research Database (Denmark)

Johansen, Søren; Nielsen, Bent

We show tightness of a general M-estimator for multiple linear regression in time series. The positive criterion function for the M-estimator is assumed lower semi-continuous and sufficiently large for large argument: Particular cases are the Huber-skip and quantile regression. Tightness requires...

Does intense monitoring matter? A quantile regression approach

Directory of Open Access Journals (Sweden)

Fekri Ali Shawtari

2017-06-01

Full Text Available Corporate governance has become a centre of attention in corporate management at both micro and macro levels due to adverse consequences and repercussion of insufficient accountability. In this study, we include the Malaysian stock market as sample to explore the impact of intense monitoring on the relationship between intellectual capital performance and market valuation. The objectives of the paper are threefold: i to investigate whether intense monitoring affects the intellectual capital performance of listed companies; ii to explore the impact of intense monitoring on firm value; iii to examine the extent to which the directors serving more than two board committees affects the linkage between intellectual capital performance and firms' value. We employ two approaches, namely, the Ordinary Least Square (OLS and the quantile regression approach. The purpose of the latter is to estimate and generate inference about conditional quantile functions. This method is useful when the conditional distribution does not have a standard shape such as an asymmetric, fat-tailed, or truncated distribution. In terms of variables, the intellectual capital is measured using the value added intellectual coefficient (VAIC, while the market valuation is proxied by firm's market capitalization. The findings of the quantile regression shows that some of the results do not coincide with the results of OLS. We found that intensity of monitoring does not influence the intellectual capital of all firms. It is also evident that intensity of monitoring does not influence the market valuation. However, to some extent, it moderates the relationship between intellectual capital performance and market valuation. This paper contributes to the existing literature as it presents new empirical evidences on the moderating effects of the intensity of monitoring of the board committees on the relationship between performance and intellectual capital.

Utilizing the Quantile Regression to Explore the Determinants on the Application of E-Learning

OpenAIRE

Quang Linh Huynh; Thuy Lan Le Thi

2014-01-01

In this research, the quantile regression is applied to investigate the affecting factors associated with the application of e-learning. The findings provide a comprehensive picture about the relationships between the application of e-learning and its determinants. It sheds light on these complicated relationships that, at the different quantiles of the conditional distribution of e-learning adopting levels, the influence of the determinants on the application of e-learning is different. More...

Error Estimation for the Linearized Auto-Localization Algorithm

Directory of Open Access Journals (Sweden)

Fernando Seco

2012-02-01

Full Text Available The Linearized Auto-Localization (LAL algorithm estimates the position of beacon nodes in Local Positioning Systems (LPSs, using only the distance measurements to a mobile node whose position is also unknown. The LAL algorithm calculates the inter-beacon distances, used for the estimation of the beacons’ positions, from the linearized trilateration equations. In this paper we propose a method to estimate the propagation of the errors of the inter-beacon distances obtained with the LAL algorithm, based on a first order Taylor approximation of the equations. Since the method depends on such approximation, a confidence parameter τ is defined to measure the reliability of the estimated error. Field evaluations showed that by applying this information to an improved weighted-based auto-localization algorithm (WLAL, the standard deviation of the inter-beacon distances can be improved by more than 30% on average with respect to the original LAL method.

Unstable volatility functions: the break preserving local linear estimator

DEFF Research Database (Denmark)

Casas, Isabel; Gijbels, Irene

The objective of this paper is to introduce the break preserving local linear (BPLL) estimator for the estimation of unstable volatility functions. Breaks in the structure of the conditional mean and/or the volatility functions are common in Finance. Markov switching models (Hamilton, 1989......) and threshold models (Lin and Terasvirta, 1994) are amongst the most popular models to describe the behaviour of data with structural breaks. The local linear (LL) estimator is not consistent at points where the volatility function has a break and it may even report negative values for finite samples...

Linearized versus non-linear inverse methods for seismic localization of underground sources

DEFF Research Database (Denmark)

Oh, Geok Lian; Jacobsen, Finn

2013-01-01

The problem of localization of underground sources from seismic measurements detected by several geophones located on the ground surface is addressed. Two main approaches to the solution of the problem are considered: a beamforming approach that is derived from the linearized inversion problem, a...

Impacts on CO2 Emission Allowance Prices in China: A Quantile Regression Analysis of the Shanghai Emission Trading Scheme

Directory of Open Access Journals (Sweden)

Jie Zhang

2016-11-01

Full Text Available A pilot regional carbon emission trading scheme (ETS has been implemented in China for more than two years. An investigation into the impacts of different factors on carbon dioxide (CO2 emission allowance prices provides guidance for price-making in 2017 when the nation-wide ETS of China will be established. This paper adopts a quantile regression approach to estimate the impacts of different factors in Shanghai emission trading scheme (SH-ETS, namely, economic growth, energy prices and temperature. The empirical analysis shows that: (i the economic growth in Shanghai leads to a drop in the carbon allowance prices; (ii the oil price has a slightly positive effect on the allowance prices regardless of the ordinary least squares (OLS or quantile regression method; (iii a long-run negative relationship exists between the coal price and the Shanghai emission allowances (SHEA prices, but a positive interaction under different quantiles, especially the 25%–50% quantiles; (iv temperature has a significantly positive effect at the 20%–30% quantiles and a conspicuous negative impact at the right tail of the allowances prices.

The quantile regression approach to efficiency measurement: insights from Monte Carlo simulations.

Science.gov (United States)

Liu, Chunping; Laporte, Audrey; Ferguson, Brian S

2008-09-01

In the health economics literature there is an ongoing debate over approaches used to estimate the efficiency of health systems at various levels, from the level of the individual hospital - or nursing home - up to that of the health system as a whole. The two most widely used approaches to evaluating the efficiency with which various units deliver care are non-parametric data envelopment analysis (DEA) and parametric stochastic frontier analysis (SFA). Productivity researchers tend to have very strong preferences over which methodology to use for efficiency estimation. In this paper, we use Monte Carlo simulation to compare the performance of DEA and SFA in terms of their ability to accurately estimate efficiency. We also evaluate quantile regression as a potential alternative approach. A Cobb-Douglas production function, random error terms and a technical inefficiency term with different distributions are used to calculate the observed output. The results, based on these experiments, suggest that neither DEA nor SFA can be regarded as clearly dominant, and that, depending on the quantile estimated, the quantile regression approach may be a useful addition to the armamentarium of methods for estimating technical efficiency.

Local linear heat rate ramps in the WWER-440 transient regimes

International Nuclear Information System (INIS)

Brik, A.N.; Bibilashvili, Ju.L.; Bogatyr, S.M.; Medvedev, A.V.

1998-01-01

The operation of the WWER-440 reactors must be accomplished in such a way that the fuel rods durability would be high enough during the whole operation period. The important factors determining the absence of fuel rod failures are the criteria limiting the core characteristics (fuel rod and fuel assembly power, local linear heat rate, etc.). For the transient and load follow conditions the limitations on the permissible local linear rate ramp are also introduced. This limitation is the result of design limit of stress corrosion cracking of the fuel cladding and depends on the local fuel burn-up. The control rod motion is accompanied by power redistribution, which, in principle, can result in violating the design and operation limitations. Consequently, this motion have to be such as the core parameters, including the local ramps of the linear heat generation rates would not exceed the permissible ones.The paper considers the problem of WWER-440 reactor control under transient and load follow conditions and the associated optimisation of local linear heat generation rate ramps. The main factors affecting the solution of the problem under consideration are discussed. Some recommendations for a more optimal reactor operation are given.(Author)

Fused Adaptive Lasso for Spatial and Temporal Quantile Function Estimation

KAUST Repository

Sun, Ying; Wang, Huixia J.; Fuentes, Montserrat

2015-01-01

and temporal data with a fused adaptive Lasso penalty to accommodate the dependence in space and time. This method penalizes the difference among neighboring quantiles, hence it is desirable for applications with features ordered in time or space without

Toward Optimal Manifold Hashing via Discrete Locally Linear Embedding.

Science.gov (United States)

Rongrong Ji; Hong Liu; Liujuan Cao; Di Liu; Yongjian Wu; Feiyue Huang

2017-11-01

Binary code learning, also known as hashing, has received increasing attention in large-scale visual search. By transforming high-dimensional features to binary codes, the original Euclidean distance is approximated via Hamming distance. More recently, it is advocated that it is the manifold distance, rather than the Euclidean distance, that should be preserved in the Hamming space. However, it retains as an open problem to directly preserve the manifold structure by hashing. In particular, it first needs to build the local linear embedding in the original feature space, and then quantize such embedding to binary codes. Such a two-step coding is problematic and less optimized. Besides, the off-line learning is extremely time and memory consuming, which needs to calculate the similarity matrix of the original data. In this paper, we propose a novel hashing algorithm, termed discrete locality linear embedding hashing (DLLH), which well addresses the above challenges. The DLLH directly reconstructs the manifold structure in the Hamming space, which learns optimal hash codes to maintain the local linear relationship of data points. To learn discrete locally linear embeddingcodes, we further propose a discrete optimization algorithm with an iterative parameters updating scheme. Moreover, an anchor-based acceleration scheme, termed Anchor-DLLH, is further introduced, which approximates the large similarity matrix by the product of two low-rank matrices. Experimental results on three widely used benchmark data sets, i.e., CIFAR10, NUS-WIDE, and YouTube Face, have shown superior performance of the proposed DLLH over the state-of-the-art approaches.

New developments in fruit and vegetables consumption in the period 1999-2004 in Denmark - a quantile regression approach

DEFF Research Database (Denmark)

Hansen, Aslak Hedemann

2008-01-01

The development in the consumption of fruit and vegetables in the period 1999-2004 in Denmark was investigated using quantile regression and two previously overlooked problems were identified. First, the change in the ten percent quantile samples decreased. This could have been caused by changes ...

Beyond the mean estimate: a quantile regression analysis of inequalities in educational outcomes using INVALSI survey data

Directory of Open Access Journals (Sweden)

Antonella Costanzo

2017-09-01

Full Text Available Abstract The number of studies addressing issues of inequality in educational outcomes using cognitive achievement tests and variables from large-scale assessment data has increased. Here the value of using a quantile regression approach is compared with a classical regression analysis approach to study the relationships between educational outcomes and likely predictor variables. Italian primary school data from INVALSI large-scale assessments were analyzed using both quantile and standard regression approaches. Mathematics and reading scores were regressed on students' characteristics and geographical variables selected for their theoretical and policy relevance. The results demonstrated that, in Italy, the role of gender and immigrant status varied across the entire conditional distribution of students’ performance. Analogous results emerged pertaining to the difference in students’ performance across Italian geographic areas. These findings suggest that quantile regression analysis is a useful tool to explore the determinants and mechanisms of inequality in educational outcomes. A proper interpretation of quantile estimates may enable teachers to identify effective learning activities and help policymakers to develop tailored programs that increase equity in education.

Semiparametric nonlinear quantile regression model for financial returns

Czech Academy of Sciences Publication Activity Database

Avdulaj, Krenar; Baruník, Jozef

2017-01-01

Roč. 21, č. 1 (2017), s. 81-97 ISSN 1081-1826 R&D Projects: GA ČR(CZ) GBP402/12/G097 Institutional support: RVO:67985556 Keywords : copula quantile regression * realized volatility * value-at-risk Subject RIV: AH - Economic s OBOR OECD: Applied Economic s, Econometrics Impact factor: 0.649, year: 2016 http://library.utia.cas.cz/separaty/2017/E/avdulaj-0472346.pdf

Environmental determinants of different blood lead levels in children: a quantile analysis from a nationwide survey.

Science.gov (United States)

Etchevers, Anne; Le Tertre, Alain; Lucas, Jean-Paul; Bretin, Philippe; Oulhote, Youssef; Le Bot, Barbara; Glorennec, Philippe

2015-01-01

Blood lead levels (BLLs) have substantially decreased in recent decades in children in France. However, further reducing exposure is a public health goal because there is no clear toxicological threshold. The identification of the environmental determinants of BLLs as well as risk factors associated with high BLLs is important to update prevention strategies. We aimed to estimate the contribution of environmental sources of lead to different BLLs in children in France. We enrolled 484 children aged from 6months to 6years, in a nationwide cross-sectional survey in 2008-2009. We measured lead concentrations in blood and environmental samples (water, soils, household settled dusts, paints, cosmetics and traditional cookware). We performed two models: a multivariate generalized additive model on the geometric mean (GM), and a quantile regression model on the 10th, 25th, 50th, 75th and 90th quantile of BLLs. The GM of BLLs was 13.8μg/L (=1.38μg/dL) (95% confidence intervals (CI): 12.7-14.9) and the 90th quantile was 25.7μg/L (CI: 24.2-29.5). Household and common area dust, tap water, interior paint, ceramic cookware, traditional cosmetics, playground soil and dust, and environmental tobacco smoke were associated with the GM of BLLs. Household dust and tap water made the largest contributions to both the GM and the 90th quantile of BLLs. The concentration of lead in dust was positively correlated with all quantiles of BLLs even at low concentrations. Lead concentrations in tap water above 5μg/L were also positively correlated with the GM, 75th and 90th quantiles of BLLs in children drinking tap water. Preventative actions must target household settled dust and tap water to reduce the BLLs of children in France. The use of traditional cosmetics should be avoided whereas ceramic cookware should be limited to decorative purposes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Forecasting Uncertainty in Electricity Smart Meter Data by Boosting Additive Quantile Regression

KAUST Repository

Taieb, Souhaib Ben

2016-03-02

Smart electricity meters are currently deployed in millions of households to collect detailed individual electricity consumption data. Compared with traditional electricity data based on aggregated consumption, smart meter data are much more volatile and less predictable. There is a need within the energy industry for probabilistic forecasts of household electricity consumption to quantify the uncertainty of future electricity demand in order to undertake appropriate planning of generation and distribution. We propose to estimate an additive quantile regression model for a set of quantiles of the future distribution using a boosting procedure. By doing so, we can benefit from flexible and interpretable models, which include an automatic variable selection. We compare our approach with three benchmark methods on both aggregated and disaggregated scales using a smart meter data set collected from 3639 households in Ireland at 30-min intervals over a period of 1.5 years. The empirical results demonstrate that our approach based on quantile regression provides better forecast accuracy for disaggregated demand, while the traditional approach based on a normality assumption (possibly after an appropriate Box-Cox transformation) is a better approximation for aggregated demand. These results are particularly useful since more energy data will become available at the disaggregated level in the future.

Local Fractional Laplace Variational Iteration Method for Solving Linear Partial Differential Equations with Local Fractional Derivative

Directory of Open Access Journals (Sweden)

Ai-Min Yang

2014-01-01

Full Text Available The local fractional Laplace variational iteration method was applied to solve the linear local fractional partial differential equations. The local fractional Laplace variational iteration method is coupled by the local fractional variational iteration method and Laplace transform. The nondifferentiable approximate solutions are obtained and their graphs are also shown.

Domestic Multinationals and Foreign-Owned Firms in Italy: Evidence from Quantile Regression

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Grasseni, Mara

2010-06-01

Full Text Available This paper investigates the performance differences across and within foreign-owned firms and domestic multinationals in Italy. Used for the empirical analysis are non-parametric tests based on the concept of first order stochastic dominance and quantile regression technique. The firm-level analysis distinguishes between foreign-owned firms of different nationalities and domestic MNEs according to the location of their FDI, and it focuses not only on productivity but also on differences in average wages, capital intensity, and financial and non-financial indicators, namely ROS, ROI and debt leverage. Overall, the results provide evidence of remarkable heterogeneity across and within multinationals. In particular, it seems not possible to identify a clear foreign advantage at least in terms of productivity, because foreign-owned firms do not outperform domestic multinationals. Interesting results are obtained when focusing on ROS and ROI, where the profitability gaps change as one moves from the bottom to the top of the conditional distribution. Domestic multinationals investing only in developed countries present higher ROS and ROI compared with the subgroups of foreign-owned firms, but only at the lower quantiles, while at the upper quantiles the advantage seems to favour foreign firms. Finally, in regard to domestic multinationals, there is strong evidence that those active only in less developed countries persistently exhibit the worst performances

Object matching using a locally affine invariant and linear programming techniques.

Science.gov (United States)

Li, Hongsheng; Huang, Xiaolei; He, Lei

2013-02-01

In this paper, we introduce a new matching method based on a novel locally affine-invariant geometric constraint and linear programming techniques. To model and solve the matching problem in a linear programming formulation, all geometric constraints should be able to be exactly or approximately reformulated into a linear form. This is a major difficulty for this kind of matching algorithm. We propose a novel locally affine-invariant constraint which can be exactly linearized and requires a lot fewer auxiliary variables than other linear programming-based methods do. The key idea behind it is that each point in the template point set can be exactly represented by an affine combination of its neighboring points, whose weights can be solved easily by least squares. Errors of reconstructing each matched point using such weights are used to penalize the disagreement of geometric relationships between the template points and the matched points. The resulting overall objective function can be solved efficiently by linear programming techniques. Our experimental results on both rigid and nonrigid object matching show the effectiveness of the proposed algorithm.

Divergence from, and Convergence to, Uniformity of Probability Density Quantiles

Directory of Open Access Journals (Sweden)

Robert G. Staudte

2018-04-01

Full Text Available We demonstrate that questions of convergence and divergence regarding shapes of distributions can be carried out in a location- and scale-free environment. This environment is the class of probability density quantiles (pdQs, obtained by normalizing the composition of the density with the associated quantile function. It has earlier been shown that the pdQ is representative of a location-scale family and carries essential information regarding shape and tail behavior of the family. The class of pdQs are densities of continuous distributions with common domain, the unit interval, facilitating metric and semi-metric comparisons. The Kullback–Leibler divergences from uniformity of these pdQs are mapped to illustrate their relative positions with respect to uniformity. To gain more insight into the information that is conserved under the pdQ mapping, we repeatedly apply the pdQ mapping and find that further applications of it are quite generally entropy increasing so convergence to the uniform distribution is investigated. New fixed point theorems are established with elementary probabilistic arguments and illustrated by examples.

Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings.

Science.gov (United States)

Choi, Jae-Seok; Kim, Munchurl

2017-03-01

Super-resolution (SR) has become more vital, because of its capability to generate high-quality ultra-high definition (UHD) high-resolution (HR) images from low-resolution (LR) input images. Conventional SR methods entail high computational complexity, which makes them difficult to be implemented for up-scaling of full-high-definition input images into UHD-resolution images. Nevertheless, our previous super-interpolation (SI) method showed a good compromise between Peak-Signal-to-Noise Ratio (PSNR) performances and computational complexity. However, since SI only utilizes simple linear mappings, it may fail to precisely reconstruct HR patches with complex texture. In this paper, we present a novel SR method, which inherits the large-to-small patch conversion scheme from SI but uses global regression based on local linear mappings (GLM). Thus, our new SR method is called GLM-SI. In GLM-SI, each LR input patch is divided into 25 overlapped subpatches. Next, based on the local properties of these subpatches, 25 different local linear mappings are applied to the current LR input patch to generate 25 HR patch candidates, which are then regressed into one final HR patch using a global regressor. The local linear mappings are learned cluster-wise in our off-line training phase. The main contribution of this paper is as follows: Previously, linear-mapping-based conventional SR methods, including SI only used one simple yet coarse linear mapping to each patch to reconstruct its HR version. On the contrary, for each LR input patch, our GLM-SI is the first to apply a combination of multiple local linear mappings, where each local linear mapping is found according to local properties of the current LR patch. Therefore, it can better approximate nonlinear LR-to-HR mappings for HR patches with complex texture. Experiment results show that the proposed GLM-SI method outperforms most of the state-of-the-art methods, and shows comparable PSNR performance with much lower

Wage Inequality and Return to Education in Indonesia: Quantile Regression Analysis

Directory of Open Access Journals (Sweden)

Restuning Dyah Widyanti

2018-01-01

Full Text Available It is essential to the government to recognize the factors causing the increasing trend of income inequality in Indonesia since the Gini coefficient increased between 1996 and 2016. Moreover, wage inequality, which represented by high percentile and low percentile of income, also shows widening gap since 2003. This study focuses on the factors of wage inequality acceleration through the supply side approach that follows the Mincerian wage equation model. Specifically, this paper aims to investigate the association between the return to education and wage inequality in Indonesia. The quantile regression method is applied to compute the return on the investment at different points of the wage distribution. The main finding is that education contributes to an increasing wage inequality due to the significant variation in the rate of return to education in different quantile and as increasing wage dispersion within the same education.DOI: 10.15408/sjie.v7i1.6071

Gait recognition using kinect and locally linear embedding ...

African Journals Online (AJOL)

This paper presents the use of locally linear embedding (LLE) as feature extraction technique for classifying a person's identity based on their walking gait patterns. Skeleton data acquired from Microsoft Kinect camera were used as an input for (1). Multilayer Perceptron (MLP) and (2). LLE with MLP. The MLP classification ...

On Estimating Quantiles Using Auxiliary Information

Directory of Open Access Journals (Sweden)

Berger Yves G.

2015-03-01

Full Text Available We propose a transformation-based approach for estimating quantiles using auxiliary information. The proposed estimators can be easily implemented using a regression estimator. We show that the proposed estimators are consistent and asymptotically unbiased. The main advantage of the proposed estimators is their simplicity. Despite the fact the proposed estimators are not necessarily more efficient than their competitors, they offer a good compromise between accuracy and simplicity. They can be used under single and multistage sampling designs with unequal selection probabilities. A simulation study supports our finding and shows that the proposed estimators are robust and of an acceptable accuracy compared to alternative estimators, which can be more computationally intensive.

Prediction intervals for future BMI values of individual children - a non-parametric approach by quantile boosting

Directory of Open Access Journals (Sweden)

Mayr Andreas

2012-01-01

Full Text Available Abstract Background The construction of prediction intervals (PIs for future body mass index (BMI values of individual children based on a recent German birth cohort study with n = 2007 children is problematic for standard parametric approaches, as the BMI distribution in childhood is typically skewed depending on age. Methods We avoid distributional assumptions by directly modelling the borders of PIs by additive quantile regression, estimated by boosting. We point out the concept of conditional coverage to prove the accuracy of PIs. As conditional coverage can hardly be evaluated in practical applications, we conduct a simulation study before fitting child- and covariate-specific PIs for future BMI values and BMI patterns for the present data. Results The results of our simulation study suggest that PIs fitted by quantile boosting cover future observations with the predefined coverage probability and outperform the benchmark approach. For the prediction of future BMI values, quantile boosting automatically selects informative covariates and adapts to the age-specific skewness of the BMI distribution. The lengths of the estimated PIs are child-specific and increase, as expected, with the age of the child. Conclusions Quantile boosting is a promising approach to construct PIs with correct conditional coverage in a non-parametric way. It is in particular suitable for the prediction of BMI patterns depending on covariates, since it provides an interpretable predictor structure, inherent variable selection properties and can even account for longitudinal data structures.

Predicting birth weight with conditionally linear transformation models.

Science.gov (United States)

Möst, Lisa; Schmid, Matthias; Faschingbauer, Florian; Hothorn, Torsten

2016-12-01

Low and high birth weight (BW) are important risk factors for neonatal morbidity and mortality. Gynecologists must therefore accurately predict BW before delivery. Most prediction formulas for BW are based on prenatal ultrasound measurements carried out within one week prior to birth. Although successfully used in clinical practice, these formulas focus on point predictions of BW but do not systematically quantify uncertainty of the predictions, i.e. they result in estimates of the conditional mean of BW but do not deliver prediction intervals. To overcome this problem, we introduce conditionally linear transformation models (CLTMs) to predict BW. Instead of focusing only on the conditional mean, CLTMs model the whole conditional distribution function of BW given prenatal ultrasound parameters. Consequently, the CLTM approach delivers both point predictions of BW and fetus-specific prediction intervals. Prediction intervals constitute an easy-to-interpret measure of prediction accuracy and allow identification of fetuses subject to high prediction uncertainty. Using a data set of 8712 deliveries at the Perinatal Centre at the University Clinic Erlangen (Germany), we analyzed variants of CLTMs and compared them to standard linear regression estimation techniques used in the past and to quantile regression approaches. The best-performing CLTM variant was competitive with quantile regression and linear regression approaches in terms of conditional coverage and average length of the prediction intervals. We propose that CLTMs be used because they are able to account for possible heteroscedasticity, kurtosis, and skewness of the distribution of BWs. © The Author(s) 2014.

Heterogeneous effects of oil shocks on exchange rates: evidence from a quantile regression approach.

Science.gov (United States)

Su, Xianfang; Zhu, Huiming; You, Wanhai; Ren, Yinghua

2016-01-01

The determinants of exchange rates have attracted considerable attention among researchers over the past several decades. Most studies, however, ignore the possibility that the impact of oil shocks on exchange rates could vary across the exchange rate returns distribution. We employ a quantile regression approach to address this issue. Our results indicate that the effect of oil shocks on exchange rates is heterogeneous across quantiles. A large US depreciation or appreciation tends to heighten the effects of oil shocks on exchange rate returns. Positive oil demand shocks lead to appreciation pressures in oil-exporting countries and this result is robust across lower and upper return distributions. These results offer rich and useful information for investors and decision-makers.

Violations of local equilibrium and linear response in classical lattice systems

International Nuclear Information System (INIS)

Aoki, Kenichiro; Kusnezov, Dimitri

2003-01-01

We quantitatively and systematically analyze how local equilibrium, and linear response in transport are violated as systems move far from equilibrium. This is done by studying heat flow in classical lattice models with and without bulk transport behavior, in 1-3 dimensions, at various temperatures. Equations of motion for the system are integrated numerically to construct the non-equilibrium steady states. Linear response and local equilibrium assumptions are seen to break down in a similar manner. We quantify the breakdown through the analysis of both microscopic and macroscopic observables and examine its transformation properties under general redefinitions of the non-equilibrium temperature

Using Gamma and Quantile Regressions to Explore the Association between Job Strain and Adiposity in the ELSA-Brasil Study: Does Gender Matter?

Science.gov (United States)

Fonseca, Maria de Jesus Mendes da; Juvanhol, Leidjaira Lopes; Rotenberg, Lúcia; Nobre, Aline Araújo; Griep, Rosane Härter; Alves, Márcia Guimarães de Mello; Cardoso, Letícia de Oliveira; Giatti, Luana; Nunes, Maria Angélica; Aquino, Estela M L; Chor, Dóra

2017-11-17

This paper explores the association between job strain and adiposity, using two statistical analysis approaches and considering the role of gender. The research evaluated 11,960 active baseline participants (2008-2010) in the ELSA-Brasil study. Job strain was evaluated through a demand-control questionnaire, while body mass index (BMI) and waist circumference (WC) were evaluated in continuous form. The associations were estimated using gamma regression models with an identity link function. Quantile regression models were also estimated from the final set of co-variables established by gamma regression. The relationship that was found varied by analytical approach and gender. Among the women, no association was observed between job strain and adiposity in the fitted gamma models. In the quantile models, a pattern of increasing effects of high strain was observed at higher BMI and WC distribution quantiles. Among the men, high strain was associated with adiposity in the gamma regression models. However, when quantile regression was used, that association was found not to be homogeneous across outcome distributions. In addition, in the quantile models an association was observed between active jobs and BMI. Our results point to an association between job strain and adiposity, which follows a heterogeneous pattern. Modelling strategies can produce different results and should, accordingly, be used to complement one another.

Quantile-based Bayesian maximum entropy approach for spatiotemporal modeling of ambient air quality levels.

Science.gov (United States)

Yu, Hwa-Lung; Wang, Chih-Hsin

2013-02-05

Understanding the daily changes in ambient air quality concentrations is important to the assessing human exposure and environmental health. However, the fine temporal scales (e.g., hourly) involved in this assessment often lead to high variability in air quality concentrations. This is because of the complex short-term physical and chemical mechanisms among the pollutants. Consequently, high heterogeneity is usually present in not only the averaged pollution levels, but also the intraday variance levels of the daily observations of ambient concentration across space and time. This characteristic decreases the estimation performance of common techniques. This study proposes a novel quantile-based Bayesian maximum entropy (QBME) method to account for the nonstationary and nonhomogeneous characteristics of ambient air pollution dynamics. The QBME method characterizes the spatiotemporal dependence among the ambient air quality levels based on their location-specific quantiles and accounts for spatiotemporal variations using a local weighted smoothing technique. The epistemic framework of the QBME method can allow researchers to further consider the uncertainty of space-time observations. This study presents the spatiotemporal modeling of daily CO and PM10 concentrations across Taiwan from 1998 to 2009 using the QBME method. Results show that the QBME method can effectively improve estimation accuracy in terms of lower mean absolute errors and standard deviations over space and time, especially for pollutants with strong nonhomogeneous variances across space. In addition, the epistemic framework can allow researchers to assimilate the site-specific secondary information where the observations are absent because of the common preferential sampling issues of environmental data. The proposed QBME method provides a practical and powerful framework for the spatiotemporal modeling of ambient pollutants.

Estimating Mean and Variance Through Quantiles : An Experimental Comparison of Different Methods

NARCIS (Netherlands)

Moors, J.J.A.; Strijbosch, L.W.G.; van Groenendaal, W.J.H.

2002-01-01

If estimates of mean and variance are needed and only experts' opinions are available, the literature agrees that it is wise behaviour to ask only for their (subjective) estimates of quantiles: from these, estimates of the desired parameters are calculated.Quite a number of methods have been

Estimating monotonic rates from biological data using local linear regression.

Science.gov (United States)

Olito, Colin; White, Craig R; Marshall, Dustin J; Barneche, Diego R

2017-03-01

Accessing many fundamental questions in biology begins with empirical estimation of simple monotonic rates of underlying biological processes. Across a variety of disciplines, ranging from physiology to biogeochemistry, these rates are routinely estimated from non-linear and noisy time series data using linear regression and ad hoc manual truncation of non-linearities. Here, we introduce the R package LoLinR, a flexible toolkit to implement local linear regression techniques to objectively and reproducibly estimate monotonic biological rates from non-linear time series data, and demonstrate possible applications using metabolic rate data. LoLinR provides methods to easily and reliably estimate monotonic rates from time series data in a way that is statistically robust, facilitates reproducible research and is applicable to a wide variety of research disciplines in the biological sciences. © 2017. Published by The Company of Biologists Ltd.

The Determinants of Equity Risk and Their Forecasting Implications: A Quantile Regression Perspective

Directory of Open Access Journals (Sweden)

Giovanni Bonaccolto

2016-07-01

Full Text Available Several market and macro-level variables influence the evolution of equity risk in addition to the well-known volatility persistence. However, the impact of those covariates might change depending on the risk level, being different between low and high volatility states. By combining equity risk estimates, obtained from the Realized Range Volatility, corrected for microstructure noise and jumps, and quantile regression methods, we evaluate the forecasting implications of the equity risk determinants in different volatility states and, without distributional assumptions on the realized range innovations, we recover both the points and the conditional distribution forecasts. In addition, we analyse how the the relationships among the involved variables evolve over time, through a rolling window procedure. The results show evidence of the selected variables’ relevant impacts and, particularly during periods of market stress, highlight heterogeneous effects across quantiles.

Localization of the eigenvalues of linear integral equations with applications to linear ordinary differential equations.

Science.gov (United States)

Sloss, J. M.; Kranzler, S. K.

1972-01-01

The equivalence of a considered integral equation form with an infinite system of linear equations is proved, and the localization of the eigenvalues of the infinite system is expressed. Error estimates are derived, and the problems of finding upper bounds and lower bounds for the eigenvalues are solved simultaneously.

Linear local stability of electrostatic drift modes in helical systems

International Nuclear Information System (INIS)

Yamagishi, O.; Nakajima, N.; Sugama, H.; Nakamura, Y.

2003-01-01

We investigate the stability of the drift wave in helical systems. For this purpose, we solve the linear local gyrokinetic-Poisson equation, in the electrostatic regime. As a model of helical plasmas, Large helical Device (LHD) is considered. The equation we apply is rather exact in the framework of linear gyrokinetic theory, where only the approximation is the ballooning representation. In this paper, we consider only collisionless cases. All the frequency regime can be naturally reated without any assumptions, and in such cases, ion temperature gradient modes (ITG), trapped electron modes (TEM), and electron temperature gradient modes (ETG) are expected to become unstable linearly independently. (orig.)

Trait Mindfulness as a Limiting Factor for Residual Depressive Symptoms: An Explorative Study Using Quantile Regression

Science.gov (United States)

Radford, Sholto; Eames, Catrin; Brennan, Kate; Lambert, Gwladys; Crane, Catherine; Williams, J. Mark G.; Duggan, Danielle S.; Barnhofer, Thorsten

2014-01-01

Mindfulness has been suggested to be an important protective factor for emotional health. However, this effect might vary with regard to context. This study applied a novel statistical approach, quantile regression, in order to investigate the relation between trait mindfulness and residual depressive symptoms in individuals with a history of recurrent depression, while taking into account symptom severity and number of episodes as contextual factors. Rather than fitting to a single indicator of central tendency, quantile regression allows exploration of relations across the entire range of the response variable. Analysis of self-report data from 274 participants with a history of three or more previous episodes of depression showed that relatively higher levels of mindfulness were associated with relatively lower levels of residual depressive symptoms. This relationship was most pronounced near the upper end of the response distribution and moderated by the number of previous episodes of depression at the higher quantiles. The findings suggest that with lower levels of mindfulness, residual symptoms are less constrained and more likely to be influenced by other factors. Further, the limiting effect of mindfulness on residual symptoms is most salient in those with higher numbers of episodes. PMID:24988072

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

Science.gov (United States)

Xu, Jiucheng; Mu, Huiyu; Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC 2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.

Linear-scaling evaluation of the local energy in quantum Monte Carlo

International Nuclear Information System (INIS)

Austin, Brian; Aspuru-Guzik, Alan; Salomon-Ferrer, Romelia; Lester, William A. Jr.

2006-01-01

For atomic and molecular quantum Monte Carlo calculations, most of the computational effort is spent in the evaluation of the local energy. We describe a scheme for reducing the computational cost of the evaluation of the Slater determinants and correlation function for the correlated molecular orbital (CMO) ansatz. A sparse representation of the Slater determinants makes possible efficient evaluation of molecular orbitals. A modification to the scaled distance function facilitates a linear scaling implementation of the Schmidt-Moskowitz-Boys-Handy (SMBH) correlation function that preserves the efficient matrix multiplication structure of the SMBH function. For the evaluation of the local energy, these two methods lead to asymptotic linear scaling with respect to the molecule size

Least-squares reverse time migration with local Radon-based preconditioning

KAUST Repository

Dutta, Gaurav; Giboli, Matteo; Agut, Cyril; Williamson, Paul; Schuster, Gerard T.

2017-01-01

amplitudes of the local dips or assigned using quantile measures. Numerical tests on synthetic and field data validate the effectiveness of our approach in producing images with good S/N and fewer aliasing artifacts when compared with standard RTM or standard

Analysis of quantile regression as alternative to ordinary least squares

OpenAIRE

Ibrahim Abdullahi; Abubakar Yahaya

2015-01-01

In this article, an alternative to ordinary least squares (OLS) regression based on analytical solution in the Statgraphics software is considered, and this alternative is no other than quantile regression (QR) model. We also present goodness of fit statistic as well as approximate distributions of the associated test statistics for the parameters. Furthermore, we suggest a goodness of fit statistic called the least absolute deviation (LAD) coefficient of determination. The procedure is well ...

A quantile regression analysis of the rebound effect: Evidence from the 2009 National Household Transportation Survey in the United States

International Nuclear Information System (INIS)

Su Qing

2012-01-01

This paper applies quantile regression method to measure the rebound effect and differentiate it with respect to demand for mobility using the 2009 National Household Transportation Survey (NHTS). The quantile regression results indicate that the rebound effect varies with the distribution of vehicle miles traveled (VMT), ranging between 0.11 and 0.19. Road network density and population density also play an important role in determining travel demand. Regression results indicate that travelers living in areas with higher road network density travel more miles although this positive impact consistently declines along the VMT distribution. Travelers living in areas with population density of at most 3000 persons per square miles travel more miles than those living in higher density areas. The quantile regression results also indicate that the impact of income is positive but declines consistently along the VMT distribution. - Highlights: ► This paper examines the magnitude of rebound effect using the 2009 National Household Transportation Survey data. ► Quantile regression method is applied to capture the variation of the rebound effect given the heterogeneous travelers. ► The regression results indicate that the rebound effect varies with VMT distribution. ► The estimated rebound effect fluctuates between 0.11 and 0.19.

Quantile Forecasting for Credit Risk Management Using Possibly Mis-specified Hidden Markov Models

NARCIS (Netherlands)

Banachewicz, K.P.; Lucas, A.

2008-01-01

Recent models for credit risk management make use of hidden Markov models (HMMs). HMMs are used to forecast quantiles of corporate default rates. Little research has been done on the quality of such forecasts if the underlying HMM is potentially misspecified. In this paper, we focus on

Early Home Activities and Oral Language Skills in Middle Childhood: A Quantile Analysis

Science.gov (United States)

Law, James; Rush, Robert; King, Tom; Westrupp, Elizabeth; Reilly, Sheena

2018-01-01

Oral language development is a key outcome of elementary school, and it is important to identify factors that predict it most effectively. Commonly researchers use ordinary least squares regression with conclusions restricted to average performance conditional on relevant covariates. Quantile regression offers a more sophisticated alternative.…

Local energy decay for linear wave equations with variable coefficients

Science.gov (United States)

Ikehata, Ryo

2005-06-01

A uniform local energy decay result is derived to the linear wave equation with spatial variable coefficients. We deal with this equation in an exterior domain with a star-shaped complement. Our advantage is that we do not assume any compactness of the support on the initial data, and its proof is quite simple. This generalizes a previous famous result due to Morawetz [The decay of solutions of the exterior initial-boundary value problem for the wave equation, Comm. Pure Appl. Math. 14 (1961) 561-568]. In order to prove local energy decay, we mainly apply two types of ideas due to Ikehata-Matsuyama [L2-behaviour of solutions to the linear heat and wave equations in exterior domains, Sci. Math. Japon. 55 (2002) 33-42] and Todorova-Yordanov [Critical exponent for a nonlinear wave equation with damping, J. Differential Equations 174 (2001) 464-489].

Local beam angle optimization with linear programming and gradient search

International Nuclear Information System (INIS)

Craft, David

2007-01-01

The optimization of beam angles in IMRT planning is still an open problem, with literature focusing on heuristic strategies and exhaustive searches on discrete angle grids. We show how a beam angle set can be locally refined in a continuous manner using gradient-based optimization in the beam angle space. The gradient is derived using linear programming duality theory. Applying this local search to 100 random initial angle sets of a phantom pancreatic case demonstrates the method, and highlights the many-local-minima aspect of the BAO problem. Due to this function structure, we recommend a search strategy of a thorough global search followed by local refinement at promising beam angle sets. Extensions to nonlinear IMRT formulations are discussed. (note)

Locally Linear Embedding of Local Orthogonal Least Squares Images for Face Recognition

Science.gov (United States)

Hafizhelmi Kamaru Zaman, Fadhlan

2018-03-01

Dimensionality reduction is very important in face recognition since it ensures that high-dimensionality data can be mapped to lower dimensional space without losing salient and integral facial information. Locally Linear Embedding (LLE) has been previously used to serve this purpose, however, the process of acquiring LLE features requires high computation and resources. To overcome this limitation, we propose a locally-applied Local Orthogonal Least Squares (LOLS) model can be used as initial feature extraction before the application of LLE. By construction of least squares regression under orthogonal constraints we can preserve more discriminant information in the local subspace of facial features while reducing the overall features into a more compact form that we called LOLS images. LLE can then be applied on the LOLS images to maps its representation into a global coordinate system of much lower dimensionality. Several experiments carried out using publicly available face datasets such as AR, ORL, YaleB, and FERET under Single Sample Per Person (SSPP) constraint demonstrates that our proposed method can reduce the time required to compute LLE features while delivering better accuracy when compared to when either LLE or OLS alone is used. Comparison against several other feature extraction methods and more recent feature-learning method such as state-of-the-art Convolutional Neural Networks (CNN) also reveal the superiority of the proposed method under SSPP constraint.

Linear Time Local Approximation Algorithm for Maximum Stable Marriage

Directory of Open Access Journals (Sweden)

Zoltán Király

2013-08-01

Full Text Available We consider a two-sided market under incomplete preference lists with ties, where the goal is to find a maximum size stable matching. The problem is APX-hard, and a 3/2-approximation was given by McDermid [1]. This algorithm has a non-linear running time, and, more importantly needs global knowledge of all preference lists. We present a very natural, economically reasonable, local, linear time algorithm with the same ratio, using some ideas of Paluch [2]. In this algorithm every person make decisions using only their own list, and some information asked from members of these lists (as in the case of the famous algorithm of Gale and Shapley. Some consequences to the Hospitals/Residents problem are also discussed.

The effect of foreign aid on corruption: A quantile regression approach

OpenAIRE

Okada, Keisuke; Samreth, Sovannroeun

2011-01-01

This paper investigates the effect of foreign aid on corruption using a quantile regression method. Our estimation results illustrate that foreign aid generally lessens corruption and, in particular, its reduction effect is larger in countries with low levels of corruption. In addition, considering foreign aid by donors, our analysis indicates that while multilateral aid has a larger reduction impact on corruption, bilateral aid from the world’s leading donors, such as France, the United King...

What a Quantile Approach Can Tell Us about Returns to Education in Europe

Science.gov (United States)

Prieto-Rodriguez, Juan; Barros, Carlos Pestana; Vieira, Jose A. C.

2008-01-01

This paper seeks to analyse the relationship between wages and education at a European level, using a quantile regression in order to be able to extend the study along the whole wage distribution. This analysis is carried out for a sample of 14 European countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy,…

Local linearization methods for the numerical integration of ordinary differential equations: An overview

International Nuclear Information System (INIS)

Jimenez, J.C.

2009-06-01

Local Linearization (LL) methods conform a class of one-step explicit integrators for ODEs derived from the following primary and common strategy: the vector field of the differential equation is locally (piecewise) approximated through a first-order Taylor expansion at each time step, thus obtaining successive linear equations that are explicitly integrated. Hereafter, the LL approach may include some additional strategies to improve that basic affine approximation. Theoretical and practical results have shown that the LL integrators have a number of convenient properties. These include arbitrary order of convergence, A-stability, linearization preserving, regularity under quite general conditions, preservation of the dynamics of the exact solution around hyperbolic equilibrium points and periodic orbits, integration of stiff and high-dimensional equations, low computational cost, and others. In this paper, a review of the LL methods and their properties is presented. (author)

Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network.

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Gilra, Aditya; Gerstner, Wulfram

2017-11-27

The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically.

High Quantile of Environmental Screening Methods, San Joaquin Valley CA, 2013, Occidental College of Los Angeles

Data.gov (United States)

U.S. Environmental Protection Agency — This layer combines the high quantiles of the CES, CEVA, and EJSM layers so that viewers can see the overlap of â??hot spotsâ?? for each method. This layer was...

A Bayesian nonparametric approach to causal inference on quantiles.

Science.gov (United States)

Xu, Dandan; Daniels, Michael J; Winterstein, Almut G

2018-02-25

We propose a Bayesian nonparametric approach (BNP) for causal inference on quantiles in the presence of many confounders. In particular, we define relevant causal quantities and specify BNP models to avoid bias from restrictive parametric assumptions. We first use Bayesian additive regression trees (BART) to model the propensity score and then construct the distribution of potential outcomes given the propensity score using a Dirichlet process mixture (DPM) of normals model. We thoroughly evaluate the operating characteristics of our approach and compare it to Bayesian and frequentist competitors. We use our approach to answer an important clinical question involving acute kidney injury using electronic health records. © 2018, The International Biometric Society.

Locally linear approximation for Kernel methods : the Railway Kernel

OpenAIRE

Muñoz, Alberto; González, Javier

2008-01-01

In this paper we present a new kernel, the Railway Kernel, that works properly for general (nonlinear) classification problems, with the interesting property that acts locally as a linear kernel. In this way, we avoid potential problems due to the use of a general purpose kernel, like the RBF kernel, as the high dimension of the induced feature space. As a consequence, following our methodology the number of support vectors is much lower and, therefore, the generalization capab...

Accelerating Approximate Bayesian Computation with Quantile Regression: application to cosmological redshift distributions

Science.gov (United States)

Kacprzak, T.; Herbel, J.; Amara, A.; Réfrégier, A.

2018-02-01

Approximate Bayesian Computation (ABC) is a method to obtain a posterior distribution without a likelihood function, using simulations and a set of distance metrics. For that reason, it has recently been gaining popularity as an analysis tool in cosmology and astrophysics. Its drawback, however, is a slow convergence rate. We propose a novel method, which we call qABC, to accelerate ABC with Quantile Regression. In this method, we create a model of quantiles of distance measure as a function of input parameters. This model is trained on a small number of simulations and estimates which regions of the prior space are likely to be accepted into the posterior. Other regions are then immediately rejected. This procedure is then repeated as more simulations are available. We apply it to the practical problem of estimation of redshift distribution of cosmological samples, using forward modelling developed in previous work. The qABC method converges to nearly same posterior as the basic ABC. It uses, however, only 20% of the number of simulations compared to basic ABC, achieving a fivefold gain in execution time for our problem. For other problems the acceleration rate may vary; it depends on how close the prior is to the final posterior. We discuss possible improvements and extensions to this method.

