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Sample records for random regression cubic

  1. Randomized Block Cubic Newton Method

    KAUST Repository

    Doikov, Nikita

    2018-02-12

    We study the problem of minimizing the sum of three convex functions: a differentiable, twice-differentiable and a non-smooth term in a high dimensional setting. To this effect we propose and analyze a randomized block cubic Newton (RBCN) method, which in each iteration builds a model of the objective function formed as the sum of the natural models of its three components: a linear model with a quadratic regularizer for the differentiable term, a quadratic model with a cubic regularizer for the twice differentiable term, and perfect (proximal) model for the nonsmooth term. Our method in each iteration minimizes the model over a random subset of blocks of the search variable. RBCN is the first algorithm with these properties, generalizing several existing methods, matching the best known bounds in all special cases. We establish ${\\\\cal O}(1/\\\\epsilon)$, ${\\\\cal O}(1/\\\\sqrt{\\\\epsilon})$ and ${\\\\cal O}(\\\\log (1/\\\\epsilon))$ rates under different assumptions on the component functions. Lastly, we show numerically that our method outperforms the state-of-the-art on a variety of machine learning problems, including cubically regularized least-squares, logistic regression with constraints, and Poisson regression.

  2. Random regression models

    African Journals Online (AJOL)

    zlukovi

    modelled as a quadratic regression, nested within parity. The previous lactation length was ... This proportion was mainly covered by linear and quadratic coefficients. Results suggest that RRM could .... The multiple trait models in scalar notation are presented by equations (1, 2), while equation. (3) represents the random ...

  3. The Norwegian Healthier Goats program--modeling lactation curves using a multilevel cubic spline regression model.

    Science.gov (United States)

    Nagel-Alne, G E; Krontveit, R; Bohlin, J; Valle, P S; Skjerve, E; Sølverød, L S

    2014-07-01

    In 2001, the Norwegian Goat Health Service initiated the Healthier Goats program (HG), with the aim of eradicating caprine arthritis encephalitis, caseous lymphadenitis, and Johne's disease (caprine paratuberculosis) in Norwegian goat herds. The aim of the present study was to explore how control and eradication of the above-mentioned diseases by enrolling in HG affected milk yield by comparison with herds not enrolled in HG. Lactation curves were modeled using a multilevel cubic spline regression model where farm, goat, and lactation were included as random effect parameters. The data material contained 135,446 registrations of daily milk yield from 28,829 lactations in 43 herds. The multilevel cubic spline regression model was applied to 4 categories of data: enrolled early, control early, enrolled late, and control late. For enrolled herds, the early and late notations refer to the situation before and after enrolling in HG; for nonenrolled herds (controls), they refer to development over time, independent of HG. Total milk yield increased in the enrolled herds after eradication: the total milk yields in the fourth lactation were 634.2 and 873.3 kg in enrolled early and enrolled late herds, respectively, and 613.2 and 701.4 kg in the control early and control late herds, respectively. Day of peak yield differed between enrolled and control herds. The day of peak yield came on d 6 of lactation for the control early category for parities 2, 3, and 4, indicating an inability of the goats to further increase their milk yield from the initial level. For enrolled herds, on the other hand, peak yield came between d 49 and 56, indicating a gradual increase in milk yield after kidding. Our results indicate that enrollment in the HG disease eradication program improved the milk yield of dairy goats considerably, and that the multilevel cubic spline regression was a suitable model for exploring effects of disease control and eradication on milk yield. Copyright © 2014

  4. Damage Identification Based on Curvature Mode Shape using Cubic Polynomial Regression and Chebyshev Filters

    Science.gov (United States)