Bayesian estimation of extreme flood quantiles using a rainfall-runoff model and a stochastic daily rainfall generator

Science.gov (United States)

Costa, Veber; Fernandes, Wilson

2017-11-01

Extreme flood estimation has been a key research topic in hydrological sciences. Reliable estimates of such events are necessary as structures for flood conveyance are continuously evolving in size and complexity and, as a result, their failure-associated hazards become more and more pronounced. Due to this fact, several estimation techniques intended to improve flood frequency analysis and reducing uncertainty in extreme quantile estimation have been addressed in the literature in the last decades. In this paper, we develop a Bayesian framework for the indirect estimation of extreme flood quantiles from rainfall-runoff models. In the proposed approach, an ensemble of long daily rainfall series is simulated with a stochastic generator, which models extreme rainfall amounts with an upper-bounded distribution function, namely, the 4-parameter lognormal model. The rationale behind the generation model is that physical limits for rainfall amounts, and consequently for floods, exist and, by imposing an appropriate upper bound for the probabilistic model, more plausible estimates can be obtained for those rainfall quantiles with very low exceedance probabilities. Daily rainfall time series are converted into streamflows by routing each realization of the synthetic ensemble through a conceptual hydrologic model, the Rio Grande rainfall-runoff model. Calibration of parameters is performed through a nonlinear regression model, by means of the specification of a statistical model for the residuals that is able to accommodate autocorrelation, heteroscedasticity and nonnormality. By combining the outlined steps in a Bayesian structure of analysis, one is able to properly summarize the resulting uncertainty and estimating more accurate credible intervals for a set of flood quantiles of interest. The method for extreme flood indirect estimation was applied to the American river catchment, at the Folsom dam, in the state of California, USA. Results show that most floods

Examining Predictive Validity of Oral Reading Fluency Slope in Upper Elementary Grades Using Quantile Regression.

Science.gov (United States)

Cho, Eunsoo; Capin, Philip; Roberts, Greg; Vaughn, Sharon

2017-07-01

Within multitiered instructional delivery models, progress monitoring is a key mechanism for determining whether a child demonstrates an adequate response to instruction. One measure commonly used to monitor the reading progress of students is oral reading fluency (ORF). This study examined the extent to which ORF slope predicts reading comprehension outcomes for fifth-grade struggling readers ( n = 102) participating in an intensive reading intervention. Quantile regression models showed that ORF slope significantly predicted performance on a sentence-level fluency and comprehension assessment, regardless of the students' reading skills, controlling for initial ORF performance. However, ORF slope was differentially predictive of a passage-level comprehension assessment based on students' reading skills when controlling for initial ORF status. Results showed that ORF explained unique variance for struggling readers whose posttest performance was at the upper quantiles at the end of the reading intervention, but slope was not a significant predictor of passage-level comprehension for students whose reading problems were the most difficult to remediate.

Local correlation detection with linearity enhancement in streaming data

KAUST Repository

Xie, Qing

2013-01-01

This paper addresses the challenges in detecting the potential correlation between numerical data streams, which facilitates the research of data stream mining and pattern discovery. We focus on local correlation with delay, which may occur in burst at different time in different streams, and last for a limited period. The uncertainty on the correlation occurrence and the time delay make it diff cult to monitor the correlation online. Furthermore, the conventional correlation measure lacks the ability of ref ecting visual linearity, which is more desirable in reality. This paper proposes effective methods to continuously detect the correlation between data streams. Our approach is based on the Discrete Fourier Transform to make rapid cross-correlation calculation with time delay allowed. In addition, we introduce a shape-based similarity measure into the framework, which ref nes the results by representative trend patterns to enhance the signif cance of linearity. The similarity of proposed linear representations can quickly estimate the correlation, and the window sliding strategy in segment level improves the eff ciency for online detection. The empirical study demonstrates the accuracy of our detection approach, as well as more than 30% improvement of eff ciency. Copyright 2013 ACM.

Modelling the return distribution of salmon farming companies : a quantile regression approach

OpenAIRE

Jacobsen, Fredrik

2017-01-01

The salmon farming industry has gained increased attention from investors, portfolio managers, financial analysts and other stakeholders the recent years. Despite this development, very little is known about the risk and return of salmon farming company stocks, and especially how the relationship between risk and return varies under different market conditions, given the volatile nature of the salmon farming industry. We approach this problem by using quantile regression to examine the relati...

Fault Diagnosis of Supervision and Homogenization Distance Based on Local Linear Embedding Algorithm

Directory of Open Access Journals (Sweden)

Guangbin Wang

2015-01-01

Full Text Available In view of the problems of uneven distribution of reality fault samples and dimension reduction effect of locally linear embedding (LLE algorithm which is easily affected by neighboring points, an improved local linear embedding algorithm of homogenization distance (HLLE is developed. The method makes the overall distribution of sample points tend to be homogenization and reduces the influence of neighboring points using homogenization distance instead of the traditional Euclidean distance. It is helpful to choose effective neighboring points to construct weight matrix for dimension reduction. Because the fault recognition performance improvement of HLLE is limited and unstable, the paper further proposes a new local linear embedding algorithm of supervision and homogenization distance (SHLLE by adding the supervised learning mechanism. On the basis of homogenization distance, supervised learning increases the category information of sample points so that the same category of sample points will be gathered and the heterogeneous category of sample points will be scattered. It effectively improves the performance of fault diagnosis and maintains stability at the same time. A comparison of the methods mentioned above was made by simulation experiment with rotor system fault diagnosis, and the results show that SHLLE algorithm has superior fault recognition performance.

Nonlinear aeroacoustic characterization of Helmholtz resonators with a local-linear neuro-fuzzy network model

Science.gov (United States)

Förner, K.; Polifke, W.

2017-10-01

The nonlinear acoustic behavior of Helmholtz resonators is characterized by a data-based reduced-order model, which is obtained by a combination of high-resolution CFD simulation and system identification. It is shown that even in the nonlinear regime, a linear model is capable of describing the reflection behavior at a particular amplitude with quantitative accuracy. This observation motivates to choose a local-linear model structure for this study, which consists of a network of parallel linear submodels. A so-called fuzzy-neuron layer distributes the input signal over the linear submodels, depending on the root mean square of the particle velocity at the resonator surface. The resulting model structure is referred to as an local-linear neuro-fuzzy network. System identification techniques are used to estimate the free parameters of this model from training data. The training data are generated by CFD simulations of the resonator, with persistent acoustic excitation over a wide range of frequencies and sound pressure levels. The estimated nonlinear, reduced-order models show good agreement with CFD and experimental data over a wide range of amplitudes for several test cases.

Robust neural network with applications to credit portfolio data analysis.

Science.gov (United States)

Feng, Yijia; Li, Runze; Sudjianto, Agus; Zhang, Yiyun

2010-01-01

In this article, we study nonparametric conditional quantile estimation via neural network structure. We proposed an estimation method that combines quantile regression and neural network (robust neural network, RNN). It provides good smoothing performance in the presence of outliers and can be used to construct prediction bands. A Majorization-Minimization (MM) algorithm was developed for optimization. Monte Carlo simulation study is conducted to assess the performance of RNN. Comparison with other nonparametric regression methods (e.g., local linear regression and regression splines) in real data application demonstrate the advantage of the newly proposed procedure.

Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

Science.gov (United States)

Cannon, Alex J.

2018-01-01

Most bias correction algorithms used in climatology, for example quantile mapping, are applied to univariate time series. They neglect the dependence between different variables. Those that are multivariate often correct only limited measures of joint dependence, such as Pearson or Spearman rank correlation. Here, an image processing technique designed to transfer colour information from one image to another—the N-dimensional probability density function transform—is adapted for use as a multivariate bias correction algorithm (MBCn) for climate model projections/predictions of multiple climate variables. MBCn is a multivariate generalization of quantile mapping that transfers all aspects of an observed continuous multivariate distribution to the corresponding multivariate distribution of variables from a climate model. When applied to climate model projections, changes in quantiles of each variable between the historical and projection period are also preserved. The MBCn algorithm is demonstrated on three case studies. First, the method is applied to an image processing example with characteristics that mimic a climate projection problem. Second, MBCn is used to correct a suite of 3-hourly surface meteorological variables from the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) across a North American domain. Components of the Canadian Forest Fire Weather Index (FWI) System, a complicated set of multivariate indices that characterizes the risk of wildfire, are then calculated and verified against observed values. Third, MBCn is used to correct biases in the spatial dependence structure of CanRCM4 precipitation fields. Results are compared against a univariate quantile mapping algorithm, which neglects the dependence between variables, and two multivariate bias correction algorithms, each of which corrects a different form of inter-variable correlation structure. MBCn outperforms these alternatives, often by a large margin

Identifying the Safety Factors over Traffic Signs in State Roads using a Panel Quantile Regression Approach.

Science.gov (United States)

Šarić, Željko; Xu, Xuecai; Duan, Li; Babić, Darko

2018-06-20

This study intended to investigate the interactions between accident rate and traffic signs in state roads located in Croatia, and accommodate the heterogeneity attributed to unobserved factors. The data from 130 state roads between 2012 and 2016 were collected from Traffic Accident Database System maintained by the Republic of Croatia Ministry of the Interior. To address the heterogeneity, a panel quantile regression model was proposed, in which quantile regression model offers a more complete view and a highly comprehensive analysis of the relationship between accident rate and traffic signs, while the panel data model accommodates the heterogeneity attributed to unobserved factors. Results revealed that (1) low visibility of material damage (MD) and death or injured (DI) increased the accident rate; (2) the number of mandatory signs and the number of warning signs were more likely to reduce the accident rate; (3)average speed limit and the number of invalid traffic signs per km exhibited a high accident rate. To our knowledge, it's the first attempt to analyze the interactions between accident consequences and traffic signs by employing a panel quantile regression model; by involving the visibility, the present study demonstrates that the low visibility causes a relatively higher risk of MD and DI; It is noteworthy that average speed limit corresponds with accident rate positively; The number of mandatory signs and the number of warning signs are more likely to reduce the accident rate; The number of invalid traffic signs per km are significant for accident rate, thus regular maintenance should be kept for a safer roadway environment.

Use of Flood Seasonality in Pooling-Group Formation and Quantile Estimation: An Application in Great Britain

Science.gov (United States)

Formetta, Giuseppe; Bell, Victoria; Stewart, Elizabeth

2018-02-01

Regional flood frequency analysis is one of the most commonly applied methods for estimating extreme flood events at ungauged sites or locations with short measurement records. It is based on: (i) the definition of a homogeneous group (pooling-group) of catchments, and on (ii) the use of the pooling-group data to estimate flood quantiles. Although many methods to define a pooling-group (pooling schemes, PS) are based on catchment physiographic similarity measures, in the last decade methods based on flood seasonality similarity have been contemplated. In this paper, two seasonality-based PS are proposed and tested both in terms of the homogeneity of the pooling-groups they generate and in terms of the accuracy in estimating extreme flood events. The method has been applied in 420 catchments in Great Britain (considered as both gauged and ungauged) and compared against the current Flood Estimation Handbook (FEH) PS. Results for gauged sites show that, compared to the current PS, the seasonality-based PS performs better both in terms of homogeneity of the pooling-group and in terms of the accuracy of flood quantile estimates. For ungauged locations, a national-scale hydrological model has been used for the first time to quantify flood seasonality. Results show that in 75% of the tested locations the seasonality-based PS provides an improvement in the accuracy of the flood quantile estimates. The remaining 25% were located in highly urbanized, groundwater-dependent catchments. The promising results support the aspiration that large-scale hydrological models complement traditional methods for estimating design floods.

The algebra of non-local charges in non-linear sigma models

International Nuclear Information System (INIS)

Abdalla, E.; Abdalla, M.C.B.; Brunelli, J.C.; Zadra, A.

1993-07-01

We obtain the exact Dirac algebra obeyed by the conserved non-local charges in bosonic non-linear sigma models. Part of the computation is specialized for a symmetry group O(N). As it turns out the algebra corresponds to a cubic deformation of the Kac-Moody algebra. The non-linear terms are computed in closed form. In each Dirac bracket we only find highest order terms (as explained in the paper), defining a saturated algebra. We generalize the results for the presence of a Wess-Zumino term. The algebra is very similar to the previous one, containing now a calculable correction of order one unit lower. (author). 22 refs, 5 figs

From neurons to circuits: linear estimation of local field potentials

Science.gov (United States)

Rasch, Malte; Logthetis, Nikos K.; Kreiman, Gabriel

2010-01-01

Extracellular physiological recordings are typically separated into two frequency bands: local field potentials (LFPs, a circuit property) and spiking multi-unit activity (MUA). There has been increased interest in LFPs due to their correlation with fMRI measurements and the possibility of studying local processing and neuronal synchrony. To further understand the biophysical origin of LFPs, we asked whether it is possible to estimate their time course based on the spiking activity from the same or nearby electrodes. We used Signal Estimation Theory to show that a linear filter operation on the activity of one/few neurons can explain a significant fraction of the LFP time course in the macaque primary visual cortex. The linear filter used to estimate the LFPs had a stereotypical shape characterized by a sharp downstroke at negative time lags and a slower positive upstroke for positve time lags. The filter was similar across neocortical regions and behavioral conditions including spontaneous activity and visual stimulation. The estimations had a spatial resolution of ~1 mm and a temporal resolution of ~200 ms. By considering a causal filter, we observed a temporal asymmetry such that the positive time lags in the filter contributed more to the LFP estimation than negative time lags. Additionally, we showed that spikes occurring within ~10 ms of spikes from nearby neurons yielded better estimation accuracies than nonsynchronous spikes. In sum, our results suggest that at least some circuit-level local properties of the field potentials can be predicted from the activity of one or a few neurons. PMID:19889990

Gender Gaps in Mathematics, Science and Reading Achievements in Muslim Countries: A Quantile Regression Approach

Science.gov (United States)

Shafiq, M. Najeeb

2013-01-01

Using quantile regression analyses, this study examines gender gaps in mathematics, science, and reading in Azerbaijan, Indonesia, Jordan, the Kyrgyz Republic, Qatar, Tunisia, and Turkey among 15-year-old students. The analyses show that girls in Azerbaijan achieve as well as boys in mathematics and science and overachieve in reading. In Jordan,…

Error Analysis for RADAR Neighbor Matching Localization in Linear Logarithmic Strength Varying Wi-Fi Environment

Directory of Open Access Journals (Sweden)

Mu Zhou

2014-01-01

Full Text Available This paper studies the statistical errors for the fingerprint-based RADAR neighbor matching localization with the linearly calibrated reference points (RPs in logarithmic received signal strength (RSS varying Wi-Fi environment. To the best of our knowledge, little comprehensive analysis work has appeared on the error performance of neighbor matching localization with respect to the deployment of RPs. However, in order to achieve the efficient and reliable location-based services (LBSs as well as the ubiquitous context-awareness in Wi-Fi environment, much attention has to be paid to the highly accurate and cost-efficient localization systems. To this end, the statistical errors by the widely used neighbor matching localization are significantly discussed in this paper to examine the inherent mathematical relations between the localization errors and the locations of RPs by using a basic linear logarithmic strength varying model. Furthermore, based on the mathematical demonstrations and some testing results, the closed-form solutions to the statistical errors by RADAR neighbor matching localization can be an effective tool to explore alternative deployment of fingerprint-based neighbor matching localization systems in the future.

Error Analysis for RADAR Neighbor Matching Localization in Linear Logarithmic Strength Varying Wi-Fi Environment

Science.gov (United States)

Tian, Zengshan; Xu, Kunjie; Yu, Xiang

2014-01-01

This paper studies the statistical errors for the fingerprint-based RADAR neighbor matching localization with the linearly calibrated reference points (RPs) in logarithmic received signal strength (RSS) varying Wi-Fi environment. To the best of our knowledge, little comprehensive analysis work has appeared on the error performance of neighbor matching localization with respect to the deployment of RPs. However, in order to achieve the efficient and reliable location-based services (LBSs) as well as the ubiquitous context-awareness in Wi-Fi environment, much attention has to be paid to the highly accurate and cost-efficient localization systems. To this end, the statistical errors by the widely used neighbor matching localization are significantly discussed in this paper to examine the inherent mathematical relations between the localization errors and the locations of RPs by using a basic linear logarithmic strength varying model. Furthermore, based on the mathematical demonstrations and some testing results, the closed-form solutions to the statistical errors by RADAR neighbor matching localization can be an effective tool to explore alternative deployment of fingerprint-based neighbor matching localization systems in the future. PMID:24683349

Bayesian nonparametric inference on quantile residual life function: Application to breast cancer data.

Science.gov (United States)

Park, Taeyoung; Jeong, Jong-Hyeon; Lee, Jae Won

2012-08-15

There is often an interest in estimating a residual life function as a summary measure of survival data. For ease in presentation of the potential therapeutic effect of a new drug, investigators may summarize survival data in terms of the remaining life years of patients. Under heavy right censoring, however, some reasonably high quantiles (e.g., median) of a residual lifetime distribution cannot be always estimated via a popular nonparametric approach on the basis of the Kaplan-Meier estimator. To overcome the difficulties in dealing with heavily censored survival data, this paper develops a Bayesian nonparametric approach that takes advantage of a fully model-based but highly flexible probabilistic framework. We use a Dirichlet process mixture of Weibull distributions to avoid strong parametric assumptions on the unknown failure time distribution, making it possible to estimate any quantile residual life function under heavy censoring. Posterior computation through Markov chain Monte Carlo is straightforward and efficient because of conjugacy properties and partial collapse. We illustrate the proposed methods by using both simulated data and heavily censored survival data from a recent breast cancer clinical trial conducted by the National Surgical Adjuvant Breast and Bowel Project. Copyright © 2012 John Wiley & Sons, Ltd.

Predicting Posttraumatic Stress Symptom Prevalence and Local Distribution after an Earthquake with Scarce Data.

Science.gov (United States)

Dussaillant, Francisca; Apablaza, Mauricio

2017-08-01

After a major earthquake, the assignment of scarce mental health emergency personnel to different geographic areas is crucial to the effective management of the crisis. The scarce information that is available in the aftermath of a disaster may be valuable in helping predict where are the populations that are in most need. The objectives of this study were to derive algorithms to predict posttraumatic stress (PTS) symptom prevalence and local distribution after an earthquake and to test whether there are algorithms that require few input data and are still reasonably predictive. A rich database of PTS symptoms, informed after Chile's 2010 earthquake and tsunami, was used. Several model specifications for the mean and centiles of the distribution of PTS symptoms, together with posttraumatic stress disorder (PTSD) prevalence, were estimated via linear and quantile regressions. The models varied in the set of covariates included. Adjusted R2 for the most liberal specifications (in terms of numbers of covariates included) ranged from 0.62 to 0.74, depending on the outcome. When only including peak ground acceleration (PGA), poverty rate, and household damage in linear and quadratic form, predictive capacity was still good (adjusted R2 from 0.59 to 0.67 were obtained). Information about local poverty, household damage, and PGA can be used as an aid to predict PTS symptom prevalence and local distribution after an earthquake. This can be of help to improve the assignment of mental health personnel to the affected localities. Dussaillant F , Apablaza M . Predicting posttraumatic stress symptom prevalence and local distribution after an earthquake with scarce data. Prehosp Disaster Med. 2017;32(4):357-367.

Several localized waves induced by linear interference between a nonlinear plane wave and bright solitons

Science.gov (United States)

Qin, Yan-Hong; Zhao, Li-Chen; Yang, Zhan-Ying; Yang, Wen-Li

2018-01-01

We investigate linear interference effects between a nonlinear plane wave and bright solitons, which are admitted by a pair-transition coupled two-component Bose-Einstein condensate. We demonstrate that the interference effects can induce several localized waves possessing distinctive wave structures, mainly including anti-dark solitons, W-shaped solitons, multi-peak solitons, Kuznetsov-Ma like breathers, and multi-peak breathers. Specifically, the explicit conditions for them are clarified by a phase diagram based on the linear interference properties. Furthermore, the interactions between these localized waves are discussed. The detailed analysis indicates that the soliton-soliton interaction induced phase shift brings the collision between these localized waves which can be inelastic for solitons involving collision and can be elastic for breathers. These characters come from the fact that the profile of solitons depends on the relative phase between bright solitons and a plane wave, and the profile of breathers does not depend on the relative phase. These results would motivate more discussions on linear interference between other nonlinear waves. Specifically, the solitons or breathers obtained here are not related to modulational instability. The underlying reasons are discussed in detail. In addition, possibilities to observe these localized waves are discussed in a two species Bose-Einstein condensate.

Smooth conditional distribution function and quantiles under random censorship.

Science.gov (United States)

Leconte, Eve; Poiraud-Casanova, Sandrine; Thomas-Agnan, Christine

2002-09-01

We consider a nonparametric random design regression model in which the response variable is possibly right censored. The aim of this paper is to estimate the conditional distribution function and the conditional alpha-quantile of the response variable. We restrict attention to the case where the response variable as well as the explanatory variable are unidimensional and continuous. We propose and discuss two classes of estimators which are smooth with respect to the response variable as well as to the covariate. Some simulations demonstrate that the new methods have better mean square error performances than the generalized Kaplan-Meier estimator introduced by Beran (1981) and considered in the literature by Dabrowska (1989, 1992) and Gonzalez-Manteiga and Cadarso-Suarez (1994).

Does a Threshold Inflation Rate Exist? Quantile Inferences for Inflation and Its Variability

OpenAIRE

WenShwo Fang; Stephen M. Miller; Chih-Chuan Yeh

2009-01-01

Using quantile regressions and cross-sectional data from 152 countries, we examine the relationship between inflation and its variability. We consider two measures of inflation – the mean and median – and three different measures of inflation variability – the standard deviation, relative variation, and median deviation. All results from the mean and standard deviation, the mean and relative variation, or the median and the median deviation support both the hypothesis that higher inflation cr...

Customized Fetal Growth Charts for Parents' Characteristics, Race, and Parity by Quantile Regression Analysis: A Cross-sectional Multicenter Italian Study.

Science.gov (United States)

Ghi, Tullio; Cariello, Luisa; Rizzo, Ludovica; Ferrazzi, Enrico; Periti, Enrico; Prefumo, Federico; Stampalija, Tamara; Viora, Elsa; Verrotti, Carla; Rizzo, Giuseppe

2016-01-01

The purpose of this study was to construct fetal biometric charts between 16 and 40 weeks' gestation that were customized for parental characteristics, race, and parity, using quantile regression analysis. In a multicenter cross-sectional study, 8070 sonographic examinations from low-risk pregnancies between 16 and 40 weeks' gestation were analyzed. The fetal measurements obtained were biparietal diameter, head circumference, abdominal circumference, and femur diaphysis length. Quantile regression was used to examine the impact of parental height and weight, parity, and race across biometric percentiles for the fetal measurements considered. Paternal and maternal height were significant covariates for all of the measurements considered (P < .05). Maternal weight significantly influenced head circumference, abdominal circumference, and femur diaphysis length. Parity was significantly associated with biparietal diameter and head circumference. Central African race was associated with head circumference and femur diaphysis length, whereas North African race was only associated with femur diaphysis length. In this study we constructed customized biometric growth charts using quantile regression in a large cohort of low-risk pregnancies. These charts offer the advantage of defining individualized normal ranges of fetal biometric parameters at each specific percentile corrected for parental height and weight, parity, and race. This study supports the importance of including these variables in routine sonographic screening for fetal growth abnormalities.

Quantile regression of microgeographic variation in population characteristics of an invasive vertebrate predator

Science.gov (United States)

Siers, Shane R.; Savidge, Julie A.; Reed, Robert

2017-01-01

Localized ecological conditions have the potential to induce variation in population characteristics such as size distributions and body conditions. The ability to generalize the influence of ecological characteristics on such population traits may be particularly meaningful when those traits influence prospects for successful management interventions. To characterize variability in invasive Brown Treesnake population attributes within and among habitat types, we conducted systematic and seasonally-balanced surveys, collecting 100 snakes from each of 18 sites: three replicates within each of six major habitat types comprising 95% of Guam’s geographic expanse. Our study constitutes one of the most comprehensive and controlled samplings of any published snake study. Quantile regression on snake size and body condition indicated significant ecological heterogeneity, with a general trend of relative consistency of size classes and body conditions within and among scrub and Leucaena forest habitat types and more heterogeneity among ravine forest, savanna, and urban residential sites. Larger and more robust snakes were found within some savanna and urban habitat replicates, likely due to relative availability of larger prey. Compared to more homogeneous samples in the wet season, variability in size distributions and body conditions was greater during the dry season. Although there is evidence of habitat influencing Brown Treesnake populations at localized scales (e.g., the higher prevalence of larger snakes—particularly males—in savanna and urban sites), the level of variability among sites within habitat types indicates little ability to make meaningful predictions about these traits at unsampled locations. Seasonal variability within sites and habitats indicates that localized population characterization should include sampling in both wet and dry seasons. Extreme values at single replicates occasionally influenced overall habitat patterns, while pooling

Quantile index for gradual and abrupt change detection from CFB boiler sensor data in online settings

NARCIS (Netherlands)

Maslov, A.; Pechenizkiy, M.; Kärkkäinen, T.; Tähtinen, M.

2012-01-01

In this paper we consider the problem of online detection of gradual and abrupt changes in sensor data having high levels of noise and outliers. We propose a simple heuristic method based on the Quantile Index (QI) and study how robust this method is for detecting both gradual and abrupt changes

Fast and local non-linear evolution of steep wave-groups on deep water: A comparison of approximate models to fully non-linear simulations

International Nuclear Information System (INIS)

Adcock, T. A. A.; Taylor, P. H.

2016-01-01

The non-linear Schrödinger equation and its higher order extensions are routinely used for analysis of extreme ocean waves. This paper compares the evolution of individual wave-packets modelled using non-linear Schrödinger type equations with packets modelled using fully non-linear potential flow models. The modified non-linear Schrödinger Equation accurately models the relatively large scale non-linear changes to the shape of wave-groups, with a dramatic contraction of the group along the mean propagation direction and a corresponding extension of the width of the wave-crests. In addition, as extreme wave form, there is a local non-linear contraction of the wave-group around the crest which leads to a localised broadening of the wave spectrum which the bandwidth limited non-linear Schrödinger Equations struggle to capture. This limitation occurs for waves of moderate steepness and a narrow underlying spectrum

Ordinary Least Squares and Quantile Regression: An Inquiry-Based Learning Approach to a Comparison of Regression Methods

Science.gov (United States)

Helmreich, James E.; Krog, K. Peter

2018-01-01

We present a short, inquiry-based learning course on concepts and methods underlying ordinary least squares (OLS), least absolute deviation (LAD), and quantile regression (QR). Students investigate squared, absolute, and weighted absolute distance functions (metrics) as location measures. Using differential calculus and properties of convex…

Adaptive local backlight dimming algorithm based on local histogram and image characteristics

DEFF Research Database (Denmark)

Nadernejad, Ehsan; Burini, Nino; Korhonen, Jari

2013-01-01

-off between power consumption and image quality preservation than the other algorithms representing the state of the art among feature based backlight algorithms. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.......Liquid Crystal Display (LCDs) with Light Emitting Diode (LED) backlight is a very popular display technology, used for instance in television sets, monitors and mobile phones. This paper presents a new backlight dimming algorithm that exploits the characteristics of the target image......, such as the local histograms and the average pixel intensity of each backlight segment, to reduce the power consumption of the backlight and enhance image quality. The local histogram of the pixels within each backlight segment is calculated and, based on this average, an adaptive quantile value is extracted...

Managing more than the mean: Using quantile regression to identify factors related to large elk groups

Science.gov (United States)

Brennan, Angela K.; Cross, Paul C.; Creely, Scott

2015-01-01

Summary Animal group size distributions are often right-skewed, whereby most groups are small, but most individuals occur in larger groups that may also disproportionately affect ecology and policy. In this case, examining covariates associated with upper quantiles of the group size distribution could facilitate better understanding and management of large animal groups.

Approaches to linear local gauge-invariant observables in inflationary cosmologies

Science.gov (United States)

Fröb, Markus B.; Hack, Thomas-Paul; Khavkine, Igor

2018-06-01

We review and relate two recent complementary constructions of linear local gauge-invariant observables for cosmological perturbations in generic spatially flat single-field inflationary cosmologies. After briefly discussing their physical significance, we give explicit, covariant and mutually invertible transformations between the two sets of observables, thus resolving any doubts about their equivalence. In this way, we get a geometric interpretation and show the completeness of both sets of observables, while previously each of these properties was available only for one of them.

Forecasting peak asthma admissions in London: an application of quantile regression models

Science.gov (United States)

Soyiri, Ireneous N.; Reidpath, Daniel D.; Sarran, Christophe

2013-07-01

Asthma is a chronic condition of great public health concern globally. The associated morbidity, mortality and healthcare utilisation place an enormous burden on healthcare infrastructure and services. This study demonstrates a multistage quantile regression approach to predicting excess demand for health care services in the form of asthma daily admissions in London, using retrospective data from the Hospital Episode Statistics, weather and air quality. Trivariate quantile regression models (QRM) of asthma daily admissions were fitted to a 14-day range of lags of environmental factors, accounting for seasonality in a hold-in sample of the data. Representative lags were pooled to form multivariate predictive models, selected through a systematic backward stepwise reduction approach. Models were cross-validated using a hold-out sample of the data, and their respective root mean square error measures, sensitivity, specificity and predictive values compared. Two of the predictive models were able to detect extreme number of daily asthma admissions at sensitivity levels of 76 % and 62 %, as well as specificities of 66 % and 76 %. Their positive predictive values were slightly higher for the hold-out sample (29 % and 28 %) than for the hold-in model development sample (16 % and 18 %). QRMs can be used in multistage to select suitable variables to forecast extreme asthma events. The associations between asthma and environmental factors, including temperature, ozone and carbon monoxide can be exploited in predicting future events using QRMs.

Two-step variable selection in quantile regression models

Directory of Open Access Journals (Sweden)

FAN Yali

2015-06-01

Full Text Available We propose a two-step variable selection procedure for high dimensional quantile regressions, in which the dimension of the covariates, pn is much larger than the sample size n. In the first step, we perform ℓ1 penalty, and we demonstrate that the first step penalized estimator with the LASSO penalty can reduce the model from an ultra-high dimensional to a model whose size has the same order as that of the true model, and the selected model can cover the true model. The second step excludes the remained irrelevant covariates by applying the adaptive LASSO penalty to the reduced model obtained from the first step. Under some regularity conditions, we show that our procedure enjoys the model selection consistency. We conduct a simulation study and a real data analysis to evaluate the finite sample performance of the proposed approach.

THE GENDER PAY GAP IN VIETNAM, 1993-2002: A QUANTILE REGRESSION APPROACH

OpenAIRE

Pham, Hung T; Reilly, Barry

2007-01-01

This paper uses mean and quantile regression analysis to investigate the gender pay gap for the wage employed in Vietnam over the period 1993 to 2002. It finds that the Doi moi reforms appear to have been associated with a sharp reduction in gender pay gap disparities for the wage employed. The average gender pay gap in this sector halved between 1993 and 2002 with most of the contraction evident by 1998. There has also been a narrowing in the gender pay gap at most selected points of the con...

The Gender Pay Gap In Vietnam, 1993-2002: A Quantile Regression Approach

OpenAIRE

Barry Reilly & T. Hung Pham

2006-01-01

This paper uses mean and quantile regression analysis to investigate the gender pay gap for the wage employed in Vietnam over the period 1993 to 2002. It finds that the Doi moi reforms have been associated with a sharp reduction in gender wage disparities for the wage employed. The average gender pay gap in this sector halved between 1993 and 2002 with most of the contraction evident by 1998. There has also been a contraction in the gender pay at most selected points of the conditional wage d...

The non-linear evolution of edge localized modes

International Nuclear Information System (INIS)

Wenninger, Ronald

2013-01-01

Edge localized modes (ELMs) are instabilities in the edge of tokamak plasmas in the high confinement regime (H-mode). Without them the edge transport in ordinary H-mode plasmas is too low to establish a stationary situation. However in a future device large unmitigated ELMs are believed to cause divertor power flux densities far in excess of tolerable material limits. Hence the size of energy loss per ELM and the resulting ELM frequency must be controlled. To proceed in understanding how the ELM size is determined and how ELM mitigation methods work it is necessary to characterize the non-linear evolution of pedestal erosion. In order to achieve this experimental data is compared to the results of ELM simulations with the code JOREK (reduced MHD, non-linear) applying a specially developed synthetic magnetic diagnostic. The experimental data are acquired by several fast sampling diagnostics at the experiments ASDEX Upgrade and TCV at a large number of toroidal/poloidal positions. A central element of the presented work is the detailed characterization of dominant magnetic perturbations during ELMs. These footprints of the instability can be observed most intensely in close temporal vicinity to the onset of pedestal erosion. Dominant magnetic perturbations are caused by current perturbations located at or inside the last closed flux surface. In ASDEX Upgrade under certain conditions dominant magnetic perturbations like other H-mode edge instabilities display a similarity to solitons. Furthermore - as expected - they are often observed to be correlated to a perturbation of electron temperature. In TCV it is possible to characterize the evolution of the toroidal structure of dominant magnetic perturbations. Between growing above the level of background fluctuations and the maximum perturbation level for all time instance a similar toroidal structure is observed. This rigid mode-structure is an indication for non-linear coupling. Most frequently the dominant toroidal

The non-linear evolution of edge localized modes

Energy Technology Data Exchange (ETDEWEB)

Wenninger, Ronald

2013-01-09

Edge localized modes (ELMs) are instabilities in the edge of tokamak plasmas in the high confinement regime (H-mode). Without them the edge transport in ordinary H-mode plasmas is too low to establish a stationary situation. However in a future device large unmitigated ELMs are believed to cause divertor power flux densities far in excess of tolerable material limits. Hence the size of energy loss per ELM and the resulting ELM frequency must be controlled. To proceed in understanding how the ELM size is determined and how ELM mitigation methods work it is necessary to characterize the non-linear evolution of pedestal erosion. In order to achieve this experimental data is compared to the results of ELM simulations with the code JOREK (reduced MHD, non-linear) applying a specially developed synthetic magnetic diagnostic. The experimental data are acquired by several fast sampling diagnostics at the experiments ASDEX Upgrade and TCV at a large number of toroidal/poloidal positions. A central element of the presented work is the detailed characterization of dominant magnetic perturbations during ELMs. These footprints of the instability can be observed most intensely in close temporal vicinity to the onset of pedestal erosion. Dominant magnetic perturbations are caused by current perturbations located at or inside the last closed flux surface. In ASDEX Upgrade under certain conditions dominant magnetic perturbations like other H-mode edge instabilities display a similarity to solitons. Furthermore - as expected - they are often observed to be correlated to a perturbation of electron temperature. In TCV it is possible to characterize the evolution of the toroidal structure of dominant magnetic perturbations. Between growing above the level of background fluctuations and the maximum perturbation level for all time instance a similar toroidal structure is observed. This rigid mode-structure is an indication for non-linear coupling. Most frequently the dominant toroidal

Modeling soil organic carbon with Quantile Regression: Dissecting predictors' effects on carbon stocks

KAUST Repository

Lombardo, Luigi

2017-08-13

Soil Organic Carbon (SOC) estimation is crucial to manage both natural and anthropic ecosystems and has recently been put under the magnifying glass after the Paris agreement 2016 due to its relationship with greenhouse gas. Statistical applications have dominated the SOC stock mapping at regional scale so far. However, the community has hardly ever attempted to implement Quantile Regression (QR) to spatially predict the SOC distribution. In this contribution, we test QR to estimate SOC stock (0-30 $cm$ depth) in the agricultural areas of a highly variable semi-arid region (Sicily, Italy, around 25,000 $km2$) by using topographic and remotely sensed predictors. We also compare the results with those from available SOC stock measurement. The QR models produced robust performances and allowed to recognize dominant effects among the predictors with respect to the considered quantile. This information, currently lacking, suggests that QR can discern predictor influences on SOC stock at specific sub-domains of each predictors. In this work, the predictive map generated at the median shows lower errors than those of the Joint Research Centre and International Soil Reference, and Information Centre benchmarks. The results suggest the use of QR as a comprehensive and effective method to map SOC using legacy data in agro-ecosystems. The R code scripted in this study for QR is included.

Chimera states in an ensemble of linearly locally coupled bistable oscillators

Science.gov (United States)

Shchapin, D. S.; Dmitrichev, A. S.; Nekorkin, V. I.

2017-11-01

Chimera states in a system with linear local connections have been studied. The system is a ring ensemble of analog bistable self-excited oscillators with a resistive coupling. It has been shown that the existence of chimera states is not due to the nonidentity of oscillators and noise, which is always present in real experiments, but is due to the nonlinear dynamics of the system on invariant tori with various dimensions.

A New Quantile Regression Model to forecast one-day-ahead Value-at-Risk

OpenAIRE

Steine, Sturla Aavik; Eliassen, Markus Thorsø

2014-01-01

This master thesis focuses on the problem of forecasting volatility and Value-at-Risk (VaR) in the nancial markets. There are numerous methods for calculating VaR. However, research in this area has not currently reached one universally accepted method that can produce good VaR estimates across dierent data series, and VaR prediction and quality testing is still a very challenging statistical problem. The thesis has two main purposes, the rst is to propose a simple quantile regression mod...

Stock Market Autoregressive Dynamics: A Multinational Comparative Study with Quantile Regression

Directory of Open Access Journals (Sweden)

Lili Li

2016-01-01

Full Text Available We study the nonlinear autoregressive dynamics of stock index returns in seven major advanced economies (G7 and China. The quantile autoregression model (QAR enables us to investigate the autocorrelation across the whole spectrum of return distribution, which provides more insightful conditional information on multinational stock market dynamics than conventional time series models. The relation between index return and contemporaneous trading volume is also investigated. While prior studies have mixed results on stock market autocorrelations, we find that the dynamics is usually state dependent. The results for G7 stock markets exhibit conspicuous similarities, but they are in manifest contrast to the findings on Chinese stock markets.

Measuring risk of crude oil at extreme quantiles

Directory of Open Access Journals (Sweden)

Saša Žiković

2011-06-01

Full Text Available The purpose of this paper is to investigate the performance of VaR models at measuring risk for WTI oil one-month futures returns. Risk models, ranging from industry standards such as RiskMetrics and historical simulation to conditional extreme value model, are used to calculate commodity market risk at extreme quantiles: 0.95, 0.99, 0.995 and 0.999 for both long and short trading positions. Our results show that out of the tested fat tailed distributions, generalised Pareto distribution provides the best fit to both tails of oil returns although tails differ significantly, with the right tail having a higher tail index, indicative of more extreme events. The main conclusion is that, in the analysed period, only extreme value theory based models provide a reasonable degree of safety while widespread VaR models do not provide adequate risk coverage and their performance is especially weak for short position in oil.

Longitudinal analysis of the strengths and difficulties questionnaire scores of the Millennium Cohort Study children in England using M-quantile random-effects regression.

Science.gov (United States)

Tzavidis, Nikos; Salvati, Nicola; Schmid, Timo; Flouri, Eirini; Midouhas, Emily

2016-02-01

Multilevel modelling is a popular approach for longitudinal data analysis. Statistical models conventionally target a parameter at the centre of a distribution. However, when the distribution of the data is asymmetric, modelling other location parameters, e.g. percentiles, may be more informative. We present a new approach, M -quantile random-effects regression, for modelling multilevel data. The proposed method is used for modelling location parameters of the distribution of the strengths and difficulties questionnaire scores of children in England who participate in the Millennium Cohort Study. Quantile mixed models are also considered. The analyses offer insights to child psychologists about the differential effects of risk factors on children's outcomes.

Subcellular localization for Gram positive and Gram negative bacterial proteins using linear interpolation smoothing model.

Science.gov (United States)

Saini, Harsh; Raicar, Gaurav; Dehzangi, Abdollah; Lal, Sunil; Sharma, Alok

2015-12-07

Protein subcellular localization is an important topic in proteomics since it is related to a protein׳s overall function, helps in the understanding of metabolic pathways, and in drug design and discovery. In this paper, a basic approximation technique from natural language processing called the linear interpolation smoothing model is applied for predicting protein subcellular localizations. The proposed approach extracts features from syntactical information in protein sequences to build probabilistic profiles using dependency models, which are used in linear interpolation to determine how likely is a sequence to belong to a particular subcellular location. This technique builds a statistical model based on maximum likelihood. It is able to deal effectively with high dimensionality that hinders other traditional classifiers such as Support Vector Machines or k-Nearest Neighbours without sacrificing performance. This approach has been evaluated by predicting subcellular localizations of Gram positive and Gram negative bacterial proteins. Copyright © 2015 Elsevier Ltd. All rights reserved.

Unique solvability of a non-linear non-local boundary-value problem for systems of non-linear functional differential equations

Czech Academy of Sciences Publication Activity Database

Dilna, N.; Rontó, András

2010-01-01

Roč. 60, č. 3 (2010), s. 327-338 ISSN 0139-9918 R&D Projects: GA ČR(CZ) GA201/06/0254 Institutional research plan: CEZ:AV0Z10190503 Keywords : non-linear boundary value-problem * functional differential equation * non-local condition * unique solvability * differential inequality Subject RIV: BA - General Mathematics Impact factor: 0.316, year: 2010 http://link.springer.com/article/10.2478%2Fs12175-010-0015-9

The algebra of non-local charges in non-linear sigma models

International Nuclear Information System (INIS)

Abdalla, E.; Abdalla, M.C.B.; Brunelli, J.C.; Zadra, A.

1994-01-01

It is derived the complete Dirac algebra satisfied by non-local charges conserved in non-linear sigma models. Some examples of calculation are given for the O(N) symmetry group. The resulting algebra corresponds to a saturated cubic deformation (with only maximum order terms) of the Kac-Moody algebra. The results are generalized for when a Wess-Zumino term be present. In that case the algebra contains a minor order correction (sub-saturation). (author). 1 ref

Locally supersymmetric D=3 non-linear sigma models

International Nuclear Information System (INIS)

Wit, B. de; Tollsten, A.K.; Nicolai, H.

1993-01-01

We study non-linear sigma models with N local supersymmetries in three space-time dimensions. For N=1 and 2 the target space of these models is riemannian or Kaehler, respectively. All N>2 theories are associated with Einstein spaces. For N=3 the target space is quaternionic, while for N=4 it generally decomposes, into two separate quaternionic spaces, associated with inequivalent supermultiplets. For N=5, 6, 8 there is a unique (symmetric) space for any given number of supermultiplets. Beyond that there are only theories based on a single supermultiplet for N=9, 10, 12 and 16, associated with coset spaces with the exceptional isometry groups F 4(-20) , E 6(-14) , E 7(-5) and E 8(+8) , respectively. For N=3 and N ≥ 5 the D=2 theories obtained by dimensional reduction are two-loop finite. (orig.)

Active learning for semi-supervised clustering based on locally linear propagation reconstruction.

Science.gov (United States)

Chang, Chin-Chun; Lin, Po-Yi

2015-03-01

The success of semi-supervised clustering relies on the effectiveness of side information. To get effective side information, a new active learner learning pairwise constraints known as must-link and cannot-link constraints is proposed in this paper. Three novel techniques are developed for learning effective pairwise constraints. The first technique is used to identify samples less important to cluster structures. This technique makes use of a kernel version of locally linear embedding for manifold learning. Samples neither important to locally linear propagation reconstructions of other samples nor on flat patches in the learned manifold are regarded as unimportant samples. The second is a novel criterion for query selection. This criterion considers not only the importance of a sample to expanding the space coverage of the learned samples but also the expected number of queries needed to learn the sample. To facilitate semi-supervised clustering, the third technique yields inferred must-links for passing information about flat patches in the learned manifold to semi-supervised clustering algorithms. Experimental results have shown that the learned pairwise constraints can capture the underlying cluster structures and proven the feasibility of the proposed approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Asymmetric Effects of Oil Price Shocks on the Chinese Stock Market: Evidence from a Quantile Impulse Response Perspective

Directory of Open Access Journals (Sweden)

Huiming Zhu

2016-08-01

Full Text Available This paper uses a quantile impulse response approach to investigate the impact of oil price shocks on Chinese stock returns. This process allows us to uncover asymmetric effects of oil price shocks on stock market returns by taking into account the different quantiles of oil price shocks. Our results show that the responses of Chinese stock market returns to oil price shocks differ greatly, depending on whether the oil and stock market is in a bust or boom state and whether the shock is driven by demand or supply. The impacts of oil price shocks on Chinese stock returns present asymmetric features. In particular during a bust phase, oil supply and demand shocks significantly depress stock market returns, while during a boom period, the aggregate demand shock enhances stock market returns. These results suggest some important implications for investors and decision makers.

Local Ray-Based Traveltime Computation Using the Linearized Eikonal Equation

KAUST Repository

Almubarak, Mohammed S.

2013-05-01

The computation of traveltimes plays a critical role in the conventional implementations of Kirchhoff migration. Finite-difference-based methods are considered one of the most effective approaches for traveltime calculations and are therefore widely used. However, these eikonal solvers are mainly used to obtain early-arrival traveltime. Ray tracing can be used to pick later traveltime branches, besides the early arrivals, which may lead to an improvement in velocity estimation or in seismic imaging. In this thesis, I improved the accuracy of the solution of the linearized eikonal equation by constructing a linear system of equations (LSE) based on finite-difference approximation, which is of second-order accuracy. The ill-conditioned LSE is initially regularized and subsequently solved to calculate the traveltime update. Numerical tests proved that this method is as accurate as the second-order eikonal solver. Later arrivals are picked using ray tracing. These traveltimes are binned to the nearest node on a regular grid and empty nodes are estimated by interpolating the known values. The resulting traveltime field is used as an input to the linearized eikonal algorithm, which improves the accuracy of the interpolated nodes and yields a local ray-based traveltime. This is a preliminary study and further investigation is required to test the efficiency and the convergence of the solutions.

Quantification of local and global elastic anisotropy in ultrafine grained gradient microstructures, produced by linear flow splitting

DEFF Research Database (Denmark)

Niehuesbernd, Jörn; Müller, Clemens; Pantleon, Wolfgang

2013-01-01

. Consequently, the macroscopic elastic behavior results from the local elastic properties within the gradient. In the present investigation profiles produced by the linear flow splitting process were examined with respect to local and global elastic anisotropy, which develops during the complex forming process...

Determinants of Birthweight Outcomes: Quantile Regressions Based on Panel Data

DEFF Research Database (Denmark)

Bache, Stefan Holst; Dahl, Christian Møller; Kristensen, Johannes Tang

to the possibility that smoking habits can be influenced through policy conduct. It is widely believed that maternal smoking reduces birthweight; however, the crucial difficulty in estimating such effects is the unobserved heterogeneity among mothers. We consider extensions of three panel data models to a quantile......Low birthweight outcomes are associated with large social and economic costs, and therefore the possible determinants of low birthweight are of great interest. One such determinant which has received considerable attention is maternal smoking. From an economic perspective this is in part due...... regression framework in order to control for heterogeneity and to infer conclusions about causality across the entire birthweight distribution. We obtain estimation results for maternal smoking and other interesting determinants, applying these to data obtained from Aarhus University Hospital, Skejby...

Localization of periodic orbits of polynomial vector fields of even degree by linear functions

Energy Technology Data Exchange (ETDEWEB)

Starkov, Konstantin E. [CITEDI-IPN, Av. del Parque 1310, Mesa de Otay, Tijuana, BC (Mexico)] e-mail: konst@citedi.mx

2005-08-01

This paper is concerned with the localization problem of periodic orbits of polynomial vector fields of even degree by using linear functions. Conditions of the localization of all periodic orbits in sets of a simple structure are obtained. Our results are based on the solution of the conditional extremum problem and the application of homogeneous polynomial forms of even degrees. As examples, the Lanford system, the jerky system with one quadratic monomial and a quartically perturbed harmonic oscillator are considered.

Localization of periodic orbits of polynomial vector fields of even degree by linear functions

International Nuclear Information System (INIS)

Starkov, Konstantin E.

2005-01-01

This paper is concerned with the localization problem of periodic orbits of polynomial vector fields of even degree by using linear functions. Conditions of the localization of all periodic orbits in sets of a simple structure are obtained. Our results are based on the solution of the conditional extremum problem and the application of homogeneous polynomial forms of even degrees. As examples, the Lanford system, the jerky system with one quadratic monomial and a quartically perturbed harmonic oscillator are considered

Detecting Long-term Trend of Water Quality Indices of Dong-gang River, Taiwan Using Quantile Regression

Science.gov (United States)

Yang, D.; Shiau, J.

2013-12-01

ABSTRACT BODY: Abstract Surface water quality is an essential issue in water-supply for human uses and sustaining healthy ecosystem of rivers. However, water quality of rivers is easily influenced by anthropogenic activities such as urban development and wastewater disposal. Long-term monitoring of water quality can assess whether water quality of rivers deteriorates or not. Taiwan is a population-dense area and heavily depends on surface water for domestic, industrial, and agricultural uses. Dong-gang River is one of major resources in southern Taiwan for agricultural requirements. The water-quality data of four monitoring stations of the Dong-gang River for the period of 2000-2012 are selected for trend analysis. The parameters used to characterize water quality of rivers include biochemical oxygen demand (BOD), dissolved oxygen (DO), suspended solids (SS), and ammonia nitrogen (NH3-N). These four water-quality parameters are integrated into an index called river pollution index (RPI) to indicate the pollution level of rivers. Although widely used non-parametric Mann-Kendall test and linear regression exhibit computational efficiency to identify trends of water-quality indices, limitations of such approaches include sensitive to outliers and estimations of conditional mean only. Quantile regression, capable of identifying changes over time of any percentile values, is employed in this study to detect long-term trend of water-quality indices for the Dong-gang River located in southern Taiwan. The results show that Dong-gang River 4 stations from 2000 to 2012 monthly long-term trends in water quality.To analyze s Dong-gang River long-term water quality trends and pollution characteristics. The results showed that the bridge measuring ammonia Long-dong, BOD5 measure in that station on a downward trend, DO, and SS is on the rise, River Pollution Index (RPI) on a downward trend. The results form Chau-Jhou station also ahowed simialar trends .more and more near the

Localization of Non-Linearly Modeled Autonomous Mobile Robots Using Out-of-Sequence Measurements

Directory of Open Access Journals (Sweden)

Jesus M. de la Cruz

2012-02-01

Full Text Available This paper presents a state of the art of the estimation algorithms dealing with Out-of-Sequence (OOS measurements for non-linearly modeled systems. The state of the art includes a critical analysis of the algorithm properties that takes into account the applicability of these techniques to autonomous mobile robot navigation based on the fusion of the measurements provided, delayed and OOS, by multiple sensors. Besides, it shows a representative example of the use of one of the most computationally efficient approaches in the localization module of the control software of a real robot (which has non-linear dynamics, and linear and non-linear sensors and compares its performance against other approaches. The simulated results obtained with the selected OOS algorithm shows the computational requirements that each sensor of the robot imposes to it. The real experiments show how the inclusion of the selected OOS algorithm in the control software lets the robot successfully navigate in spite of receiving many OOS measurements. Finally, the comparison highlights that not only is the selected OOS algorithm among the best performing ones of the comparison, but it also has the lowest computational and memory cost.

A uniform law for convergence to the local times of linear fractional stable motions

OpenAIRE

Duffy, James A.

2016-01-01

We provide a uniform law for the weak convergence of additive functionals of partial sum processes to the local times of linear fractional stable motions, in a setting sufficiently general for statistical applications. Our results are fundamental to the analysis of the global properties of nonparametric estimators of nonlinear statistical models that involve such processes as covariates.

Application of local area networks to accelerator control systems at the Stanford Linear Accelerator

International Nuclear Information System (INIS)

Fox, J.D.; Linstadt, E.; Melen, R.

1983-03-01

The history and current status of SLAC's SDLC networks for distributed accelerator control systems are discussed. These local area networks have been used for instrumentation and control of the linear accelerator. Network topologies, protocols, physical links, and logical interconnections are discussed for specific applications in distributed data acquisition and control system, computer networks and accelerator operations

Quantile regression analysis of body mass and wages.

Science.gov (United States)

Johar, Meliyanni; Katayama, Hajime

2012-05-01

Using the National Longitudinal Survey of Youth 1979, we explore the relationship between body mass and wages. We use quantile regression to provide a broad description of the relationship across the wage distribution. We also allow the relationship to vary by the degree of social skills involved in different jobs. Our results find that for female workers body mass and wages are negatively correlated at all points in their wage distribution. The strength of the relationship is larger at higher-wage levels. For male workers, the relationship is relatively constant across wage distribution but heterogeneous across ethnic groups. When controlling for the endogeneity of body mass, we find that additional body mass has a negative causal impact on the wages of white females earning more than the median wages and of white males around the median wages. Among these workers, the wage penalties are larger for those employed in jobs that require extensive social skills. These findings may suggest that labor markets reward white workers for good physical shape differently, depending on the level of wages and the type of job a worker has. Copyright © 2011 John Wiley & Sons, Ltd.

Refining Our Understanding of Beta through Quantile Regressions

Directory of Open Access Journals (Sweden)

Allen B. Atkins

2014-05-01

Full Text Available The Capital Asset Pricing Model (CAPM has been a key theory in financial economics since the 1960s. One of its main contributions is to attempt to identify how the risk of a particular stock is related to the risk of the overall stock market using the risk measure Beta. If the relationship between an individual stock’s returns and the returns of the market exhibit heteroskedasticity, then the estimates of Beta for different quantiles of the relationship can be quite different. The behavioral ideas first proposed by Kahneman and Tversky (1979, which they called prospect theory, postulate that: (i people exhibit “loss-aversion” in a gain frame; and (ii people exhibit “risk-seeking” in a loss frame. If this is true, people could prefer lower Beta stocks after they have experienced a gain and higher Beta stocks after they have experienced a loss. Stocks that exhibit converging heteroskedasticity (22.2% of our sample should be preferred by investors, and stocks that exhibit diverging heteroskedasticity (12.6% of our sample should not be preferred. Investors may be able to benefit by choosing portfolios that are more closely aligned with their preferences.

Ensemble Linear Neighborhood Propagation for Predicting Subchloroplast Localization of Multi-Location Proteins.

Science.gov (United States)

Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

2016-12-02

In the postgenomic era, the number of unreviewed protein sequences is remarkably larger and grows tremendously faster than that of reviewed ones. However, existing methods for protein subchloroplast localization often ignore the information from these unlabeled proteins. This paper proposes a multi-label predictor based on ensemble linear neighborhood propagation (LNP), namely, LNP-Chlo, which leverages hybrid sequence-based feature information from both labeled and unlabeled proteins for predicting localization of both single- and multi-label chloroplast proteins. Experimental results on a stringent benchmark dataset and a novel independent dataset suggest that LNP-Chlo performs at least 6% (absolute) better than state-of-the-art predictors. This paper also demonstrates that ensemble LNP significantly outperforms LNP based on individual features. For readers' convenience, the online Web server LNP-Chlo is freely available at http://bioinfo.eie.polyu.edu.hk/LNPChloServer/ .

Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care.

Science.gov (United States)

Kowalski, Amanda

2016-01-02

Efforts to control medical care costs depend critically on how individuals respond to prices. I estimate the price elasticity of expenditure on medical care using a censored quantile instrumental variable (CQIV) estimator. CQIV allows estimates to vary across the conditional expenditure distribution, relaxes traditional censored model assumptions, and addresses endogeneity with an instrumental variable. My instrumental variable strategy uses a family member's injury to induce variation in an individual's own price. Across the conditional deciles of the expenditure distribution, I find elasticities that vary from -0.76 to -1.49, which are an order of magnitude larger than previous estimates.

A New Spectral Local Linearization Method for Nonlinear Boundary Layer Flow Problems

Directory of Open Access Journals (Sweden)

S. S. Motsa

2013-01-01

Full Text Available We propose a simple and efficient method for solving highly nonlinear systems of boundary layer flow problems with exponentially decaying profiles. The algorithm of the proposed method is based on an innovative idea of linearizing and decoupling the governing systems of equations and reducing them into a sequence of subsystems of differential equations which are solved using spectral collocation methods. The applicability of the proposed method, hereinafter referred to as the spectral local linearization method (SLLM, is tested on some well-known boundary layer flow equations. The numerical results presented in this investigation indicate that the proposed method, despite being easy to develop and numerically implement, is very robust in that it converges rapidly to yield accurate results and is more efficient in solving very large systems of nonlinear boundary value problems of the similarity variable boundary layer type. The accuracy and numerical stability of the SLLM can further be improved by using successive overrelaxation techniques.

Existence and uniqueness to the Cauchy problem for linear and semilinear parabolic equations with local conditions⋆

Directory of Open Access Journals (Sweden)

Rubio Gerardo

2011-03-01

Full Text Available We consider the Cauchy problem in ℝd for a class of semilinear parabolic partial differential equations that arises in some stochastic control problems. We assume that the coefficients are unbounded and locally Lipschitz, not necessarily differentiable, with continuous data and local uniform ellipticity. We construct a classical solution by approximation with linear parabolic equations. The linear equations involved can not be solved with the traditional results. Therefore, we construct a classical solution to the linear Cauchy problem under the same hypotheses on the coefficients for the semilinear equation. Our approach is using stochastic differential equations and parabolic differential equations in bounded domains. Finally, we apply the results to a stochastic optimal consumption problem. Nous considérons le problème de Cauchy dans ℝd pour une classe d’équations aux dérivées partielles paraboliques semi linéaires qui se pose dans certains problèmes de contrôle stochastique. Nous supposons que les coefficients ne sont pas bornés et sont localement Lipschitziennes, pas nécessairement différentiables, avec des données continues et ellipticité local uniforme. Nous construisons une solution classique par approximation avec les équations paraboliques linéaires. Les équations linéaires impliquées ne peuvent être résolues avec les résultats traditionnels. Par conséquent, nous construisons une solution classique au problème de Cauchy linéaire sous les mêmes hypothèses sur les coefficients pour l’équation semi-linéaire. Notre approche utilise les équations différentielles stochastiques et les équations différentielles paraboliques dans les domaines bornés. Enfin, nous appliquons les résultats à un problème stochastique de consommation optimale.

Quantile regression and the gender wage gap: Is there a glass ceiling in the Turkish labor market?

OpenAIRE

Kaya, Ezgi

2017-01-01

Recent studies from different countries suggest that the gender gap is not constant across the wage distribution and the average wage gap provides limited information on women’s relative position in the labour market. Using micro level data from official statistics, this study explores the gender wage‐gap in Turkey across the wage distribution. The quantile regression and counterfactual decomposition analysis results reveal three striking features of the Turkish labour market. The first is th...

Use of Quantile Regression to Determine the Impact on Total Health Care Costs of Surgical Site Infections Following Common Ambulatory Procedures.

Science.gov (United States)

Olsen, Margaret A; Tian, Fang; Wallace, Anna E; Nickel, Katelin B; Warren, David K; Fraser, Victoria J; Selvam, Nandini; Hamilton, Barton H

2017-02-01

To determine the impact of surgical site infections (SSIs) on health care costs following common ambulatory surgical procedures throughout the cost distribution. Data on costs of SSIs following ambulatory surgery are sparse, particularly variation beyond just mean costs. We performed a retrospective cohort study of persons undergoing cholecystectomy, breast-conserving surgery, anterior cruciate ligament reconstruction, and hernia repair from December 31, 2004 to December 31, 2010 using commercial insurer claims data. SSIs within 90 days post-procedure were identified; infections during a hospitalization or requiring surgery were considered serious. We used quantile regression, controlling for patient, operative, and postoperative factors to examine the impact of SSIs on 180-day health care costs throughout the cost distribution. The incidence of serious and nonserious SSIs was 0.8% and 0.2%, respectively, after 21,062 anterior cruciate ligament reconstruction, 0.5% and 0.3% after 57,750 cholecystectomy, 0.6% and 0.5% after 60,681 hernia, and 0.8% and 0.8% after 42,489 breast-conserving surgery procedures. Serious SSIs were associated with significantly higher costs than nonserious SSIs for all 4 procedures throughout the cost distribution. The attributable cost of serious SSIs increased for both cholecystectomy and hernia repair as the quantile of total costs increased ($38,410 for cholecystectomy with serious SSI vs no SSI at the 70th percentile of costs, up to $89,371 at the 90th percentile). SSIs, particularly serious infections resulting in hospitalization or surgical treatment, were associated with significantly increased health care costs after 4 common surgical procedures. Quantile regression illustrated the differential effect of serious SSIs on health care costs at the upper end of the cost distribution.

On the structure on non-local conservation laws in the two-dimensional non-linear sigma-model

International Nuclear Information System (INIS)

Zamolodchikov, Al.B.

1978-01-01

The non-local conserved charges are supposed to satisfy a special multiplicative law in the space of asymptotic states of the non-linear sigma-model. This supposition leads to factorization equations for two-particle scattering matrix elements and determines to some extent the action of these charges in the asymptotic space. Their conservation turns out to be consistent with the factorized S-matrix of the non-linear sigma-model. It is shown also that the factorized sine-Gordon S-matrix is consistent with a similar family of conservation laws

Solvability conditions for non-local boundary value problems for two-dimensional half-linear differential systems

Czech Academy of Sciences Publication Activity Database

Kiguradze, I.; Šremr, Jiří

2011-01-01

Roč. 74, č. 17 (2011), s. 6537-6552 ISSN 0362-546X Institutional research plan: CEZ:AV0Z10190503 Keywords : half-linear differential system * non-local boundary value problem * solvability Subject RIV: BA - General Mathematics Impact factor: 1.536, year: 2011 http://www.sciencedirect.com/science/article/pii/S0362546X11004573

Logistic quantile regression provides improved estimates for bounded avian counts: a case study of California Spotted Owl fledgling production

Science.gov (United States)

Brian S. Cade; Barry R. Noon; Rick D. Scherer; John J. Keane

2017-01-01

Counts of avian fledglings, nestlings, or clutch size that are bounded below by zero and above by some small integer form a discrete random variable distribution that is not approximated well by conventional parametric count distributions such as the Poisson or negative binomial. We developed a logistic quantile regression model to provide estimates of the empirical...

Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model

KAUST Repository

Camilo, Daniela Castro; Lombardo, Luigi; Mai, Paul Martin; Dou, Jie; Huser, Raphaë l

2017-01-01

Grid-based landslide susceptibility models at regional scales are computationally demanding when using a fine grid resolution. Conversely, Slope-Unit (SU) based susceptibility models allows to investigate the same areas offering two main advantages: 1) a smaller computational burden and 2) a more geomorphologically-oriented interpretation. In this contribution, we generate SU-based landslide susceptibility for the Sado Island in Japan. This island is characterized by deep-seated landslides which we assume can only limitedly be explained by the first two statistical moments (mean and variance) of a set of predictors within each slope unit. As a consequence, in a nested experiment, we first analyse the distributions of a set of continuous predictors within each slope unit computing the standard deviation and quantiles from 0.05 to 0.95 with a step of 0.05. These are then used as predictors for landslide susceptibility. In addition, we combine shape indices for polygon features and the normalized extent of each class belonging to the outcropping lithology in a given SU. This procedure significantly enlarges the size of the predictor hyperspace, thus producing a high level of slope-unit characterization. In a second step, we adopt a LASSO-penalized Generalized Linear Model to shrink back the predictor set to a sensible and interpretable number, carrying only the most significant covariates in the models. As a result, we are able to document the geomorphic features (e.g., 95% quantile of Elevation and 5% quantile of Plan Curvature) that primarily control the SU-based susceptibility within the test area while producing high predictive performances. The implementation of the statistical analyses are included in a parallelized R script (LUDARA) which is here made available for the community to replicate analogous experiments.

Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model

KAUST Repository

Camilo, Daniela Castro

2017-08-30

Grid-based landslide susceptibility models at regional scales are computationally demanding when using a fine grid resolution. Conversely, Slope-Unit (SU) based susceptibility models allows to investigate the same areas offering two main advantages: 1) a smaller computational burden and 2) a more geomorphologically-oriented interpretation. In this contribution, we generate SU-based landslide susceptibility for the Sado Island in Japan. This island is characterized by deep-seated landslides which we assume can only limitedly be explained by the first two statistical moments (mean and variance) of a set of predictors within each slope unit. As a consequence, in a nested experiment, we first analyse the distributions of a set of continuous predictors within each slope unit computing the standard deviation and quantiles from 0.05 to 0.95 with a step of 0.05. These are then used as predictors for landslide susceptibility. In addition, we combine shape indices for polygon features and the normalized extent of each class belonging to the outcropping lithology in a given SU. This procedure significantly enlarges the size of the predictor hyperspace, thus producing a high level of slope-unit characterization. In a second step, we adopt a LASSO-penalized Generalized Linear Model to shrink back the predictor set to a sensible and interpretable number, carrying only the most significant covariates in the models. As a result, we are able to document the geomorphic features (e.g., 95% quantile of Elevation and 5% quantile of Plan Curvature) that primarily control the SU-based susceptibility within the test area while producing high predictive performances. The implementation of the statistical analyses are included in a parallelized R script (LUDARA) which is here made available for the community to replicate analogous experiments.

A Quantile Mapping Bias Correction Method Based on Hydroclimatic Classification of the Guiana Shield.

Science.gov (United States)

Ringard, Justine; Seyler, Frederique; Linguet, Laurent

2017-06-16

Satellite precipitation products (SPPs) provide alternative precipitation data for regions with sparse rain gauge measurements. However, SPPs are subject to different types of error that need correction. Most SPP bias correction methods use the statistical properties of the rain gauge data to adjust the corresponding SPP data. The statistical adjustment does not make it possible to correct the pixels of SPP data for which there is no rain gauge data. The solution proposed in this article is to correct the daily SPP data for the Guiana Shield using a novel two set approach, without taking into account the daily gauge data of the pixel to be corrected, but the daily gauge data from surrounding pixels. In this case, a spatial analysis must be involved. The first step defines hydroclimatic areas using a spatial classification that considers precipitation data with the same temporal distributions. The second step uses the Quantile Mapping bias correction method to correct the daily SPP data contained within each hydroclimatic area. We validate the results by comparing the corrected SPP data and daily rain gauge measurements using relative RMSE and relative bias statistical errors. The results show that analysis scale variation reduces rBIAS and rRMSE significantly. The spatial classification avoids mixing rainfall data with different temporal characteristics in each hydroclimatic area, and the defined bias correction parameters are more realistic and appropriate. This study demonstrates that hydroclimatic classification is relevant for implementing bias correction methods at the local scale.

Correlation coefficient based supervised locally linear embedding for pulmonary nodule recognition.

Science.gov (United States)

Wu, Panpan; Xia, Kewen; Yu, Hengyong

2016-11-01

Dimensionality reduction techniques are developed to suppress the negative effects of high dimensional feature space of lung CT images on classification performance in computer aided detection (CAD) systems for pulmonary nodule detection. An improved supervised locally linear embedding (SLLE) algorithm is proposed based on the concept of correlation coefficient. The Spearman's rank correlation coefficient is introduced to adjust the distance metric in the SLLE algorithm to ensure that more suitable neighborhood points could be identified, and thus to enhance the discriminating power of embedded data. The proposed Spearman's rank correlation coefficient based SLLE (SC(2)SLLE) is implemented and validated in our pilot CAD system using a clinical dataset collected from the publicly available lung image database consortium and image database resource initiative (LICD-IDRI). Particularly, a representative CAD system for solitary pulmonary nodule detection is designed and implemented. After a sequential medical image processing steps, 64 nodules and 140 non-nodules are extracted, and 34 representative features are calculated. The SC(2)SLLE, as well as SLLE and LLE algorithm, are applied to reduce the dimensionality. Several quantitative measurements are also used to evaluate and compare the performances. Using a 5-fold cross-validation methodology, the proposed algorithm achieves 87.65% accuracy, 79.23% sensitivity, 91.43% specificity, and 8.57% false positive rate, on average. Experimental results indicate that the proposed algorithm outperforms the original locally linear embedding and SLLE coupled with the support vector machine (SVM) classifier. Based on the preliminary results from a limited number of nodules in our dataset, this study demonstrates the great potential to improve the performance of a CAD system for nodule detection using the proposed SC(2)SLLE. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

L1-norm locally linear representation regularization multi-source adaptation learning.

Science.gov (United States)

Tao, Jianwen; Wen, Shiting; Hu, Wenjun

2015-09-01

In most supervised domain adaptation learning (DAL) tasks, one has access only to a small number of labeled examples from target domain. Therefore the success of supervised DAL in this "small sample" regime needs the effective utilization of the large amounts of unlabeled data to extract information that is useful for generalization. Toward this end, we here use the geometric intuition of manifold assumption to extend the established frameworks in existing model-based DAL methods for function learning by incorporating additional information about the target geometric structure of the marginal distribution. We would like to ensure that the solution is smooth with respect to both the ambient space and the target marginal distribution. In doing this, we propose a novel L1-norm locally linear representation regularization multi-source adaptation learning framework which exploits the geometry of the probability distribution, which has two techniques. Firstly, an L1-norm locally linear representation method is presented for robust graph construction by replacing the L2-norm reconstruction measure in LLE with L1-norm one, which is termed as L1-LLR for short. Secondly, considering the robust graph regularization, we replace traditional graph Laplacian regularization with our new L1-LLR graph Laplacian regularization and therefore construct new graph-based semi-supervised learning framework with multi-source adaptation constraint, which is coined as L1-MSAL method. Moreover, to deal with the nonlinear learning problem, we also generalize the L1-MSAL method by mapping the input data points from the input space to a high-dimensional reproducing kernel Hilbert space (RKHS) via a nonlinear mapping. Promising experimental results have been obtained on several real-world datasets such as face, visual video and object. Copyright © 2015 Elsevier Ltd. All rights reserved.

A generalized L1-approach for a kernel estimator of conditional quantile with functional regressors: Consistency and asymptotic normality

OpenAIRE

2009-01-01

Abstract A kernel estimator of the conditional quantile is defined for a scalar response variable given a covariate taking values in a semi-metric space. The approach generalizes the median?s L1-norm estimator. The almost complete consistency and asymptotic normality are stated. correspondance: Corresponding author. Tel: +33 320 964 933; fax: +33 320 964 704. (Lemdani, Mohamed) (Laksaci, Ali) mohamed.lemdani@univ-lill...

Localized and periodic exact solutions to the nonlinear Schroedinger equation with spatially modulated parameters: Linear and nonlinear lattices

International Nuclear Information System (INIS)

Belmonte-Beitia, Juan; Konotop, Vladimir V.; Perez-Garcia, Victor M.; Vekslerchik, Vadym E.

2009-01-01

Using similarity transformations we construct explicit solutions of the nonlinear Schroedinger equation with linear and nonlinear periodic potentials. We present explicit forms of spatially localized and periodic solutions, and study their properties. We put our results in the framework of the exploited perturbation techniques and discuss their implications on the properties of associated linear periodic potentials and on the possibilities of stabilization of gap solitons using polychromatic lattices.

Local and linear chemical reactivity response functions at finite temperature in density functional theory

International Nuclear Information System (INIS)

Franco-Pérez, Marco; Ayers, Paul W.; Gázquez, José L.; Vela, Alberto

2015-01-01

We explore the local and nonlocal response functions of the grand canonical potential density functional at nonzero temperature. In analogy to the zero-temperature treatment, local (e.g., the average electron density and the local softness) and nonlocal (e.g., the softness kernel) intrinsic response functions are defined as partial derivatives of the grand canonical potential with respect to its thermodynamic variables (i.e., the chemical potential of the electron reservoir and the external potential generated by the atomic nuclei). To define the local and nonlocal response functions of the electron density (e.g., the Fukui function, the linear density response function, and the dual descriptor), we differentiate with respect to the average electron number and the external potential. The well-known mathematical relationships between the intrinsic response functions and the electron-density responses are generalized to nonzero temperature, and we prove that in the zero-temperature limit, our results recover well-known identities from the density functional theory of chemical reactivity. Specific working equations and numerical results are provided for the 3-state ensemble model

Distribution of Budget Shares for Food: An Application of Quantile Regression to Food Security 1

Directory of Open Access Journals (Sweden)

Charles B. Moss

2016-04-01

Full Text Available This study examines, using quantile regression, the linkage between food security and efforts to enhance smallholder coffee producer incomes in Rwanda. Even though in Rwanda smallholder coffee producer incomes have increased, inhabitants these areas still experience stunting and wasting. This study examines whether the distribution of the income elasticity for food is the same for coffee and noncoffee growing provinces. We find that that the share of expenditures on food is statistically different in coffee growing and noncoffee growing provinces. Thus, the increase in expenditure on food is smaller for coffee growing provinces than noncoffee growing provinces.

Growth of linear Ni-filled carbon nanotubes by local arc discharge in liquid ethanol

Energy Technology Data Exchange (ETDEWEB)

Sagara, Takuya [Department of Electric Engineering, Graduated School of Science and Technology, Nihon University, 1-8-14 Surugadai Kanda, Chiyoda, Tokyo 101-8308 (Japan); Kurumi, Satoshi [Department of Electric Engineering, College of Science and Technology, Nihon University, 1-8-14 Surugadai Kanda, Chiyoda, Tokyo 101-8308 (Japan); Suzuki, Kaoru, E-mail: kaoru@ele.cst.nihon-u.ac.jp [Department of Electric Engineering, College of Science and Technology, Nihon University, 1-8-14 Surugadai Kanda, Chiyoda, Tokyo 101-8308 (Japan)

2014-02-15

The cylindrical geometry of carbon nanotubes (CNTs) allows them to be filled with metal catalysts; the resulting metal-filled CNTs possess different properties depending on the filler metal. Here we report the synthesis of Ni-filled CNTs in which Ni is situated linearly and homogeneously by local arc discharge in liquid ethanol. The structural characteristics of synthesized Ni-filled CNTs were determined by transmission electron microscopy (TEM), and the relationship between pyrolysis conditions and the length and diameter of Ni-filled CNTs was examined. The encapsulated Ni was identified by a TEM-equipped energy-dispersive X-ray spectroscope and found to have a single-crystal fcc structure by nano-beam diffraction. The features of linear Ni-filled CNT are expected to be applicable to probes for magnetic force microscopy.

A Cross-Domain Collaborative Filtering Algorithm Based on Feature Construction and Locally Weighted Linear Regression.

Science.gov (United States)

Yu, Xu; Lin, Jun-Yu; Jiang, Feng; Du, Jun-Wei; Han, Ji-Zhong

2018-01-01

Cross-domain collaborative filtering (CDCF) solves the sparsity problem by transferring rating knowledge from auxiliary domains. Obviously, different auxiliary domains have different importance to the target domain. However, previous works cannot evaluate effectively the significance of different auxiliary domains. To overcome this drawback, we propose a cross-domain collaborative filtering algorithm based on Feature Construction and Locally Weighted Linear Regression (FCLWLR). We first construct features in different domains and use these features to represent different auxiliary domains. Thus the weight computation across different domains can be converted as the weight computation across different features. Then we combine the features in the target domain and in the auxiliary domains together and convert the cross-domain recommendation problem into a regression problem. Finally, we employ a Locally Weighted Linear Regression (LWLR) model to solve the regression problem. As LWLR is a nonparametric regression method, it can effectively avoid underfitting or overfitting problem occurring in parametric regression methods. We conduct extensive experiments to show that the proposed FCLWLR algorithm is effective in addressing the data sparsity problem by transferring the useful knowledge from the auxiliary domains, as compared to many state-of-the-art single-domain or cross-domain CF methods.

Quantum non-local charges and absence of particle production in the two-dimensional non-linear sigma-model

International Nuclear Information System (INIS)

Luescher, M.

1977-12-01

Conserved non-local charges are shown to exist in the quantum non-linear sigma-model by a non-perturbative method. They imply the absence of particle production and the 'factorization equations' for the two particle S-matrix, which can then be calculated explicitly. (Auth.)

A local-global problem for linear differential equations

NARCIS (Netherlands)

Put, Marius van der; Reversat, Marc

An inhomogeneous linear differential equation Ly = f over a global differential field can have a formal solution for each place without having a global solution. The vector space lgl(L) measures this phenomenon. This space is interpreted in terms of cohomology of linear algebraic groups and is

A local-global problem for linear differential equations

NARCIS (Netherlands)

Put, Marius van der; Reversat, Marc

2008-01-01

An inhomogeneous linear differential equation Ly = f over a global differential field can have a formal solution for each place without having a global solution. The vector space lgl(L) measures this phenomenon. This space is interpreted in terms of cohomology of linear algebraic groups and is

Non-linear optical materials

CERN Document Server

Saravanan, R

2018-01-01

Non-linear optical materials have widespread and promising applications, but the efforts to understand the local structure, electron density distribution and bonding is still lacking. The present work explores the structural details, the electron density distribution and the local bond length distribution of some non-linear optical materials. It also gives estimation of the optical band gap, the particle size, crystallite size, and the elemental composition from UV-Visible analysis, SEM, XRD and EDS of some non-linear optical materials respectively.

The N-shaped environmental Kuznets curve: an empirical evaluation using a panel quantile regression approach.

Science.gov (United States)

Allard, Alexandra; Takman, Johanna; Uddin, Gazi Salah; Ahmed, Ali

2018-02-01

We evaluate the N-shaped environmental Kuznets curve (EKC) using panel quantile regression analysis. We investigate the relationship between CO 2 emissions and GDP per capita for 74 countries over the period of 1994-2012. We include additional explanatory variables, such as renewable energy consumption, technological development, trade, and institutional quality. We find evidence for the N-shaped EKC in all income groups, except for the upper-middle-income countries. Heterogeneous characteristics are, however, observed over the N-shaped EKC. Finally, we find a negative relationship between renewable energy consumption and CO 2 emissions, which highlights the importance of promoting greener energy in order to combat global warming.

Extending Local Canonical Correlation Analysis to Handle General Linear Contrasts for fMRI Data

Directory of Open Access Journals (Sweden)

Mingwu Jin

2012-01-01

Full Text Available Local canonical correlation analysis (CCA is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM, a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic.

The Public-Private Sector Wage Gap in Zambia in the 1990s: A Quantile Regression Approach

DEFF Research Database (Denmark)

Nielsen, Helena Skyt; Rosholm, Michael

2001-01-01

of economic transition, because items as privatization and deregulation were on the political agenda. The focus is placed on the public-private sector wage gap, and the results show that this gap was relatively favorable for the low-skilled and less favorable for the high-skilled. This picture was further......We investigate the determinants of wages in Zambia and based on the quantile regression approach, we analyze how their effects differ at different points in the wage distribution and over time. We use three cross-sections of Zambian household data from the early nineties, which was a period...

Super-resolved linear fluorescence localization microscopy using photostable fluorophores: A virtual microscopy study

Science.gov (United States)

Birk, Udo; Szczurek, Aleksander; Cremer, Christoph

2017-12-01

Current approaches to overcome the conventional limit of the resolution potential of light microscopy (of about 200 nm for visible light), often suffer from non-linear effects, which render the quantification of the image intensities in the reconstructions difficult, and also affect the quantification of the biological structure under investigation. As an attempt to face these difficulties, we discuss a particular method of localization microscopy which is based on photostable fluorescent dyes. The proposed method can potentially be implemented as a fast alternative for quantitative localization microscopy, circumventing the need for the acquisition of thousands of image frames and complex, highly dye-specific imaging buffers. Although the need for calibration remains in order to extract quantitative data (such as the number of emitters), multispectral approaches are largely facilitated due to the much less stringent requirements on imaging buffers. Furthermore, multispectral acquisitions can be readily obtained using commercial instrumentation such as e.g. the conventional confocal laser scanning microscope.

A Cross-Domain Collaborative Filtering Algorithm Based on Feature Construction and Locally Weighted Linear Regression

Directory of Open Access Journals (Sweden)

Xu Yu

2018-01-01

Full Text Available Cross-domain collaborative filtering (CDCF solves the sparsity problem by transferring rating knowledge from auxiliary domains. Obviously, different auxiliary domains have different importance to the target domain. However, previous works cannot evaluate effectively the significance of different auxiliary domains. To overcome this drawback, we propose a cross-domain collaborative filtering algorithm based on Feature Construction and Locally Weighted Linear Regression (FCLWLR. We first construct features in different domains and use these features to represent different auxiliary domains. Thus the weight computation across different domains can be converted as the weight computation across different features. Then we combine the features in the target domain and in the auxiliary domains together and convert the cross-domain recommendation problem into a regression problem. Finally, we employ a Locally Weighted Linear Regression (LWLR model to solve the regression problem. As LWLR is a nonparametric regression method, it can effectively avoid underfitting or overfitting problem occurring in parametric regression methods. We conduct extensive experiments to show that the proposed FCLWLR algorithm is effective in addressing the data sparsity problem by transferring the useful knowledge from the auxiliary domains, as compared to many state-of-the-art single-domain or cross-domain CF methods.

STRONG ORACLE OPTIMALITY OF FOLDED CONCAVE PENALIZED ESTIMATION.

Science.gov (United States)

Fan, Jianqing; Xue, Lingzhou; Zou, Hui

2014-06-01

Folded concave penalization methods have been shown to enjoy the strong oracle property for high-dimensional sparse estimation. However, a folded concave penalization problem usually has multiple local solutions and the oracle property is established only for one of the unknown local solutions. A challenging fundamental issue still remains that it is not clear whether the local optimum computed by a given optimization algorithm possesses those nice theoretical properties. To close this important theoretical gap in over a decade, we provide a unified theory to show explicitly how to obtain the oracle solution via the local linear approximation algorithm. For a folded concave penalized estimation problem, we show that as long as the problem is localizable and the oracle estimator is well behaved, we can obtain the oracle estimator by using the one-step local linear approximation. In addition, once the oracle estimator is obtained, the local linear approximation algorithm converges, namely it produces the same estimator in the next iteration. The general theory is demonstrated by using four classical sparse estimation problems, i.e., sparse linear regression, sparse logistic regression, sparse precision matrix estimation and sparse quantile regression.

Probing the Locality of Excited States with Linear Algebra.

Science.gov (United States)

Etienne, Thibaud

2015-04-14

This article reports a novel theoretical approach related to the analysis of molecular excited states. The strategy introduced here involves gathering two pieces of physical information, coming from Hilbert and direct space operations, into a general, unique quantum mechanical descriptor of electronic transitions' locality. Moreover, the projection of Hilbert and direct space-derived indices in an Argand plane delivers a straightforward way to visually probe the ability of a dye to undergo a long- or short-range charge-transfer. This information can be applied, for instance, to the analysis of the electronic response of families of dyes to light absorption by unveiling the trend of a given push-pull chromophore to increase the electronic cloud polarization magnitude of its main transition with respect to the size extension of its conjugated spacer. We finally demonstrate that all the quantities reported in this article can be reliably approximated by a linear algebraic derivation, based on the contraction of detachment/attachment density matrices from canonical to atomic space. This alternative derivation has the remarkable advantage of a very low computational cost with respect to the previously used numerical integrations, making fast and accurate characterization of large molecular systems' excited states easily affordable.

Bearing Fault Diagnosis Based on Statistical Locally Linear Embedding.

Science.gov (United States)

Wang, Xiang; Zheng, Yuan; Zhao, Zhenzhou; Wang, Jinping

2015-07-06

Fault diagnosis is essentially a kind of pattern recognition. The measured signal samples usually distribute on nonlinear low-dimensional manifolds embedded in the high-dimensional signal space, so how to implement feature extraction, dimensionality reduction and improve recognition performance is a crucial task. In this paper a novel machinery fault diagnosis approach based on a statistical locally linear embedding (S-LLE) algorithm which is an extension of LLE by exploiting the fault class label information is proposed. The fault diagnosis approach first extracts the intrinsic manifold features from the high-dimensional feature vectors which are obtained from vibration signals that feature extraction by time-domain, frequency-domain and empirical mode decomposition (EMD), and then translates the complex mode space into a salient low-dimensional feature space by the manifold learning algorithm S-LLE, which outperforms other feature reduction methods such as PCA, LDA and LLE. Finally in the feature reduction space pattern classification and fault diagnosis by classifier are carried out easily and rapidly. Rolling bearing fault signals are used to validate the proposed fault diagnosis approach. The results indicate that the proposed approach obviously improves the classification performance of fault pattern recognition and outperforms the other traditional approaches.

String Chopping and Time-ordered Products of Linear String-localized Quantum Fields

Science.gov (United States)

Cardoso, Lucas T.; Mund, Jens; Várilly, Joseph C.

2018-03-01

For a renormalizability proof of perturbative models in the Epstein-Glaser scheme with string-localized quantum fields, one needs to know what freedom one has in the definition of time-ordered products of the interaction Lagrangian. This paper provides a first step in that direction. The basic issue is the presence of an open set of n-tuples of strings which cannot be chronologically ordered. We resolve it by showing that almost all such string configurations can be dissected into finitely many pieces which can indeed be chronologically ordered. This fixes the time-ordered products of linear field factors outside a nullset of string configurations. (The extension across the nullset, as well as the definition of time-ordered products of Wick monomials, will be discussed elsewhere).

Quantile selection procedure and assoiated distribution of ratios of order statistics from a restricted family of probability distributions

International Nuclear Information System (INIS)

Gupta, S.S.; Panchapakesan, S.

1975-01-01

A quantile selection procedure in reliability problems pertaining to a restricted family of probability distributions is discussed. This family is assumed to be star-ordered with respect to the standard normal distribution folded at the origin. Motivation for this formulation of the problem is described. Both exact and asymptotic results dealing with the distribution of the maximum of ratios of order statistics from such a family are obtained and tables of the appropriate constants, percentiles of this statistic, are given in order to facilitate the use of the selection procedure

Local correlation detection with linearity enhancement in streaming data

KAUST Repository

Xie, Qing; Shang, Shuo; Yuan, Bo; Pang, Chaoyi; Zhang, Xiangliang

2013-01-01

-correlation calculation with time delay allowed. In addition, we introduce a shape-based similarity measure into the framework, which ref nes the results by representative trend patterns to enhance the signif cance of linearity. The similarity of proposed linear

Global hybrids from the semiclassical atom theory satisfying the local density linear response.

Science.gov (United States)

Fabiano, Eduardo; Constantin, Lucian A; Cortona, Pietro; Della Sala, Fabio

2015-01-13

We propose global hybrid approximations of the exchange-correlation (XC) energy functional which reproduce well the modified fourth-order gradient expansion of the exchange energy in the semiclassical limit of many-electron neutral atoms and recover the full local density approximation (LDA) linear response. These XC functionals represent the hybrid versions of the APBE functional [Phys. Rev. Lett. 2011, 106, 186406] yet employing an additional correlation functional which uses the localization concept of the correlation energy density to improve the compatibility with the Hartree-Fock exchange as well as the coupling-constant-resolved XC potential energy. Broad energetic and structural testing, including thermochemistry and geometry, transition metal complexes, noncovalent interactions, gold clusters and small gold-molecule interfaces, as well as an analysis of the hybrid parameters, show that our construction is quite robust. In particular, our testing shows that the resulting hybrid, including 20% of Hartree-Fock exchange and named hAPBE, performs remarkably well for a broad palette of systems and properties, being generally better than popular hybrids (PBE0 and B3LYP). Semiempirical dispersion corrections are also provided.

Alternative regression models to assess increase in childhood BMI.

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Beyerlein, Andreas; Fahrmeir, Ludwig; Mansmann, Ulrich; Toschke, André M

2008-09-08

Body mass index (BMI) data usually have skewed distributions, for which common statistical modeling approaches such as simple linear or logistic regression have limitations. Different regression approaches to predict childhood BMI by goodness-of-fit measures and means of interpretation were compared including generalized linear models (GLMs), quantile regression and Generalized Additive Models for Location, Scale and Shape (GAMLSS). We analyzed data of 4967 children participating in the school entry health examination in Bavaria, Germany, from 2001 to 2002. TV watching, meal frequency, breastfeeding, smoking in pregnancy, maternal obesity, parental social class and weight gain in the first 2 years of life were considered as risk factors for obesity. GAMLSS showed a much better fit regarding the estimation of risk factors effects on transformed and untransformed BMI data than common GLMs with respect to the generalized Akaike information criterion. In comparison with GAMLSS, quantile regression allowed for additional interpretation of prespecified distribution quantiles, such as quantiles referring to overweight or obesity. The variables TV watching, maternal BMI and weight gain in the first 2 years were directly, and meal frequency was inversely significantly associated with body composition in any model type examined. In contrast, smoking in pregnancy was not directly, and breastfeeding and parental social class were not inversely significantly associated with body composition in GLM models, but in GAMLSS and partly in quantile regression models. Risk factor specific BMI percentile curves could be estimated from GAMLSS and quantile regression models. GAMLSS and quantile regression seem to be more appropriate than common GLMs for risk factor modeling of BMI data.

The heterogeneous effects of urbanization and income inequality on CO2 emissions in BRICS economies: evidence from panel quantile regression.

Science.gov (United States)

Zhu, Huiming; Xia, Hang; Guo, Yawei; Peng, Cheng

2018-04-12

This paper empirically examines the effects of urbanization and income inequality on CO 2 emissions in the BRICS economies (i.e., Brazil, Russia, India, China, and South Africa) during the periods 1994-2013. The method we used is the panel quantile regression, which takes into account the unobserved individual heterogeneity and distributional heterogeneity. Our empirical results indicate that urbanization has a significant and negative impact on carbon emissions, except in the 80 th , 90 th , and 95 th quantiles. We also quantitatively investigate the direct and indirect effect of urbanization on carbon emissions, and the results show that we may underestimate urbanization's effect on carbon emissions if we ignore its indirect effect. In addition, in middle- and high-emission countries, income inequality has a significant and positive impact on carbon emissions. The results of our study indicate that in the BRICS economies, there is an inverted U-shaped environmental Kuznets curve (EKC) between the GDP per capita and carbon emissions. The conclusions of this study have important policy implications for policymakers. Policymakers should try to narrow the income gap between the rich and the poor to improve environmental quality; the BRICS economies can speed up urbanization to reduce carbon emissions, but they must improve energy efficiency and use clean energy to the greatest extent in the process.

Technical Note: The normal quantile transformation and its application in a flood forecasting system

Directory of Open Access Journals (Sweden)

K. Bogner

2012-04-01

Full Text Available The Normal Quantile Transform (NQT has been used in many hydrological and meteorological applications in order to make the Cumulated Distribution Function (CDF of the observed, simulated and forecast river discharge, water level or precipitation data Gaussian. It is also the heart of the meta-Gaussian model for assessing the total predictive uncertainty of the Hydrological Uncertainty Processor (HUP developed by Krzysztofowicz. In the field of geo-statistics this transformation is better known as the Normal-Score Transform. In this paper some possible problems caused by small sample sizes when applying the NQT in flood forecasting systems will be discussed and a novel way to solve the problem will be outlined by combining extreme value analysis and non-parametric regression methods. The method will be illustrated by examples of hydrological stream-flow forecasts.

Investment determinants of young and old Portuguese SMEs: A quantile approach

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Sílvia Mendes

2014-10-01

Full Text Available Considering two samples of Portuguese SMEs: 582 young SMEs and 1654 old SMEs, using the two-step estimation method and quantile regressions, the empirical evidence allows us to conclude that the determinants of investment have a different impact on young and old SMEs, depending on a firm’ level of investment. In the framework of Acceleration Principle and Neoclassical Theories, the determinants are relevant in explaining the investment of young and old SMEs with high levels of investment. The Growth Domestic Product, as the investment determinant of Acceleration Principle Theory, has a greater impact on the investment of young SMEs with high levels of investment. Sales, as the investment determinant of Neoclassical Theory, have greater impact on the investment of old SMEs with high levels of investment. Cash flow, as the investment determinant of Free Cash Flow Theory, is important in explaining the investment of young and old SMEs with low levels of investment. However, cash flow has greater impact on the investment of young SMEs with low levels of investment. The empirical evidence obtained allows us to make suggestions for policy-makers and the owners/managers of Portuguese SMEs.

Structured Additive Quantile Regression for Assessing the Determinants of Childhood Anemia in Rwanda

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Faustin Habyarimana

2017-06-01

Full Text Available Childhood anemia is among the most significant health problems faced by public health departments in developing countries. This study aims at assessing the determinants and possible spatial effects associated with childhood anemia in Rwanda. The 2014/2015 Rwanda Demographic and Health Survey (RDHS data was used. The analysis was done using the structured spatial additive quantile regression model. The findings of this study revealed that the child’s age; the duration of breastfeeding; gender of the child; the nutritional status of the child (whether underweight and/or wasting; whether the child had a fever; had a cough in the two weeks prior to the survey or not; whether the child received vitamin A supplementation in the six weeks before the survey or not; the household wealth index; literacy of the mother; mother’s anemia status; mother’s age at the birth are all significant factors associated with childhood anemia in Rwanda. Furthermore, significant structured spatial location effects on childhood anemia was found.

Structured Additive Quantile Regression for Assessing the Determinants of Childhood Anemia in Rwanda.