    Hasrizam, C. M.; Fawazi, Noor

    2017-11-01

    Structure Health Monitoring (SHM) has been applied in various application such as aerospace, machinery and civil structures to maintain structure’s safety and integrity. Gapped smoothing method (GSM) is most popular non-destructive identification (NDI) method due to its simplicity and did not require baseline data for comparisons. However, GSM is less accurate to detect wide size of damage in structure and cause false detection. Objective of this study is to propose a method to detect damage in structure using curvature mode shape data estimated from damaged structure and did not require data from undamaged structure. Finite element analysis (FEA) on a free-free boundary condition steel beam was carried out to demonstrate the feasibility of the proposed method that estimate undamaged curvature mode shape data using cubic polynomial regression (CPR) and Chebyshev filters (CF) methods. The results shows proposed method that used Chebyshev filters has better accuracy damage detection on wide notch compared to GSM. Although application of an interpolation and Chebyshev filters showed results with a high potential for overcoming the issue of false detection due to different notch size, however the proposed method still need refinement to better detection of different damage cases.

  5. Interpreting parameters in the logistic regression model with random effects

    DEFF Research Database (Denmark)

    Larsen, Klaus; Petersen, Jørgen Holm; Budtz-Jørgensen, Esben

    2000-01-01

    interpretation, interval odds ratio, logistic regression, median odds ratio, normally distributed random effects......interpretation, interval odds ratio, logistic regression, median odds ratio, normally distributed random effects...

  6. SDE based regression for random PDEs

    KAUST Repository

    Bayer, Christian

    2016-01-06

    A simulation based method for the numerical solution of PDE with random coefficients is presented. By the Feynman-Kac formula, the solution can be represented as conditional expectation of a functional of a corresponding stochastic differential equation driven by independent noise. A time discretization of the SDE for a set of points in the domain and a subsequent Monte Carlo regression lead to an approximation of the global solution of the random PDE. We provide an initial error and complexity analysis of the proposed method along with numerical examples illustrating its behaviour.

  7. Neither fixed nor random: weighted least squares meta-regression.

    Science.gov (United States)

    Stanley, T D; Doucouliagos, Hristos

    2017-03-01

    Our study revisits and challenges two core conventional meta-regression estimators: the prevalent use of 'mixed-effects' or random-effects meta-regression analysis and the correction of standard errors that defines fixed-effects meta-regression analysis (FE-MRA). We show how and explain why an unrestricted weighted least squares MRA (WLS-MRA) estimator is superior to conventional random-effects (or mixed-effects) meta-regression when there is publication (or small-sample) bias that is as good as FE-MRA in all cases and better than fixed effects in most practical applications. Simulations and statistical theory show that WLS-MRA provides satisfactory estimates of meta-regression coefficients that are practically equivalent to mixed effects or random effects when there is no publication bias. When there is publication selection bias, WLS-MRA always has smaller bias than mixed effects or random effects. In practical applications, an unrestricted WLS meta-regression is likely to give practically equivalent or superior estimates to fixed-effects, random-effects, and mixed-effects meta-regression approaches. However, random-effects meta-regression remains viable and perhaps somewhat preferable if selection for statistical significance (publication bias) can be ruled out and when random, additive normal heterogeneity is known to directly affect the 'true' regression coefficient. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  8. Evaluation of random forest regression for prediction of breeding ...

    Indian Academy of Sciences (India)

    cation of the random forest (RF), a model-free ensemble learning method, is not widely used for prediction. In this study, the ... [Sarkar R. K., Rao A. R., Meher P. K., Nepolean T. and Mohapatra T. 2015 Evaluation of random forest regression for prediction of breeding value from .... Ten-fold cross validation technique (Stone.