Science.gov (United States)

Habyarimana, Faustin; Zewotir, Temesgen; Ramroop, Shaun

2017-06-17

Childhood anemia is among the most significant health problems faced by public health departments in developing countries. This study aims at assessing the determinants and possible spatial effects associated with childhood anemia in Rwanda. The 2014/2015 Rwanda Demographic and Health Survey (RDHS) data was used. The analysis was done using the structured spatial additive quantile regression model. The findings of this study revealed that the child's age; the duration of breastfeeding; gender of the child; the nutritional status of the child (whether underweight and/or wasting); whether the child had a fever; had a cough in the two weeks prior to the survey or not; whether the child received vitamin A supplementation in the six weeks before the survey or not; the household wealth index; literacy of the mother; mother's anemia status; mother's age at the birth are all significant factors associated with childhood anemia in Rwanda. Furthermore, significant structured spatial location effects on childhood anemia was found.

Alternative regression models to assess increase in childhood BMI

Directory of Open Access Journals (Sweden)

Mansmann Ulrich

2008-09-01

Full Text Available Abstract Background Body mass index (BMI data usually have skewed distributions, for which common statistical modeling approaches such as simple linear or logistic regression have limitations. Methods Different regression approaches to predict childhood BMI by goodness-of-fit measures and means of interpretation were compared including generalized linear models (GLMs, quantile regression and Generalized Additive Models for Location, Scale and Shape (GAMLSS. We analyzed data of 4967 children participating in the school entry health examination in Bavaria, Germany, from 2001 to 2002. TV watching, meal frequency, breastfeeding, smoking in pregnancy, maternal obesity, parental social class and weight gain in the first 2 years of life were considered as risk factors for obesity. Results GAMLSS showed a much better fit regarding the estimation of risk factors effects on transformed and untransformed BMI data than common GLMs with respect to the generalized Akaike information criterion. In comparison with GAMLSS, quantile regression allowed for additional interpretation of prespecified distribution quantiles, such as quantiles referring to overweight or obesity. The variables TV watching, maternal BMI and weight gain in the first 2 years were directly, and meal frequency was inversely significantly associated with body composition in any model type examined. In contrast, smoking in pregnancy was not directly, and breastfeeding and parental social class were not inversely significantly associated with body composition in GLM models, but in GAMLSS and partly in quantile regression models. Risk factor specific BMI percentile curves could be estimated from GAMLSS and quantile regression models. Conclusion GAMLSS and quantile regression seem to be more appropriate than common GLMs for risk factor modeling of BMI data.

Turbulence Spreading into Linearly Stable Zone and Transport Scaling

International Nuclear Information System (INIS)

Hahm, T.S.; Diamond, P.H.; Lin, Z.; Itoh, K.; Itoh, S.-I.

2003-01-01

We study the simplest problem of turbulence spreading corresponding to the spatio-temporal propagation of a patch of turbulence from a region where it is locally excited to a region of weaker excitation, or even local damping. A single model equation for the local turbulence intensity I(x, t) includes the effects of local linear growth and damping, spatially local nonlinear coupling to dissipation and spatial scattering of turbulence energy induced by nonlinear coupling. In the absence of dissipation, the front propagation into the linearly stable zone occurs with the property of rapid progression at small t, followed by slower subdiffusive progression at late times. The turbulence radial spreading into the linearly stable zone reduces the turbulent intensity in the linearly unstable zone, and introduces an additional dependence on the rho* is always equal to rho i/a to the turbulent intensity and the transport scaling. These are in broad, semi-quantitative agreements with a number of global gyrokinetic simulation results with zonal flows and without zonal flows. The front propagation stops when the radial flux of fluctuation energy from the linearly unstable region is balanced by local dissipation in the linearly stable region

A quantile approach to assess the effectiveness of the subsidy policy for energy-efficient home appliances: Evidence from Rizhao, China

International Nuclear Information System (INIS)

Yao, Xi-Long; Liu, Yang; Yan, Xiao

2014-01-01

A one-year subsidy program for energy-efficient home appliances has been implemented in China. We construct a dataset consisting of participant and non-participant households in both urban and rural areas of Rizhao city. By applying a quantile regression and counterfactual analysis, this study disentangles the impact of this subsidy program and inherent household attributes on per capita residential electricity consumption. First, contrary to the mean regression, the elasticity of electricity consumption to household's income, age, education and energy-saving awareness, varies markedly across the electricity consumption distribution and shows discrepancy between urban and rural areas. Second, while inherent household attributes are identified as a primary determinant to the changes in residential electricity consumption, the effect induced by the subsidy incentive is more significant at the middle of the electricity consumption distribution than at the tails. Third, there are significant rebound effects that lead to overall increase in household electricity consumption. Our results suggest that the disparity between urban and rural regions and targeted consumer behavior changes should be taken into account to ensure the effectiveness of a future energy-efficient subsidy program. - Highlights: • The effect of the subsidy policy on electricity consumption is assessed with a quantile regression. • Policy induced effect is more significant at the middle of the distribution than at the tails. • The rebound effects lead to overall increase in electricity consumption. • The impact of households attributes varies markedly across electricity consumption distribution

General rigid motion correction for computed tomography imaging based on locally linear embedding

Science.gov (United States)

Chen, Mianyi; He, Peng; Feng, Peng; Liu, Baodong; Yang, Qingsong; Wei, Biao; Wang, Ge

2018-02-01

The patient motion can damage the quality of computed tomography images, which are typically acquired in cone-beam geometry. The rigid patient motion is characterized by six geometric parameters and are more challenging to correct than in fan-beam geometry. We extend our previous rigid patient motion correction method based on the principle of locally linear embedding (LLE) from fan-beam to cone-beam geometry and accelerate the computational procedure with the graphics processing unit (GPU)-based all scale tomographic reconstruction Antwerp toolbox. The major merit of our method is that we need neither fiducial markers nor motion-tracking devices. The numerical and experimental studies show that the LLE-based patient motion correction is capable of calibrating the six parameters of the patient motion simultaneously, reducing patient motion artifacts significantly.

Localized irradiation of mouse legs using an image-guided robotic linear accelerator.

Science.gov (United States)

Kufeld, Markus; Escobar, Helena; Marg, Andreas; Pasemann, Diana; Budach, Volker; Spuler, Simone

2017-04-01

To investigate the potential of human satellite cells in muscle regeneration small animal models are useful to evaluate muscle regeneration. To suppress the inherent regeneration ability of the tibialis muscle of mice before transplantation of human muscle fibers, a localized irradiation of the mouse leg should be conducted. We analyzed the feasibility of an image-guided robotic irradiation procedure, a routine treatment method in radiation oncology, for the focal irradiation of mouse legs. After conducting a planning computed tomography (CT) scan of one mouse in its customized mold a three-dimensional dose plan was calculated using a dedicated planning workstation. 18 Gy have been applied to the right anterior tibial muscle of 4 healthy and 12 mice with immune defect in general anesthesia using an image-guided robotic linear accelerator (LINAC). The mice were fixed in a customized acrylic mold with attached fiducial markers for image guided tracking. All 16 mice could be irradiated as prevised without signs of acute radiation toxicity or anesthesiological side effects. The animals survived until scarification after 8, 21 and 49 days as planned. The procedure was straight forward and the irradiation process took 5 minutes to apply the dose of 18 Gy. Localized irradiation of mice legs using a robotic LINAC could be conducted as planned. It is a feasible procedure without recognizable side effects. Image guidance offers precise dose delivery and preserves adjacent body parts and tissues.

Accurate Evaluation of Expected Shortfall for Linear Portfolios with Elliptically Distributed Risk Factors

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Dobrislav Dobrev∗

2017-02-01

Full Text Available We provide an accurate closed-form expression for the expected shortfall of linear portfolios with elliptically distributed risk factors. Our results aim to correct inaccuracies that originate in Kamdem (2005 and are present also in at least thirty other papers referencing it, including the recent survey by Nadarajah et al. (2014 on estimation methods for expected shortfall. In particular, we show that the correction we provide in the popular multivariate Student t setting eliminates understatement of expected shortfall by a factor varying from at least four to more than 100 across different tail quantiles and degrees of freedom. As such, the resulting economic impact in financial risk management applications could be significant. We further correct such errors encountered also in closely related results in Kamdem (2007 and 2009 for mixtures of elliptical distributions. More generally, our findings point to the extra scrutiny required when deploying new methods for expected shortfall estimation in practice.

Linear scaling of density functional algorithms

International Nuclear Information System (INIS)

Stechel, E.B.; Feibelman, P.J.; Williams, A.R.

1993-01-01

An efficient density functional algorithm (DFA) that scales linearly with system size will revolutionize electronic structure calculations. Density functional calculations are reliable and accurate in determining many condensed matter and molecular ground-state properties. However, because current DFA's, including methods related to that of Car and Parrinello, scale with the cube of the system size, density functional studies are not routinely applied to large systems. Linear scaling is achieved by constructing functions that are both localized and fully occupied, thereby eliminating the need to calculate global eigenfunctions. It is, however, widely believed that exponential localization requires the existence of an energy gap between the occupied and unoccupied states. Despite this, the authors demonstrate that linear scaling can still be achieved for metals. Using a linear scaling algorithm, they have explicitly constructed localized, almost fully occupied orbitals for the quintessential metallic system, jellium. The algorithm is readily generalizable to any system geometry and Hamiltonian. They will discuss the conceptual issues involved, convergence properties and scaling for their new algorithm

Localized modelling and feedback control of linear instabilities in 2-D wall bounded shear flows

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Tol, Henry; Kotsonis, Marios; de Visser, Coen

2016-11-01

A new approach is presented for control of instabilities in 2-D wall bounded shear flows described by the linearized Navier-Stokes equations (LNSE). The control design accounts both for spatially localized actuators/sensors and the dominant perturbation dynamics in an optimal control framework. An inflow disturbance model is proposed for streamwise instabilities that drive laminar-turbulent transition. The perturbation modes that contribute to the transition process can be selected and are included in the control design. A reduced order model is derived from the LNSE that captures the input-output behavior and the dominant perturbation dynamics. This model is used to design an optimal controller for suppressing the instability growth. A 2-D channel flow and a 2-D boundary layer flow over a flat plate are considered as application cases. Disturbances are generated upstream of the control domain and the resulting flow perturbations are estimated/controlled using wall shear measurements and localized unsteady blowing and suction at the wall. It will be shown that the controller is able to cancel the perturbations and is robust to unmodelled disturbances.

Two-Stage Method Based on Local Polynomial Fitting for a Linear Heteroscedastic Regression Model and Its Application in Economics

Directory of Open Access Journals (Sweden)

Liyun Su

2012-01-01

Full Text Available We introduce the extension of local polynomial fitting to the linear heteroscedastic regression model. Firstly, the local polynomial fitting is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using generalized least squares method. One noteworthy feature of our approach is that we avoid the testing for heteroscedasticity by improving the traditional two-stage method. Due to nonparametric technique of local polynomial estimation, we do not need to know the heteroscedastic function. Therefore, we can improve the estimation precision, when the heteroscedastic function is unknown. Furthermore, we focus on comparison of parameters and reach an optimal fitting. Besides, we verify the asymptotic normality of parameters based on numerical simulations. Finally, this approach is applied to a case of economics, and it indicates that our method is surely effective in finite-sample situations.

Fast decay of solutions for linear wave equations with dissipation localized near infinity in an exterior domain

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Ryo, Ikehata

Uniform energy and L2 decay of solutions for linear wave equations with localized dissipation will be given. In order to derive the L2-decay property of the solution, a useful device whose idea comes from Ikehata-Matsuyama (Sci. Math. Japon. 55 (2002) 33) is used. In fact, we shall show that the L2-norm and the total energy of solutions, respectively, decay like O(1/ t) and O(1/ t2) as t→+∞ for a kind of the weighted initial data.

Local measurement and numerical modeling of mass/heat transfer from a turbine blade in a linear cascade with tip clearance

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Jin, Peitong

2000-11-01

Local mass/heat transfer measurements from the turbine blade near-tip and the tip surfaces are performed using the naphthalene sublimation technique. The experiments are conducted in a linear cascade consisting of five high-pressure blades with a central test-blade configuration. The incoming flow conditions are close to those of the gas turbine engine environment (boundary layer displacement thickness is about 0.01 of chord) with an exit Reynolds number of 6.2 x 105. The effects of tip clearance level (0.86%--6.90% of chord), mainstream Reynolds number and turbulence intensity (0.2 and 12.0%) are investigated. Two methods of flow visualization---oil and lampblack, laser light sheet smoke wire---as well as static pressure measurement on the blade surface are used to study the tip leakage flow and vortex in the cascade. In addition, numerical modeling of the flow and heat transfer processes in the linear cascade with different tip clearances is conducted using commercial software incorporating advanced turbulence models. The present study confirms many important results on the tip leakage flow and vortex from the literature, contributes to the current understanding in the effects of tip leakage flow and vortex on local heat transfer from the blade near-tip and the tip surfaces, and provides detailed local and average heat/mass transfer data applicable to turbine blade tip cooling design.

Bayesian uncertainty quantification in linear models for diffusion MRI.

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Sjölund, Jens; Eklund, Anders; Özarslan, Evren; Herberthson, Magnus; Bånkestad, Maria; Knutsson, Hans

2018-03-29

Diffusion MRI (dMRI) is a valuable tool in the assessment of tissue microstructure. By fitting a model to the dMRI signal it is possible to derive various quantitative features. Several of the most popular dMRI signal models are expansions in an appropriately chosen basis, where the coefficients are determined using some variation of least-squares. However, such approaches lack any notion of uncertainty, which could be valuable in e.g. group analyses. In this work, we use a probabilistic interpretation of linear least-squares methods to recast popular dMRI models as Bayesian ones. This makes it possible to quantify the uncertainty of any derived quantity. In particular, for quantities that are affine functions of the coefficients, the posterior distribution can be expressed in closed-form. We simulated measurements from single- and double-tensor models where the correct values of several quantities are known, to validate that the theoretically derived quantiles agree with those observed empirically. We included results from residual bootstrap for comparison and found good agreement. The validation employed several different models: Diffusion Tensor Imaging (DTI), Mean Apparent Propagator MRI (MAP-MRI) and Constrained Spherical Deconvolution (CSD). We also used in vivo data to visualize maps of quantitative features and corresponding uncertainties, and to show how our approach can be used in a group analysis to downweight subjects with high uncertainty. In summary, we convert successful linear models for dMRI signal estimation to probabilistic models, capable of accurate uncertainty quantification. Copyright © 2018 Elsevier Inc. All rights reserved.

Non linear structures seismic analysis by modal synthesis

International Nuclear Information System (INIS)

Aita, S.; Brochard, D.; Guilbaud, D.; Gibert, R.J.

1987-01-01

The structures submitted to a seismic excitation, may present a great amplitude response which induces a non linear behaviour. These non linearities have an important influence on the response of the structure. Even in this case (local shocks) the modal synthesis method remains attractive. In this paper we will present the way of taking into account, a local non linearity (shock between structures) in the seismic response of structures, by using the modal synthesis method [fr

Edge localized linear ideal magnetohydrodynamic instability studies in an extended-magnetohydrodynamic code

International Nuclear Information System (INIS)

Burke, B. J.; Kruger, S. E.; Hegna, C. C.; Zhu, P.; Snyder, P. B.; Sovinec, C. R.; Howell, E. C.

2010-01-01

A linear benchmark between the linear ideal MHD stability codes ELITE [H. R. Wilson et al., Phys. Plasmas 9, 1277 (2002)], GATO [L. Bernard et al., Comput. Phys. Commun. 24, 377 (1981)], and the extended nonlinear magnetohydrodynamic (MHD) code, NIMROD [C. R. Sovinec et al.., J. Comput. Phys. 195, 355 (2004)] is undertaken for edge-localized (MHD) instabilities. Two ballooning-unstable, shifted-circle tokamak equilibria are compared where the stability characteristics are varied by changing the equilibrium plasma profiles. The equilibria model an H-mode plasma with a pedestal pressure profile and parallel edge currents. For both equilibria, NIMROD accurately reproduces the transition to instability (the marginally unstable mode), as well as the ideal growth spectrum for a large range of toroidal modes (n=1-20). The results use the compressible MHD model and depend on a precise representation of 'ideal-like' and 'vacuumlike' or 'halo' regions within the code. The halo region is modeled by the introduction of a Lundquist-value profile that transitions from a large to a small value at a flux surface location outside of the pedestal region. To model an ideal-like MHD response in the core and a vacuumlike response outside the transition, separate criteria on the plasma and halo Lundquist values are required. For the benchmarked equilibria the critical Lundquist values are 10 8 and 10 3 for the ideal-like and halo regions, respectively. Notably, this gives a ratio on the order of 10 5 , which is much larger than experimentally measured values using T e values associated with the top of the pedestal and separatrix. Excellent agreement with ELITE and GATO calculations are made when sharp boundary transitions in the resistivity are used and a small amount of physical dissipation is added for conditions very near and below marginal ideal stability.

Using quantile regression to examine health care expenditures during the Great Recession.

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Chen, Jie; Vargas-Bustamante, Arturo; Mortensen, Karoline; Thomas, Stephen B

2014-04-01

To examine the association between the Great Recession of 2007-2009 and health care expenditures along the health care spending distribution, with a focus on racial/ethnic disparities. Secondary data analyses of the Medical Expenditure Panel Survey (2005-2006 and 2008-2009). Quantile multivariate regressions are employed to measure the different associations between the economic recession of 2007-2009 and health care spending. Race/ethnicity and interaction terms between race/ethnicity and a recession indicator are controlled to examine whether minorities encountered disproportionately lower health spending during the economic recession. The Great Recession was significantly associated with reductions in health care expenditures at the 10th-50th percentiles of the distribution, but not at the 75th-90th percentiles. Racial and ethnic disparities were more substantial at the lower end of the health expenditure distribution; however, on average the reduction in expenditures was similar for all race/ethnic groups. The Great Recession was also positively associated with spending on emergency department visits. This study shows that the relationship between the Great Recession and health care spending varied along the health expenditure distribution. More variability was observed in the lower end of the health spending distribution compared to the higher end. © Health Research and Educational Trust.

Automatic coronary artery segmentation based on multi-domains remapping and quantile regression in angiographies.

Science.gov (United States)

Li, Zhixun; Zhang, Yingtao; Gong, Huiling; Li, Weimin; Tang, Xianglong

2016-12-01

Coronary artery disease has become the most dangerous diseases to human life. And coronary artery segmentation is the basis of computer aided diagnosis and analysis. Existing segmentation methods are difficult to handle the complex vascular texture due to the projective nature in conventional coronary angiography. Due to large amount of data and complex vascular shapes, any manual annotation has become increasingly unrealistic. A fully automatic segmentation method is necessary in clinic practice. In this work, we study a method based on reliable boundaries via multi-domains remapping and robust discrepancy correction via distance balance and quantile regression for automatic coronary artery segmentation of angiography images. The proposed method can not only segment overlapping vascular structures robustly, but also achieve good performance in low contrast regions. The effectiveness of our approach is demonstrated on a variety of coronary blood vessels compared with the existing methods. The overall segmentation performances si, fnvf, fvpf and tpvf were 95.135%, 3.733%, 6.113%, 96.268%, respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.

Obesity inequality in Malaysia: decomposing differences by gender and ethnicity using quantile regression.

Science.gov (United States)

Dunn, Richard A; Tan, Andrew K G; Nayga, Rodolfo M

2012-01-01

Obesity prevalence is unequally distributed across gender and ethnic group in Malaysia. In this paper, we examine the role of socioeconomic inequality in explaining these disparities. The body mass index (BMI) distributions of Malays and Chinese, the two largest ethnic groups in Malaysia, are estimated through the use of quantile regression. The differences in the BMI distributions are then decomposed into two parts: attributable to differences in socioeconomic endowments and attributable to differences in responses to endowments. For both males and females, the BMI distribution of Malays is shifted toward the right of the distribution of Chinese, i.e., Malays exhibit higher obesity rates. In the lower 75% of the distribution, differences in socioeconomic endowments explain none of this difference. At the 90th percentile, differences in socioeconomic endowments account for no more than 30% of the difference in BMI between ethnic groups. Our results demonstrate that the higher levels of income and education that accrue with economic development will likely not eliminate obesity inequality. This leads us to conclude that reduction of obesity inequality, as well the overall level of obesity, requires increased efforts to alter the lifestyle behaviors of Malaysians.

Inferring river bathymetry via Image-to-Depth Quantile Transformation (IDQT)

Science.gov (United States)

Legleiter, Carl

2016-01-01

Conventional, regression-based methods of inferring depth from passive optical image data undermine the advantages of remote sensing for characterizing river systems. This study introduces and evaluates a more flexible framework, Image-to-Depth Quantile Transformation (IDQT), that involves linking the frequency distribution of pixel values to that of depth. In addition, a new image processing workflow involving deep water correction and Minimum Noise Fraction (MNF) transformation can reduce a hyperspectral data set to a single variable related to depth and thus suitable for input to IDQT. Applied to a gravel bed river, IDQT avoided negative depth estimates along channel margins and underpredictions of pool depth. Depth retrieval accuracy (R25 0.79) and precision (0.27 m) were comparable to an established band ratio-based method, although a small shallow bias (0.04 m) was observed. Several ways of specifying distributions of pixel values and depths were evaluated but had negligible impact on the resulting depth estimates, implying that IDQT was robust to these implementation details. In essence, IDQT uses frequency distributions of pixel values and depths to achieve an aspatial calibration; the image itself provides information on the spatial distribution of depths. The approach thus reduces sensitivity to misalignment between field and image data sets and allows greater flexibility in the timing of field data collection relative to image acquisition, a significant advantage in dynamic channels. IDQT also creates new possibilities for depth retrieval in the absence of field data if a model could be used to predict the distribution of depths within a reach.

Least-squares reverse time migration with local Radon-based preconditioning

KAUST Repository

Dutta, Gaurav

2017-03-08

Least-squares migration (LSM) can produce images with better balanced amplitudes and fewer artifacts than standard migration. The conventional objective function used for LSM minimizes the L2-norm of the data residual between the predicted and the observed data. However, for field-data applications in which the recorded data are noisy and undersampled, the conventional formulation of LSM fails to provide the desired uplift in the quality of the inverted image. We have developed a leastsquares reverse time migration (LSRTM) method using local Radon-based preconditioning to overcome the low signal-tonoise ratio (S/N) problem of noisy or severely undersampled data. A high-resolution local Radon transform of the reflectivity is used, and sparseness constraints are imposed on the inverted reflectivity in the local Radon domain. The sparseness constraint is that the inverted reflectivity is sparse in the Radon domain and each location of the subsurface is represented by a limited number of geologic dips. The forward and the inverse mapping of the reflectivity to the local Radon domain and vice versa is done through 3D Fourier-based discrete Radon transform operators. The weights for the preconditioning are chosen to be varying locally based on the relative amplitudes of the local dips or assigned using quantile measures. Numerical tests on synthetic and field data validate the effectiveness of our approach in producing images with good S/N and fewer aliasing artifacts when compared with standard RTM or standard LSRTM.

Quantile-based permutation thresholds for quantitative trait loci hotspots.

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Neto, Elias Chaibub; Keller, Mark P; Broman, Andrew F; Attie, Alan D; Jansen, Ritsert C; Broman, Karl W; Yandell, Brian S

2012-08-01

Quantitative trait loci (QTL) hotspots (genomic locations affecting many traits) are a common feature in genetical genomics studies and are biologically interesting since they may harbor critical regulators. Therefore, statistical procedures to assess the significance of hotspots are of key importance. One approach, randomly allocating observed QTL across the genomic locations separately by trait, implicitly assumes all traits are uncorrelated. Recently, an empirical test for QTL hotspots was proposed on the basis of the number of traits that exceed a predetermined LOD value, such as the standard permutation LOD threshold. The permutation null distribution of the maximum number of traits across all genomic locations preserves the correlation structure among the phenotypes, avoiding the detection of spurious hotspots due to nongenetic correlation induced by uncontrolled environmental factors and unmeasured variables. However, by considering only the number of traits above a threshold, without accounting for the magnitude of the LOD scores, relevant information is lost. In particular, biologically interesting hotspots composed of a moderate to small number of traits with strong LOD scores may be neglected as nonsignificant. In this article we propose a quantile-based permutation approach that simultaneously accounts for the number and the LOD scores of traits within the hotspots. By considering a sliding scale of mapping thresholds, our method can assess the statistical significance of both small and large hotspots. Although the proposed approach can be applied to any type of heritable high-volume "omic" data set, we restrict our attention to expression (e)QTL analysis. We assess and compare the performances of these three methods in simulations and we illustrate how our approach can effectively assess the significance of moderate and small hotspots with strong LOD scores in a yeast expression data set.

Accuracy of panoramic radiography and linear tomography in mandibular canal localization

Directory of Open Access Journals (Sweden)

Bashizadeh Fakhar H.

2008-10-01

Full Text Available "nBackground and Aim: Accurate bone measurements are essential to determine the optimal size and length of dental implants. The magnification factor of radiographic images may vary with the imaging technique used. The purpose of this study was to compare the accuracy of linear tomography and panoramic radiography in vertical measurements, as well as the accuracy of linear tomography in mandibular width estimation. "nMaterials and Methods: In this test evaluation study, the vertical distances between the crest and the superior border of the inferior alveolar canal, marked with a metal ball, was measured by linear tomography and panoramic radiography in 23 sites of four dry mandible bones. Also the mandibular width was measured at the same sites. Then, the bones were sectioned through the marked spots and the radiographic measurements were compared with actual values. "nResults: The vertical magnification factor in tomograms and panoramic radiographs was 1.79 (SD=0.17 and 1.69 (SD=0.23, respectively. The horizontal magnification of tomograms was 1.47 (SD=0.17. A significant correlation was found between the linear tomographic and actual values, regarding vertical dimensions (p<0.001, r=0.968 and width (p<0.001, r=0.813. The correlation was significant but lower in panoramic radiographs (p<0.001, r=0.795. Applying the magnification values suggested by the manufacturer, the mean difference of vertical measurements between the tomographic sections was 2.5 mm (SD=3.4 but 3.8 mm (SD=1.65 in panoramic radiographs. The mean of absolute difference in mandibular width between the tomographic sections and reality was 0.3mm (SD=1.13. In the linear tomograms, 4.3% of vertical and 56.5% of the width measurements were in the ±1mm error limit. Only 4.3% of the vertical measurements were within this range in the panthomographs. The linear regression equation between the actual values and those obtained by radiography in vertical dimensions showed that 87.5% of

Efficient linear criterion for witnessing Einstein-Podolsky-Rosen nonlocality under many-setting local measurements

Science.gov (United States)

Zheng, Yu-Lin; Zhen, Yi-Zheng; Chen, Zeng-Bing; Liu, Nai-Le; Chen, Kai; Pan, Jian-Wei

2017-01-01

The striking and distinctive nonlocal features of quantum mechanics were discovered by Einstein, Podolsky, and Rosen (EPR) beyond classical physics. At the core of the EPR argument, it was "steering" that Schrödinger proposed in 1935. Besides its fundamental significance, quantum steering opens up a novel application for quantum communication. Recent work has precisely characterized its properties; however, witnessing the EPR nonlocality remains a big challenge under arbitrary local measurements. Here we present an alternative linear criterion and complement existing results to efficiently testify steering for high-dimensional system in practice. By developing a novel and analytical method to tackle the maximization problem in deriving the bound of a steering criterion, we show how observed correlations can reveal powerfully the EPR nonlocality in an easily accessed manner. Although the criteria is not necessary and sufficient, it can recover some of the known results under a few settings of local measurements and is applicable even if the size of the system or the number of measurement settings are high. Remarkably, a deep connection is explicitly established between the steering and amount of entanglement. The results promise viable paths for secure communication with an untrusted source, providing optional loophole-free tests of the EPR nonlocality for high-dimensional states, as well as motivating solutions for other related problems in quantum information theory.

An application of locally linear model tree algorithm with combination of feature selection in credit scoring

Science.gov (United States)

Siami, Mohammad; Gholamian, Mohammad Reza; Basiri, Javad

2014-10-01

Nowadays, credit scoring is one of the most important topics in the banking sector. Credit scoring models have been widely used to facilitate the process of credit assessing. In this paper, an application of the locally linear model tree algorithm (LOLIMOT) was experimented to evaluate the superiority of its performance to predict the customer's credit status. The algorithm is improved with an aim of adjustment by credit scoring domain by means of data fusion and feature selection techniques. Two real world credit data sets - Australian and German - from UCI machine learning database were selected to demonstrate the performance of our new classifier. The analytical results indicate that the improved LOLIMOT significantly increase the prediction accuracy.

Localization of twisted N=(0,2) gauged linear sigma models in two dimensions

Energy Technology Data Exchange (ETDEWEB)

Closset, Cyril [Simons Center for Geometry and Physics, State University of New York, Stony Brook, NY 11794 (United States); Gu, Wei [Department of Physics MC 0435, Virginia Tech, 850 West Campus Drive, Blacksburg, VA 24061 (United States); Jia, Bei [Theory Group, Physics Department, University of Texas, Austin, TX 78612 (United States); Sharpe, Eric [Department of Physics MC 0435, Virginia Tech, 850 West Campus Drive, Blacksburg, VA 24061 (United States)

2016-03-14

We study two-dimensional N=(0,2) supersymmetric gauged linear sigma models (GLSMs) using supersymmetric localization. We consider N=(0,2) theories with an R-symmetry, which can always be defined on curved space by a pseudo-topological twist while preserving one of the two supercharges of flat space. For GLSMs which are deformations of N=(2,2) GLSMs and retain a Coulomb branch, we consider the A/2-twist and compute the genus-zero correlation functions of certain pseudo-chiral operators, which generalize the simplest twisted chiral ring operators away from the N=(2,2) locus. These correlation functions can be written in terms of a certain residue operation on the Coulomb branch, generalizing the Jeffrey-Kirwan residue prescription relevant for the N=(2,2) locus. For abelian GLSMs, we reproduce existing results with new formulas that render the quantum sheaf cohomology relations and other properties manifest. For non-abelian GLSMs, our methods lead to new results. As an example, we briefly discuss the quantum sheaf cohomology of the Grassmannian manifold.

Introduction to geometric nonlinear control; Linearization, observability, decoupling

Energy Technology Data Exchange (ETDEWEB)

Respondek, W [Laboratoire de Mathematiques, INSA de Rouen (France)

2002-07-15

These notes are devoted to the problems of linearization, observability, and decoupling of nonlinear control systems. Together with notes of Bronislaw Jakubczyk in the same volume, they form an introduction to geometric methods in nonlinear control theory. In the first part we discuss equivalence of control systems. We consider various aspects of the problem: state-space and feedback equivalence, local and global equivalence, equivalence to linear and partially linear systems. In the second part we present the notion of observability and give a geometric rank condition for local observability and an algebraic characterization of local observability. We discuss unm observability, decompositions of non-observable systems, and properties of generic observable systems. In the third part we introduce the notion of invariant distributions and discuss disturbance decoupling and input-output decoupling. Many concepts and results are illustrated with examples. (author)

KEPLER ECLIPSING BINARY STARS. III. CLASSIFICATION OF KEPLER ECLIPSING BINARY LIGHT CURVES WITH LOCALLY LINEAR EMBEDDING

International Nuclear Information System (INIS)

Matijevič, Gal; Prša, Andrej; Orosz, Jerome A.; Welsh, William F.; Bloemen, Steven; Barclay, Thomas

2012-01-01

We present an automated classification of 2165 Kepler eclipsing binary (EB) light curves that accompanied the second Kepler data release. The light curves are classified using locally linear embedding, a general nonlinear dimensionality reduction tool, into morphology types (detached, semi-detached, overcontact, ellipsoidal). The method, related to a more widely used principal component analysis, produces a lower-dimensional representation of the input data while preserving local geometry and, consequently, the similarity between neighboring data points. We use this property to reduce the dimensionality in a series of steps to a one-dimensional manifold and classify light curves with a single parameter that is a measure of 'detachedness' of the system. This fully automated classification correlates well with the manual determination of morphology from the data release, and also efficiently highlights any misclassified objects. Once a lower-dimensional projection space is defined, the classification of additional light curves runs in a negligible time and the method can therefore be used as a fully automated classifier in pipeline structures. The classifier forms a tier of the Kepler EB pipeline that pre-processes light curves for the artificial intelligence based parameter estimator.

Localized chaoticity in two linearly coupled inverted double-well ...

African Journals Online (AJOL)

Two linearly coupled inverted double-well oscillators for a fixed energy and varying coupling strength were studied. The dynamics yielded a chaotic system in which the Poincare surface was characterised by two non-mixing regions, one of regular motion and the other region that became chaotic as the coupling increased.

Height premium for job performance.

Science.gov (United States)

Kim, Tae Hyun; Han, Euna

2017-08-01

This study assessed the relationship of height with wages, using the 1998 and 2012 Korean Labor and Income Panel Study data. The key independent variable was height measured in centimeters, which was included as a series of dummy indicators of height per 5cm span (wages to assess the heterogeneity in the height-wage relationship, across the conditional distribution of monthly wages. We found a non-linear relationship of height with monthly wages. For men, the magnitude of the height wage premium was overall larger at the upper quantile of the conditional distribution of log monthly wages than at the median to low quantile, particularly in professional and semi-professional occupations. The height-wage premium was also larger at the 90th quantile for self-employed women and salaried men. Our findings add a global dimension to the existing evidence on height-wage premium, demonstrating non-linearity in the association between height and wages and heterogeneous changes in the dispersion and direction of the association between height and wages, by wage level. Copyright © 2017 Elsevier B.V. All rights reserved.

Orthogonal sparse linear discriminant analysis

Science.gov (United States)

Liu, Zhonghua; Liu, Gang; Pu, Jiexin; Wang, Xiaohong; Wang, Haijun

2018-03-01

Linear discriminant analysis (LDA) is a linear feature extraction approach, and it has received much attention. On the basis of LDA, researchers have done a lot of research work on it, and many variant versions of LDA were proposed. However, the inherent problem of LDA cannot be solved very well by the variant methods. The major disadvantages of the classical LDA are as follows. First, it is sensitive to outliers and noises. Second, only the global discriminant structure is preserved, while the local discriminant information is ignored. In this paper, we present a new orthogonal sparse linear discriminant analysis (OSLDA) algorithm. The k nearest neighbour graph is first constructed to preserve the locality discriminant information of sample points. Then, L2,1-norm constraint on the projection matrix is used to act as loss function, which can make the proposed method robust to outliers in data points. Extensive experiments have been performed on several standard public image databases, and the experiment results demonstrate the performance of the proposed OSLDA algorithm.

Linearly Adjustable International Portfolios

International Nuclear Information System (INIS)

Fonseca, R. J.; Kuhn, D.; Rustem, B.

2010-01-01

We present an approach to multi-stage international portfolio optimization based on the imposition of a linear structure on the recourse decisions. Multiperiod decision problems are traditionally formulated as stochastic programs. Scenario tree based solutions however can become intractable as the number of stages increases. By restricting the space of decision policies to linear rules, we obtain a conservative tractable approximation to the original problem. Local asset prices and foreign exchange rates are modelled separately, which allows for a direct measure of their impact on the final portfolio value.

Linearly Adjustable International Portfolios

Science.gov (United States)

Fonseca, R. J.; Kuhn, D.; Rustem, B.

2010-09-01

We present an approach to multi-stage international portfolio optimization based on the imposition of a linear structure on the recourse decisions. Multiperiod decision problems are traditionally formulated as stochastic programs. Scenario tree based solutions however can become intractable as the number of stages increases. By restricting the space of decision policies to linear rules, we obtain a conservative tractable approximation to the original problem. Local asset prices and foreign exchange rates are modelled separately, which allows for a direct measure of their impact on the final portfolio value.

Percentile-Based ETCCDI Temperature Extremes Indices for CMIP5 Model Output: New Results through Semiparametric Quantile Regression Approach

Science.gov (United States)

Li, L.; Yang, C.

2017-12-01

Climate extremes often manifest as rare events in terms of surface air temperature and precipitation with an annual reoccurrence period. In order to represent the manifold characteristics of climate extremes for monitoring and analysis, the Expert Team on Climate Change Detection and Indices (ETCCDI) had worked out a set of 27 core indices based on daily temperature and precipitation data, describing extreme weather and climate events on an annual basis. The CLIMDEX project (http://www.climdex.org) had produced public domain datasets of such indices for data from a variety of sources, including output from global climate models (GCM) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Among the 27 ETCCDI indices, there are six percentile-based temperature extremes indices that may fall into two groups: exceedance rates (ER) (TN10p, TN90p, TX10p and TX90p) and durations (CSDI and WSDI). Percentiles must be estimated prior to the calculation of the indices, and could more or less be biased by the adopted algorithm. Such biases will in turn be propagated to the final results of indices. The CLIMDEX used an empirical quantile estimator combined with a bootstrap resampling procedure to reduce the inhomogeneity in the annual series of the ER indices. However, there are still some problems remained in the CLIMDEX datasets, namely the overestimated climate variability due to unaccounted autocorrelation in the daily temperature data, seasonally varying biases and inconsistency between algorithms applied to the ER indices and to the duration indices. We now present new results of the six indices through a semiparametric quantile regression approach for the CMIP5 model output. By using the base-period data as a whole and taking seasonality and autocorrelation into account, this approach successfully addressed the aforementioned issues and came out with consistent results. The new datasets cover the historical and three projected (RCP2.6, RCP4.5 and RCP

Groundwater decline and tree change in floodplain landscapes: Identifying non-linear threshold responses in canopy condition

Directory of Open Access Journals (Sweden)

J. Kath

2014-12-01

Full Text Available Groundwater decline is widespread, yet its implications for natural systems are poorly understood. Previous research has revealed links between groundwater depth and tree condition; however, critical thresholds which might indicate ecological ‘tipping points’ associated with rapid and potentially irreversible change have been difficult to quantify. This study collated data for two dominant floodplain species, Eucalyptus camaldulensis (river red gum and E. populnea (poplar box from 118 sites in eastern Australia where significant groundwater decline has occurred. Boosted regression trees, quantile regression and Threshold Indicator Taxa Analysis were used to investigate the relationship between tree condition and groundwater depth. Distinct non-linear responses were found, with groundwater depth thresholds identified in the range from 12.1 m to 22.6 m for E. camaldulensis and 12.6 m to 26.6 m for E. populnea beyond which canopy condition declined abruptly. Non-linear threshold responses in canopy condition in these species may be linked to rooting depth, with chronic groundwater decline decoupling trees from deep soil moisture resources. The quantification of groundwater depth thresholds is likely to be critical for management aimed at conserving groundwater dependent biodiversity. Identifying thresholds will be important in regions where water extraction and drying climates may contribute to further groundwater decline. Keywords: Canopy condition, Dieback, Drought, Tipping point, Ecological threshold, Groundwater dependent ecosystems

On A Quasi-local Mass

OpenAIRE

Zhang, Xiao

2009-01-01

We modify previous quasi-local mass definition. The new definition provides expressions of the quasi-local energy, the quasi-local linear momentum and the quasi-local mass. And they are equal to the ADM expressions at spatial infinity. Moreover, the new quasi-local energy has the positivity property.

Distributed 3D Source Localization from 2D DOA Measurements Using Multiple Linear Arrays

Directory of Open Access Journals (Sweden)

Antonio Canclini

2017-01-01

Full Text Available This manuscript addresses the problem of 3D source localization from direction of arrivals (DOAs in wireless acoustic sensor networks. In this context, multiple sensors measure the DOA of the source, and a central node combines the measurements to yield the source location estimate. Traditional approaches require 3D DOA measurements; that is, each sensor estimates the azimuth and elevation of the source by means of a microphone array, typically in a planar or spherical configuration. The proposed methodology aims at reducing the hardware and computational costs by combining measurements related to 2D DOAs estimated from linear arrays arbitrarily displaced in the 3D space. Each sensor measures the DOA in the plane containing the array and the source. Measurements are then translated into an equivalent planar geometry, in which a set of coplanar equivalent arrays observe the source preserving the original DOAs. This formulation is exploited to define a cost function, whose minimization leads to the source location estimation. An extensive simulation campaign validates the proposed approach and compares its accuracy with state-of-the-art methodologies.

Application of a local linearization technique for the solution of a system of stiff differential equations associated with the simulation of a magnetic bearing assembly

Science.gov (United States)

Kibler, K. S.; Mcdaniel, G. A.

1981-01-01

A digital local linearization technique was used to solve a system of stiff differential equations which simulate a magnetic bearing assembly. The results prove the technique to be accurate, stable, and efficient when compared to a general purpose variable order Adams method with a stiff option.

Localized transversal-rotational modes in linear chains of equal masses.

Science.gov (United States)

Pichard, H; Duclos, A; Groby, J-P; Tournat, V; Gusev, V E

2014-01-01

The propagation and localization of transversal-rotational waves in a two-dimensional granular chain of equal masses are analyzed in this study. The masses are infinitely long cylinders possessing one translational and one rotational degree of freedom. Two dispersive propagating modes are predicted in this granular crystal. By considering the semi-infinite chain with a boundary condition applied at its beginning, the analytical study demonstrates the existence of localized modes, each mode composed of two evanescent modes. Their existence, position (either in the gap between the propagating modes or in the gap above the upper propagating mode), and structure of spatial localization are analyzed as a function of the relative strength of the shear and bending interparticle interactions and for different boundary conditions. This demonstrates the existence of a localized mode in a semi-infinite monatomic chain when transversal-rotational waves are considered, while it is well known that these types of modes do not exist when longitudinal waves are considered.

Non linear identification applied to PWR steam generators

International Nuclear Information System (INIS)

Poncet, B.

1982-11-01

For the precise industrial purpose of PWR nuclear power plant steam generator water level control, a natural method is developed where classical techniques seem not to be efficient enough. From this essentially non-linear practical problem, an input-output identification of dynamic systems is proposed. Through Homodynamic Systems, characterized by a regularity property which can be found in most industrial processes with balance set, state form realizations are built, which resolve the exact joining of local dynamic behaviors, in both discrete and continuous time cases, avoiding any load parameter. Specifically non-linear modelling analytical means, which have no influence on local joined behaviors, are also pointed out. Non-linear autoregressive realizations allow us to perform indirect adaptive control under constraint of an admissible given dynamic family [fr

Linear approximation model network and its formation via ...

Indian Academy of Sciences (India)

To overcome the deficiency of `local model network' (LMN) techniques, an alternative `linear approximation model' (LAM) network approach is proposed. Such a network models a nonlinear or practical system with multiple linear models fitted along operating trajectories, where individual models are simply networked ...

Preliminary Experience in Treatment of Papillary and Macular Retinoblastoma: Evaluation of Local Control and Local Complications After Treatment With Linear Accelerator-Based Stereotactic Radiotherapy With Micromultileaf Collimator as Second-Line or Salvage Treatment After Chemotherapy

Energy Technology Data Exchange (ETDEWEB)

Pica, Alessia, E-mail: Alessia.Pica@chuv.ch [Department of Radiation Oncology, Centre Hospitalier Universitaire Vaudois, Lausanne (Switzerland); Moeckli, Raphael [University Institute for Radiation Physics, Centre Hospitalier Universitaire Vaudois, Lausanne (Switzerland); Balmer, Aubin [Department of Radiation Oncology, Jules Gonin Eye Hospital, Lausanne (Switzerland); Beck-Popovic, Maja [Unit of Pediatric Oncology, University of Lausanne, Lausanne (Switzerland); Chollet-Rivier, Madeleine [Department of Anesthesiology, University of Lausanne, Lausanne (Switzerland); Do, Huu-Phuoc [University Institute for Radiation Physics, Centre Hospitalier Universitaire Vaudois, Lausanne (Switzerland); Weber, Damien C. [Department of Radiation Oncology, Geneva University Hospital, University of Geneva, Geneva (Switzerland); Munier, Francis L. [Department of Radiation Oncology, Jules Gonin Eye Hospital, Lausanne (Switzerland)

2011-12-01

Purpose: To determine the local control and complication rates for children with papillary and/or macular retinoblastoma progressing after chemotherapy and undergoing stereotactic radiotherapy (SRT) with a micromultileaf collimator. Methods and Materials: Between 2004 and 2008, 11 children (15 eyes) with macular and/or papillary retinoblastoma were treated with SRT. The mean age was 19 months (range, 2-111). Of the 15 eyes, 7, 6, and 2 were classified as International Classification of Intraocular Retinoblastoma Group B, C, and E, respectively. The delivered dose of SRT was 50.4 Gy in 28 fractions using a dedicated micromultileaf collimator linear accelerator. Results: The median follow-up was 20 months (range, 13-39). Local control was achieved in 13 eyes (87%). The actuarial 1- and 2-year local control rates were both 82%. SRT was well tolerated. Late adverse events were reported in 4 patients. Of the 4 patients, 2 had developed focal microangiopathy 20 months after SRT; 1 had developed a transient recurrence of retinal detachment; and 1 had developed bilateral cataracts. No optic neuropathy was observed. Conclusions: Linear accelerator-based SRT for papillary and/or macular retinoblastoma in children resulted in excellent tumor control rates with acceptable toxicity. Additional research regarding SRT and its intrinsic organ-at-risk sparing capability is justified in the framework of prospective trials.

Contribution to the development of a food guide in Benin: linear programming for the optimization of local diets.

Science.gov (United States)

Levesque, Sarah; Delisle, Hélène; Agueh, Victoire

2015-03-01

Food guides are important tools for nutrition education. While developing a food guide in Benin, the objective was to determine the daily number of servings per food group and the portion sizes of common foods to be recommended. Linear programming (LP) was used to determine, for each predefined food group, the optimal number and size of servings of commonly consumed foods. Two types of constraints were introduced into the LP models: (i) WHO/FAO Recommended Nutrient Intakes and dietary guidelines for the prevention of chronic diseases; and (ii) dietary patterns based on local food consumption data recently collected in southern Benin in 541 adults. Dietary intakes of the upper tertile of participants for diet quality based on prevention and micronutrient adequacy scores were used in the LP algorithms. Southern area of the Republic of Benin. Local key-players in nutrition (n 30) from the government, academic institutions, international organizations and civil society were partners in the development of the food guide directed at the population. The number of servings per food group and the portion size for eight age-sex groups were determined. For four limiting micronutrients (Fe, Ca, folate and Zn), local diets could be optimized to meet only 70 % of the Recommended Nutrient Intakes, not 100 %. It was possible to determine the daily number of servings and the portion sizes of common foods that can be recommended in Benin with the help of LP to optimize local diets, although Recommended Nutrient Intakes were not fully met for a few critical micronutrients.