  9. Buffalos milk yield analysis using random regression models

    Directory of Open Access Journals (Sweden)

    A.S. Schierholt

    2010-02-01

    Full Text Available Data comprising 1,719 milk yield records from 357 females (predominantly Murrah breed, daughters of 110 sires, with births from 1974 to 2004, obtained from the Programa de Melhoramento Genético de Bubalinos (PROMEBUL and from records of EMBRAPA Amazônia Oriental - EAO herd, located in Belém, Pará, Brazil, were used to compare random regression models for estimating variance components and predicting breeding values of the sires. The data were analyzed by different models using the Legendre’s polynomial functions from second to fourth orders. The random regression models included the effects of herd-year, month of parity date of the control; regression coefficients for age of females (in order to describe the fixed part of the lactation curve and random regression coefficients related to the direct genetic and permanent environment effects. The comparisons among the models were based on the Akaike Infromation Criterion. The random effects regression model using third order Legendre’s polynomials with four classes of the environmental effect were the one that best described the additive genetic variation in milk yield. The heritability estimates varied from 0.08 to 0.40. The genetic correlation between milk yields in younger ages was close to the unit, but in older ages it was low.

  10. Generalized and synthetic regression estimators for randomized branch sampling

    Science.gov (United States)

    David L. R. Affleck; Timothy G. Gregoire

    2015-01-01

    In felled-tree studies, ratio and regression estimators are commonly used to convert more readily measured branch characteristics to dry crown mass estimates. In some cases, data from multiple trees are pooled to form these estimates. This research evaluates the utility of both tactics in the estimation of crown biomass following randomized branch sampling (...

  11. Bioprocess data mining using regularized regression and random forests.

    Science.gov (United States)

    Hassan, Syeda; Farhan, Muhammad; Mangayil, Rahul; Huttunen, Heikki; Aho, Tommi

    2013-01-01

    In bioprocess development, the needs of data analysis include (1) getting overview to existing data sets, (2) identifying primary control parameters, (3) determining a useful control direction, and (4) planning future experiments. In particular, the integration of multiple data sets causes that these needs cannot be properly addressed by regression models that assume linear input-output relationship or unimodality of the response function. Regularized regression and random forests, on the other hand, have several properties that may appear important in this context. They are capable, e.g., in handling small number of samples with respect to the number of variables, feature selection, and the visualization of response surfaces in order to present the prediction results in an illustrative way. In this work, the applicability of regularized regression (Lasso) and random forests (RF) in bioprocess data mining was examined, and their performance was benchmarked against multiple linear regression. As an example, we used data from a culture media optimization study for microbial hydrogen production. All the three methods were capable in providing a significant model when the five variables of the culture media optimization were linearly included in modeling. However, multiple linear regression failed when also the multiplications and squares of the variables were included in modeling. In this case, the modeling was still successful with Lasso (correlation between the observed and predicted yield was 0.69) and RF (0.91). We found that both regularized regression and random forests were able to produce feasible models, and the latter was efficient in capturing the non-linearity in the data. In this kind of a data mining task of bioprocess data, both methods outperform multiple linear regression.

  12. Bayesian Nonparametric Regression Analysis of Data with Random Effects Covariates from Longitudinal Measurements

    KAUST Repository

    Ryu, Duchwan

    2010-09-28

    We consider nonparametric regression analysis in a generalized linear model (GLM) framework for data with covariates that are the subject-specific random effects of longitudinal measurements. The usual assumption that the effects of the longitudinal covariate processes are linear in the GLM may be unrealistic and if this happens it can cast doubt on the inference of observed covariate effects. Allowing the regression functions to be unknown, we propose to apply Bayesian nonparametric methods including cubic smoothing splines or P-splines for the possible nonlinearity and use an additive model in this complex setting. To improve computational efficiency, we propose the use of data-augmentation schemes. The approach allows flexible covariance structures for the random effects and within-subject measurement errors of the longitudinal processes. The posterior model space is explored through a Markov chain Monte Carlo (MCMC) sampler. The proposed methods are illustrated and compared to other approaches, the "naive" approach and the regression calibration, via simulations and by an application that investigates the relationship between obesity in adulthood and childhood growth curves. © 2010, The International Biometric Society.

  13. A comparison of random forest regression and multiple linear regression for prediction in neuroscience.

    Science.gov (United States)

    Smith, Paul F; Ganesh, Siva; Liu, Ping

    2013-10-30

    Regression is a common statistical tool for prediction in neuroscience. However, linear regression is by far the most common form of regression used, with regression trees receiving comparatively little attention. In this study, the results of conventional multiple linear regression (MLR) were compared with those of random forest regression (RFR), in the prediction of the concentrations of 9 neurochemicals in the vestibular nucleus complex and cerebellum that are part of the l-arginine biochemical pathway (agmatine, putrescine, spermidine, spermine, l-arginine, l-ornithine, l-citrulline, glutamate and γ-aminobutyric acid (GABA)). The R(2) values for the MLRs were higher than the proportion of variance explained values for the RFRs: 6/9 of them were ≥ 0.70 compared to 4/9 for RFRs. Even the variables that had the lowest R(2) values for the MLRs, e.g. ornithine (0.50) and glutamate (0.61), had much lower proportion of variance explained values for the RFRs (0.27 and 0.49, respectively). The RSE values for the MLRs were lower than those for the RFRs in all but two cases. In general, MLRs seemed to be superior to the RFRs in terms of predictive value and error. In the case of this data set, MLR appeared to be superior to RFR in terms of its explanatory value and error. This result suggests that MLR may have advantages over RFR for prediction in neuroscience with this kind of data set, but that RFR can still have good predictive value in some cases. Copyright © 2013 Elsevier B.V. All rights reserved.

  14. Genetic evaluation of European quails by random regression models

    Directory of Open Access Journals (Sweden)

    Flaviana Miranda Gonçalves

    2012-09-01

    Full Text Available The objective of this study was to compare different random regression models, defined from different classes of heterogeneity of variance combined with different Legendre polynomial orders for the estimate of (covariance of quails. The data came from 28,076 observations of 4,507 female meat quails of the LF1 lineage. Quail body weights were determined at birth and 1, 14, 21, 28, 35 and 42 days of age. Six different classes of residual variance were fitted to Legendre polynomial functions (orders ranging from 2 to 6 to determine which model had the best fit to describe the (covariance structures as a function of time. According to the evaluated criteria (AIC, BIC and LRT, the model with six classes of residual variances and of sixth-order Legendre polynomial was the best fit. The estimated additive genetic variance increased from birth to 28 days of age, and dropped slightly from 35 to 42 days. The heritability estimates decreased along the growth curve and changed from 0.51 (1 day to 0.16 (42 days. Animal genetic and permanent environmental correlation estimates between weights and age classes were always high and positive, except for birth weight. The sixth order Legendre polynomial, along with the residual variance divided into six classes was the best fit for the growth rate curve of meat quails; therefore, they should be considered for breeding evaluation processes by random regression models.

  15. ESTIMATION OF GENETIC PARAMETERS IN TROPICARNE CATTLE WITH RANDOM REGRESSION MODELS USING B-SPLINES

    Directory of Open Access Journals (Sweden)

    Joel Domínguez Viveros

    2015-04-01

    Full Text Available The objectives were to estimate variance components, and direct (h2 and maternal (m2 heritability in the growth of Tropicarne cattle based on a random regression model using B-Splines for random effects modeling. Information from 12 890 monthly weightings of 1787 calves, from birth to 24 months old, was analyzed. The pedigree included 2504 animals. The random effects model included genetic and permanent environmental (direct and maternal of cubic order, and residuals. The fixed effects included contemporaneous groups (year – season of weighed, sex and the covariate age of the cow (linear and quadratic. The B-Splines were defined in four knots through the growth period analyzed. Analyses were performed with the software Wombat. The variances (phenotypic and residual presented a similar behavior; of 7 to 12 months of age had a negative trend; from birth to 6 months and 13 to 18 months had positive trend; after 19 months were maintained constant. The m2 were low and near to zero, with an average of 0.06 in an interval of 0.04 to 0.11; the h2 also were close to zero, with an average of 0.10 in an interval of 0.03 to 0.23.