Complex linear Goldstino superfield and supergravity

Energy Technology Data Exchange (ETDEWEB)

Kuzenko, Sergei M. [School of Physics M013, The University of Western Australia,35 Stirling Highway, Crawley W.A. 6009 (Australia)

2015-10-01

The complex linear Goldstino superfield was proposed in http://arxiv.org/abs/1102.3042 for the cases of global and local four-dimensional N=1 supersymmetry. Here we make use of this superfield to construct a supergravity action which is invariant under spontaneously broken local N=1 supersymmetry and has a positive cosmological constant for certain values of the parameters.

Association Between Local Bipolar Voltage and Conduction Gap Along the Left Atrial Linear Ablation Lesion in Patients With Atrial Fibrillation.

Science.gov (United States)

Masuda, Masaharu; Fujita, Masashi; Iida, Osamu; Okamoto, Shin; Ishihara, Takayuki; Nanto, Kiyonori; Kanda, Takashi; Sunaga, Akihiro; Tsujimura, Takuya; Matsuda, Yasuhiro; Mano, Toshiaki

2017-08-01

A bipolar voltage reflects a thick musculature where formation of a transmural lesion may be hard to achieve. The purpose of this study was to explore the association between local bipolar voltage and conduction gap in patients with persistent atrial fibrillation (AF) who underwent atrial roof or septal linear ablation. This prospective observational study included 42 and 36 consecutive patients with persistent AF who underwent roof or septal linear ablations, respectively. After pulmonary vein isolation, left atrial linear ablations were performed, and conduction gap sites were identified and ablated after first-touch radiofrequency application. Conduction gap(s) after the first-touch roof and septal linear ablation were observed in 13 (32%) and 19 patients (53%), respectively. Roof and septal area voltages were higher in patients with conduction gap(s) than in those without (roof, 1.23 ± 0.77 vs 0.73 ± 0.42 mV, p = 0.010; septal, 0.96 ± 0.43 vs 0.54 ± 0.18 mV, p = 0.001). Trisected regional analyses revealed that the voltage was higher at the region with a conduction gap than at the region without. Complete conduction block across the roof and septal lines was not achieved in 3 (7%) and 6 patients (17%), respectively. Patients in whom a linear conduction block could not be achieved demonstrated higher ablation area voltage than those with a successful conduction block (roof, 1.91 ± 0.74 vs 0.81 ± 0.51 mV, p = 0.001; septal, 1.15 ± 0.56 vs 0.69 ± 0.31 mV, p = 0.006). In conclusion, a high regional bipolar voltage predicts failure to achieve conduction block after left atrial roof or septal linear ablation. In addition, the conduction gap was located at the preserved voltage area. Copyright © 2017 Elsevier Inc. All rights reserved.

Quantized, piecewise linear filter network

DEFF Research Database (Denmark)

Sørensen, John Aasted

1993-01-01

A quantization based piecewise linear filter network is defined. A method for the training of this network based on local approximation in the input space is devised. The training is carried out by repeatedly alternating between vector quantization of the training set into quantization classes...... and equalization of the quantization classes linear filter mean square training errors. The equalization of the mean square training errors is carried out by adapting the boundaries between neighbor quantization classes such that the differences in mean square training errors are reduced...

Assessing the Impact of Wind/PV Power Generation and Market Policies on Decentralized Hybrid Systems

DEFF Research Database (Denmark)

S.M. Arnoux, Luciana; Santiago, Leonardo

In this paper, we offer a comprehensive approach to assess the impact of wind and photovoltaic power generation on decentralized hybrid systems. In particular, we focus on three performance measures of the energy system, namely reliability, costs, and efficiency. Most of the current studies focus...... level. Therefore, we appropriately assess the inherent uncertainty and design options. First, we use linear and quantile regression models to estimate the wind speed and solar insolation. Then, we use different quantiles as an input for the hybrid system design to assess market policies (e.g., net...

A Linear Active Disturbance Rejection Control for a Ball and Rigid Triangle System

Directory of Open Access Journals (Sweden)

Carlos Aguilar-Ibanez

2016-01-01

Full Text Available This paper proposes an application of linear flatness control along with active disturbance rejection control (ADRC for the local stabilization and trajectory tracking problems in the underactuated ball and rigid triangle system. To this end, an observer-based linear controller of the ADRC type is designed based on the flat tangent linearization of the system around its corresponding unstable equilibrium rest position. It was accomplished through two decoupled linear extended observers and a single linear output feedback controller, with disturbance cancelation features. The controller guarantees locally exponentially asymptotic stability for the stabilization problem and practical local stability in the solution of the tracking error. An advantage of combining the flatness and the ADRC methods is that it possible to perform online estimates and cancels the undesirable effects of the higher-order nonlinearities discarded by the linearization approximation. Simulation indicates that the proposed controller behaves remarkably well, having an acceptable domain of attraction.

Statistical inference for financial engineering

CERN Document Server

Taniguchi, Masanobu; Ogata, Hiroaki; Taniai, Hiroyuki

2014-01-01

This monograph provides the fundamentals of statistical inference for financial engineering and covers some selected methods suitable for analyzing financial time series data. In order to describe the actual financial data, various stochastic processes, e.g. non-Gaussian linear processes, non-linear processes, long-memory processes, locally stationary processes etc. are introduced and their optimal estimation is considered as well. This book also includes several statistical approaches, e.g., discriminant analysis, the empirical likelihood method, control variate method, quantile regression, realized volatility etc., which have been recently developed and are considered to be powerful tools for analyzing the financial data, establishing a new bridge between time series and financial engineering. This book is well suited as a professional reference book on finance, statistics and statistical financial engineering. Readers are expected to have an undergraduate-level knowledge of statistics.

Small-sized linear accelerator of 2.5 MeV electrons with a local radiation shield for custom examination of freight transported by motor transport

International Nuclear Information System (INIS)

Baklanov, A.V.; Gavrish, Yu.N.; Klinov, A.P.; Krest'yaninov, A.S.; Nikolaev, V.M.; Fomin, L.P.; Linkenbach, H.A.; Geus, G.; Knospel, W.

2001-01-01

A new development of a small-sized linear accelerator of 2.5 MeV electrons with a local radiation protection is described. The accelerator is intended for movable facilities of radiation custom of the freight transported by motor transport. Main constructive solutions, mass and dimension characteristics and results of preliminary tests of the accelerator parameters and characteristics of radiation protection are presented [ru

Physical Attractiveness, Employment, and Earnings

OpenAIRE

Christian Pfeifer

2011-01-01

Survey data is used to estimate the impact of physical attractiveness rated by the interviewer as well as by the respondent on employment probability and labor income of men and women. In addition to mean linear and non-linear effects on earnings, simultaneous quantile regressions are applied to analyze heterogeneity across the wage distribution.

[Socioeconomic factors conditioning obesity in adults. Evidence based on quantile regression and panel data].

Science.gov (United States)

Temporelli, Karina L; Viego, Valentina N

2016-08-01

Objective To measure the effect of socioeconomic variables on the prevalence of obesity. Factors such as income level, urbanization, incorporation of women into the labor market and access to unhealthy foods are considered in this paper. Method Econometric estimates of the proportion of obese men and women by country were calculated using models based on panel data and quantile regressions, with data from 192 countries for the period 2002-2005.Levels of per capita income, urbanization, income/big mac ratio price and labor indicators for female population were considered as explanatory variables. Results Factors that have influence over obesity in adults differ between men and women; accessibility to fast food is related to male obesity, while the employment mode causes higher rates in women. The underlying socioeconomic factors for obesity are also different depending on the magnitude of this problem in each country; in countries with low prevalence, a greater level of income favor the transition to obesogenic habits, while a higher income level mitigates the problem in those countries with high rates of obesity. Discussion Identifying the socio-economic causes of the significant increase in the prevalence of obesity is essential for the implementation of effective strategies for prevention, since this condition not only affects the quality of life of those who suffer from it but also puts pressure on health systems due to the treatment costs of associated diseases.

On the Approximate Solutions of Local Fractional Differential Equations with Local Fractional Operators

Directory of Open Access Journals (Sweden)

Hossein Jafari

2016-04-01

Full Text Available In this paper, we consider the local fractional decomposition method, variational iteration method, and differential transform method for analytic treatment of linear and nonlinear local fractional differential equations, homogeneous or nonhomogeneous. The operators are taken in the local fractional sense. Some examples are given to demonstrate the simplicity and the efficiency of the presented methods.

Attributing uncertainty in streamflow simulations due to variable inputs via the Quantile Flow Deviation metric

Science.gov (United States)

Shoaib, Syed Abu; Marshall, Lucy; Sharma, Ashish

2018-06-01

Every model to characterise a real world process is affected by uncertainty. Selecting a suitable model is a vital aspect of engineering planning and design. Observation or input errors make the prediction of modelled responses more uncertain. By way of a recently developed attribution metric, this study is aimed at developing a method for analysing variability in model inputs together with model structure variability to quantify their relative contributions in typical hydrological modelling applications. The Quantile Flow Deviation (QFD) metric is used to assess these alternate sources of uncertainty. The Australian Water Availability Project (AWAP) precipitation data for four different Australian catchments is used to analyse the impact of spatial rainfall variability on simulated streamflow variability via the QFD. The QFD metric attributes the variability in flow ensembles to uncertainty associated with the selection of a model structure and input time series. For the case study catchments, the relative contribution of input uncertainty due to rainfall is higher than that due to potential evapotranspiration, and overall input uncertainty is significant compared to model structure and parameter uncertainty. Overall, this study investigates the propagation of input uncertainty in a daily streamflow modelling scenario and demonstrates how input errors manifest across different streamflow magnitudes.

Probing Anderson localization of light by weak non-linear effects

International Nuclear Information System (INIS)

Sperling, T; Bührer, W; Maret, G; Ackermann, M; Aegerter, C M

2014-01-01

Breakdown of wave transport due to strong disorder is a universal phenomenon known as Anderson localization (AL). It occurs because of the macroscopic population of reciprocal multiple scattering paths, which in three dimensional systems happens at a critical scattering strength. Intensities on these random loops should thus be highly increased relative to those of a diffusive sample. In order to highlight localized modes of light, we exploit the optical nonlinearities of TiO 2 . Power dependent and spectrally resolved time of flight distribution measurements in transmission through slabs of TiO 2 powders at various turbidities reveal that mostly long loops are affected by nonlinearities and that the deviations from diffusive transport observed at long times are due to these localized modes. Our data are a first step in the experimental investigation of the interplay between nonlinear effects and AL in 3D. (fast track communication)

Preface: Introductory Remarks: Linear Scaling Methods

Science.gov (United States)

Bowler, D. R.; Fattebert, J.-L.; Gillan, M. J.; Haynes, P. D.; Skylaris, C.-K.

2008-07-01

implementation questions relating to parallelization (particularly with multi-core processors starting to dominate the market) and inherent scaling and basis sets (in both normal and linear scaling codes). For now, the answer seems to lie between 100-1,000 atoms, though this depends on the type of simulation used among other factors. Basis sets are still a problematic question in the area of electronic structure calculations. The linear scaling community has largely split into two camps: those using relatively small basis sets based on local atomic-like functions (where systematic convergence to the full basis set limit is hard to achieve); and those that use necessarily larger basis sets which allow convergence systematically and therefore are the localised equivalent of plane waves. Related to basis sets is the study of Wannier functions, on which some linear scaling methods are based and which give a good point of contact with traditional techniques; they are particularly interesting for modelling unoccupied states with linear scaling methods. There are, of course, as many approaches to linear scaling solution for the density matrix as there are groups in the area, though there are various broad areas: McWeeny-based methods, fragment-based methods, recursion methods, and combinations of these. While many ideas have been in development for several years, there are still improvements emerging, as shown by the rich variety of the talks below. Applications using O(N) DFT methods are now starting to emerge, though they are still clearly not trivial. Once systems to be simulated cross the 10,000 atom barrier, only linear scaling methods can be applied, even with the most efficient standard techniques. One of the most challenging problems remaining, now that ab initio methods can be applied to large systems, is the long timescale problem. Although much of the work presented was concerned with improving the performance of the codes, and applying them to scientificallyimportant

Unilateral Enophthalmos in Linear Scleroderma: A Case Report

Energy Technology Data Exchange (ETDEWEB)

Cho, So hyun; Hwang, Hee Young; Choi, Hye Young; Kim, Hyung Sik [Gachon University, Gil Hospital, Incheon (Korea, Republic of)

2010-04-15

Linear scleroderma is an uncommon subtype of localized scleroderma, which is characterized by a linear streak that crosses dermatomes and is associated with the tracking of fibrosis from the skin into deeper tissues, including muscle and fascia. A severe form of this condition sometimes causes growth atrophy of bone and supporting tissue in the affected area. Enophthalmos as a manifestation of linear scleroderma is very rare and occurs due to the replacement of orbital fat and muscle with collagen, which finally leads to atrophy of the affected orbit. This report introduces imaging findings of two cases of enophthalmos caused by linear scleroderma

Unilateral Enophthalmos in Linear Scleroderma: A Case Report

International Nuclear Information System (INIS)

Cho, So hyun; Hwang, Hee Young; Choi, Hye Young; Kim, Hyung Sik

2010-01-01

Linear scleroderma is an uncommon subtype of localized scleroderma, which is characterized by a linear streak that crosses dermatomes and is associated with the tracking of fibrosis from the skin into deeper tissues, including muscle and fascia. A severe form of this condition sometimes causes growth atrophy of bone and supporting tissue in the affected area. Enophthalmos as a manifestation of linear scleroderma is very rare and occurs due to the replacement of orbital fat and muscle with collagen, which finally leads to atrophy of the affected orbit. This report introduces imaging findings of two cases of enophthalmos caused by linear scleroderma

Non-susceptible landslide areas in Italy and in the Mediterranean region

Science.gov (United States)

Marchesini, I.; Ardizzone, F.; Alvioli, M.; Rossi, M.; Guzzetti, F.

2014-08-01

We used landslide information for 13 study areas in Italy and morphometric information obtained from the 3-arcseconds shuttle radar topography mission digital elevation model (SRTM DEM) to determine areas where landslide susceptibility is expected to be negligible in Italy and in the landmasses surrounding the Mediterranean Sea. The morphometric information consisted of the local terrain slope which was computed in a square 3 × 3-cell moving window, and in the regional relative relief computed in a circular 15 × 15-cell moving window. We tested three different models to classify the "non-susceptible" landslide areas, including a linear model (LNR), a quantile linear model (QLR), and a quantile, non-linear model (QNL). We tested the performance of the three models using independent landslide information presented by the Italian Landslide Inventory (Inventario Fenomeni Franosi in Italia - IFFI). Best results were obtained using the QNL model. The corresponding zonation of non-susceptible landslide areas was intersected in a geographic information system (GIS) with geographical census data for Italy. The result determined that 57.5% of the population of Italy (in 2001) was located in areas where landslide susceptibility is expected to be negligible. We applied the QNL model to the landmasses surrounding the Mediterranean Sea, and we tested the synoptic non-susceptibility zonation using independent landslide information for three study areas in Spain. Results showed that the QNL model was capable of determining where landslide susceptibility is expected to be negligible in the validation areas in Spain. We expect our results to be applicable in similar study areas, facilitating the identification of non-susceptible landslide areas, at the synoptic scale.

Modeling the thermal behavior of fluid flow inside channels using an artificial locally linear neuro-fuzzy approach

Directory of Open Access Journals (Sweden)

Azadeh Hashemian

2008-06-01

Full Text Available Enhanced surface heat exchangers are commonly used all worldwide. If applicable, due to their complicated geometry, simulating corrugated plate heat exchangers is a time-consuming process. In the present study, first we simulate the heat transfer in a sharp V-shape corrugation cell with constant temperature walls; then, we use a Locally Linear Neuro-Fuzzy method based on a radial basis function (RBFs to model the temperature field in the whole channel. New approach is developed to deal with fast computational and low memory resources that can be used with the largest available data sets. The purpose of the research is to reveal the advantages of proposed Neuro-Fuzzy model as a powerful modeling system designed for predicting and to make a fair comparison between it and the successful FLUENT simulated approaches in its best structures.

Localized vortices in ηi-modes

International Nuclear Information System (INIS)

Nycander, J.; Lynov, J.P.; Juul Rasmussen, J.

1992-01-01

For a wide variety of nonlinear wave equations necessary conditions for the existence of localized, stationary structures can be found by applying a simple procedure, involving two steps: First the linear dispersion relation is obtained and the regions of the phase velocity of linear waves found. Secondly, assuming that localized solutions exist, their velocities are determined by using integral relations. The obtained velocity takes the form of a ''center of mass velocity''. If this velocity falls outside the regions of phase velocities for linear waves then nonlinear localized vortices may exist. Otherwise, the structure will couple to the linear waves and gradually disperse. Applying this method we have shown that monopole vortex solutions exist for drift waves driven by the ion temperature gradient in a magnetized plasma, the so-called η i -modes. Numerical solutions show that such vortices are steadily propagating and stable and they generally emerge from localized initial conditions. Our study is motivated by recent high resolution simulations of η i -turbulence, where it was observed that coherent vortices developed spontaneously. These had a dominating influence on the evolution of the turbulence, and the associated anomalous transport was found to be significantly reduced as compared with the predictions from quasilinear theory. (author) 8 refs., 3 figs

On deformations of linear differential systems

NARCIS (Netherlands)

Gontsov, R.R.; Poberezhnyi, V.A.; Helminck, G.F.

2011-01-01

This article concerns deformations of meromorphic linear differential systems. Problems relating to their existence and classification are reviewed, and the global and local behaviour of solutions to deformation equations in a neighbourhood of their singular set is analysed. Certain classical

Linear morphoea follows Blaschko's lines.

Science.gov (United States)

Weibel, L; Harper, J I

2008-07-01

The aetiology of morphoea (or localized scleroderma) remains unknown. It has previously been suggested that lesions of linear morphoea may follow Blaschko's lines and thus reflect an embryological development. However, the distribution of linear morphoea has never been accurately evaluated. We aimed to identify common patterns of clinical presentation in children with linear morphoea and to establish whether linear morphoea follows the lines of Blaschko. A retrospective chart review of 65 children with linear morphoea was performed. According to clinical photographs the skin lesions of these patients were plotted on to standardized head and body charts. With the aid of Adobe Illustrator a final figure was produced including an overlay of all individual lesions which was used for comparison with the published lines of Blaschko. Thirty-four (53%) patients had the en coup de sabre subtype, 27 (41%) presented with linear morphoea on the trunk and/or limbs and four (6%) children had a combination of the two. In 55 (85%) children the skin lesions were confined to one side of the body, showing no preference for either left or right side. On comparing the overlays of all body and head lesions with the original lines of Blaschko there was an excellent correlation. Our data indicate that linear morphoea follows the lines of Blaschko. We hypothesize that in patients with linear morphoea susceptible cells are present in a mosaic state and that exposure to some trigger factor may result in the development of this condition.

Sparse PDF maps for non-linear multi-resolution image operations

KAUST Repository

Hadwiger, Markus; Sicat, Ronell Barrera; Beyer, Johanna; Krü ger, Jens J.; Mö ller, Torsten

2012-01-01

feasible for gigapixel images, while enabling direct evaluation of a variety of non-linear operators from the same representation. We illustrate this versatility for antialiased color mapping, O(n) local Laplacian filters, smoothed local histogram filters

Effect of Cisplatin on the Flexibility of Linear DNA

International Nuclear Information System (INIS)

Ji Chao; Zhang Ling-Yun; Hou Xi-Miao; Dou Shuo-Xing; Wang Peng-Ye

2011-01-01

With the aid of an atomic force microscope (AFM), we study the interaction between linear DNA fragment and cisplatin. For different cisplatin concentrations, the AFM used to observe the conformation of DNA has a gradual change. The contour length, the end-to-end distance and the local bend angles of the linear DNA fragment can be accurately measured. The persistence length of DNA interacting with cisplatin is decreased with the increasing cisplatin concentration. Furthermore, it is demonstrated that the local bend angles of DNA chains are increased by the binding interaction of cisplatin. (cross-disciplinary physics and related areas of science and technology)

PERBANDINGAN TRANSFORMASI BOX-COX DAN REGRESI KUANTIL MEDIAN DALAM MENGATASI HETEROSKEDASTISITAS

Directory of Open Access Journals (Sweden)

NI WAYAN YUNI CAHYANI

2015-01-01

Full Text Available Ordinary least square (OLS is a method that can be used to estimate the parameter in linear regression analysis. There are some assumption which should be satisfied on OLS, one of this assumption is homoscedasticity, that is the variance of error is constant. If variance of the error is unequal that so-called heteroscedasticity. The presence heteroscedasticity can cause estimation with OLS becomes inefficient. Therefore, heteroscedasticity shall be overcome. There are some method that can used to overcome heteroscedasticity, two among those are Box-Cox power transformation and median quantile regression. This research compared Box-Cox power transformation and median quantile regression to overcome heteroscedasticity. Applied Box-Cox power transformation on OLS result ????2point are greater, smaller RMSE point and confidencen interval more narrow, therefore can be concluded that applied of Box-Cox power transformation on OLS better of median quantile regression to overcome heteroscedasticity.

PERBANDINGAN TRANSFORMASI BOX-COX DAN REGRESI KUANTIL MEDIAN DALAM MENGATASI HETEROSKEDASTISITAS

Directory of Open Access Journals (Sweden)

NI WAYAN YUNI CAHYANI

2015-03-01

Full Text Available Ordinary least square (OLS is a method that can be used to estimate the parameter in linear regression analysis. There are some assumption which should be satisfied on OLS, one of this assumption is homoscedasticity, that is the variance of error is constant. If variance of the error is unequal that so-called heteroscedasticity. The presence heteroscedasticity can cause estimation with OLS becomes inefficient. Therefore, heteroscedasticity shall be overcome. There are some method that can used to overcome heteroscedasticity, two among those are Box-Cox power transformation and median quantile regression. This research compared Box-Cox power transformation and median quantile regression to overcome heteroscedasticity. Applied Box-Cox power transformation on OLS result ????2point are greater, smaller RMSE point and confidencen interval more narrow, therefore can be concluded that applied of Box-Cox power transformation on OLS better of median quantile regression to overcome heteroscedasticity.

Hybrid ARIMAX quantile regression method for forecasting short term electricity consumption in east java

Science.gov (United States)

Prastuti, M.; Suhartono; Salehah, NA

2018-04-01

The need for energy supply, especially for electricity in Indonesia has been increasing in the last past years. Furthermore, the high electricity usage by people at different times leads to the occurrence of heteroscedasticity issue. Estimate the electricity supply that could fulfilled the community’s need is very important, but the heteroscedasticity issue often made electricity forecasting hard to be done. An accurate forecast of electricity consumptions is one of the key challenges for energy provider to make better resources and service planning and also take control actions in order to balance the electricity supply and demand for community. In this paper, hybrid ARIMAX Quantile Regression (ARIMAX-QR) approach was proposed to predict the short-term electricity consumption in East Java. This method will also be compared to time series regression using RMSE, MAPE, and MdAPE criteria. The data used in this research was the electricity consumption per half-an-hour data during the period of September 2015 to April 2016. The results show that the proposed approach can be a competitive alternative to forecast short-term electricity in East Java. ARIMAX-QR using lag values and dummy variables as predictors yield more accurate prediction in both in-sample and out-sample data. Moreover, both time series regression and ARIMAX-QR methods with addition of lag values as predictor could capture accurately the patterns in the data. Hence, it produces better predictions compared to the models that not use additional lag variables.

Localized scleroderma: a series of 52 patients.

Science.gov (United States)

Toledano, C; Rabhi, S; Kettaneh, A; Fabre, B; Fardet, L; Tiev, K P; Cabane, J

2009-05-01

Localized scleroderma also called morphea is a skin disorder of undetermined cause. The widely recognized Mayo Clinic Classification identifies 5 main morphea types: plaque, generalized, bullous, linear and deep. Whether each of these distinct types has a particular clinical course or is associated with some patient-related features is still unclear. We report here a retrospective series of patients with localized scleroderma with an attempt to identify features related to the type of lesion involved. The medical records of all patients with a diagnosis of localized scleroderma were reviewed by skilled practitioners. Lesions were classified according to the Mayo Clinic Classification. The relationship between each lesion type and various clinical features was tested by non-parametrical methods. The sample of 52 patients included 43 females and 9 males. Median age at onset was 30 y (range 1-76). Frequencies of patients according to morphea types were: plaque morphea 41 (78.8%) (including morphea en plaque 30 (57.7%) and atrophoderma of Pasini-Pierini 11 (21.1%)), linear scleroderma 14 (26.9%). Nine patients (17.3%) had both types of localized scleroderma. Median age at onset was lower in patients with linear scleroderma (8 y (range 3-44)) than in others (36 y (range 1-77)) (p=0.0003). Head involvement was more common in patients with linear scleroderma (37.5%) than in other subtypes (11.1%) (p=0.05). Atrophoderma of Pasini-Pierini was never located at the head. Systemic symptoms, antinuclear antibodies and the rheumatic factor were not associated with localized scleroderma types or subtypes. These results suggest that morphea types, in adults are not associated with distinct patient features except for age at disease onset (lower) and the localization on the head (more frequent), in patients with lesions of the linear type.

Final Focus Systems in Linear Colliders

International Nuclear Information System (INIS)

Raubenheimer, Tor

1998-01-01

In colliding beam facilities, the ''final focus system'' must demagnify the beams to attain the very small spot sizes required at the interaction points. The first final focus system with local chromatic correction was developed for the Stanford Linear Collider where very large demagnifications were desired. This same conceptual design has been adopted by all the future linear collider designs as well as the SuperConducting Supercollider, the Stanford and KEK B-Factories, and the proposed Muon Collider. In this paper, the over-all layout, physics constraints, and optimization techniques relevant to the design of final focus systems for high-energy electron-positron linear colliders are reviewed. Finally, advanced concepts to avoid some of the limitations of these systems are discussed

Non-linear elasticity of extracellular matrices enables contractile cells to communicate local position and orientation.

Directory of Open Access Journals (Sweden)

Jessamine P Winer

2009-07-01

Full Text Available Most tissue cells grown in sparse cultures on linearly elastic substrates typically display a small, round phenotype on soft substrates and become increasingly spread as the modulus of the substrate increases until their spread area reaches a maximum value. As cell density increases, individual cells retain the same stiffness-dependent differences unless they are very close or in molecular contact. On nonlinear strain-stiffening fibrin gels, the same cell types become maximally spread even when the low strain elastic modulus would predict a round morphology, and cells are influenced by the presence of neighbors hundreds of microns away. Time lapse microscopy reveals that fibroblasts and human mesenchymal stem cells on fibrin deform the substrate by several microns up to five cell lengths away from their plasma membrane through a force limited mechanism. Atomic force microscopy and rheology confirm that these strains locally and globally stiffen the gel, depending on cell density, and this effect leads to long distance cell-cell communication and alignment. Thus cells are acutely responsive to the nonlinear elasticity of their substrates and can manipulate this rheological property to induce patterning.

Optimal local dimming for LED-backlit LCD displays via linear programming

DEFF Research Database (Denmark)

Shu, Xiao; Wu, Xiaolin; Forchhammer, Søren

2012-01-01

and the attenuations of LCD pixels. The objective is to minimize the distortion in luminance reproduction due to the leakage of LCD and the coarse granularity of the LED lights. The optimization problem is formulated as one of linear programming, and both exact and approximate algorithms are proposed. Simulation...

Linear Transformation of the Polarization Modes in Coiled Optical Spun-Fibers with Strong Unperturbed Linear Birefringence. I. Nonresonant Transformation

Science.gov (United States)

Malykin, G. B.; Pozdnyakova, V. I.

2018-03-01

A linear transformation of orthogonal polarization modes in coiled optical spun-fibers with strong unperturbed linear birefringence, which causes the emergence of the dependences of the integrated elliptical birefringence and the ellipticity and azimuth of the major axis of the ellipse, as well as the polarization state of radiation (PSR), on the length of optical fiber has been considered. Optical spun-fibers are subjected to a strong mechanical twisting, which is frozen into the structure of the optical fiber upon cooling, in the process of being drawn out from the workpiece. Since the values of the local polarization parameters of coiled spunwaveguides vary according to a rather complex law, the calculations were carried out by numerical modeling of the parameters of the Jones matrices. Since the rotation speed of the axes of the birefringence is constant on a relatively short segment of a coiled optical spun-fiber in the accompanying torsion (helical) coordinate system, the so-called "Ginzburg helical polarization modes" (GHPMs)—two mutually orthogonal ellipses with the opposite directions of traversal, the axis of which rotate relative to the fixed coordinate system uniformly and unidirectionally—are approximately the local normal polarization modes of such optical fiber. It has been shown that, despite the fact that the unperturbed linear birefringence of the spun-fibers significantly exceeds the linear birefringence, which is caused by the winding on a coil, the integral birefringence of an extended segment of such a fiber coincides in order of magnitude with the linear birefringence, which is caused by the winding on the coil, and the integral polarization modes tend asymptotically to circular ones. It has been also shown that the values of the circular birefringence of twisted single-mode fibers, which were calculated in a nonrotating and torsion helical coordinate systems, differ significantly. It has been shown that the polarization phenomena occur

Electromagnetic response in kinetic energy driven cuprate superconductors: Linear response approach

International Nuclear Information System (INIS)

Krzyzosiak, Mateusz; Huang, Zheyu; Feng, Shiping; Gonczarek, Ryszard

2010-01-01

Within the framework of the kinetic energy driven superconductivity, the electromagnetic response in cuprate superconductors is studied in the linear response approach. The kernel of the response function is evaluated and employed to calculate the local magnetic field profile, the magnetic field penetration depth, and the superfluid density, based on the specular reflection model for a purely transverse vector potential. It is shown that the low temperature magnetic field profile follows an exponential decay at the surface, while the magnetic field penetration depth depends linearly on temperature, except for the strong deviation from the linear characteristics at extremely low temperatures. The superfluid density is found to decrease linearly with decreasing doping concentration in the underdoped regime. The problem of gauge invariance is addressed and an approximation for the dressed current vertex, which does not violate local charge conservation is proposed and discussed.

Local E11

International Nuclear Information System (INIS)

Riccioni, Fabio; West, Peter

2009-01-01

We give a method of deriving the field-strengths of all massless and massive maximal supergravity theories in any dimension starting from the Kac-Moody algebra E 11 . Considering the subalgebra of E 11 that acts on the fields in the non-linear realisation as a global symmetry, we show how this is promoted to a gauge symmetry enlarging the algebra by the inclusion of additional generators. We show how this works in eleven dimensions, and we call the resulting enlarged algebra E 11 local . Torus reduction to D dimensions corresponds to taking a subalgebra of E 11 local , called E 11,D local , that encodes the full gauge algebra of the corresponding D-dimensional massless supergravity. We show that each massive maximal supergravity in D dimensions is a non-linear realisation of an algebra E-tilde 11,D local . We show how this works in detail for the case of Scherk-Schwarz reduction of IIB to nine dimensions, and in particular we show how E-tilde 11,9 local arises as a subalgebra of the algebra E 11,10B local associated to the ten-dimensional IIB theory. This subalgebra corresponds to taking a combination of generators which is different to the massless case. We then show that E-tilde 11,D local appears as a deformation of the massless algebra E 11,D local in which the commutation relations between the E 11 and the additional generators are modified. We explicitly illustrate how the deformed algebra is constructed in the case of massive IIA and of gauged five-dimensional supergravity. These results prove the naturalness and power of the method.

Exact solution of a coupled spin–electron linear chain composed of localized Ising spins and mobile electrons

International Nuclear Information System (INIS)

Čisárová, Jana; Strečka, Jozef

2014-01-01

Exact solution of a coupled spin–electron linear chain composed of localized Ising spins and mobile electrons is found. The investigated spin–electron model is exactly solvable by the use of a transfer-matrix method after tracing out the degrees of freedom of mobile electrons delocalized over a couple of interstitial (decorating) sites. The exact ground-state phase diagram reveals an existence of five phases with different number of mobile electrons per unit cell, two of which are ferromagnetic, two are paramagnetic and one is antiferromagnetic. We have studied in particular the dependencies of compressibility and specific heat on temperature and electron density. - Highlights: • A coupled spin–electron chain composed of Ising spins and mobile electrons is exactly solved. • Quantum paramagnetic, ferromagnetic and antiferromagnetic ground states are found. • A compressibility shows a non-monotonous dependence on temperature and electron density. • Thermal dependences of specific heat display two distinct peaks

[Localized scleroderma (morphea) in childhood].

Science.gov (United States)

Weibel, L

2012-02-01

Localized scleroderma or morphea is a sclerosing connective tissue disease of the skin, which may affect underlying tissues such as subcutis, muscle and bone. Many patients show extracutaneous symptoms and antinuclear antibodies, however, secondary transformation into systemic sclerosis does not occur. Localized scleroderma usually begins in childhood with a wide variation in its clinical spectrum. The linear variant is the most common subtype in children, associated with a progressive course and increased risk of complications. The disease may progress over years and result in severe functional and cosmetic disability. The etiology of localized scleroderma remains unknown. A genetic background is suspected, while triggers such as trauma, vaccinations and infections may lead to secondary immunologic phenomena. Localized scleroderma often remains unrecognized for a long time, resulting in substantial delay in treatment. The combination of systemic corticosteroids and methotrexate has been established as first-line therapy for progressive (usually linear) disease, whereas phototherapy (UVA-1 or UVB-narrow band) is suitable for adolescents with superficial circumscribed subtypes.

An analogue of Morse theory for planar linear networks and the generalized Steiner problem

International Nuclear Information System (INIS)

Karpunin, G A

2000-01-01

A study is made of the generalized Steiner problem: the problem of finding all the locally minimal networks spanning a given boundary set (terminal set). It is proposed to solve this problem by using an analogue of Morse theory developed here for planar linear networks. The space K of all planar linear networks spanning a given boundary set is constructed. The concept of a critical point and its index is defined for the length function l of a planar linear network. It is shown that locally minimal networks are local minima of l on K and are critical points of index 1. The theorem is proved that the sum of the indices of all the critical points is equal to χ(K)=1. This theorem is used to find estimates for the number of locally minimal networks spanning a given boundary set

LINEAR2007, Linear-Linear Interpolation of ENDF Format Cross-Sections

International Nuclear Information System (INIS)

2007-01-01

1 - Description of program or function: LINEAR converts evaluated cross sections in the ENDF/B format into a tabular form that is subject to linear-linear interpolation in energy and cross section. The code also thins tables of cross sections already in that form. Codes used subsequently need thus to consider only linear-linear data. IAEA1311/15: This version include the updates up to January 30, 2007. Changes in ENDF/B-VII Format and procedures, as well as the evaluations themselves, make it impossible for versions of the ENDF/B pre-processing codes earlier than PREPRO 2007 (2007 Version) to accurately process current ENDF/B-VII evaluations. The present code can handle all existing ENDF/B-VI evaluations through release 8, which will be the last release of ENDF/B-VI. Modifications from previous versions: - Linear VERS. 2007-1 (JAN. 2007): checked against all ENDF/B-VII; increased page size from 60,000 to 600,000 points 2 - Method of solution: Each section of data is considered separately. Each section of File 3, 23, and 27 data consists of a table of cross section versus energy with any of five interpolation laws. LINEAR will replace each section with a new table of energy versus cross section data in which the interpolation law is always linear in energy and cross section. The histogram (constant cross section between two energies) interpolation law is converted to linear-linear by substituting two points for each initial point. The linear-linear is not altered. For the log-linear, linear-log and log- log laws, the cross section data are converted to linear by an interval halving algorithm. Each interval is divided in half until the value at the middle of the interval can be approximated by linear-linear interpolation to within a given accuracy. The LINEAR program uses a multipoint fractional error thinning algorithm to minimize the size of each cross section table

Statistically Efficient Construction of α-Risk-Minimizing Portfolio

Directory of Open Access Journals (Sweden)

Hiroyuki Taniai

2012-01-01

Full Text Available We propose a semiparametrically efficient estimator for α-risk-minimizing portfolio weights. Based on the work of Bassett et al. (2004, an α-risk-minimizing portfolio optimization is formulated as a linear quantile regression problem. The quantile regression method uses a pseudolikelihood based on an asymmetric Laplace reference density, and asymptotic properties such as consistency and asymptotic normality are obtained. We apply the results of Hallin et al. (2008 to the problem of constructing α-risk-minimizing portfolios using residual signs and ranks and a general reference density. Monte Carlo simulations assess the performance of the proposed method. Empirical applications are also investigated.

INLA goes extreme: Bayesian tail regression for the estimation of high spatio-temporal quantiles

KAUST Repository

Opitz, Thomas

2018-05-25

This work is motivated by the challenge organized for the 10th International Conference on Extreme-Value Analysis (EVA2017) to predict daily precipitation quantiles at the 99.8% level for each month at observed and unobserved locations. Our approach is based on a Bayesian generalized additive modeling framework that is designed to estimate complex trends in marginal extremes over space and time. First, we estimate a high non-stationary threshold using a gamma distribution for precipitation intensities that incorporates spatial and temporal random effects. Then, we use the Bernoulli and generalized Pareto (GP) distributions to model the rate and size of threshold exceedances, respectively, which we also assume to vary in space and time. The latent random effects are modeled additively using Gaussian process priors, which provide high flexibility and interpretability. We develop a penalized complexity (PC) prior specification for the tail index that shrinks the GP model towards the exponential distribution, thus preventing unrealistically heavy tails. Fast and accurate estimation of the posterior distributions is performed thanks to the integrated nested Laplace approximation (INLA). We illustrate this methodology by modeling the daily precipitation data provided by the EVA2017 challenge, which consist of observations from 40 stations in the Netherlands recorded during the period 1972–2016. Capitalizing on INLA’s fast computational capacity and powerful distributed computing resources, we conduct an extensive cross-validation study to select the model parameters that govern the smoothness of trends. Our results clearly outperform simple benchmarks and are comparable to the best-scoring approaches of the other teams.

[Localized scleroderma (morphea)].

Science.gov (United States)

Bono, Waafa; Dupin, Nicolas

2006-12-01

DEFINITION AND FREQUENCY: Localized scleroderma, also known as morphea, is a sclerotic condition limited to the skin. The specific clinical entity depends on the extent, linear disposition and depth of the lesions. Morphea is ten times more prevalent than systemic sclerosis, and its prognosis is generally good: superficial forms resolve within 3 years. In the absence of symptoms, examinations to detect systemic involvement are purposeless. Plaque morphea is the most frequent clinical presentation. Serious manifestations include extensive morphea that may involve the entire skin or linear forms, especially in children, where they may be severe, especially on the face. There are no immunological markers clearly associated with morphea and no causative agents have been implicated in its pathogenesis, although sclerodermiform dermatitis is reported to be associated with some drugs and toxic agents. There is no consensual treatment for morphea. Treatment should be decided according to severity and extent of lesions. Limited lesions may be treated with local steroids such as class IV corticosteroids. Systemic treatment (methotrexate) should be discussed in extensive and linear forms when there is a risk of functional or esthetic complications.

Automated linear regression tools improve RSSI WSN localization in multipath indoor environment

Directory of Open Access Journals (Sweden)

Laermans Eric

2011-01-01

Full Text Available Abstract Received signal strength indication (RSSI-based localization is emerging in wireless sensor networks (WSNs. Localization algorithms need to include the physical and hardware limitations of RSSI measurements in order to give more accurate results in dynamic real-life indoor environments. In this study, we use the Interdisciplinary Institute for Broadband Technology real-life test bed and present an automated method to optimize and calibrate the experimental data before offering them to a positioning engine. In a preprocessing localization step, we introduce a new method to provide bounds for the range, thereby further improving the accuracy of our simple and fast 2D localization algorithm based on corrected distance circles. A maximum likelihood algorithm with a mean square error cost function has a higher position error median than our algorithm. Our experiments further show that the complete proposed algorithm eliminates outliers and avoids any manual calibration procedure.

Linearization Method and Linear Complexity

Science.gov (United States)

Tanaka, Hidema

We focus on the relationship between the linearization method and linear complexity and show that the linearization method is another effective technique for calculating linear complexity. We analyze its effectiveness by comparing with the logic circuit method. We compare the relevant conditions and necessary computational cost with those of the Berlekamp-Massey algorithm and the Games-Chan algorithm. The significant property of a linearization method is that it needs no output sequence from a pseudo-random number generator (PRNG) because it calculates linear complexity using the algebraic expression of its algorithm. When a PRNG has n [bit] stages (registers or internal states), the necessary computational cost is smaller than O(2n). On the other hand, the Berlekamp-Massey algorithm needs O(N2) where N(≅2n) denotes period. Since existing methods calculate using the output sequence, an initial value of PRNG influences a resultant value of linear complexity. Therefore, a linear complexity is generally given as an estimate value. On the other hand, a linearization method calculates from an algorithm of PRNG, it can determine the lower bound of linear complexity.

Duality in linearized gravity

International Nuclear Information System (INIS)

Henneaux, Marc; Teitelboim, Claudio

2005-01-01

We show that duality transformations of linearized gravity in four dimensions, i.e., rotations of the linearized Riemann tensor and its dual into each other, can be extended to the dynamical fields of the theory so as to be symmetries of the action and not just symmetries of the equations of motion. Our approach relies on the introduction of two superpotentials, one for the spatial components of the spin-2 field and the other for their canonically conjugate momenta. These superpotentials are two-index, symmetric tensors. They can be taken to be the basic dynamical fields and appear locally in the action. They are simply rotated into each other under duality. In terms of the superpotentials, the canonical generator of duality rotations is found to have a Chern-Simons-like structure, as in the Maxwell case

Performance Analysis of Local Ensemble Kalman Filter

Science.gov (United States)

Tong, Xin T.

2018-03-01

Ensemble Kalman filter (EnKF) is an important data assimilation method for high-dimensional geophysical systems. Efficient implementation of EnKF in practice often involves the localization technique, which updates each component using only information within a local radius. This paper rigorously analyzes the local EnKF (LEnKF) for linear systems and shows that the filter error can be dominated by the ensemble covariance, as long as (1) the sample size exceeds the logarithmic of state dimension and a constant that depends only on the local radius; (2) the forecast covariance matrix admits a stable localized structure. In particular, this indicates that with small system and observation noises, the filter error will be accurate in long time even if the initialization is not. The analysis also reveals an intrinsic inconsistency caused by the localization technique, and a stable localized structure is necessary to control this inconsistency. While this structure is usually taken for granted for the operation of LEnKF, it can also be rigorously proved for linear systems with sparse local observations and weak local interactions. These theoretical results are also validated by numerical implementation of LEnKF on a simple stochastic turbulence in two dynamical regimes.

Normalization Approaches for Removing Systematic Biases Associated with Mass Spectrometry and Label-Free Proteomics

Energy Technology Data Exchange (ETDEWEB)

Callister, Stephen J.; Barry, Richard C.; Adkins, Joshua N.; Johnson, Ethan T.; Qian, Weijun; Webb-Robertson, Bobbie-Jo M.; Smith, Richard D.; Lipton, Mary S.

2006-02-01

Central tendency, linear regression, locally weighted regression, and quantile techniques were investigated for normalization of peptide abundance measurements obtained from high-throughput liquid chromatography-Fourier transform ion cyclotron resonance mass spectrometry (LC-FTICR MS). Arbitrary abundances of peptides were obtained from three sample sets, including a standard protein sample, two Deinococcus radiodurans samples taken from different growth phases, and two mouse striatum samples from control and methamphetamine-stressed mice (strain C57BL/6). The selected normalization techniques were evaluated in both the absence and presence of biological variability by estimating extraneous variability prior to and following normalization. Prior to normalization, replicate runs from each sample set were observed to be statistically different, while following normalization replicate runs were no longer statistically different. Although all techniques reduced systematic bias, assigned ranks among the techniques revealed significant trends. For most LC-FTICR MS analyses, linear regression normalization ranked either first or second among the four techniques, suggesting that this technique was more generally suitable for reducing systematic biases.

Global and local curvature in density functional theory.

Science.gov (United States)

Zhao, Qing; Ioannidis, Efthymios I; Kulik, Heather J

2016-08-07

Piecewise linearity of the energy with respect to fractional electron removal or addition is a requirement of an electronic structure method that necessitates the presence of a derivative discontinuity at integer electron occupation. Semi-local exchange-correlation (xc) approximations within density functional theory (DFT) fail to reproduce this behavior, giving rise to deviations from linearity with a convex global curvature that is evidence of many-electron, self-interaction error and electron delocalization. Popular functional tuning strategies focus on reproducing piecewise linearity, especially to improve predictions of optical properties. In a divergent approach, Hubbard U-augmented DFT (i.e., DFT+U) treats self-interaction errors by reducing the local curvature of the energy with respect to electron removal or addition from one localized subshell to the surrounding system. Although it has been suggested that DFT+U should simultaneously alleviate global and local curvature in the atomic limit, no detailed study on real systems has been carried out to probe the validity of this statement. In this work, we show when DFT+U should minimize deviations from linearity and demonstrate that a "+U" correction will never worsen the deviation from linearity of the underlying xc approximation. However, we explain varying degrees of efficiency of the approach over 27 octahedral transition metal complexes with respect to transition metal (Sc-Cu) and ligand strength (CO, NH3, and H2O) and investigate select pathological cases where the delocalization error is invisible to DFT+U within an atomic projection framework. Finally, we demonstrate that the global and local curvatures represent different quantities that show opposing behavior with increasing ligand field strength, and we identify where these two may still coincide.

Impacts of altimeter corrections on local linear sea level trends around Taiwan

DEFF Research Database (Denmark)

Cheng, Yongcun; Andersen, Ole Baltazar

2013-01-01

.e. the inverted barometer correction, wet tropospheric correction, and sea state bias correction, have significant impacts on the determination of local LSLT. The trend of default corrections contribute more than 1.4 mm year-1 along the coastline of China mainland and 2.1 mm year-1 to local LSLT in the Taiwan...