  16. Calibration of stormwater quality regression models: a random process?

    Science.gov (United States)

    Dembélé, A; Bertrand-Krajewski, J-L; Barillon, B

    2010-01-01

    Regression models are among the most frequently used models to estimate pollutants event mean concentrations (EMC) in wet weather discharges in urban catchments. Two main questions dealing with the calibration of EMC regression models are investigated: i) the sensitivity of models to the size and the content of data sets used for their calibration, ii) the change of modelling results when models are re-calibrated when data sets grow and change with time when new experimental data are collected. Based on an experimental data set of 64 rain events monitored in a densely urbanised catchment, four TSS EMC regression models (two log-linear and two linear models) with two or three explanatory variables have been derived and analysed. Model calibration with the iterative re-weighted least squares method is less sensitive and leads to more robust results than the ordinary least squares method. Three calibration options have been investigated: two options accounting for the chronological order of the observations, one option using random samples of events from the whole available data set. Results obtained with the best performing non linear model clearly indicate that the model is highly sensitive to the size and the content of the data set used for its calibration.

  17. Cubic anisotropy created by defects of "random local anisotropy" type, and phase diagram of the O( n) Model

    Science.gov (United States)

    Berzin, A. A.; Morosov, A. I.; Sigov, A. S.

    2017-12-01

    The expression for the cubic-type-anisotropy constant created by defects of "random local anisotropy" type is derived. It is shown that the Imry-Ma theorem stating that in space dimensions d equilibrium one. At the defect concentration lower than the critical one the long-range order takes place in the system. For a strongly anisotropic distribution of the easy axes, the Imry-Ma state is suppressed completely and the long-range order state takes place at any defect concentration.

  18. Random forest regression for magnetic resonance image synthesis.

    Science.gov (United States)

    Jog, Amod; Carass, Aaron; Roy, Snehashis; Pham, Dzung L; Prince, Jerry L

    2017-01-01

    By choosing different pulse sequences and their parameters, magnetic resonance imaging (MRI) can generate a large variety of tissue contrasts. This very flexibility, however, can yield inconsistencies with MRI acquisitions across datasets or scanning sessions that can in turn cause inconsistent automated image analysis. Although image synthesis of MR images has been shown to be helpful in addressing this problem, an inability to synthesize both T2-weighted brain images that include the skull and FLuid Attenuated Inversion Recovery (FLAIR) images has been reported. The method described herein, called REPLICA, addresses these limitations. REPLICA is a supervised random forest image synthesis approach that learns a nonlinear regression to predict intensities of alternate tissue contrasts given specific input tissue contrasts. Experimental results include direct image comparisons between synthetic and real images, results from image analysis tasks on both synthetic and real images, and comparison against other state-of-the-art image synthesis methods. REPLICA is computationally fast, and is shown to be comparable to other methods on tasks they are able to perform. Additionally REPLICA has the capability to synthesize both T2-weighted images of the full head and FLAIR images, and perform intensity standardization between different imaging datasets. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. Comparison of Fixed Regression and Random Regression Test-Day Models for genetic evaluation of milk yield trait in Holstein cows Razavi Khorasan province

    Directory of Open Access Journals (Sweden)

    Y Shamshirgaran

    2011-12-01

    Full Text Available The Fixed Regression Test-Day Model (FRM and Random Regression Test-Day Model (RRM for genetic evaluation of milk yield trait of dairy cattle in Khorasan Razavi province were studied. Breeding values and genetic parameters of milk yield trait from two models were compared. A total of 164391 monthly test day milk records (three times milking per day obtained from 19217 Holstein cows distributed in 172 herds and calved from 1991 to 2008, were used to estimate genetic parameters and to predict breeding values. The contemporary group of herd- year- month of production was fitted as fixed effects in the models. Also linear and quadratic forms of age at calving and Holstein gene percentage were fitted as covariate. The random factors of the models were additive genetic and permanent environmental effects. In the random regression model, orthogonal legendre polynomial up to order 4(cubic was implemented to take account of genetic and environmental aspects of milk production over the course of lactation. Heritability estimates resulted from the FRM was 0.15. The average heritability estimates resulted from the RRM of monthly test day milk production for the second half of the lactation was higher than that of the first half of lactation period. The highest and lowest heritability values were found for the first (0.102 and sixth (0.235 month of lactation. Breeding value of animals predicted from FRM and RRM were also compared. The results showed similar ranking of animals based on their breeding values from both models.