Perturbation analysis of linear control problems

International Nuclear Information System (INIS)

Petkov, Petko; Konstantinov, Mihail

2017-01-01

The paper presents a brief overview of the technique of splitting operators, proposed by the authors and intended for perturbation analysis of control problems involving unitary and orthogonal matrices. Combined with the technique of Lyapunov majorants and the implementation of the Banach and Schauder fixed point principles, it allows to obtain rigorous non-local perturbation bounds for a set of sensitivity analysis problems. Among them are the reduction of linear systems into orthogonal canonical forms, the feedback synthesis problem and pole assignment problem in particular, as well as other important problems in control theory and linear algebra. Key words: perturbation analysis, canonical forms, feedback synthesis

Food Standards are Good– for Middle-class Farmers

DEFF Research Database (Denmark)

Hansen, Henrik; Trifkovic, Neda

results indicate that large returns can be accrued from food standards, but only for the upper middle-class farmers, i.e., those between the 50% and 85% quantiles of the expenditure distribution. Overall, our result points to an exclusionary impact of standards for the poorest farmers while the richest do......We estimate the causal effect of food standards on Vietnamese pangasius farmers’ wellbeing measured by per capita consumption expenditure. We estimate both the average effects and the local average treatment effects on poorer and richer farmers by instrumental variable quantile regression. Our...

Food Standards are Good – for Middle-Class Farmers

DEFF Research Database (Denmark)

Hansen, Henrik; Trifkovic, Neda

2014-01-01

We estimate the causal effect of food standards on Vietnamese pangasius farmers’ wellbeing measured by per capita consumption expenditure. We estimate both the average effects and the local average treatment effects on poorer and richer farmers by instrumental variable quantile regression. Our...... results indicate that large returns can be accrued from food standards, but only for the upper middle-class farmers, i.e., those between the 50% and 85% quantiles of the expenditure distribution. Overall, our result points to an exclusionary impact of standards for the poorest farmers while the richest do...

Bianchi-Baecklund transformations, conservation laws, and linearization of various field theories

International Nuclear Information System (INIS)

Chau Wang, L.L.

1980-01-01

The discussion includes: the Sine-Gordon equation, parametric Bianchi-Baecklund transformations and the derivation of local conservation laws; chiral fields, parametric Bianchi-Baecklund transformations, local and non-local conservation laws, and linearization; super chiral fields, a parallel development similar to the chiral field; and self-dual Yang-Mills fields in 4-dimensional Euclidean space; loop-cpace chiral equations, parallel development but with subtlety

Decentralized linear quadratic power system stabilizers for multi ...

Indian Academy of Sciences (India)

Introduction. Modern excitation systems considerably enhance the overall transient stability of power systems ..... to the local bus rather than the angle δ measured with respect to the remote bus. ... With this in view, the linear and nonlinear per-.

Alternative regression models to assess increase in childhood BMI

OpenAIRE

Beyerlein, Andreas; Fahrmeir, Ludwig; Mansmann, Ulrich; Toschke, André M

2008-01-01

Abstract Background Body mass index (BMI) data usually have skewed distributions, for which common statistical modeling approaches such as simple linear or logistic regression have limitations. Methods Different regression approaches to predict childhood BMI by goodness-of-fit measures and means of interpretation were compared including generalized linear models (GLMs), quantile regression and Generalized Additive Models for Location, Scale and Shape (GAMLSS). We analyzed data of 4967 childre...

Regression analysis of growth responses to water depth in three wetland plant species

DEFF Research Database (Denmark)

Sorrell, Brian K; Tanner, Chris C; Brix, Hans

2012-01-01

depths from 0 – 0.5 m. Morphological and growth responses to depth were followed for 54 days before harvest, and then analysed by repeated measures analysis of covariance, and non-linear and quantile regression analysis (QRA), to compare flooding tolerances. Principal results Growth responses to depth...

Localized solutions for a nonlocal discrete NLS equation

International Nuclear Information System (INIS)

Ben, Roberto I.; Cisneros Ake, Luís; Minzoni, A.A.; Panayotaros, Panayotis

2015-01-01

We study spatially localized time-periodic solutions of breather type for a cubic discrete NLS equation with a nonlocal nonlinearity that models light propagation in a liquid crystal waveguide array. We show the existence of breather solutions in the limit where both linear and nonlinear intersite couplings vanish, and in the limit where the linear coupling vanishes with arbitrary nonlinear intersite coupling. Breathers of this nonlocal regime exhibit some interesting features that depart from what is seen in the NLS breathers with power nonlinearity. One property we see theoretically is the presence of higher amplitude at interfaces between sites with zero and nonzero amplitude in the vanishing linear coupling limit. A numerical study also suggests the presence of internal modes of orbitally stable localized modes. - Highlights: • Show existence of spatially localized solutions in nonlocal discrete NLS model. • Study spatial properties of localized solutions for arbitrary nonlinear nonlocal coupling. • Present numerical evidence that nonlocality leads to internal modes around stable breathers. • Present theoretical and numerical evidence for amplitude maxima at interfaces

Localized solutions for a nonlocal discrete NLS equation

Energy Technology Data Exchange (ETDEWEB)

Ben, Roberto I. [Instituto de Desarrollo Humano, Universidad Nacional de General Sarmiento, J.M. Gutiérrez 1150, 1613 Los Polvorines (Argentina); Cisneros Ake, Luís [Department of Mathematics, ESFM, Instituto Politécnico Nacional, Unidad Profesional Adolfo López Mateos Edificio 9, 07738 México D.F. (Mexico); Minzoni, A.A. [Depto. Matemáticas y Mecánica, I.I.M.A.S.-U.N.A.M., Apdo. Postal 20-726, 01000 México D.F. (Mexico); Panayotaros, Panayotis, E-mail: panos@mym.iimas.unam.mx [Depto. Matemáticas y Mecánica, I.I.M.A.S.-U.N.A.M., Apdo. Postal 20-726, 01000 México D.F. (Mexico)

2015-09-04

We study spatially localized time-periodic solutions of breather type for a cubic discrete NLS equation with a nonlocal nonlinearity that models light propagation in a liquid crystal waveguide array. We show the existence of breather solutions in the limit where both linear and nonlinear intersite couplings vanish, and in the limit where the linear coupling vanishes with arbitrary nonlinear intersite coupling. Breathers of this nonlocal regime exhibit some interesting features that depart from what is seen in the NLS breathers with power nonlinearity. One property we see theoretically is the presence of higher amplitude at interfaces between sites with zero and nonzero amplitude in the vanishing linear coupling limit. A numerical study also suggests the presence of internal modes of orbitally stable localized modes. - Highlights: • Show existence of spatially localized solutions in nonlocal discrete NLS model. • Study spatial properties of localized solutions for arbitrary nonlinear nonlocal coupling. • Present numerical evidence that nonlocality leads to internal modes around stable breathers. • Present theoretical and numerical evidence for amplitude maxima at interfaces.

Model Related Estimates of time dependent quantiles of peak flows - case study for selected catchments in Poland

Science.gov (United States)

Strupczewski, Witold G.; Bogdanowich, Ewa; Debele, Sisay

2016-04-01

Under Polish climate conditions the series of Annual Maxima (AM) flows are usually a mixture of peak flows of thaw- and rainfall- originated floods. The northern, lowland regions are dominated by snowmelt floods whilst in mountainous regions the proportion of rainfall floods is predominant. In many stations the majority of AM can be of snowmelt origin, but the greatest peak flows come from rainfall floods or vice versa. In a warming climate, precipitation is less likely to occur as snowfall. A shift from a snow- towards a rain-dominated regime results in a decreasing trend in mean and standard deviations of winter peak flows whilst rainfall floods do not exhibit any trace of non-stationarity. That is why a simple form of trends (i.e. linear trends) are more difficult to identify in AM time-series than in Seasonal Maxima (SM), usually winter season time-series. Hence it is recommended to analyse trends in SM, where a trend in standard deviation strongly influences the time -dependent upper quantiles. The uncertainty associated with the extrapolation of the trend makes it necessary to apply a relationship for trend which has time derivative tending to zero, e.g. we can assume a new climate equilibrium epoch approaching, or a time horizon is limited by the validity of the trend model. For both winter and summer SM time series, at least three distributions functions with trend model in the location, scale and shape parameters are estimated by means of the GAMLSS package using the ML-techniques. The resulting trend estimates in mean and standard deviation are mutually compared to the observed trends. Then, using AIC measures as weights, a multi-model distribution is constructed for each of two seasons separately. Further, assuming a mutual independence of the seasonal maxima, an AM model with time-dependent parameters can be obtained. The use of a multi-model approach can alleviate the effects of different and often contradictory trends obtained by using and identifying

STABLE STATIONARY STATES OF NON-LOCAL INTERACTION EQUATIONS

KAUST Repository

FELLNER, KLEMENS; RAOUL, GAË L

2010-01-01

.r.t. shifts and reallocations of individual Dirac masses, and (iii) show that these linear stability conditions imply local non-linear stability. Finally, we show that for regular repulsive interaction potential Wε converging to a singular repulsive

Boundary Lax pairs from non-ultra-local Poisson algebras

International Nuclear Information System (INIS)

Avan, Jean; Doikou, Anastasia

2009-01-01

We consider non-ultra-local linear Poisson algebras on a continuous line. Suitable combinations of representations of these algebras yield representations of novel generalized linear Poisson algebras or 'boundary' extensions. They are parametrized by a boundary scalar matrix and depend, in addition, on the choice of an antiautomorphism. The new algebras are the classical-linear counterparts of the known quadratic quantum boundary algebras. For any choice of parameters, the non-ultra-local contribution of the original Poisson algebra disappears. We also systematically construct the associated classical Lax pair. The classical boundary principal chiral model is examined as a physical example.

Low-cost, ready-to-use therapeutic foods can be designed using locally available commodities with the aid of linear programming.

Science.gov (United States)

Dibari, Filippo; Diop, El Hadji I; Collins, Steven; Seal, Andrew

2012-05-01

According to the United Nations (UN), 25 million children linear programming (LP) analysis was developed and piloted in the design of a RUTF prototype for the treatment of wasting in East African children and adults. The LP objective function and decision variables consisted of the lowest formulation price and the weights of the chosen commodities (soy, sorghum, maize, oil, and sugar), respectively. The LP constraints were based on current UN recommendations for the macronutrient content of therapeutic food and included palatability, texture, and maximum food ingredient weight criteria. Nonlinear constraints for nutrient ratios were converted to linear equations to allow their use in LP. The formulation was considered accurate if laboratory results confirmed an energy density difference <10% and a protein or lipid difference <5 g · 100 g(-1) compared to the LP formulation estimates. With this test prototype, the differences were 7%, and 2.3 and -1.0 g · 100 g(-1), respectively, and the formulation accuracy was considered good. LP can contribute to the design of ready-to-use foods (therapeutic, supplementary, or complementary), targeting different forms of malnutrition, while using commodities that are cheaper, regionally available, and meet local cultural preferences. However, as with all prototype feeding products for medical use, composition analysis, safety, acceptability, and clinical effectiveness trials must be conducted to validate the formulation.

Decoherence of histories and hydrodynamic equations for a linear oscillator chain

International Nuclear Information System (INIS)

Halliwell, J.J.

2003-01-01

We investigate the decoherence of histories of local densities for linear oscillators models. It is shown that histories of local number, momentum and energy density are approximately decoherent, when coarse grained over sufficiently large volumes. Decoherence arises directly from the proximity of these variables to exactly conserved quantities (which are exactly decoherent), and not from environmentally induced decoherence. We discuss the approach to local equilibrium and the subsequent emergence of hydrodynamic equations for the local densities

Imaging of Caenorhabditis elegans samples and sub-cellular localization of new generation photosensitizers for photodynamic therapy, using non-linear microscopy

Energy Technology Data Exchange (ETDEWEB)

Filippidis, G [Institute of Electronic Structure and Laser, Foundation of Research and Technology-Hellas, PO Box 1527, 71110 Heraklion (Greece); Kouloumentas, C [Institute of Electronic Structure and Laser, Foundation of Research and Technology-Hellas, PO Box 1527, 71110 Heraklion (Greece); Kapsokalyvas, D [Institute of Electronic Structure and Laser, Foundation of Research and Technology-Hellas, PO Box 1527, 71110 Heraklion (Greece); Voglis, G [Institute of Molecular Biology and Biotechnology, Foundation of Research and Technology, Heraklion 71110, Crete (Greece); Tavernarakis, N [Institute of Molecular Biology and Biotechnology, Foundation of Research and Technology, Heraklion 71110, Crete (Greece); Papazoglou, T G [Institute of Electronic Structure and Laser, Foundation of Research and Technology-Hellas, PO Box 1527, 71110 Heraklion (Greece)

2005-08-07

Two-photon excitation fluorescence (TPEF) and second-harmonic generation (SHG) are relatively new promising tools for the imaging and mapping of biological structures and processes at the microscopic level. The combination of the two image-contrast modes in a single instrument can provide unique and complementary information concerning the structure and the function of tissues and individual cells. The extended application of this novel, innovative technique by the biological community is limited due to the high price of commercial multiphoton microscopes. In this study, a compact, inexpensive and reliable setup utilizing femtosecond pulses for excitation was developed for the TPEF and SHG imaging of biological samples. Specific cell types of the nematode Caenorhabditis elegans were imaged. Detection of the endogenous structural proteins of the worm, which are responsible for observation of SHG signals, was achieved. Additionally, the binding of different photosensitizers in the HL-60 cell line was investigated, using non-linear microscopy. The sub-cellular localization of photosensitizers of a new generation, very promising for photodynamic therapy (PDT) (Hypericum perforatum L. extracts) was achieved. The sub-cellular localization of these novel photosensitizers was linked with their photodynamic action during PDT, and the possible mechanisms for cell killing have been elucidated.

Multiplicative perturbations of local C-semigroups

Indian Academy of Sciences (India)

In this paper, we establish some left and right multiplicative perturbation theorems concerning local -semigroups when the generator of a perturbed local -semigroup S ( ⋅ ) may not be densely defined and the perturbation operator is a bounded linear operator from D ( A ) ¯ into () such that = on D ( A ) ¯ ...

Multiplicative perturbations of local C-semigroups

Indian Academy of Sciences (India)

2016-08-26

Aug 26, 2016 ... In this paper, we establish some left and right multiplicative perturbation theorems concerning local -semigroups when the generator of a perturbed local -semigroup S(⋅) may not be densely defined and the perturbation operator is a bounded linear operator from ¯D(A) into () such that = ...

On the local equilibrium condition

International Nuclear Information System (INIS)

Hessling, H.

1994-11-01

A physical system is in local equilibrium if it cannot be distinguished from a global equilibrium by ''infinitesimally localized measurements''. This should be a natural characterization of local equilibrium, but the problem is to give a precise meaning to the qualitative phrase ''infinitesimally localized measurements''. A solution is suggested in form of a Local Equilibrium Condition (LEC), which can be applied to linear relativistic quantum field theories but not directly to selfinteracting quantum fields. The concept of local temperature resulting from LEC is compared to an old approach to local temperature based on the principle of maximal entropy. It is shown that the principle of maximal entropy does not always lead to physical states if it is applied to relativistic quantum field theories. (orig.)

Results of radiotherapy in craniopharyngiomas analysed by the linear quadratic model

Energy Technology Data Exchange (ETDEWEB)

Guerkaynak, M. [Dept. of Radiation Oncology, Hacettepe Univ., Ankara (Turkey); Oezyar, E. [Dept. of Radiation Oncology, Hacettepe Univ., Ankara (Turkey); Zorlu, F. [Dept. of Radiation Oncology, Hacettepe Univ., Ankara (Turkey); Akyol, F.H. [Dept. of Radiation Oncology, Hacettepe Univ., Ankara (Turkey); Lale Atahan, I. [Dept. of Radiation Oncology, Hacettepe Univ., Ankara (Turkey)

1994-12-31

In 23 craniopharyngioma patients treated by limited surgery and external radiotherapy, the results concerning local control were analysed by linear quadratic formula. A biologically effective dose (BED) of 55 Gy, calculated with time factor and an {alpha}/{beta} value of 10 Gy, seemed to be adequate for local control. (orig.).

Robust estimation for partially linear models with large-dimensional covariates.

Science.gov (United States)

Zhu, LiPing; Li, RunZe; Cui, HengJian

2013-10-01

We are concerned with robust estimation procedures to estimate the parameters in partially linear models with large-dimensional covariates. To enhance the interpretability, we suggest implementing a noncon-cave regularization method in the robust estimation procedure to select important covariates from the linear component. We establish the consistency for both the linear and the nonlinear components when the covariate dimension diverges at the rate of [Formula: see text], where n is the sample size. We show that the robust estimate of linear component performs asymptotically as well as its oracle counterpart which assumes the baseline function and the unimportant covariates were known a priori. With a consistent estimator of the linear component, we estimate the nonparametric component by a robust local linear regression. It is proved that the robust estimate of nonlinear component performs asymptotically as well as if the linear component were known in advance. Comprehensive simulation studies are carried out and an application is presented to examine the finite-sample performance of the proposed procedures.

Observability of linear control systems on Lie groups

International Nuclear Information System (INIS)

Ayala, V.; Hacibekiroglu, A.K.

1995-01-01

In this paper, we study the observability problem for a linear control system Σ on a Lie group G. The drift vector field of Σ is an infinitesimal automorphism of G and the control vectors are elements in the Lie algebra of G. We establish algebraic conditions to characterize locally and globally observability for Σ. As in the linear case on R n , these conditions are independent of the control vector. We give an algorithm on the co-tangent bundle of G to calculate the equivalence class of the neutral element. (author). 6 refs

Modelling Loudspeaker Non-Linearities

DEFF Research Database (Denmark)

Agerkvist, Finn T.

2007-01-01

This paper investigates different techniques for modelling the non-linear parameters of the electrodynamic loudspeaker. The methods are tested not only for their accuracy within the range of original data, but also for the ability to work reasonable outside that range, and it is demonstrated...... that polynomial expansions are rather poor at this, whereas an inverse polynomial expansion or localized fitting functions such as the gaussian are better suited for modelling the Bl-factor and compliance. For the inductance the sigmoid function is shown to give very good results. Finally the time varying...

Sparse maps—A systematic infrastructure for reduced-scaling electronic structure methods. I. An efficient and simple linear scaling local MP2 method that uses an intermediate basis of pair natural orbitals

Energy Technology Data Exchange (ETDEWEB)

Pinski, Peter; Riplinger, Christoph; Neese, Frank, E-mail: evaleev@vt.edu, E-mail: frank.neese@cec.mpg.de [Max Planck Institute for Chemical Energy Conversion, Stiftstr. 34-36, D-45470 Mülheim an der Ruhr (Germany); Valeev, Edward F., E-mail: evaleev@vt.edu, E-mail: frank.neese@cec.mpg.de [Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061 (United States)

2015-07-21

In this work, a systematic infrastructure is described that formalizes concepts implicit in previous work and greatly simplifies computer implementation of reduced-scaling electronic structure methods. The key concept is sparse representation of tensors using chains of sparse maps between two index sets. Sparse map representation can be viewed as a generalization of compressed sparse row, a common representation of a sparse matrix, to tensor data. By combining few elementary operations on sparse maps (inversion, chaining, intersection, etc.), complex algorithms can be developed, illustrated here by a linear-scaling transformation of three-center Coulomb integrals based on our compact code library that implements sparse maps and operations on them. The sparsity of the three-center integrals arises from spatial locality of the basis functions and domain density fitting approximation. A novel feature of our approach is the use of differential overlap integrals computed in linear-scaling fashion for screening products of basis functions. Finally, a robust linear scaling domain based local pair natural orbital second-order Möller-Plesset (DLPNO-MP2) method is described based on the sparse map infrastructure that only depends on a minimal number of cutoff parameters that can be systematically tightened to approach 100% of the canonical MP2 correlation energy. With default truncation thresholds, DLPNO-MP2 recovers more than 99.9% of the canonical resolution of the identity MP2 (RI-MP2) energy while still showing a very early crossover with respect to the computational effort. Based on extensive benchmark calculations, relative energies are reproduced with an error of typically <0.2 kcal/mol. The efficiency of the local MP2 (LMP2) method can be drastically improved by carrying out the LMP2 iterations in a basis of pair natural orbitals. While the present work focuses on local electron correlation, it is of much broader applicability to computation with sparse tensors in

The price elasticity of electricity demand in South Australia

International Nuclear Information System (INIS)

Fan Shu; Hyndman, Rob J.

2011-01-01

In this paper, the price elasticity of electricity demand, representing the sensitivity of customer demand to the price of electricity, has been estimated for South Australia. We first undertake a review of the scholarly literature regarding electricity price elasticity for different regions and systems. Then we perform an empirical evaluation of the historic South Australian price elasticity, focussing on the relationship between price and demand quantiles at each half-hour of the day. This work attempts to determine whether there is any variation in price sensitivity with the time of day or quantile, and to estimate the form of any relationships that might exist in South Australia. - Highlights: → We review the scholarly literature on electricity own-price elasticity for different regions and systems. → We use annual log-linear econometric models of the electricity demand to estimate the historic South Australian price elasticity. → We focus on the relationship between price and demand quantiles at each half-hour of the day. → The overall price elasticity in South Australia ranges from -0.363 to -0.428.

Linear Algebra and Smarandache Linear Algebra

OpenAIRE

Vasantha, Kandasamy

2003-01-01

The present book, on Smarandache linear algebra, not only studies the Smarandache analogues of linear algebra and its applications, it also aims to bridge the need for new research topics pertaining to linear algebra, purely in the algebraic sense. We have introduced Smarandache semilinear algebra, Smarandache bilinear algebra and Smarandache anti-linear algebra and their fuzzy equivalents. Moreover, in this book, we have brought out the study of linear algebra and vector spaces over finite p...

The Parkinsonian Subthalamic Network: Measures of Power, Linear, and Non-linear Synchronization and their Relationship to L-DOPA Treatment and OFF State Motor Severity.

Science.gov (United States)

West, Timothy; Farmer, Simon; Berthouze, Luc; Jha, Ashwani; Beudel, Martijn; Foltynie, Thomas; Limousin, Patricia; Zrinzo, Ludvic; Brown, Peter; Litvak, Vladimir

2016-01-01

In this paper we investigated the dopaminergic modulation of neuronal interactions occurring in the subthalamic nucleus (STN) during Parkinson's disease (PD). We utilized linear measures of local and long range synchrony such as power and coherence, as well as Detrended Fluctuation Analysis for Phase Synchrony (DFA-PS)- a recently developed non-linear method that computes the extent of long tailed autocorrelations present in the phase interactions between two coupled signals. Through analysis of local field potentials (LFPs) taken from the STN we seek to determine changes in the neurodynamics that may underpin the pathophysiology of PD in a group of 12 patients who had undergone surgery for deep brain stimulation. We demonstrate up modulation of alpha-theta (5-12 Hz) band power in response to L-DOPA treatment, whilst low beta band power (15-20 Hz) band-power is suppressed. We also find evidence for significant local connectivity within the region surrounding STN although there was evidence for its modulation via administration of L-DOPA. Further to this we present evidence for a positive correlation between the phase ordering of bilateral STN interactions and the severity of bradykinetic and rigidity symptoms in PD. Although, the ability of non-linear measures to predict clinical state did not exceed standard measures such as beta power, these measures may help identify the connections which play a role in pathological dynamics.

Orosensory responsiveness and alcohol behaviour.

Science.gov (United States)

Thibodeau, Margaret; Bajec, Martha; Pickering, Gary

2017-08-01

Consumption of alcoholic beverages is widespread through much of the world, and significantly impacts human health and well-being. We sought to determine the contribution of orosensation ('taste') to several alcohol intake measures by examining general responsiveness to taste and somatosensory stimuli in a convenience sample of 435 adults recruited from six cohorts. Each cohort was divided into quantiles based on their responsiveness to sweet, sour, bitter, salty, umami, metallic, and astringent stimuli, and the resulting quantiles pooled for analysis (Kruskal-Wallis ANOVA). Responsiveness to bitter and astringent stimuli was associated in a non-linear fashion with intake of all alcoholic beverage types, with the highest consumption observed in middle quantiles. Sourness responsiveness tended to be inversely associated with all measures of alcohol consumption. Regardless of sensation, the most responsive quantiles tended to drink less, although sweetness showed little relationship between responsiveness and intake. For wine, increased umami and metallic responsiveness tended to predict lower total consumption and frequency. A limited examination of individuals who abstain from all alcohol indicated a tendency toward higher responsiveness than alcohol consumers to sweetness, sourness, bitterness, and saltiness (biserial correlation), suggesting that broadly-tuned orosensory responsiveness may be protective against alcohol use and possibly misuse. Overall, these findings confirm the importance of orosensory responsiveness in mediating consumption of alcohol, and indicate areas for further research. Copyright © 2017. Published by Elsevier Inc.

Magnetic shielding for coreless linear permanent magnet motors

NARCIS (Netherlands)

Pluk, K.J.W.; Jansen, J.W.; Lomonova, E.

2013-01-01

This paper concerns the local reduction of the magnetic flux density by means of magnetic shielding. Using a spatial frequency description, a 2-D semi-analytical periodic model is obtained for a coreless single-sided linear permanent magnet motor. The magnetic shield is included in the modeling

Deformation theory and local-global compatibility of Langlands correspondences

CERN Document Server

Luu, Martin

2015-01-01

The deformation theory of automorphic representations is used to study local properties of Galois representations associated to automorphic representations of general linear groups and symplectic groups. In some cases this allows to identify the local Galois representations with representations predicted by a local Langlands correspondence.

Supervised linear dimensionality reduction with robust margins for object recognition

Science.gov (United States)

Dornaika, F.; Assoum, A.

2013-01-01

Linear Dimensionality Reduction (LDR) techniques have been increasingly important in computer vision and pattern recognition since they permit a relatively simple mapping of data onto a lower dimensional subspace, leading to simple and computationally efficient classification strategies. Recently, many linear discriminant methods have been developed in order to reduce the dimensionality of visual data and to enhance the discrimination between different groups or classes. Many existing linear embedding techniques relied on the use of local margins in order to get a good discrimination performance. However, dealing with outliers and within-class diversity has not been addressed by margin-based embedding method. In this paper, we explored the use of different margin-based linear embedding methods. More precisely, we propose to use the concepts of Median miss and Median hit for building robust margin-based criteria. Based on such margins, we seek the projection directions (linear embedding) such that the sum of local margins is maximized. Our proposed approach has been applied to the problem of appearance-based face recognition. Experiments performed on four public face databases show that the proposed approach can give better generalization performance than the classic Average Neighborhood Margin Maximization (ANMM). Moreover, thanks to the use of robust margins, the proposed method down-grades gracefully when label outliers contaminate the training data set. In particular, we show that the concept of Median hit was crucial in order to get robust performance in the presence of outliers.

A gauge model describing N relativistic particles bound by linear forces

International Nuclear Information System (INIS)

Filippov, A.T.

1988-01-01

A relativistic model of N particles bound by linear forces is obtained by applying the gauging procedure to the linear canonical symmteries of a simple (rudimentary) nonrelativistic N-particle Lagrangian extended to relativistic phase space. The new (gauged) Lagrangian is formally Poincare invariant, the Hamiltonian is a linear combination of first-class constraints which are closed with respect to Pisson brackets and generate the localized canonical symmteries. The gauge potentials appear as the Lagrange multipliers of the constraints. Gauge fixing and quantization of the model are also briefly discussed. 11 refs

Longitudinally Vibrating Elastic Rods with Locally and Non-Locally Reacting Viscous Dampers

Directory of Open Access Journals (Sweden)

Şefaatdin Yüksel

2005-01-01

Full Text Available Eigencharacteristics of a longitudinally vibrating elastic rod with locally and non-locally reacting damping are analyzed. The rod is considered as a continuous system and complex eigenfrequencies are determined as solution of a characteristic equation. The variation of the damping ratios with respect to damper locations and damping coefficients for the first four eigenfrequencies are obtained. It is shown that at any mode of locally or non-locally damped elastic rod, the variation of damping ratio with damper location is linearly proportional to absolute value of the mode shape of undamped system. It is seen that the increasing damping coefficient does not always increase the damping ratio and there are optimal values for the damping ratio. Optimal values for external damping coefficients of viscous dampers and locations of the dampers are presented.

Reduction of Linear Programming to Linear Approximation

OpenAIRE

Vaserstein, Leonid N.

2006-01-01

It is well known that every Chebyshev linear approximation problem can be reduced to a linear program. In this paper we show that conversely every linear program can be reduced to a Chebyshev linear approximation problem.

Sparse PDF maps for non-linear multi-resolution image operations

KAUST Repository

Hadwiger, Markus

2012-11-01

We introduce a new type of multi-resolution image pyramid for high-resolution images called sparse pdf maps (sPDF-maps). Each pyramid level consists of a sparse encoding of continuous probability density functions (pdfs) of pixel neighborhoods in the original image. The encoded pdfs enable the accurate computation of non-linear image operations directly in any pyramid level with proper pre-filtering for anti-aliasing, without accessing higher or lower resolutions. The sparsity of sPDF-maps makes them feasible for gigapixel images, while enabling direct evaluation of a variety of non-linear operators from the same representation. We illustrate this versatility for antialiased color mapping, O(n) local Laplacian filters, smoothed local histogram filters (e.g., median or mode filters), and bilateral filters. © 2012 ACM.

Statistical analysis of yearly series of maximum daily rainfall in Spain. Analisis estadistico de las series anuales de maximas lluvias diarias en Espaa

Energy Technology Data Exchange (ETDEWEB)

Ferrer Polo, J.; Ardiles Lopez, K. L. (CEDEX, Ministerio de Obras Publicas, Transportes y Medio ambiente, Madrid (Spain))

1994-01-01

Work on the statistical modelling of maximum daily rainfalls is presented, with a view to estimating the quantiles for different return periods. An index flood approach has been adopted in which the local quantiles are a result of rescaling a regional law using the mean of each series of values, that is utilized as a local scale factor. The annual maximum series have been taken from 1.545 meteorological stations over a 30 year period, and these have been classified into 26 regions defined according to meteorological criteria, the homogeneity of wich has been checked by means of a statistical analysis of the coefficients of variation of the samples,using the. An estimation has been made of the parameters for the following four distribution models: Two Component Extreme Value (TCEV); General Extreme Value (GEV); Log-Pearson III (LP3); and SQRT-Exponential Type Distribution of Maximum. The analysis of the quantiles obtained reveals slight differences in the results thus detracting from the importance of the model selection. The last of the above-mentioned distribution has been finally chosen, on the basis of the following: it is defined with fewer parameters it is the only that was proposed specifically for the analysis of daily rainfall maximums; it yields more conservative results than the traditional Gumbel distribution for the high return periods; and it is capable of providing a good description of the main sampling statistics concerning the right-hand tail of the distribution, a fact that has been checked with Montecarlo's simulation techniques. The choice of a distribution model with only two parameters has led to the selection of the regional coefficient of variation as the only determining parameter for the regional quantiles. This has permitted the elimination of the quantiles discontinuity of the classical regional approach, thus smoothing the values of that coefficient by means of an isoline plan on a national scale.

Direct energy rebound effect for road passenger transport in China: A dynamic panel quantile regression approach

International Nuclear Information System (INIS)

Zhang, Yue-Jun; Peng, Hua-Rong; Liu, Zhao; Tan, Weiping

2015-01-01

The transport sector appears a main energy consumer in China and plays a significant role in energy conservation. Improving energy efficiency proves an effective way to reduce energy consumption in transport sector, whereas its effectiveness may be affected by the rebound effect. This paper proposes a dynamic panel quantile regression model to estimate the direct energy rebound effect for road passenger transport in the whole country, eastern, central and western China, respectively, based on the data of 30 provinces from 2003 to 2012. The empirical results reveal that, first of all, the direct rebound effect does exist for road passenger transport and on the whole country, the short-term and long-term direct rebound effects are 25.53% and 26.56% on average, respectively. Second, the direct rebound effect for road passenger transport in central and eastern China tends to decrease, increase and then decrease again, whereas that in western China decreases and then increases, with the increasing passenger kilometers. Finally, when implementing energy efficiency policy in road passenger transport sector, the effectiveness of energy conservation in western China proves much better than that in central China overall, while the effectiveness in central China is relatively better than that in eastern China. - Highlights: • The direct rebound effect (RE) for road passenger transport in China is estimated. • The direct RE in the whole country, eastern, central, and western China is analyzed. • The short and long-term direct REs are 25.53% and 26.56% within the sample period. • Western China has better energy-saving performance than central and eastern China.

Linear zonal atmospheric prediction for adaptive optics

Science.gov (United States)

McGuire, Patrick C.; Rhoadarmer, Troy A.; Coy, Hanna A.; Angel, J. Roger P.; Lloyd-Hart, Michael

2000-07-01

We compare linear zonal predictors of atmospheric turbulence for adaptive optics. Zonal prediction has the possible advantage of being able to interpret and utilize wind-velocity information from the wavefront sensor better than modal prediction. For simulated open-loop atmospheric data for a 2- meter 16-subaperture AO telescope with 5 millisecond prediction and a lookback of 4 slope-vectors, we find that Widrow-Hoff Delta-Rule training of linear nets and Back- Propagation training of non-linear multilayer neural networks is quite slow, getting stuck on plateaus or in local minima. Recursive Least Squares training of linear predictors is two orders of magnitude faster and it also converges to the solution with global minimum error. We have successfully implemented Amari's Adaptive Natural Gradient Learning (ANGL) technique for a linear zonal predictor, which premultiplies the Delta-Rule gradients with a matrix that orthogonalizes the parameter space and speeds up the training by two orders of magnitude, like the Recursive Least Squares predictor. This shows that the simple Widrow-Hoff Delta-Rule's slow convergence is not a fluke. In the case of bright guidestars, the ANGL, RLS, and standard matrix-inversion least-squares (MILS) algorithms all converge to the same global minimum linear total phase error (approximately 0.18 rad2), which is only approximately 5% higher than the spatial phase error (approximately 0.17 rad2), and is approximately 33% lower than the total 'naive' phase error without prediction (approximately 0.27 rad2). ANGL can, in principle, also be extended to make non-linear neural network training feasible for these large networks, with the potential to lower the predictor error below the linear predictor error. We will soon scale our linear work to the approximately 108-subaperture MMT AO system, both with simulations and real wavefront sensor data from prime focus.

Trends of VOC exposures among a nationally representative sample: Analysis of the NHANES 1988 through 2004 data sets

Science.gov (United States)

Su, Feng-Chiao; Mukherjee, Bhramar; Batterman, Stuart

2011-09-01

Exposures to volatile organic compounds (VOCs) are ubiquitous due to emissions from personal, commercial and industrial products, but quantitative and representative information regarding long term exposure trends is lacking. This study characterizes trends from 1988 to 2004 for the 15 VOCs measured in blood in five cohorts of the National Health and Nutrition Examination Survey (NHANES), a large and representative sample of U.S. adults. Trends were evaluated at various percentiles using linear quantile regression (QR) models, which were adjusted for solvent-related occupations and cotinine levels. Most VOCs showed decreasing trends at all quantiles, e.g., median exposures declined by 2.5 (m,p-xylene) to 6.4 (tetrachloroethene) percent per year over the 15 year period. Trends varied by VOC and quantile, and were grouped into three patterns: similar decreases at all quantiles (including benzene, toluene); most rapid decreases at upper quantiles (ethylbenzene, m,p-xylene, o-xylene, styrene, chloroform, tetrachloroethene); and fastest declines at central quantiles (1,4-dichlorobenzene). These patterns reflect changes in exposure sources, e.g., upper-percentile exposures may result mostly from occupational exposure, while lower percentile exposures arise from general environmental sources. Both VOC emissions aggregated at the national level and VOC concentrations measured in ambient air also have declined substantially over the study period and are supportive of the exposure trends, although the NHANES data suggest the importance of indoor sources and personal activities on VOC exposures. While piecewise QR models suggest that exposures of several VOCs decreased little or any during the 1990's, followed by more rapid decreases from 1999 to 2004, questions are raised concerning the reliability of VOC data in several of the NHANES cohorts and its applicability as an exposure indicator, as demonstrated by the modest correlation between VOC levels in blood and personal air

Incidence of childhood linear scleroderma and systemic sclerosis in the UK and Ireland.

Science.gov (United States)

Herrick, Ariane L; Ennis, Holly; Bhushan, Monica; Silman, Alan J; Baildam, Eileen M

2010-02-01

Childhood scleroderma encompasses a rare, poorly understood spectrum of conditions. Our aim was to ascertain the incidence of childhood scleroderma in its different forms in the UK and Ireland, and to describe the age, sex, and ethnicity of the cases. The members of 5 specialist medical associations including pediatricians, dermatologists, and rheumatologists were asked to report all cases of abnormal skin thickening suspected to be localized (including linear) scleroderma or systemic sclerosis (SSc) in children scleroderma and 7 (7%) with SSc. This gave an incidence rate per million children per year of 3.4 (95% confidence interval [95% CI] 2.7-4.1) for localized scleroderma, including an incidence rate of 2.5 (95% CI 1.8-3.1) for linear scleroderma, and 0.27 (95% CI 0.1-0.5) for SSc. Of the 87 localized cases, 62 (71%) had linear disease. Of localized disease cases, 55 (63%) were female, 71 (82%) were classified as white British, and the patients' mean age when first seen in secondary care was 10.4 years. Of the 7 SSc cases, all were female, 6 (86%) were white British, and the mean age when first seen was 12.1 years. The median delay between onset and being first seen was 13.1 months for localized scleroderma and 7.2 months for SSc. These data provide additional estimates of the incidence of this rare disorder and its subforms.

Linear study and bundle adjustment data fusion; Application to vision localization

International Nuclear Information System (INIS)

Michot, J.

2010-01-01

The works presented in this manuscript are in the field of computer vision, and tackle the problem of real-time vision based localization and 3D reconstruction. In this context, the trajectory of a camera and the 3D structure of the filmed scene are initially estimated by linear algorithms and then optimized by a nonlinear algorithm, bundle adjustment. The thesis first presents a new technique of line search, dedicated to the nonlinear minimization algorithms used in Structure-from-Motion. The proposed technique is not iterative and can be quickly installed in traditional bundle adjustment frameworks. This technique, called Global Algebraic Line Search (G-ALS), and its two-dimensional variant (Two way-ALS), accelerate the convergence of the bundle adjustment algorithm. The approximation of the re-projection error by an algebraic distance enables the analytical calculation of an effective displacement amplitude (or two amplitudes for the Two way-ALS variant) by solving a degree 3 (G-ALS) or 5 (Two way-ALS) polynomial. Our experiments, conducted on simulated and real data, show that this amplitude, which is optimal for the algebraic distance, is also efficient for the Euclidean distance and reduces the convergence time of minimizations. One difficulty of real-time tracking algorithms (monocular SLAM) is that the estimated trajectory is often affected by drifts: on the absolute orientation, position and scale. Since these algorithms are incremental, errors and approximations are accumulated throughout the trajectory and cause global drifts. In addition, a tracking vision system can always be dazzled or used under conditions which prevented temporarily to calculate the location of the system. To solve these problems, we propose to use an additional sensor measuring the displacement of the camera. The type of sensor used will vary depending on the targeted application (an odometer for a vehicle, a lightweight inertial navigation system for a person). We propose to

Non-linear realization of α0 -extended supersymmetry

International Nuclear Information System (INIS)

Nishino, Hitoshi

2000-01-01

As generalizations of the original Volkov-Akulov action in four-dimensions, actions are found for all space-time dimensions D invariant under N non-linear realized global supersymmetries. We also give other such actions invariant under the global non-linear supersymmetry. As an interesting consequence, we find a non-linear supersymmetric Born-Infeld action for a non-Abelian gauge group for arbitrary D and N , which coincides with the linearly supersymmetric Born-Infeld action in D=10 at the lowest order. For the gauge group U(N) for M(atrix)-theory, this model has N 2 -extended non-linear supersymmetries, so that its large N limit corresponds to the infinitely many (α 0 ) supersymmetries. We also perform a duality transformation from F μν into its Hodge dual N μ 1 ctdot μD-2 . We next point out that any Chern-Simons action for any (super)groups has the non-linear supersymmetry as a hidden symmetry. Subsequently, we present a superspace formulation for the component results. We further find that as long as superspace supergravity is consistent, this generalized Volkov-Akulov action can further accommodate such curved superspace backgrounds with local supersymmetry, as a super p -brane action with fermionic kappa-symmetry. We further elaborate these results to what we call 'simplified' (Supersymmetry) 2 -models, with both linear and non-linear representations of supersymmetries in superspace at the same time. Our result gives a proof that there is no restriction on D or N for global non-linear supersymmetry. We also see that the non-linear realization of supersymmetry in 'curved' space-time can be interpreted as 'non-perturbative' effect starting with the 'flat' space-time

Hypocoercivity for linear kinetic equations conserving mass

KAUST Repository

Dolbeault, Jean; Mouhot, Clé ment; Schmeiser, Christian

2015-01-01

We develop a new method for proving hypocoercivity for a large class of linear kinetic equations with only one conservation law. Local mass conservation is assumed at the level of the collision kernel, while transport involves a confining potential, so that the solution relaxes towards a unique equilibrium state. Our goal is to evaluate in an appropriately weighted $ L^2$ norm the exponential rate of convergence to the equilibrium. The method covers various models, ranging from diffusive kinetic equations like Vlasov-Fokker-Planck equations, to scattering models or models with time relaxation collision kernels corresponding to polytropic Gibbs equilibria, including the case of the linear Boltzmann model. In this last case and in the case of Vlasov-Fokker-Planck equations, any linear or superlinear growth of the potential is allowed. - See more at: http://www.ams.org/journals/tran/2015-367-06/S0002-9947-2015-06012-7/#sthash.ChjyK6rc.dpuf

Hypocoercivity for linear kinetic equations conserving mass

KAUST Repository

Dolbeault, Jean

2015-02-03

We develop a new method for proving hypocoercivity for a large class of linear kinetic equations with only one conservation law. Local mass conservation is assumed at the level of the collision kernel, while transport involves a confining potential, so that the solution relaxes towards a unique equilibrium state. Our goal is to evaluate in an appropriately weighted $ L^2$ norm the exponential rate of convergence to the equilibrium. The method covers various models, ranging from diffusive kinetic equations like Vlasov-Fokker-Planck equations, to scattering models or models with time relaxation collision kernels corresponding to polytropic Gibbs equilibria, including the case of the linear Boltzmann model. In this last case and in the case of Vlasov-Fokker-Planck equations, any linear or superlinear growth of the potential is allowed. - See more at: http://www.ams.org/journals/tran/2015-367-06/S0002-9947-2015-06012-7/#sthash.ChjyK6rc.dpuf

Testing of camera performance standards at steady and local overloading

International Nuclear Information System (INIS)

Keszthelyine Landori, S.; Adorjanne Farkas, M.; Csirik, J.

1983-01-01

Camera performance standards are usually given for low count rates and uniform irradiation. A conventional analog gamma camera system (Gamma MB 9100 manufactured under the know-how of Picker DC 4/12 in Hungary) was studied on the basis of the Picker test procedure and the NEMA standard system. Uniformity, linearity, spatial and energy resolution were measured at high count rates and uniform irradiation (steady overloading). Linearity was studied at local overloading. Linearity, spatial and energy resolution were measured by a 1024-channel analyzer-computer system of KFKI, Hungary. The data were evaluated on the basis of NEMA standards, while uniformity was measured by the Gamma data processing system and evaluated by special SEGAMS programs. Performance variations were studied between 7500 cps and 75.000 cps pulse rates. Spatial and energy resolution were influenced strongly, uniformity slightly by pulse rates, while linearity did not change at all. Linearity was not influenced even by local overloading. (author)

A spline-based non-linear diffeomorphism for multimodal prostate registration.

Science.gov (United States)

Mitra, Jhimli; Kato, Zoltan; Martí, Robert; Oliver, Arnau; Lladó, Xavier; Sidibé, Désiré; Ghose, Soumya; Vilanova, Joan C; Comet, Josep; Meriaudeau, Fabrice

2012-08-01

This paper presents a novel method for non-rigid registration of transrectal ultrasound and magnetic resonance prostate images based on a non-linear regularized framework of point correspondences obtained from a statistical measure of shape-contexts. The segmented prostate shapes are represented by shape-contexts and the Bhattacharyya distance between the shape representations is used to find the point correspondences between the 2D fixed and moving images. The registration method involves parametric estimation of the non-linear diffeomorphism between the multimodal images and has its basis in solving a set of non-linear equations of thin-plate splines. The solution is obtained as the least-squares solution of an over-determined system of non-linear equations constructed by integrating a set of non-linear functions over the fixed and moving images. However, this may not result in clinically acceptable transformations of the anatomical targets. Therefore, the regularized bending energy of the thin-plate splines along with the localization error of established correspondences should be included in the system of equations. The registration accuracies of the proposed method are evaluated in 20 pairs of prostate mid-gland ultrasound and magnetic resonance images. The results obtained in terms of Dice similarity coefficient show an average of 0.980±0.004, average 95% Hausdorff distance of 1.63±0.48 mm and mean target registration and target localization errors of 1.60±1.17 mm and 0.15±0.12 mm respectively. Copyright © 2012 Elsevier B.V. All rights reserved.

Nonlinearity measure and internal model control based linearization in anti-windup design

Energy Technology Data Exchange (ETDEWEB)

Perev, Kamen [Systems and Control Department, Technical University of Sofia, 8 Cl. Ohridski Blvd., 1756 Sofia (Bulgaria)

2013-12-18

This paper considers the problem of internal model control based linearization in anti-windup design. The nonlinearity measure concept is used for quantifying the control system degree of nonlinearity. The linearizing effect of a modified internal model control structure is presented by comparing the nonlinearity measures of the open-loop and closed-loop systems. It is shown that the linearization properties are improved by increasing the control system local feedback gain. However, it is emphasized that at the same time the stability of the system deteriorates. The conflicting goals of stability and linearization are resolved by solving the design problem in different frequency ranges.

Microscopic model for the non-linear fluctuating hydrodynamic of 4 He superfluid helium deduced by maximum entropy method

International Nuclear Information System (INIS)

Alvarez R, J.T.

1998-01-01

This thesis presents a microscopic model for the non-linear fluctuating hydrodynamic of superfluid helium ( 4 He), model developed by means of the Maximum Entropy Method (Maxent). In the chapter 1, it is demonstrated the necessity to developing a microscopic model for the fluctuating hydrodynamic of the superfluid helium, starting from to show a brief overview of the theories and experiments developed in order to explain the behavior of the superfluid helium. On the other hand, it is presented the Morozov heuristic method for the construction of the non-linear hydrodynamic fluctuating of simple fluid. Method that will be generalized for the construction of the non-linear fluctuating hydrodynamic of the superfluid helium. Besides, it is presented a brief summary of the content of the thesis. In the chapter 2, it is reproduced the construction of a Generalized Fokker-Planck equation, (GFP), for a distribution function associated with the coarse grained variables. Function defined with aid of a nonequilibrium statistical operator ρhut FP that is evaluated as Wigneris function through ρ CG obtained by Maxent. Later this equation of GFP is reduced to a non-linear local FP equation from considering a slow and Markov process in the coarse grained variables. In this equation appears a matrix D mn defined with a nonequilibrium coarse grained statistical operator ρhut CG , matrix elements are used in the construction of the non-linear fluctuating hydrodynamics equations of the superfluid helium. In the chapter 3, the Lagrange multipliers are evaluated for to determine ρhut CG by means of the local equilibrium statistical operator ρhut l -tilde with the hypothesis that the system presents small fluctuations. Also are determined the currents associated with the coarse grained variables and furthermore are evaluated the matrix elements D mn but with aid of a quasi equilibrium statistical operator ρhut qe instead of the local equilibrium operator ρhut l -tilde. Matrix

Time-dependent transport of a localized surface plasmon through a linear array of metal nanoparticles: Precursor and normal mode contributions

Science.gov (United States)

Compaijen, P. J.; Malyshev, V. A.; Knoester, J.

2018-02-01

We theoretically investigate the time-dependent transport of a localized surface plasmon excitation through a linear array of identical and equidistantly spaced metal nanoparticles. Two different signals propagating through the array are found: one traveling with the group velocity of the surface plasmon polaritons of the system and damped exponentially, and the other running with the speed of light and decaying in a power-law fashion, as x-1 and x-2 for the transversal and longitudinal polarizations, respectively. The latter resembles the Sommerfeld-Brillouin forerunner and has not been identified in previous studies. The contribution of this signal dominates the plasmon transport at large distances. In addition, even though this signal is spread in the propagation direction and has the lateral dimension larger than the wavelength, the field profile close to the chain axis does not change with distance, indicating that this part of the signal is confined to the array.

Biochemical methane potential prediction of plant biomasses: Comparing chemical composition versus near infrared methods and linear versus non-linear models.

Science.gov (United States)

Godin, Bruno; Mayer, Frédéric; Agneessens, Richard; Gerin, Patrick; Dardenne, Pierre; Delfosse, Philippe; Delcarte, Jérôme

2015-01-01

The reliability of different models to predict the biochemical methane potential (BMP) of various plant biomasses using a multispecies dataset was compared. The most reliable prediction models of the BMP were those based on the near infrared (NIR) spectrum compared to those based on the chemical composition. The NIR predictions of local (specific regression and non-linear) models were able to estimate quantitatively, rapidly, cheaply and easily the BMP. Such a model could be further used for biomethanation plant management and optimization. The predictions of non-linear models were more reliable compared to those of linear models. The presentation form (green-dried, silage-dried and silage-wet form) of biomasses to the NIR spectrometer did not influence the performances of the NIR prediction models. The accuracy of the BMP method should be improved to enhance further the BMP prediction models. Copyright © 2014 Elsevier Ltd. All rights reserved.

Air pollution and daily mortality in Erfurt, east Germany, 1980-1989.

Science.gov (United States)

Spix, C; Heinrich, J; Dockery, D; Schwartz, J; Völksch, G; Schwinkowski, K; Cöllen, C; Wichmann, H E

1993-11-01

In Erfurt, Germany, unfavorable geography and emissions from coal burning lead to very high ambient pollution (up to about 4000 micrograms/m3 SO2 in 1980-89). To assess possible health effects of these exposures, total daily mortality was obtained for this same period. A multivariate model was fitted, including corrections for long-term fluctuations, influenza epidemics, and meterology, before analyzing the effect of pollution. The best fit for pollution was obtained for log (SO2 daily mean) with a lag of 2 days. Daily mortality increased by 10% for an increase in SO2 from 23 to 929 micrograms/m3 (5% quantile to 95% quantile). A harvesting effect (fewer people die on a given day if more deaths occurred in the last 15 days) may modify this by +/- 2%. The effect for particulates (SP, 1988-89 only) was stronger than the effect of SO2. Log SP (daily mean) increasing from 15 micrograms/m3 to 331 micrograms/m3 (5% quantile to 95% quantile) was associated with a 22% increase in mortality. Depending on harvesting, the observable effect may lie between 14% and 27%. There is no indication of a threshold or synergism. The effects of air pollution are smaller than the effects of influenza epidemics and are of the same size as meterologic effects. The results for the lower end of the dose range are in agreement with linear models fitted in studies of moderate air pollution and episode studies.

Adaptive Kronrod-Patterson integration of non-linear finite-element matrices

DEFF Research Database (Denmark)

Janssen, Hans

2010-01-01

inappropriate discretization. In response, this article develops adaptive integration, based on nested Kronrod-Patterson-Gauss integration schemes: basically, the integration order is adapted to the locally observed grade of non-linearity. Adaptive integration is developed based on a standard infiltration...

MIDAS: Regionally linear multivariate discriminative statistical mapping.

Science.gov (United States)

Varol, Erdem; Sotiras, Aristeidis; Davatzikos, Christos

2018-07-01

Statistical parametric maps formed via voxel-wise mass-univariate tests, such as the general linear model, are commonly used to test hypotheses about regionally specific effects in neuroimaging cross-sectional studies where each subject is represented by a single image. Despite being informative, these techniques remain limited as they ignore multivariate relationships in the data. Most importantly, the commonly employed local Gaussian smoothing, which is important for accounting for registration errors and making the data follow Gaussian distributions, is usually chosen in an ad hoc fashion. Thus, it is often suboptimal for the task of detecting group differences and correlations with non-imaging variables. Information mapping techniques, such as searchlight, which use pattern classifiers to exploit multivariate information and obtain more powerful statistical maps, have become increasingly popular in recent years. However, existing methods may lead to important interpretation errors in practice (i.e., misidentifying a cluster as informative, or failing to detect truly informative voxels), while often being computationally expensive. To address these issues, we introduce a novel efficient multivariate statistical framework for cross-sectional studies, termed MIDAS, seeking highly sensitive and specific voxel-wise brain maps, while leveraging the power of regional discriminant analysis. In MIDAS, locally linear discriminative learning is applied to estimate the pattern that best discriminates between two groups, or predicts a variable of interest. This pattern is equivalent to local filtering by an optimal kernel whose coefficients are the weights of the linear discriminant. By composing information from all neighborhoods that contain a given voxel, MIDAS produces a statistic that collectively reflects the contribution of the voxel to the regional classifiers as well as the discriminative power of the classifiers. Critically, MIDAS efficiently assesses the

Perfect state transfer in unitary Cayley graphs over local rings

Directory of Open Access Journals (Sweden)

Yotsanan Meemark

2014-12-01

Full Text Available In this work, using eigenvalues and eigenvectors of unitary Cayley graphs over finite local rings and elementary linear algebra, we characterize which local rings allowing PST occurring in its unitary Cayley graph. Moreover, we have some developments when $R$ is a product of local rings.

Instrument for track linear element recognition

International Nuclear Information System (INIS)

Krupnov, V.E.; Fedotov, O.P.

1977-01-01

Described is the construction of instrument for recognizing linear elements of tracks. For designing this instrument use has been made of the algorithm for conversion of the point data into a set of linear elements. The flowsheet of the instrument shows its major units such as data converter, data representation register unit, local computers, interface with the central computer. The data representation register unit comprises sixteen registers and is capable of presenting data from sixteen lines when raster scanning of a picture taken from a track chamber. The maximum capacity of the code of the coordinate of a point recorded on a picture is up to 16 digits. The time of the inner operating cycle of the instrument is 1.3 μs. The average time required for processing data containing sixteen scanning lines is 250 μs

Canonical structure of evolution equations with non-linear ...

Indian Academy of Sciences (India)

The dispersion produced is compensated by non-linear effects resulting in the formation of exponentially localized .... determining the values of Lagrange's multipliers αis. We postulate that a slightly .... c3 «w2x -v. (36). To include the effect of the secondary constraint c3 in the total Hamiltonian H we modify. (33) as. 104.

Effect of threatening life experiences and adverse family relations in ulcerative colitis: analysis using structural equation modeling and comparison with Crohn's disease.

Science.gov (United States)

Slonim-Nevo, Vered; Sarid, Orly; Friger, Michael; Schwartz, Doron; Sergienko, Ruslan; Pereg, Avihu; Vardi, Hillel; Singer, Terri; Chernin, Elena; Greenberg, Dan; Odes, Shmuel

2017-05-01

We published that threatening life experiences and adverse family relations impact Crohn's disease (CD) adversely. In this study, we examine the influence of these stressors in ulcerative colitis (UC). Patients completed demography, economic status (ES), the Patient-Simple Clinical Colitis Activity Index (P-SCCAI), the Short Inflammatory Bowel Disease Questionnaire (SIBDQ), the Short-Form Health Survey (SF-36), the Brief Symptom Inventory (BSI), the Family Assessment Device (FAD), and the List of Threatening Life Experiences (LTE). Analysis included multiple linear and quantile regressions and structural equation modeling, comparing CD. UC patients (N=148, age 47.55±16.04 years, 50.6% women) had scores [median (interquartile range)] as follows: SCAAI, 2 (0.3-4.8); FAD, 1.8 (1.3-2.2); LTE, 1.0 (0-2.0); SF-36 Physical Health, 49.4 (36.8-55.1); SF-36 Mental Health, 45 (33.6-54.5); Brief Symptom Inventory-Global Severity Index (GSI), 0.5 (0.2-1.0). SIBDQ was 49.76±14.91. There were significant positive associations for LTE and SCAAI (25, 50, 75% quantiles), FAD and SF-36 Mental Health, FAD and LTE with GSI (50, 75, 90% quantiles), and ES with SF-36 and SIBDQ. The negative associations were as follows: LTE with SF-36 Physical/Mental Health, SIBDQ with FAD and LTE, ES with GSI (all quantiles), and P-SCCAI (75, 90% quantiles). In structural equation modeling analysis, LTE impacted ES negatively and ES impacted GSI negatively; LTE impacted GSI positively and GSI impacted P-SCCAI positively. In a split model, ES had a greater effect on GSI in UC than CD, whereas other path magnitudes were similar. Threatening life experiences, adverse family relations, and poor ES make UC patients less healthy both physically and mentally. The impact of ES is worse in UC than CD.

Local product structure for expansive homeomorphisms

OpenAIRE

Artigue, Alfonso; Brum, Joaquin; Potrie, Rafael

2008-01-01

Let $f\\colon M\\to M$ be an expansive homeomorphism with dense topologically hyperbolic periodic points, $M$ a compact manifold. Then there is a local product structure in an open and dense subset of $M$. Moreover, if some topologically hyperbolic periodic point has codimension one, then this local product structure is uniform. In particular, we conclude that the homeomorphism is conjugated to a linear Anosov diffeomorphism of a torus.

Linear-scaling implementation of the direct random-phase approximation

International Nuclear Information System (INIS)

Kállay, Mihály

2015-01-01

We report the linear-scaling implementation of the direct random-phase approximation (dRPA) for closed-shell molecular systems. As a bonus, linear-scaling algorithms are also presented for the second-order screened exchange extension of dRPA as well as for the second-order Møller–Plesset (MP2) method and its spin-scaled variants. Our approach is based on an incremental scheme which is an extension of our previous local correlation method [Rolik et al., J. Chem. Phys. 139, 094105 (2013)]. The approach extensively uses local natural orbitals to reduce the size of the molecular orbital basis of local correlation domains. In addition, we also demonstrate that using natural auxiliary functions [M. Kállay, J. Chem. Phys. 141, 244113 (2014)], the size of the auxiliary basis of the domains and thus that of the three-center Coulomb integral lists can be reduced by an order of magnitude, which results in significant savings in computation time. The new approach is validated by extensive test calculations for energies and energy differences. Our benchmark calculations also demonstrate that the new method enables dRPA calculations for molecules with more than 1000 atoms and 10 000 basis functions on a single processor

A non-differentiable solution for the local fractional telegraph equation

Directory of Open Access Journals (Sweden)

Li Jie

2017-01-01

Full Text Available In this paper, we consider the linear telegraph equations with local fractional derivative. The local fractional Laplace series expansion method is used to handle the local fractional telegraph equation. The analytical solution with the non-differentiable graphs is discussed in detail. The proposed method is efficient and accurate.

Finiteness of Ricci flat supersymmetric non-linear sigma-models

International Nuclear Information System (INIS)

Alvarez-Gaume, L.; Ginsparg, P.

1985-01-01

Combining the constraints of Kaehler differential geometry with the universality of the normal coordinate expansion in the background field method, we study the ultraviolet behavior of 2-dimensional supersymmetric non-linear sigma-models with target space an arbitrary riemannian manifold M. We show that the constraint of N=2 supersymmetry requires that all counterterms to the metric beyond one-loop order are cohomologically trivial. It follows that such supersymmetric non-linear sigma-models defined on locally symmetric spaces are super-renormalizable and that N=4 models are on-shell ultraviolet finite to all orders of perturbation theory. (orig.)

Linear versus non-linear supersymmetry, in general

Energy Technology Data Exchange (ETDEWEB)

Ferrara, Sergio [Theoretical Physics Department, CERN,CH-1211 Geneva 23 (Switzerland); INFN - Laboratori Nazionali di Frascati,Via Enrico Fermi 40, I-00044 Frascati (Italy); Department of Physics and Astronomy, UniversityC.L.A.,Los Angeles, CA 90095-1547 (United States); Kallosh, Renata [SITP and Department of Physics, Stanford University,Stanford, California 94305 (United States); Proeyen, Antoine Van [Institute for Theoretical Physics, Katholieke Universiteit Leuven,Celestijnenlaan 200D, B-3001 Leuven (Belgium); Wrase, Timm [Institute for Theoretical Physics, Technische Universität Wien,Wiedner Hauptstr. 8-10, A-1040 Vienna (Austria)

2016-04-12

We study superconformal and supergravity models with constrained superfields. The underlying version of such models with all unconstrained superfields and linearly realized supersymmetry is presented here, in addition to the physical multiplets there are Lagrange multiplier (LM) superfields. Once the equations of motion for the LM superfields are solved, some of the physical superfields become constrained. The linear supersymmetry of the original models becomes non-linearly realized, its exact form can be deduced from the original linear supersymmetry. Known examples of constrained superfields are shown to require the following LM’s: chiral superfields, linear superfields, general complex superfields, some of them are multiplets with a spin.

Linear versus non-linear supersymmetry, in general

International Nuclear Information System (INIS)

Ferrara, Sergio; Kallosh, Renata; Proeyen, Antoine Van; Wrase, Timm

2016-01-01

We study superconformal and supergravity models with constrained superfields. The underlying version of such models with all unconstrained superfields and linearly realized supersymmetry is presented here, in addition to the physical multiplets there are Lagrange multiplier (LM) superfields. Once the equations of motion for the LM superfields are solved, some of the physical superfields become constrained. The linear supersymmetry of the original models becomes non-linearly realized, its exact form can be deduced from the original linear supersymmetry. Known examples of constrained superfields are shown to require the following LM’s: chiral superfields, linear superfields, general complex superfields, some of them are multiplets with a spin.

Scattering of massless lumps and non-local charges in the two-dimensional classical non-linear sigma-model

International Nuclear Information System (INIS)

Luescher, M.; Pohlmeyer, K.

1977-09-01

Finite energy solutions of the field equations of the non-linear sigma-model are shown to decay asymptotically into massless lumps. By means of a linear eigenvalue problem connected with the field equations we then find an infinite set of dynamical conserved charges. They, however, do not provide sufficient information to decode the complicated scattering of lumps. (orig.) [de

The importance of Thermo-Hydro-Mechanical couplings and microstructure to strain localization in 3D continua with application to seismic faults. Part I: Theory and linear stability analysis

Science.gov (United States)

Rattez, Hadrien; Stefanou, Ioannis; Sulem, Jean

2018-06-01

A Thermo-Hydro-Mechanical (THM) model for Cosserat continua is developed to explore the influence of frictional heating and thermal pore fluid pressurization on the strain localization phenomenon. A general framework is presented to conduct a bifurcation analysis for elasto-plastic Cosserat continua with THM couplings and predict the onset of instability. The presence of internal lengths in Cosserat continua enables to estimate the thickness of the localization zone. This is done by performing a linear stability analysis of the system and looking for the selected wavelength corresponding to the instability mode with fastest finite growth coefficient. These concepts are applied to the study of fault zones under fast shearing. For doing so, we consider a model of a sheared saturated infinite granular layer. The influence of THM couplings on the bifurcation state and the shear band width is investigated. Taking representative parameters for a centroidal fault gouge, the evolution of the thickness of the localized zone under continuous shear is studied. Furthermore, the effect of grain crushing inside the shear band is explored by varying the internal length of the constitutive law.

Two types of physical inconsistency to avoid with quantile mapping: a case study with relative humidity over North America.

Science.gov (United States)

Grenier, P.

2017-12-01

Statistical post-processing techniques aim at generating plausible climate scenarios from climate simulations and observation-based reference products. These techniques are generally not physically-based, and consequently they remedy the problem of simulation biases at the risk of generating physical inconsistency (PI). Although this concern is often emphasized, it is rarely addressed quantitatively. Here, PI generated by quantile mapping (QM), a technique widely used in climatological and hydrological applications, is investigated using relative humidity (RH) and its parent variables, namely specific humidity (SH), temperature and pressure. PI is classified into two types: 1) inadequate value for an individual variable (e.g. RH > 100 %), and 2) breaking of an inter-variable relationship. Scenarios built for this study correspond to twelve sites representing a variety of climate types over North America. Data used are an ensemble of ten 3-hourly global (CMIP5) and regional (CORDEX-NAM) simulations, as well as the CFSR reanalysis. PI of type 1 is discussed in terms of frequency of occurrence and amplitude of unphysical cases for RH and SH variables. PI of type 2 is investigated with heuristic proxies designed to directly compare the physical inconsistency problem with the initial bias problem. Finally, recommendations are provided for an appropriate use of QM given the potential to generate physical inconsistency of types 1 and 2.

Reduced differential transform method for partial differential equations within local fractional derivative operators

Directory of Open Access Journals (Sweden)

Hossein Jafari

2016-04-01

Full Text Available The non-differentiable solution of the linear and non-linear partial differential equations on Cantor sets is implemented in this article. The reduced differential transform method is considered in the local fractional operator sense. The four illustrative examples are given to show the efficiency and accuracy features of the presented technique to solve local fractional partial differential equations.

Local p-Adic Differential Equations

NARCIS (Netherlands)

Put, Marius van der; Taelman, Lenny

2006-01-01

This paper studies divergence in solutions of p-adic linear local differential equations. Such divergence is related to the notion of p-adic Liouville numbers. Also, the influence of the divergence on the differential Galois groups of such differential equations is explored. A complete result is

Non-linear wave equations:Mathematical techniques

International Nuclear Information System (INIS)

1978-01-01

An account of certain well-established mathematical methods, which prove useful to deal with non-linear partial differential equations is presented. Within the strict framework of Functional Analysis, it describes Semigroup Techniques in Banach Spaces as well as variational approaches towards critical points. Detailed proofs are given of the existence of local and global solutions of the Cauchy problem and of the stability of stationary solutions. The formal approach based upon invariance under Lie transformations deserves attention due to its wide range of applicability, even if the explicit solutions thus obtained do not allow for a deep analysis of the equations. A compre ensive introduction to the inverse scattering approach and to the solution concept for certain non-linear equations of physical interest are also presented. A detailed discussion is made about certain convergence and stability problems which arise in importance need not be emphasized. (author) [es

Entanglement quantification by local unitary operations

Energy Technology Data Exchange (ETDEWEB)

Monras, A.; Giampaolo, S. M.; Gualdi, G.; Illuminati, F. [Dipartimento di Matematica e Informatica, Universita degli Studi di Salerno, CNISM, Unita di Salerno, and INFN, Sezione di Napoli-Gruppo Collegato di Salerno, Via Ponte don Melillo, I-84084 Fisciano (Italy); Adesso, G.; Davies, G. B. [School of Mathematical Sciences, University of Nottingham, University Park, Nottingham NG7 2RD (United Kingdom)

2011-07-15

Invariance under local unitary operations is a fundamental property that must be obeyed by every proper measure of quantum entanglement. However, this is not the only aspect of entanglement theory where local unitary operations play a relevant role. In the present work we show that the application of suitable local unitary operations defines a family of bipartite entanglement monotones, collectively referred to as ''mirror entanglement.'' They are constructed by first considering the (squared) Hilbert-Schmidt distance of the state from the set of states obtained by applying to it a given local unitary operator. To the action of each different local unitary operator there corresponds a different distance. We then minimize these distances over the sets of local unitary operations with different spectra, obtaining an entire family of different entanglement monotones. We show that these mirror-entanglement monotones are organized in a hierarchical structure, and we establish the conditions that need to be imposed on the spectrum of a local unitary operator for the associated mirror entanglement to be faithful, i.e., to vanish in and only in separable pure states. We analyze in detail the properties of one particularly relevant member of the family, the ''stellar mirror entanglement'' associated with the traceless local unitary operations with nondegenerate spectra and equispaced eigenvalues in the complex plane. This particular measure generalizes the original analysis of S. M. Giampaolo and F. Illuminati [Phys. Rev. A 76, 042301 (2007)], valid for qubits and qutrits. We prove that the stellar entanglement is a faithful bipartite entanglement monotone in any dimension and that it is bounded from below by a function proportional to the linear entropy and from above by the linear entropy itself, coinciding with it in two- and three-dimensional spaces.

Entanglement quantification by local unitary operations

Science.gov (United States)

Monras, A.; Adesso, G.; Giampaolo, S. M.; Gualdi, G.; Davies, G. B.; Illuminati, F.

2011-07-01

Invariance under local unitary operations is a fundamental property that must be obeyed by every proper measure of quantum entanglement. However, this is not the only aspect of entanglement theory where local unitary operations play a relevant role. In the present work we show that the application of suitable local unitary operations defines a family of bipartite entanglement monotones, collectively referred to as “mirror entanglement.” They are constructed by first considering the (squared) Hilbert-Schmidt distance of the state from the set of states obtained by applying to it a given local unitary operator. To the action of each different local unitary operator there corresponds a different distance. We then minimize these distances over the sets of local unitary operations with different spectra, obtaining an entire family of different entanglement monotones. We show that these mirror-entanglement monotones are organized in a hierarchical structure, and we establish the conditions that need to be imposed on the spectrum of a local unitary operator for the associated mirror entanglement to be faithful, i.e., to vanish in and only in separable pure states. We analyze in detail the properties of one particularly relevant member of the family, the “stellar mirror entanglement” associated with the traceless local unitary operations with nondegenerate spectra and equispaced eigenvalues in the complex plane. This particular measure generalizes the original analysis of S. M. Giampaolo and F. Illuminati [Phys. Rev. APLRAAN1050-294710.1103/PhysRevA.76.042301 76, 042301 (2007)], valid for qubits and qutrits. We prove that the stellar entanglement is a faithful bipartite entanglement monotone in any dimension and that it is bounded from below by a function proportional to the linear entropy and from above by the linear entropy itself, coinciding with it in two- and three-dimensional spaces.

Entanglement quantification by local unitary operations

International Nuclear Information System (INIS)

Monras, A.; Giampaolo, S. M.; Gualdi, G.; Illuminati, F.; Adesso, G.; Davies, G. B.

2011-01-01

Invariance under local unitary operations is a fundamental property that must be obeyed by every proper measure of quantum entanglement. However, this is not the only aspect of entanglement theory where local unitary operations play a relevant role. In the present work we show that the application of suitable local unitary operations defines a family of bipartite entanglement monotones, collectively referred to as ''mirror entanglement.'' They are constructed by first considering the (squared) Hilbert-Schmidt distance of the state from the set of states obtained by applying to it a given local unitary operator. To the action of each different local unitary operator there corresponds a different distance. We then minimize these distances over the sets of local unitary operations with different spectra, obtaining an entire family of different entanglement monotones. We show that these mirror-entanglement monotones are organized in a hierarchical structure, and we establish the conditions that need to be imposed on the spectrum of a local unitary operator for the associated mirror entanglement to be faithful, i.e., to vanish in and only in separable pure states. We analyze in detail the properties of one particularly relevant member of the family, the ''stellar mirror entanglement'' associated with the traceless local unitary operations with nondegenerate spectra and equispaced eigenvalues in the complex plane. This particular measure generalizes the original analysis of S. M. Giampaolo and F. Illuminati [Phys. Rev. A 76, 042301 (2007)], valid for qubits and qutrits. We prove that the stellar entanglement is a faithful bipartite entanglement monotone in any dimension and that it is bounded from below by a function proportional to the linear entropy and from above by the linear entropy itself, coinciding with it in two- and three-dimensional spaces.

Consensus for linear multi-agent system with intermittent information transmissions using the time-scale theory

Science.gov (United States)

Taousser, Fatima; Defoort, Michael; Djemai, Mohamed

2016-01-01

This paper investigates the consensus problem for linear multi-agent system with fixed communication topology in the presence of intermittent communication using the time-scale theory. Since each agent can only obtain relative local information intermittently, the proposed consensus algorithm is based on a discontinuous local interaction rule. The interaction among agents happens at a disjoint set of continuous-time intervals. The closed-loop multi-agent system can be represented using mixed linear continuous-time and linear discrete-time models due to intermittent information transmissions. The time-scale theory provides a powerful tool to combine continuous-time and discrete-time cases and study the consensus protocol under a unified framework. Using this theory, some conditions are derived to achieve exponential consensus under intermittent information transmissions. Simulations are performed to validate the theoretical results.

Application of linear and non-linear low-Re k-ε models in two-dimensional predictions of convective heat transfer in passages with sudden contractions

International Nuclear Information System (INIS)

Raisee, M.; Hejazi, S.H.

2007-01-01

This paper presents comparisons between heat transfer predictions and measurements for developing turbulent flow through straight rectangular channels with sudden contractions at the mid-channel section. The present numerical results were obtained using a two-dimensional finite-volume code which solves the governing equations in a vertical plane located at the lateral mid-point of the channel. The pressure field is obtained with the well-known SIMPLE algorithm. The hybrid scheme was employed for the discretization of convection in all transport equations. For modeling of the turbulence, a zonal low-Reynolds number k-ε model and the linear and non-linear low-Reynolds number k-ε models with the 'Yap' and 'NYP' length-scale correction terms have been employed. The main objective of present study is to examine the ability of the above turbulence models in the prediction of convective heat transfer in channels with sudden contraction at a mid-channel section. The results of this study show that a sudden contraction creates a relatively small recirculation bubble immediately downstream of the channel contraction. This separation bubble influences the distribution of local heat transfer coefficient and increases the heat transfer levels by a factor of three. Computational results indicate that all the turbulence models employed produce similar flow fields. The zonal k-ε model produces the wrong Nusselt number distribution by underpredicting heat transfer levels in the recirculation bubble and overpredicting them in the developing region. The linear low-Re k-ε model, on the other hand, returns the correct Nusselt number distribution in the recirculation region, although it somewhat overpredicts heat transfer levels in the developing region downstream of the separation bubble. The replacement of the 'Yap' term with the 'NYP' term in the linear low-Re k-ε model results in a more accurate local Nusselt number distribution. Moreover, the application of the non-linear k

The local structure of a Liouville vector field

International Nuclear Information System (INIS)

Ciriza, E.

1990-05-01

In this work we investigate the local structure of a Liouville vector field ξ of a Kaehler manifold (P,Ω) which vanishes on an isotropic submanifold Q of P. Some of the eigenvalues of its linear part at the singular points are zero and the remaining ones are in resonance. We show that there is a C 1 -smooth linearizing conjugation between the Liouville vector field ξ and its linear part. To do this we construct Darboux coordinates adapted to the unstable foliation which is provided by the Centre Manifold Theorem. We then apply recent linearization results due to G. Sell. (author). 11 refs

New results for exponential synchronization of linearly coupled ordinary differential systems

International Nuclear Information System (INIS)

Tong Ping; Chen Shi-Hua

2017-01-01

This paper investigates the exponential synchronization of linearly coupled ordinary differential systems. The intrinsic nonlinear dynamics may not satisfy the QUAD condition or weak-QUAD condition. First, it gives a new method to analyze the exponential synchronization of the systems. Second, two theorems and their corollaries are proposed for the local or global exponential synchronization of the coupled systems. Finally, an application to the linearly coupled Hopfield neural networks and several simulations are provided for verifying the effectiveness of the theoretical results. (paper)

Iterated non-linear model predictive control based on tubes and contractive constraints.

Science.gov (United States)

Murillo, M; Sánchez, G; Giovanini, L

2016-05-01

This paper presents a predictive control algorithm for non-linear systems based on successive linearizations of the non-linear dynamic around a given trajectory. A linear time varying model is obtained and the non-convex constrained optimization problem is transformed into a sequence of locally convex ones. The robustness of the proposed algorithm is addressed adding a convex contractive constraint. To account for linearization errors and to obtain more accurate results an inner iteration loop is added to the algorithm. A simple methodology to obtain an outer bounding-tube for state trajectories is also presented. The convergence of the iterative process and the stability of the closed-loop system are analyzed. The simulation results show the effectiveness of the proposed algorithm in controlling a quadcopter type unmanned aerial vehicle. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Management of vestibular schwannomas with linear accelerator-based stereotactic radiosurgery: a single center experience.

Science.gov (United States)

Sager, Omer; Beyzadeoglu, Murat; Dincoglan, Ferrat; Demiral, Selcuk; Uysal, Bora; Gamsiz, Hakan; Oysul, Kaan; Dirican, Bahar; Sirin, Sait

2013-01-01

The primary goal of treatment for vestibular schwannoma is to achieve local control without comprimising regional cranial nerve function. Stereotactic radiosurgery has emerged as a viable therapeutic option for vestibular schwannoma. The aim of the study is to report our 15-year single center experience using linear accelerator-based stereotactic radiosurgery in the management of patients with vestibular schwannoma. Between July 1998 and January 2013, 68 patients with unilateral vestibular schwannoma were treated using stereotactic radiosurgery at the Department of Radiation Oncology, Gulhane Military Medical Academy. All patients underwent high-precision stereotactic radiosurgery using a linear accelerator with 6-MV photons. Median follow-up time was 51 months (range, 9-107). Median age was 45 years (range, 20-77). Median dose was 12 Gy (range, 10-13) prescribed to the 85%-95% isodose line encompassing the target volume. Local tumor control in patients with periodic follow-up imaging was 96.1%. Overall hearing preservation rate was 76.5%. Linear accelerator-based stereotactic radiosurgery offers a safe and effective treatment for patients with vestibular schwannoma by providing high local control rates along with improved quality of life through well-preserved hearing function.

Non-linear simulations of ELMs in ASDEX upgrade

Energy Technology Data Exchange (ETDEWEB)

Lessig, Alexander; Hoelzl, Matthias; Orain, Francois; Guenter, Sibylle [Max-Planck-Institut fuer Plasmaphysik, Boltzmannstrasse 2, 85748 Garching (Germany); Becoulet, Marina; Huysmans, Guido [CEA-IRFM, Cadarache, 13108 Saint-Paul-Lez-Durance (France); Collaboration: the ASDEX Upgrade Team

2016-07-01

Large edge localized modes (ELMs) are a severe concern for the operation of future tokamak devices like ITER or DEMO due to the high transient heat loads induced on divertor targets and wall structures. It is therefore important to study ELMs both theoretically and experimentally in order to obtain a comprehensive understanding of the underlying mechanisms which is necessary for the prediction of ELM properties and the design of ELM mitigation systems. Using the non-linear MHD code JOREK, we have performed first simulations of full ELM crashes in ASDEX Upgrade, taking into account a large number of toroidal Fourier harmonics. The evolution of the toroidal mode spectrum has been investigated. In particular, we confirm the previously observed non-linear drive of linearly sub-dominant low-n components in the early non-linear phase of the ELM crash. Preliminary comparisons of the simulations with experimental observations regarding heat and particle losses, pedestal evolution and heat deposition patterns are shown. On the long run we aim at code validation as well as an improved understanding of the ELM dynamics and possibly a better characterization of different ELM types.

Foundations of linear and generalized linear models

CERN Document Server

Agresti, Alan

2015-01-01

A valuable overview of the most important ideas and results in statistical analysis Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linear statistical models. The book presents a broad, in-depth overview of the most commonly used statistical models by discussing the theory underlying the models, R software applications, and examples with crafted models to elucidate key ideas and promote practical model building. The book begins by illustrating the fundamentals of linear models,

STABLE STATIONARY STATES OF NON-LOCAL INTERACTION EQUATIONS

KAUST Repository

FELLNER, KLEMENS

2010-12-01

In this paper, we are interested in the large-time behaviour of a solution to a non-local interaction equation, where a density of particles/individuals evolves subject to an interaction potential and an external potential. It is known that for regular interaction potentials, stable stationary states of these equations are generically finite sums of Dirac masses. For a finite sum of Dirac masses, we give (i) a condition to be a stationary state, (ii) two necessary conditions of linear stability w.r.t. shifts and reallocations of individual Dirac masses, and (iii) show that these linear stability conditions imply local non-linear stability. Finally, we show that for regular repulsive interaction potential Wε converging to a singular repulsive interaction potential W, the Dirac-type stationary states ρ̄ ε approximate weakly a unique stationary state ρ̄ ∈ L∞. We illustrate our results with numerical examples. © 2010 World Scientific Publishing Company.

Nonlinear Modeling by Assembling Piecewise Linear Models

Science.gov (United States)

Yao, Weigang; Liou, Meng-Sing

2013-01-01

To preserve nonlinearity of a full order system over a parameters range of interest, we propose a simple modeling approach by assembling a set of piecewise local solutions, including the first-order Taylor series terms expanded about some sampling states. The work by Rewienski and White inspired our use of piecewise linear local solutions. The assembly of these local approximations is accomplished by assigning nonlinear weights, through radial basis functions in this study. The efficacy of the proposed procedure is validated for a two-dimensional airfoil moving at different Mach numbers and pitching motions, under which the flow exhibits prominent nonlinear behaviors. All results confirm that our nonlinear model is accurate and stable for predicting not only aerodynamic forces but also detailed flowfields. Moreover, the model is robustness-accurate for inputs considerably different from the base trajectory in form and magnitude. This modeling preserves nonlinearity of the problems considered in a rather simple and accurate manner.

Non-linear statistical downscaling of present and LGM precipitation and temperatures over Europe

Directory of Open Access Journals (Sweden)

M. Vrac

2007-12-01

Full Text Available Local-scale climate information is increasingly needed for the study of past, present and future climate changes. In this study we develop a non-linear statistical downscaling method to generate local temperatures and precipitation values from large-scale variables of a Earth System Model of Intermediate Complexity (here CLIMBER. Our statistical downscaling scheme is based on the concept of Generalized Additive Models (GAMs, capturing non-linearities via non-parametric techniques. Our GAMs are calibrated on the present Western Europe climate. For this region, annual GAMs (i.e. models based on 12 monthly values per location are fitted by combining two types of large-scale explanatory variables: geographical (e.g. topographical information and physical (i.e. entirely simulated by the CLIMBER model.

To evaluate the adequacy of the non-linear transfer functions fitted on the present Western European climate, they are applied to different spatial and temporal large-scale conditions. Local projections for present North America and Northern Europe climates are obtained and compared to local observations. This partially addresses the issue of spatial robustness of our transfer functions by answering the question "does our statistical model remain valid when applied to large-scale climate conditions from a region different from the one used for calibration?". To asses their temporal performances, local projections for the Last Glacial Maximum period are derived and compared to local reconstructions and General Circulation Model outputs.

Our downscaling methodology performs adequately for the Western Europe climate. Concerning the spatial and temporal evaluations, it does not behave as well for Northern America and Northern Europe climates because the calibration domain may be too different from the targeted regions. The physical explanatory variables alone are not capable of downscaling realistic values. However, the inclusion of

On the linear programming bound for linear Lee codes.

Science.gov (United States)

Astola, Helena; Tabus, Ioan

2016-01-01

Based on an invariance-type property of the Lee-compositions of a linear Lee code, additional equality constraints can be introduced to the linear programming problem of linear Lee codes. In this paper, we formulate this property in terms of an action of the multiplicative group of the field [Formula: see text] on the set of Lee-compositions. We show some useful properties of certain sums of Lee-numbers, which are the eigenvalues of the Lee association scheme, appearing in the linear programming problem of linear Lee codes. Using the additional equality constraints, we formulate the linear programming problem of linear Lee codes in a very compact form, leading to a fast execution, which allows to efficiently compute the bounds for large parameter values of the linear codes.

Linear-Optical Generation of Eigenstates of the Two-Site XY Model

Directory of Open Access Journals (Sweden)

Stefanie Barz

2015-04-01

Full Text Available Much of the anticipation accompanying the development of a quantum computer relates to its application to simulating dynamics of another quantum system of interest. Here, we study the building blocks for simulating quantum spin systems with linear optics. We experimentally generate the eigenstates of the XY Hamiltonian under an external magnetic field. The implemented quantum circuit consists of two cnot gates, which are realized experimentally by harnessing entanglement from a photon source and applying a cphase gate. We tune the ratio of coupling constants and the magnetic field by changing local parameters. This implementation of the XY model using linear quantum optics might open the door to future studies of quenching dynamics using linear optics.

Linear-algebraic approach to electron-molecule collisions: General formulation

International Nuclear Information System (INIS)

Collins, L.A.; Schneider, B.I.

1981-01-01

We present a linear-algebraic approach to electron-molecule collisions based on an integral equations form with either logarithmic or asymptotic boundary conditions. The introduction of exchange effects does not alter the basic form or order of the linear-algebraic equations for a local potential. In addition to the standard procedure of directly evaluating the exchange integrals by numerical quadrature, we also incorporate exchange effects through a separable-potential approximation. Efficient schemes are developed for reducing the number of points and channels that must be included. The method is applied at the static-exchange level to a number of molecular systems including H 2 , N 2 , LiH, and CO 2

Non-linear feedback neural networks VLSI implementations and applications

CERN Document Server

Ansari, Mohd Samar

2014-01-01

This book aims to present a viable alternative to the Hopfield Neural Network (HNN) model for analog computation. It is well known that the standard HNN suffers from problems of convergence to local minima, and requirement of a large number of neurons and synaptic weights. Therefore, improved solutions are needed. The non-linear synapse neural network (NoSyNN) is one such possibility and is discussed in detail in this book. This book also discusses the applications in computationally intensive tasks like graph coloring, ranking, and linear as well as quadratic programming. The material in the book is useful to students, researchers and academician working in the area of analog computation.

Dynamical heterogeneities and mechanical non-linearities: Modeling the onset of plasticity in polymer in the glass transition.

Science.gov (United States)

Masurel, R J; Gelineau, P; Lequeux, F; Cantournet, S; Montes, H

2017-12-27

In this paper we focus on the role of dynamical heterogeneities on the non-linear response of polymers in the glass transition domain. We start from a simple coarse-grained model that assumes a random distribution of the initial local relaxation times and that quantitatively describes the linear viscoelasticity of a polymer in the glass transition regime. We extend this model to non-linear mechanics assuming a local Eyring stress dependence of the relaxation times. Implementing the model in a finite element mechanics code, we derive the mechanical properties and the local mechanical fields at the beginning of the non-linear regime. The model predicts a narrowing of distribution of relaxation times and the storage of a part of the mechanical energy --internal stress-- transferred to the material during stretching in this temperature range. We show that the stress field is not spatially correlated under and after loading and follows a Gaussian distribution. In addition the strain field exhibits shear bands, but the strain distribution is narrow. Hence, most of the mechanical quantities can be calculated analytically, in a very good approximation, with the simple assumption that the strain rate is constant.

Linear bosonic and fermionic quantum gauge theories on curved spacetimes

International Nuclear Information System (INIS)

Hack, Thomas-Paul; Schenkel, Alexander

2012-05-01

We develop a general setting for the quantization of linear bosonic and fermionic field theories subject to local gauge invariance and show how standard examples such as linearized Yang-Mills theory and linearized general relativity fit into this framework. Our construction always leads to a well-defined and gauge-invariant quantum field algebra, the centre and representations of this algebra, however, have to be analysed on a case-by-case basis. We discuss an example of a fermionic gauge field theory where the necessary conditions for the existence of Hilbert space representations are not met on any spacetime. On the other hand, we prove that these conditions are met for the Rarita-Schwinger gauge field in linearized pure N=1 supergravity on certain spacetimes, including asymptotically flat spacetimes and classes of spacetimes with compact Cauchy surfaces. We also present an explicit example of a supergravity background on which the Rarita-Schwinger gauge field can not be consistently quantized.

Linear bosonic and fermionic quantum gauge theories on curved spacetimes

Energy Technology Data Exchange (ETDEWEB)

Hack, Thomas-Paul [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Schenkel, Alexander [Bergische Univ., Wuppertal (Germany). Fachgruppe Physik

2012-05-15

We develop a general setting for the quantization of linear bosonic and fermionic field theories subject to local gauge invariance and show how standard examples such as linearized Yang-Mills theory and linearized general relativity fit into this framework. Our construction always leads to a well-defined and gauge-invariant quantum field algebra, the centre and representations of this algebra, however, have to be analysed on a case-by-case basis. We discuss an example of a fermionic gauge field theory where the necessary conditions for the existence of Hilbert space representations are not met on any spacetime. On the other hand, we prove that these conditions are met for the Rarita-Schwinger gauge field in linearized pure N=1 supergravity on certain spacetimes, including asymptotically flat spacetimes and classes of spacetimes with compact Cauchy surfaces. We also present an explicit example of a supergravity background on which the Rarita-Schwinger gauge field can not be consistently quantized.

Costationarity of Locally Stationary Time Series Using costat

OpenAIRE

Cardinali, Alessandro; Nason, Guy P.

2013-01-01

This article describes the R package costat. This package enables a user to (i) perform a test for time series stationarity; (ii) compute and plot time-localized autocovariances, and (iii) to determine and explore any costationary relationship between two locally stationary time series. Two locally stationary time series are said to be costationary if there exists two time-varying combination functions such that the linear combination of the two series with the functions produces another time...

Detection and Localization of Random Signals

DEFF Research Database (Denmark)

Sporring, Jon; Olsen, Niels Holm; Nielsen, Mads

2003-01-01

filtering techniques. It is therefore interesting to extend the application to objects with many but small degrees of freedom in their geometry. These geometric variations deteriorate the linear correlation signal, both regarding its strength and localization with multiple peaks from a single object...

Linear-scaling quantum mechanical methods for excited states.

Science.gov (United States)

Yam, ChiYung; Zhang, Qing; Wang, Fan; Chen, GuanHua

2012-05-21

The poor scaling of many existing quantum mechanical methods with respect to the system size hinders their applications to large systems. In this tutorial review, we focus on latest research on linear-scaling or O(N) quantum mechanical methods for excited states. Based on the locality of quantum mechanical systems, O(N) quantum mechanical methods for excited states are comprised of two categories, the time-domain and frequency-domain methods. The former solves the dynamics of the electronic systems in real time while the latter involves direct evaluation of electronic response in the frequency-domain. The localized density matrix (LDM) method is the first and most mature linear-scaling quantum mechanical method for excited states. It has been implemented in time- and frequency-domains. The O(N) time-domain methods also include the approach that solves the time-dependent Kohn-Sham (TDKS) equation using the non-orthogonal localized molecular orbitals (NOLMOs). Besides the frequency-domain LDM method, other O(N) frequency-domain methods have been proposed and implemented at the first-principles level. Except one-dimensional or quasi-one-dimensional systems, the O(N) frequency-domain methods are often not applicable to resonant responses because of the convergence problem. For linear response, the most efficient O(N) first-principles method is found to be the LDM method with Chebyshev expansion for time integration. For off-resonant response (including nonlinear properties) at a specific frequency, the frequency-domain methods with iterative solvers are quite efficient and thus practical. For nonlinear response, both on-resonance and off-resonance, the time-domain methods can be used, however, as the time-domain first-principles methods are quite expensive, time-domain O(N) semi-empirical methods are often the practical choice. Compared to the O(N) frequency-domain methods, the O(N) time-domain methods for excited states are much more mature and numerically stable, and

Linear algebra

CERN Document Server

Shilov, Georgi E

1977-01-01

Covers determinants, linear spaces, systems of linear equations, linear functions of a vector argument, coordinate transformations, the canonical form of the matrix of a linear operator, bilinear and quadratic forms, Euclidean spaces, unitary spaces, quadratic forms in Euclidean and unitary spaces, finite-dimensional space. Problems with hints and answers.

Fiber optic configurations for local area networks

Science.gov (United States)

Nassehi, M. M.; Tobagi, F. A.; Marhic, M. E.

1985-01-01

A number of fiber optic configurations for a new class of demand assignment multiple-access local area networks requiring a physical ordering among stations are proposed. In such networks, the data transmission and linear-ordering functions may be distinguished and be provided by separate data and control subnetworks. The configurations proposed for the data subnetwork are based on the linear, star, and tree topologies. To provide the linear-ordering function, the control subnetwork must always have a linear unidirectional bus structure. Due to the reciprocity and excess loss of optical couplers, the number of stations that can be accommodated on a linear fiber optic bus is severely limited. Two techniques are proposed to overcome this limitation. For each of the data and control subnetwork configurations, the maximum number of stations as a function of the power margin, for both reciprocal and nonreciprocal couplers, is computed.

Linearized supergravity with a dynamical preferred frame

CERN Document Server

Marakulin, Arthur

2016-01-01

We study supersymmetric extension of the Einstein-aether gravitational model where local Lorentz invariance is broken down to the subgroup of spatial rotations by a vacuum expectation value of a timelike vector field. By restricting to the level of linear perturbations around Lorentz-violating vacuum and using the superfield formalism we construct the most general action invariant under the linearized supergravity transformations. We show that, unlike its non-supersymmetric counterpart, the model contains only a single free dimensionless parameter, besides the usual dimensionful gravitational coupling. This makes the model highly predictive. An analysis of the spectrum of physical excitations reveal superluminal velocity of gravitons. The latter property leads to the extension of the gravitational multiplet by additional fermonic and bosonic states with helicities $\\pm 3/2$ and $\\pm 1$. We outline the observational constraints on the model following from its low-energy phenomenology.

Linear step drive

International Nuclear Information System (INIS)

Haniger, L.; Elger, R.; Kocandrle, L.; Zdebor, J.

1986-01-01

A linear step drive is described developed in Czechoslovak-Soviet cooperation and intended for driving WWER-1000 control rods. The functional principle is explained of the motor and the mechanical and electrical parts of the drive, power control, and the indicator of position are described. The motor has latches situated in the reactor at a distance of 3 m from magnetic armatures, it has a low structural height above the reactor cover, which suggests its suitability for seismic localities. Its magnetic circuits use counterpoles; the mechanical shocks at the completion of each step are damped using special design features. The position indicator is of a special design and evaluates motor position within ±1% of total travel. A drive diagram and the flow chart of both the control electronics and the position indicator are presented. (author) 4 figs

Linear calculations of edge current driven kink modes with BOUT++ code

Energy Technology Data Exchange (ETDEWEB)

Li, G. Q., E-mail: ligq@ipp.ac.cn; Xia, T. Y. [Institute of Plasma Physics, CAS, Hefei, Anhui 230031 (China); Lawrence Livermore National Laboratory, Livermore, California 94550 (United States); Xu, X. Q. [Lawrence Livermore National Laboratory, Livermore, California 94550 (United States); Snyder, P. B.; Turnbull, A. D. [General Atomics, San Diego, California 92186 (United States); Ma, C. H.; Xi, P. W. [Lawrence Livermore National Laboratory, Livermore, California 94550 (United States); FSC, School of Physics, Peking University, Beijing 100871 (China)

2014-10-15

This work extends previous BOUT++ work to systematically study the impact of edge current density on edge localized modes, and to benchmark with the GATO and ELITE codes. Using the CORSICA code, a set of equilibria was generated with different edge current densities by keeping total current and pressure profile fixed. Based on these equilibria, the effects of the edge current density on the MHD instabilities were studied with the 3-field BOUT++ code. For the linear calculations, with increasing edge current density, the dominant modes are changed from intermediate-n and high-n ballooning modes to low-n kink modes, and the linear growth rate becomes smaller. The edge current provides stabilizing effects on ballooning modes due to the increase of local shear at the outer mid-plane with the edge current. For edge kink modes, however, the edge current does not always provide a destabilizing effect; with increasing edge current, the linear growth rate first increases, and then decreases. In benchmark calculations for BOUT++ against the linear results with the GATO and ELITE codes, the vacuum model has important effects on the edge kink mode calculations. By setting a realistic density profile and Spitzer resistivity profile in the vacuum region, the resistivity was found to have a destabilizing effect on both the kink mode and on the ballooning mode. With diamagnetic effects included, the intermediate-n and high-n ballooning modes can be totally stabilized for finite edge current density.

Linear calculations of edge current driven kink modes with BOUT++ code

International Nuclear Information System (INIS)

Li, G. Q.; Xia, T. Y.; Xu, X. Q.; Snyder, P. B.; Turnbull, A. D.; Ma, C. H.; Xi, P. W.

2014-01-01

This work extends previous BOUT++ work to systematically study the impact of edge current density on edge localized modes, and to benchmark with the GATO and ELITE codes. Using the CORSICA code, a set of equilibria was generated with different edge current densities by keeping total current and pressure profile fixed. Based on these equilibria, the effects of the edge current density on the MHD instabilities were studied with the 3-field BOUT++ code. For the linear calculations, with increasing edge current density, the dominant modes are changed from intermediate-n and high-n ballooning modes to low-n kink modes, and the linear growth rate becomes smaller. The edge current provides stabilizing effects on ballooning modes due to the increase of local shear at the outer mid-plane with the edge current. For edge kink modes, however, the edge current does not always provide a destabilizing effect; with increasing edge current, the linear growth rate first increases, and then decreases. In benchmark calculations for BOUT++ against the linear results with the GATO and ELITE codes, the vacuum model has important effects on the edge kink mode calculations. By setting a realistic density profile and Spitzer resistivity profile in the vacuum region, the resistivity was found to have a destabilizing effect on both the kink mode and on the ballooning mode. With diamagnetic effects included, the intermediate-n and high-n ballooning modes can be totally stabilized for finite edge current density

Variational and robust density fitting of four-center two-electron integrals in local metrics

Science.gov (United States)

Reine, Simen; Tellgren, Erik; Krapp, Andreas; Kjærgaard, Thomas; Helgaker, Trygve; Jansik, Branislav; Høst, Stinne; Salek, Paweł

2008-09-01

Density fitting is an important method for speeding up quantum-chemical calculations. Linear-scaling developments in Hartree-Fock and density-functional theories have highlighted the need for linear-scaling density-fitting schemes. In this paper, we present a robust variational density-fitting scheme that allows for solving the fitting equations in local metrics instead of the traditional Coulomb metric, as required for linear scaling. Results of fitting four-center two-electron integrals in the overlap and the attenuated Gaussian damped Coulomb metric are presented, and we conclude that density fitting can be performed in local metrics at little loss of chemical accuracy. We further propose to use this theory in linear-scaling density-fitting developments.

Stability of stationary states of non-local equations with singular interaction potentials

KAUST Repository

Fellner, Klemens

2011-04-01

We study the large-time behaviour of a non-local evolution equation for the density of particles or individuals subject to an external and an interaction potential. In particular, we consider interaction potentials which are singular in the sense that their first derivative is discontinuous at the origin.For locally attractive singular interaction potentials we prove under a linear stability condition local non-linear stability of stationary states consisting of a finite sum of Dirac masses. For singular repulsive interaction potentials we show the stability of stationary states of uniformly bounded solutions under a convexity condition.Finally, we present numerical simulations to illustrate our results. © 2010 Elsevier Ltd.

Aerodynamic design of horizontal axis wind turbine with innovative local linearization of chord and twist distributions

DEFF Research Database (Denmark)

Tahani, Mojtaba; Kavari, Ghazale; Masdari, Mehran

2017-01-01

This study is aimed to aerodynamically design a 1 mega-Watt horizontal axis wind turbine in order to obtain the maximum power coefficient by linearizing the chord and twist distributions. A new linearization method has been used for chord and twist distributions by crossing tangent line through...... the geometry of the blades determines the power generated by rotor, designing the blade is a very important issue. Herein, calculations are done for different types of airfoil families namely Risø-A1-21, Risø-A1-18, S809, S814 and Du 93-W-210. Hence, the effect of selecting different airfoil families is also...

Linear and non-linear optics of condensed matter

International Nuclear Information System (INIS)

McLean, T.P.

1977-01-01

Part I - Linear optics: 1. General introduction. 2. Frequency dependence of epsilon(ω, k vector). 3. Wave-vector dependence of epsilon(ω, k vector). 4. Tensor character of epsilon(ω, k vector). Part II - Non-linear optics: 5. Introduction. 6. A classical theory of non-linear response in one dimension. 7. The generalization to three dimensions. 8. General properties of the polarizability tensors. 9. The phase-matching condition. 10. Propagation in a non-linear dielectric. 11. Second harmonic generation. 12. Coupling of three waves. 13. Materials and their non-linearities. 14. Processes involving energy exchange with the medium. 15. Two-photon absorption. 16. Stimulated Raman effect. 17. Electro-optic effects. 18. Limitations of the approach presented here. (author)

Localization in an anisotropic planar aggregate of spheres

Directory of Open Access Journals (Sweden)

Ragione Luigi La

2017-01-01

Full Text Available We present a micro-mechanical model that is able to predict localization in a sheared planar aggregate of spheres. We assume a non-linear contact law between interacting particles that deform differently from an affine deformation. Equilibrium determines this deviation. The aggregate is isotropically compressed and then sheared so anisotropy develops because of contacts deletion and a non-linear contact law. Because of anisotropy and fluctuations in particles deformation, the resulting macroscopic stiffness tensor, which relates increments in the average stress with increments in the average strain, is characterized by a lack of major symmetry, Aijkl ≠ Aklij. At given shear strain and coordination number it is possible to detemine a plane over which discontinuity in strain occurs; this is identified as localization.

[Clinical characteristics of patients with juvenile localized scleroderma].

Science.gov (United States)

Sun, Qiu-Ning; Du, Wei; Hu, Bin; Liu, Pai; Yuan, Xie

2009-02-01

To investigate the clinical characteristics of juvenile localized scleroderma (JLS). The clinical data of 100 outpatients with JLS who were admitted to PUMC Hospital from 2000 to 2008 were retrospectively analyzed. Of a total of 100 cases, 51 (51%) were confirmed as linear scleroderma, 26 (26%) as plaque morphea, 26 (26%) as deep morphea, 12 (12%) as generalized morphea, and 15 (15%) as a mixed subtype. Nine patients (9%) had family histories of rheumatic or autoimmune diseases, while 16 (16%) might be triggered by unknown factors. Totally 84 patients underwent antinuclear antibody tests and 38 patients (45.2%) had positive results. Linear scleroderma are the most frequent subtype of JLS. Localized scleroderma may be associated with some autoimmune-related causes.

Positive Quasi Linear Operator Formulation

International Nuclear Information System (INIS)

Berry, L.A.; Jaeger, E.F.

2005-01-01

Expressions for the RF quasi-linear operator are biquadratic sums over the Fourier modes (or FLR equivalent) that describe the RF electric field with a kernel that is a function of the two wave vectors, k-vector L and k-vector R , in the sum. As a result of either an implicit or explicit average over field lines or flux surfaces, this kernel only depends on one parallel wave vector, conventionally k R -vector. When k-vector is an independent component of the representation for E, the sums are demonstrably positive. However, except for closed field line systems, k-vector is dependent on the local direction of the equilibrium magnetic field, and, empirically, the absorbed energy and quasi-linear diffusion coefficients are observed to have negative features. We have formally introduced an independent k-vector sum by Fourier transforming the RF electric field (assuming straight field lines) using a field-line-length coordinate. The resulting expression is positive. We have modeled this approach by calculating the quasi linear operator for 'modes' with fixed k-vector. We form these modes by discretizing k-vector and then assigning all of the Fourier components with k-vectorthat fall within a given k-vector bin to that k-vector mode. Results will be shown as a function of the number of bins. Future work will involve implementing the expressions derived from the Fourier transform and evaluating the dependence on field line length

Linear verrucous hemangioma-a rare case and dermoscopic clues to diagnosis.

Science.gov (United States)

Dhanta, Aditi; Chauhan, Payal; Meena, Dilip; Hazarika, Neirita

2018-01-01

Verrucous hemangioma (VH) is a rare, congenital and localized vascular malformation, which usually presents as warty, bluish, vascular papules, plaques, or nodules, mainly on the lower extremities. Linear presentation of the disease is rare. A deep biopsy is necessary to confirm the clinical diagnosis by histopathological examination, with dermoscopy acting as a useful tool for evaluating the precise vascular structure. Here, we report on a 13-year-old female child with linear VH presenting over her foot since infancy and dermoscopic findings of VH along with the clinical-pathologic features.

Non-local effects in kaonic atoms

International Nuclear Information System (INIS)

Lutz, M.; Florkowski, W.

2000-04-01

Optical potentials with non-local (gradient) terms are used to describe the spectra of kaonic atoms. The strength of the non-local terms is determined from a many-body calculation of the kaon self-energy in nuclear matter. The optical potentials show strong non-linearities in the nucleon density and sizeable non-local terms. We find that the non-local terms are quantitatively important and the results depend strongly on the way the gradient terms are arranged. Phenomenologically successful fits are obtained for p-wave like optical potentials. It is suggested that the microscopic form of the non-local interaction terms is obtained systematically by means of a semi-classical expansion of the nucleus structure. We conclude that a microscopic description of kaonic atom data requires further detailed studies of the microscopic K - nuclear dynamics. (orig.)

Linearity and Non-linearity of Photorefractive effect in Materials ...

African Journals Online (AJOL)

In this paper we have studied the Linearity and Non-linearity of Photorefractive effect in materials using the band transport model. For low light beam intensities the change in the refractive index is proportional to the electric field for linear optics while for non- linear optics the change in refractive index is directly proportional ...

Non-linear second-order periodic systems with non-smooth potential

Indian Academy of Sciences (India)

In this paper we study second order non-linear periodic systems driven by the ordinary vector -Laplacian with a non-smooth, locally Lipschitz potential function. Our approach is variational and it is based on the non-smooth critical point theory. We prove existence and multiplicity results under general growth conditions on ...

Non-linear second-order periodic systems with non-smooth potential

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

Abstract. In this paper we study second order non-linear periodic systems driven by the ordinary vector p-Laplacian with a non-smooth, locally Lipschitz potential function. Our approach is variational and it is based on the non-smooth critical point theory. We prove existence and multiplicity results under general growth ...

Using Linear and Non-Linear Temporal Adjustments to Align Multiple Phenology Curves, Making Vegetation Status and Health Directly Comparable

Science.gov (United States)

Hargrove, W. W.; Norman, S. P.; Kumar, J.; Hoffman, F. M.

2017-12-01

National-scale polar analysis of MODIS NDVI allows quantification of degree of seasonality expressed by local vegetation, and also selects the most optimum start/end of a local "phenological year" that is empirically customized for the vegetation that is growing at each location. Interannual differences in timing of phenology make direct comparisons of vegetation health and performance between years difficult, whether at the same or different locations. By "sliding" the two phenologies in time using a Procrustean linear time shift, any particular phenological event or "completion milestone" can be synchronized, allowing direct comparison of differences in timing of other remaining milestones. Going beyond a simple linear translation, time can be "rubber-sheeted," compressed or dilated. Considering one phenology curve to be a reference, the second phenology can be "rubber-sheeted" to fit that baseline as well as possible by stretching or shrinking time to match multiple control points, which can be any recognizable phenological events. Similar to "rubber sheeting" to georectify a map inside a GIS, rubber sheeting a phenology curve also yields a warping signature that shows at every time and every location how many days the adjusted phenology is ahead or behind the phenological development of the reference vegetation. Using such temporal methods to "adjust" phenologies may help to quantify vegetation impacts from frost, drought, wildfire, insects and diseases by permitting the most commensurate quantitative comparisons with unaffected vegetation.

Lattice Boltzmann methods for global linear instability analysis

Science.gov (United States)

Pérez, José Miguel; Aguilar, Alfonso; Theofilis, Vassilis

2017-12-01

Modal global linear instability analysis is performed using, for the first time ever, the lattice Boltzmann method (LBM) to analyze incompressible flows with two and three inhomogeneous spatial directions. Four linearization models have been implemented in order to recover the linearized Navier-Stokes equations in the incompressible limit. Two of those models employ the single relaxation time and have been proposed previously in the literature as linearization of the collision operator of the lattice Boltzmann equation. Two additional models are derived herein for the first time by linearizing the local equilibrium probability distribution function. Instability analysis results are obtained in three benchmark problems, two in closed geometries and one in open flow, namely the square and cubic lid-driven cavity flow and flow in the wake of the circular cylinder. Comparisons with results delivered by classic spectral element methods verify the accuracy of the proposed new methodologies and point potential limitations particular to the LBM approach. The known issue of appearance of numerical instabilities when the SRT model is used in direct numerical simulations employing the LBM is shown to be reflected in a spurious global eigenmode when the SRT model is used in the instability analysis. Although this mode is absent in the multiple relaxation times model, other spurious instabilities can also arise and are documented herein. Areas of potential improvements in order to make the proposed methodology competitive with established approaches for global instability analysis are discussed.

Energy localization and molecular dissociation

International Nuclear Information System (INIS)

Takeno, S.; Tsironis, G.P.

2005-01-01

We study analytically as well as numerically the role that large-amplitude vibrations play during the process of molecular dissociation. Our model consists of a linear three-atom molecule composed of identical atoms interacting with their nearest neighbors by Morse potentials. We find a close relation between energy localization and bond breaking and evaluate numerically the corresponding reaction paths

Special set linear algebra and special set fuzzy linear algebra

OpenAIRE

Kandasamy, W. B. Vasantha; Smarandache, Florentin; Ilanthenral, K.

2009-01-01

The authors in this book introduce the notion of special set linear algebra and special set fuzzy Linear algebra, which is an extension of the notion set linear algebra and set fuzzy linear algebra. These concepts are best suited in the application of multi expert models and cryptology. This book has five chapters. In chapter one the basic concepts about set linear algebra is given in order to make this book a self contained one. The notion of special set linear algebra and their fuzzy analog...

Toward the prevention of childhood undernutrition: Diet diversity strategies using locally produced food can overcome gaps in nutrient supply

DEFF Research Database (Denmark)

Parlesak, Alexandr; Geelhoed, Diederike; Robertson, Aileen

2014-01-01

nutritious food baskets (FNFB) by stepwise addition of micronutrient-dense local foods. Results. Only the top quintile of Mozambican households, using average expenditure data, could afford the FNFB that was designed using linear programming from a spectrum of local standard foods. The addition of beef heart...... programming, to investigate whether diet diversification using local foods should be prioritized in order to reduce the prevalence of chronic undernutrition. Methods. Market prices of local foods were collected in Tete City, Mozambique. Linear programming was applied to calculate the cheapest possible fully...... or liver, dried fish and fresh moringa leaves, before applying linear programming decreased the price by a factor of up to 2.6. As a result, the top three quintiles could afford the FNFB optimized using both diversification strategy and linear programming. CDFPs, when added to the baskets, were unable...

Noiseless Vlasov–Poisson simulations with linearly transformed particles

Energy Technology Data Exchange (ETDEWEB)

Campos Pinto, Martin, E-mail: campos@ann.jussieu.fr [Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); CNRS, UMR 7598, Laboratoire Jacques-Louis Lions, F-75005, Paris (France); UPMC Univ. Paris 06, UMR 7598, Laboratoire Jacques-Louis Lions, F-75005, Paris (France); Sonnendrücker, Eric, E-mail: sonnen@math.unistra.fr [IRMA, UMR 7501, Université de Strasbourg and CNRS, 7 rue René Descartes, F-67084 Strasbourg Cedex (France); Project-team CALVI, INRIA Nancy Grand Est, 7 rue René Descartes, F-67084 Strasbourg Cedex (France); Friedman, Alex, E-mail: af@llnl.gov [Lawrence Livermore National Laboratory, Livermore, CA 94550 (United States); Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); Grote, David P., E-mail: grote1@llnl.gov [Lawrence Livermore National Laboratory, Livermore, CA 94550 (United States); Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); Lund, Steve M., E-mail: smlund@llnl.gov [Lawrence Livermore National Laboratory, Livermore, CA 94550 (United States); Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States)

2014-10-15

We introduce a deterministic discrete-particle simulation approach, the Linearly-Transformed Particle-In-Cell (LTPIC) method, that employs linear deformations of the particles to reduce the noise traditionally associated with particle schemes. Formally, transforming the particles is justified by local first order expansions of the characteristic flow in phase space. In practice the method amounts of using deformation matrices within the particle shape functions; these matrices are updated via local evaluations of the forward numerical flow. Because it is necessary to periodically remap the particles on a regular grid to avoid excessively deforming their shapes, the method can be seen as a development of Denavit's Forward Semi-Lagrangian (FSL) scheme (Denavit, 1972 [8]). However, it has recently been established (Campos Pinto, 2012 [20]) that the underlying Linearly-Transformed Particle scheme converges for abstract transport problems, with no need to remap the particles; deforming the particles can thus be seen as a way to significantly lower the remapping frequency needed in the FSL schemes, and hence the associated numerical diffusion. To couple the method with electrostatic field solvers, two specific charge deposition schemes are examined, and their performance compared with that of the standard deposition method. Finally, numerical 1d1v simulations involving benchmark test cases and halo formation in an initially mismatched thermal sheet beam demonstrate some advantages of our LTPIC scheme over the classical PIC and FSL methods. Benchmarked test cases also indicate that, for numerical choices involving similar computational effort, the LTPIC method is capable of accuracy comparable to or exceeding that of state-of-the-art, high-resolution Vlasov schemes.

Comparison of Damage Models for Predicting the Non-Linear Response of Laminates Under Matrix Dominated Loading Conditions

Science.gov (United States)

Schuecker, Clara; Davila, Carlos G.; Rose, Cheryl A.

2010-01-01

Five models for matrix damage in fiber reinforced laminates are evaluated for matrix-dominated loading conditions under plane stress and are compared both qualitatively and quantitatively. The emphasis of this study is on a comparison of the response of embedded plies subjected to a homogeneous stress state. Three of the models are specifically designed for modeling the non-linear response due to distributed matrix cracking under homogeneous loading, and also account for non-linear (shear) behavior prior to the onset of cracking. The remaining two models are localized damage models intended for predicting local failure at stress concentrations. The modeling approaches of distributed vs. localized cracking as well as the different formulations of damage initiation and damage progression are compared and discussed.

Efficient Linear and Non-Linear Finite Element Formulation using a New Local Enhancement of Displacement Fields for Triangular Elements

DEFF Research Database (Denmark)

Damkilde, Lars; Pedersen, Ronnie

2012-01-01

This paper describes a new triangular plane element which can be considered as a linear strain triangular element (LST) extended with incompatible displacement modes. The extended element will have a full cubic interpolation of strains and stresses. The extended LST-element is connected with other...... elements similar to the LST-element i.e. through three corner nodes and three mid-side nodes. The incompatible modes are associated with two displacement gradients at each mid-side node and displacements in the central node. The element passes the patch test and converges to the exact solution. The element...... often show a very slow convergence, and the numerical solutions will in general overestimate the bearing capacity and underestimate the displacements. The examples show that the extended incompatible element behaves much better than the corresponding compatible elements especially for coarse meshes....

A highly linear baseband Gm—C filter for WLAN application

Science.gov (United States)

Lijun, Yang; Zheng, Gong; Yin, Shi; Zhiming, Chen

2011-09-01

A low voltage, highly linear transconductan—C (Gm—C) low-pass filter for wireless local area network (WLAN) transceiver application is proposed. This transmitter (Tx) filter adopts a 9.8 MHz 3rd-order Chebyshev low pass prototype and achieves 35 dB stop-band attenuation at 30 MHz frequency. By utilizing pseudo-differential linear-region MOS transconductors, the filter IIP3 is measured to be as high as 9.5 dBm. Fabricated in a 0.35 μm standard CMOS technology, the proposed filter chip occupies a 0.41 × 0.17 mm2 die area and consumes 3.36 mA from a 3.3-V power supply.

Dark energy and the quietness of the local Hubble flow

International Nuclear Information System (INIS)

Axenides, M.; Perivolaropoulos, L.

2002-01-01

The linearity and quietness of the local ( X (t 0 ) of dark energy obeying the time independent equation of state p X =wρ X . We find that dark energy can indeed cool the LHF. However the dark energy parameter values required to make the predicted velocity dispersion consistent with the observed value v rms ≅40 km/s have been ruled out by other observational tests constraining the dark energy parameters w and Ω X . Therefore despite the claims of recent qualitative studies, dark energy with time independent equation of state cannot by itself explain the quietness and linearity of the local Hubble flow

Impact localization on composite structures using time difference and MUSIC approach

Science.gov (United States)

Zhong, Yongteng; Xiang, Jiawei

2017-05-01

1-D uniform linear array (ULA) has the shortcoming of the half-plane mirror effect, which does not allow discriminating between a target placed above the array and a target placed below the array. This paper presents time difference (TD) and multiple signal classification (MUSIC) based omni-directional impact localization on a large stiffened composite structure using improved linear array, which is able to perform omni-directional 360° localization. This array contains 2M+3 PZT sensors, where 2M+1 PZT sensors are arranged as a uniform linear array, and the other two PZT sensors are placed above and below the array. Firstly, the arrival times of impact signals observed by the other two sensors are determined using the wavelet transform. Compared with each other, the direction range of impact source can be decided in general, 0°to 180° or 180°to 360°. And then, two dimensional multiple signal classification (2D-MUSIC) based spatial spectrum formula using the uniform linear array is applied for impact localization by the general direction range. When the arrival times of impact signals observed by upper PZT is equal to that of lower PZT, the direction can be located in x axis (0°or 180°). And time difference based MUSIC method is present to locate impact position. To verify the proposed approach, the proposed approach is applied to a composite structure. The localization results are in good agreement with the actual impact occurring positions.

Parameter identifiability of linear dynamical systems

Science.gov (United States)

Glover, K.; Willems, J. C.

1974-01-01

It is assumed that the system matrices of a stationary linear dynamical system were parametrized by a set of unknown parameters. The question considered here is, when can such a set of unknown parameters be identified from the observed data? Conditions for the local identifiability of a parametrization are derived in three situations: (1) when input/output observations are made, (2) when there exists an unknown feedback matrix in the system and (3) when the system is assumed to be driven by white noise and only output observations are made. Also a sufficient condition for global identifiability is derived.

Oscillator strengths, first-order properties, and nuclear gradients for local ADC(2)

Energy Technology Data Exchange (ETDEWEB)

Schütz, Martin, E-mail: martin.schuetz@chemie.uni-regensburg.de [Institute of Physical and Theoretical Chemistry, University of Regensburg, Universitätsstraße 31, D-93040 Regensburg (Germany)

2015-06-07

We describe theory and implementation of oscillator strengths, orbital-relaxed first-order properties, and nuclear gradients for the local algebraic diagrammatic construction scheme through second order. The formalism is derived via time-dependent linear response theory based on a second-order unitary coupled cluster model. The implementation presented here is a modification of our previously developed algorithms for Laplace transform based local time-dependent coupled cluster linear response (CC2LR); the local approximations thus are state specific and adaptive. The symmetry of the Jacobian leads to considerable simplifications relative to the local CC2LR method; as a result, a gradient evaluation is about four times less expensive. Test calculations show that in geometry optimizations, usually very similar geometries are obtained as with the local CC2LR method (provided that a second-order method is applicable). As an exemplary application, we performed geometry optimizations on the low-lying singlet states of chlorophyllide a.

Oscillator strengths, first-order properties, and nuclear gradients for local ADC(2).

Science.gov (United States)

Schütz, Martin

2015-06-07

We describe theory and implementation of oscillator strengths, orbital-relaxed first-order properties, and nuclear gradients for the local algebraic diagrammatic construction scheme through second order. The formalism is derived via time-dependent linear response theory based on a second-order unitary coupled cluster model. The implementation presented here is a modification of our previously developed algorithms for Laplace transform based local time-dependent coupled cluster linear response (CC2LR); the local approximations thus are state specific and adaptive. The symmetry of the Jacobian leads to considerable simplifications relative to the local CC2LR method; as a result, a gradient evaluation is about four times less expensive. Test calculations show that in geometry optimizations, usually very similar geometries are obtained as with the local CC2LR method (provided that a second-order method is applicable). As an exemplary application, we performed geometry optimizations on the low-lying singlet states of chlorophyllide a.

Oscillator strengths, first-order properties, and nuclear gradients for local ADC(2)

International Nuclear Information System (INIS)

Schütz, Martin

2015-01-01

We describe theory and implementation of oscillator strengths, orbital-relaxed first-order properties, and nuclear gradients for the local algebraic diagrammatic construction scheme through second order. The formalism is derived via time-dependent linear response theory based on a second-order unitary coupled cluster model. The implementation presented here is a modification of our previously developed algorithms for Laplace transform based local time-dependent coupled cluster linear response (CC2LR); the local approximations thus are state specific and adaptive. The symmetry of the Jacobian leads to considerable simplifications relative to the local CC2LR method; as a result, a gradient evaluation is about four times less expensive. Test calculations show that in geometry optimizations, usually very similar geometries are obtained as with the local CC2LR method (provided that a second-order method is applicable). As an exemplary application, we performed geometry optimizations on the low-lying singlet states of chlorophyllide a

Gromov-Witten invariants and localization

Science.gov (United States)

Morrison, David R.

2017-11-01

We give a pedagogical review of the computation of Gromov-Witten invariants via localization in 2D gauged linear sigma models. We explain the relationship between the two-sphere partition function of the theory and the Kähler potential on the conformal manifold. We show how the Kähler potential can be assembled from classical, perturbative, and non-perturbative contributions, and explain how the non-perturbative contributions are related to the Gromov-Witten invariants of the corresponding Calabi-Yau manifold. We then explain how localization enables efficient calculation of the two-sphere partition function and, ultimately, the Gromov-Witten invariants themselves. This is a contribution to the review issue ‘Localization techniques in quantum field theories’ (ed V Pestun and M Zabzine) which contains 17 chapters, available at [1].

A new localization set for generalized eigenvalues

Directory of Open Access Journals (Sweden)

Jing Gao

2017-05-01

Full Text Available Abstract A new localization set for generalized eigenvalues is obtained. It is shown that the new set is tighter than that in (Numer. Linear Algebra Appl. 16:883-898, 2009. Numerical examples are given to verify the corresponding results.

Designing a graph-based approach to landscape ecological assessment of linear infrastructures

Energy Technology Data Exchange (ETDEWEB)

Girardet, Xavier, E-mail: xavier.girardet@univ-fcomte.fr; Foltête, Jean-Christophe, E-mail: jean-christophe.foltete@univ-fcomte.fr; Clauzel, Céline, E-mail: celine.clauzel@univ-fcomte.fr

2013-09-15

The development of major linear infrastructures contributes to landscape fragmentation and impacts natural habitats and biodiversity in various ways. To anticipate and minimize such impacts, landscape planning needs to be capable of effective strategic environmental assessment (SEA) and of supporting environmental impact assessment (EIA) decisions. To this end, species distribution models (SDMs) are an effective way of making predictive maps of the presence of a given species. In this paper, we propose to combine SDMs and graph-based representation of landscape networks to integrate the potential long-distance effect of infrastructures on species distribution. A diachronic approach, comparing distribution before and after the linear infrastructure is constructed, leads to the design of a species distribution assessment (SDA), taking into account population isolation. The SDA makes it possible (1) to estimate the local variation in probability of presence and (2) to characterize the impact of the infrastructure in terms of global variation in presence and of distance of disturbance. The method is illustrated by assessing the impact of the construction of a high-speed railway line on the distribution of several virtual species in Franche-Comté (France). The study shows the capacity of the SDA to characterize the impact of a linear infrastructure either as a research concern or as a spatial planning challenge. SDAs could be helpful in deciding among several scenarios for linear infrastructure routes or for the location of mitigation measures. -- Highlights: • Graph connectivity metrics were integrated into a species distribution model. • SDM was performed before and after the implementation of linear infrastructure. • The local variation of presence provides spatial indicators of the impact.

Designing a graph-based approach to landscape ecological assessment of linear infrastructures

International Nuclear Information System (INIS)

Girardet, Xavier; Foltête, Jean-Christophe; Clauzel, Céline

2013-01-01

The development of major linear infrastructures contributes to landscape fragmentation and impacts natural habitats and biodiversity in various ways. To anticipate and minimize such impacts, landscape planning needs to be capable of effective strategic environmental assessment (SEA) and of supporting environmental impact assessment (EIA) decisions. To this end, species distribution models (SDMs) are an effective way of making predictive maps of the presence of a given species. In this paper, we propose to combine SDMs and graph-based representation of landscape networks to integrate the potential long-distance effect of infrastructures on species distribution. A diachronic approach, comparing distribution before and after the linear infrastructure is constructed, leads to the design of a species distribution assessment (SDA), taking into account population isolation. The SDA makes it possible (1) to estimate the local variation in probability of presence and (2) to characterize the impact of the infrastructure in terms of global variation in presence and of distance of disturbance. The method is illustrated by assessing the impact of the construction of a high-speed railway line on the distribution of several virtual species in Franche-Comté (France). The study shows the capacity of the SDA to characterize the impact of a linear infrastructure either as a research concern or as a spatial planning challenge. SDAs could be helpful in deciding among several scenarios for linear infrastructure routes or for the location of mitigation measures. -- Highlights: • Graph connectivity metrics were integrated into a species distribution model. • SDM was performed before and after the implementation of linear infrastructure. • The local variation of presence provides spatial indicators of the impact

The research of radar target tracking observed information linear filter method

Science.gov (United States)

Chen, Zheng; Zhao, Xuanzhi; Zhang, Wen

2018-05-01

Aiming at the problems of low precision or even precision divergent is caused by nonlinear observation equation in radar target tracking, a new filtering algorithm is proposed in this paper. In this algorithm, local linearization is carried out on the observed data of the distance and angle respectively. Then the kalman filter is performed on the linearized data. After getting filtered data, a mapping operation will provide the posteriori estimation of target state. A large number of simulation results show that this algorithm can solve above problems effectively, and performance is better than the traditional filtering algorithm for nonlinear dynamic systems.

Globally COnstrained Local Function Approximation via Hierarchical Modelling, a Framework for System Modelling under Partial Information

DEFF Research Database (Denmark)

Øjelund, Henrik; Sadegh, Payman

2000-01-01

be obtained. This paper presents a new approach for system modelling under partial (global) information (or the so called Gray-box modelling) that seeks to perserve the benefits of the global as well as local methodologies sithin a unified framework. While the proposed technique relies on local approximations......Local function approximations concern fitting low order models to weighted data in neighbourhoods of the points where the approximations are desired. Despite their generality and convenience of use, local models typically suffer, among others, from difficulties arising in physical interpretation...... simultaneously with the (local estimates of) function values. The approach is applied to modelling of a linear time variant dynamic system under prior linear time invariant structure where local regression fails as a result of high dimensionality....

Statistical downscaling of precipitation using long short-term memory recurrent neural networks

Science.gov (United States)

Misra, Saptarshi; Sarkar, Sudeshna; Mitra, Pabitra

2017-11-01

Hydrological impacts of global climate change on regional scale are generally assessed by downscaling large-scale climatic variables, simulated by General Circulation Models (GCMs), to regional, small-scale hydrometeorological variables like precipitation, temperature, etc. In this study, we propose a new statistical downscaling model based on Recurrent Neural Network with Long Short-Term Memory which captures the spatio-temporal dependencies in local rainfall. The previous studies have used several other methods such as linear regression, quantile regression, kernel regression, beta regression, and artificial neural networks. Deep neural networks and recurrent neural networks have been shown to be highly promising in modeling complex and highly non-linear relationships between input and output variables in different domains and hence we investigated their performance in the task of statistical downscaling. We have tested this model on two datasets—one on precipitation in Mahanadi basin in India and the second on precipitation in Campbell River basin in Canada. Our autoencoder coupled long short-term memory recurrent neural network model performs the best compared to other existing methods on both the datasets with respect to temporal cross-correlation, mean squared error, and capturing the extremes.

Magnetic resonance as a local probe for linear bands in the Weyl semimetals NbP and TaP

Energy Technology Data Exchange (ETDEWEB)

Baenitz, Michael; Yasuoka, Hiroshi; Majumder, Mayukh; Shekhar, Chandra; Yan, Binghai; Felser, Claudia; Schmidt, Marcus [MPI for Chemical Physics of Solids, Dresden (Germany)

2016-07-01

Some compensated d-electron semimetals, for example the monophosphites NbP and TaP, with non centrosymmetric structure and with sizable spin orbit coupling (SOC) form a new class of material: the Weyl semimetals (WSM). A unique linear crossing of valence- and conduction- band in a single point in reciprocal space defines the so called Weyl point where the fermion mass vanishes theoretically. In real materials the Fermi level E{sub F} does not exactly match the Weyl node and as a consequence residual very light fermions are found. Due to the SOC these Weyl fermions have a chirality (handedness) on their linear dispersive (E ∝k) bands and frequently a linear density of states (DOS) at the Fermi level E{sub F}. We use NMR as a probe for this linear d- electron bands. The shift provides the s- and d- electron contributions to the DOS at E{sub F}, whereas the spin lattice relaxation is governed by low energy excitations around E{sub F}. {sup 31}P (I = 1/2) - Fourier - transform - and {sup 95}Nb (I = 9/2) - broadline - sweep - NMR studies are performed. We investigated powder samples as well as single crystals on both systems. The angular dependence of the {sup 95}Nb- and {sup 31}P - NMR lines is discussed.

Linear Algebraic Method for Non-Linear Map Analysis

International Nuclear Information System (INIS)

Yu, L.; Nash, B.

2009-01-01

We present a newly developed method to analyze some non-linear dynamics problems such as the Henon map using a matrix analysis method from linear algebra. Choosing the Henon map as an example, we analyze the spectral structure, the tune-amplitude dependence, the variation of tune and amplitude during the particle motion, etc., using the method of Jordan decomposition which is widely used in conventional linear algebra.

The effects of relativistic and non-local non-linearities on modulational instabilities in non-uniform plasma

International Nuclear Information System (INIS)

Mohamed, B.F.; El-Shorbagy, Kh.H.

2000-01-01

A general detailed analysis for the nonlinear generation of localized fields due to the existence of a strong pump field inside the non-uniform plasma has been considered. We have taken into account the effects of relativistic and non-local nonlinearities on the structure of plasma resonance region. The nonlinear Schrodinger equation described the localized fields are investigated. Besides, the generalized dispersion relation is obtained to study the modulational instabilities in different cases. Keywords: Wave-plasma interaction, Nonlinear effects, Modulation instabilities

Robust Weak Chimeras in Oscillator Networks with Delayed Linear and Quadratic Interactions

Science.gov (United States)

Bick, Christian; Sebek, Michael; Kiss, István Z.

2017-10-01

We present an approach to generate chimera dynamics (localized frequency synchrony) in oscillator networks with two populations of (at least) two elements using a general method based on a delayed interaction with linear and quadratic terms. The coupling design yields robust chimeras through a phase-model-based design of the delay and the ratio of linear and quadratic components of the interactions. We demonstrate the method in the Brusselator model and experiments with electrochemical oscillators. The technique opens the way to directly bridge chimera dynamics in phase models and real-world oscillator networks.

Integrability and Linear Stability of Nonlinear Waves

Science.gov (United States)

Degasperis, Antonio; Lombardo, Sara; Sommacal, Matteo

2018-03-01

It is well known that the linear stability of solutions of 1+1 partial differential equations which are integrable can be very efficiently investigated by means of spectral methods. We present here a direct construction of the eigenmodes of the linearized equation which makes use only of the associated Lax pair with no reference to spectral data and boundary conditions. This local construction is given in the general N× N matrix scheme so as to be applicable to a large class of integrable equations, including the multicomponent nonlinear Schrödinger system and the multiwave resonant interaction system. The analytical and numerical computations involved in this general approach are detailed as an example for N=3 for the particular system of two coupled nonlinear Schrödinger equations in the defocusing, focusing and mixed regimes. The instabilities of the continuous wave solutions are fully discussed in the entire parameter space of their amplitudes and wave numbers. By defining and computing the spectrum in the complex plane of the spectral variable, the eigenfrequencies are explicitly expressed. According to their topological properties, the complete classification of these spectra in the parameter space is presented and graphically displayed. The continuous wave solutions are linearly unstable for a generic choice of the coupling constants.

Constraining generalized non-local cosmology from Noether symmetries.

Science.gov (United States)

Bahamonde, Sebastian; Capozziello, Salvatore; Dialektopoulos, Konstantinos F

2017-01-01

We study a generalized non-local theory of gravity which, in specific limits, can become either the curvature non-local or teleparallel non-local theory. Using the Noether symmetry approach, we find that the coupling functions coming from the non-local terms are constrained to be either exponential or linear in form. It is well known that in some non-local theories, a certain kind of exponential non-local couplings is needed in order to achieve a renormalizable theory. In this paper, we explicitly show that this kind of coupling does not need to be introduced by hand, instead, it appears naturally from the symmetries of the Lagrangian in flat Friedmann-Robertson-Walker cosmology. Finally, we find de Sitter and power-law cosmological solutions for different non-local theories. The symmetries for the generalized non-local theory are also found and some cosmological solutions are also achieved using the full theory.

Development of Growth Charts of Pakistani Children Aged 4-15 Years Using Quantile Regression: A Cross-sectional Study.

Science.gov (United States)

Iftikhar, Sundus; Khan, Nazeer; Siddiqui, Junaid S; Baig-Ansari, Naila

2018-02-02

Background Growth charts are essential tools used by pediatricians as well as public health researchers in assessing and monitoring the well-being of pediatric populations. Development of these growth charts, especially for children above five years of age, is challenging and requires current anthropometric data and advanced statistical analysis. These growth charts are generally presented as a series of smooth centile curves. A number of modeling approaches are available for generating growth charts and applying these on national datasets is important for generating country-specific reference growth charts. Objective To demonstrate that quantile regression (QR) as a viable statistical approach to construct growth reference charts and to assess the applicability of the World Health Organization (WHO) 2007 growth standards to a large Pakistani population of school-going children. Methodology This is a secondary data analysis using anthropometric data of 9,515 students from a Pakistani survey conducted between 2007 and 2014 in four cities of Pakistan. Growth reference charts were created using QR as well as the LMS (Box-Cox transformation (L), the median (M), and the generalized coefficient of variation (S)) method and then compared with WHO 2007 growth standards. Results Centile values estimated by the LMS method and QR procedure had few differences. The centile values attained from QR procedure of BMI-for-age, weight-for-age, and height-for-age of Pakistani children were lower than the standard WHO 2007 centile. Conclusion QR should be considered as an alternative method to develop growth charts for its simplicity and lack of necessity to transform data. WHO 2007 standards are not suitable for Pakistani children.

Alignment of the stanford linear collider Arcs

International Nuclear Information System (INIS)

Pitthan, R.; Bell, B.; Friedsam, H.

1987-01-01

The alignment of the Arcs for the Stanford Linear Collider at SLAC has posed problems in accelerator survey and alignment not encountered before. These problems come less from the tight tolerances of 0.1 mm, although reaching such a tight statistically defined accuracy in a controlled manner is difficult enough, but from the absence of a common reference plane for the Arcs. Traditional circular accelerators, including HERA and LEP, have been designed in one plane referenced to local gravity. For the SLC Arcs no such single plane exists. Methods and concepts developed to solve these and other problems, connected with the unique design of SLC, range from the first use of satellites for accelerator alignment, use of electronic laser theodolites for placement of components, computer control of the manual adjustment process, complete automation of the data flow incorporating the most advanced concepts of geodesy, strict separation of survey and alignment, to linear principal component analysis for the final statistical smoothing of the mechanical components

Convergence diagnostics for Eigenvalue problems with linear regression model

International Nuclear Information System (INIS)

Shi, Bo; Petrovic, Bojan

2011-01-01

Although the Monte Carlo method has been extensively used for criticality/Eigenvalue problems, a reliable, robust, and efficient convergence diagnostics method is still desired. Most methods are based on integral parameters (multiplication factor, entropy) and either condense the local distribution information into a single value (e.g., entropy) or even disregard it. We propose to employ the detailed cycle-by-cycle local flux evolution obtained by using mesh tally mechanism to assess the source and flux convergence. By applying a linear regression model to each individual mesh in a mesh tally for convergence diagnostics, a global convergence criterion can be obtained. We exemplify this method on two problems and obtain promising diagnostics results. (author)

Quantile Regression Analysis of the Distributional Effects of Air Pollution on Blood Pressure, Heart Rate Variability, Blood Lipids, and Biomarkers of Inflammation in Elderly American Men: The Normative Aging Study.

Science.gov (United States)

Bind, Marie-Abele; Peters, Annette; Koutrakis, Petros; Coull, Brent; Vokonas, Pantel; Schwartz, Joel

2016-08-01

Previous studies have observed associations between air pollution and heart disease. Susceptibility to air pollution effects has been examined mostly with a test of effect modification, but little evidence is available whether air pollution distorts cardiovascular risk factor distribution. This paper aims to examine distributional and heterogeneous effects of air pollution on known cardiovascular biomarkers. A total of 1,112 men from the Normative Aging Study and residents of the greater Boston, Massachusetts, area with mean age of 69 years at baseline were included in this study during the period 1995-2013. We used quantile regression and random slope models to investigate distributional effects and heterogeneity in the traffic-related responses on blood pressure, heart rate variability, repolarization, lipids, and inflammation. We considered 28-day averaged exposure to particle number, PM2.5 black carbon, and PM2.5 mass concentrations (measured at a single monitor near the site of the study visits). We observed some evidence suggesting distributional effects of traffic-related pollutants on systolic blood pressure, heart rate variability, corrected QT interval, low density lipoprotein (LDL) cholesterol, triglyceride, and intercellular adhesion molecule-1 (ICAM-1). For example, among participants with LDL cholesterol below 80 mg/dL, an interquartile range increase in PM2.5 black carbon exposure was associated with a 7-mg/dL (95% CI: 5, 10) increase in LDL cholesterol, while among subjects with LDL cholesterol levels close to 160 mg/dL, the same exposure was related to a 16-mg/dL (95% CI: 13, 20) increase in LDL cholesterol. We observed similar heterogeneous associations across low versus high percentiles of the LDL distribution for PM2.5 mass and particle number. These results suggest that air pollution distorts the distribution of cardiovascular risk factors, and that, for several outcomes, effects may be greatest among individuals who are already at high risk

A highly linear baseband Gm-C filter for WLAN application

International Nuclear Information System (INIS)

Yang Lijun; Chen Zhiming; Gong Zheng; Shi Yin

2011-01-01

A low voltage, highly linear transconductan-C (G m -C) low-pass filter for wireless local area network (WLAN) transceiver application is proposed. This transmitter (Tx) filter adopts a 9.8 MHz 3rd-order Chebyshev low pass prototype and achieves 35 dB stop-band attenuation at 30 MHz frequency. By utilizing pseudo-differential linear-region MOS transconductors, the filter IIP 3 is measured to be as high as 9.5 dBm. Fabricated in a 0.35 μm standard CMOS technology, the proposed filter chip occupies a 0.41 x 0.17 mm 2 die area and consumes 3.36 mA from a 3.3-V power supply. (semiconductor integrated circuits)

Single shot trajectory design for region-specific imaging using linear and nonlinear magnetic encoding fields.