  20. Random Walks on a Simple Cubic Lattice, the Multinomial Theorem, and Configurational Properties of Polymers

    Science.gov (United States)

    Hladky, Paul W.

    2007-01-01

    Random-climb models enable undergraduate chemistry students to visualize polymer molecules, quantify their configurational properties, and relate molecular structure to a variety of physical properties. The model could serve as an introduction to more elaborate models of polymer molecules and could help in learning topics such as lattice models of…

  1. A Unified Approach to Power Calculation and Sample Size Determination for Random Regression Models

    Science.gov (United States)

    Shieh, Gwowen

    2007-01-01

    The underlying statistical models for multiple regression analysis are typically attributed to two types of modeling: fixed and random. The procedures for calculating power and sample size under the fixed regression models are well known. However, the literature on random regression models is limited and has been confined to the case of all…

  2. Genetic parameters for various random regression models to describe the weight data of pigs

    NARCIS (Netherlands)

    Huisman, A.E.; Veerkamp, R.F.; Arendonk, van J.A.M.

    2002-01-01

    Various random regression models have been advocated for the fitting of covariance structures. It was suggested that a spline model would fit better to weight data than a random regression model that utilizes orthogonal polynomials. The objective of this study was to investigate which kind of random

  3. Genetic parameters for different random regression models to describe weight data of pigs

    NARCIS (Netherlands)

    Huisman, A.E.; Veerkamp, R.F.; Arendonk, van J.A.M.

    2001-01-01

    Various random regression models have been advocated for the fitting of covariance structures. It was suggested that a spline model would fit better to weight data than a random regression model that utilizes orthogonal polynomials. The objective of this study was to investigate which kind of random

  4. Natural Cubic Spline Regression Modeling Followed by Dynamic Network Reconstruction for the Identification of Radiation-Sensitivity Gene Association Networks from Time-Course Transcriptome Data.

    Science.gov (United States)

    Michna, Agata; Braselmann, Herbert; Selmansberger, Martin; Dietz, Anne; Hess, Julia; Gomolka, Maria; Hornhardt, Sabine; Blüthgen, Nils; Zitzelsberger, Horst; Unger, Kristian

    2016-01-01

    Gene expression time-course experiments allow to study the dynamics of transcriptomic changes in cells exposed to different stimuli. However, most approaches for the reconstruction of gene association networks (GANs) do not propose prior-selection approaches tailored to time-course transcriptome data. Here, we present a workflow for the identification of GANs from time-course data using prior selection of genes differentially expressed over time identified by natural cubic spline regression modeling (NCSRM). The workflow comprises three major steps: 1) the identification of differentially expressed genes from time-course expression data by employing NCSRM, 2) the use of regularized dynamic partial correlation as implemented in GeneNet to infer GANs from differentially expressed genes and 3) the identification and functional characterization of the key nodes in the reconstructed networks. The approach was applied on a time-resolved transcriptome data set of radiation-perturbed cell culture models of non-tumor cells with normal and increased radiation sensitivity. NCSRM detected significantly more genes than another commonly used method for time-course transcriptome analysis (BETR). While most genes detected with BETR were also detected with NCSRM the false-detection rate of NCSRM was low (3%). The GANs reconstructed from genes detected with NCSRM showed a better overlap with the interactome network Reactome compared to GANs derived from BETR detected genes. After exposure to 1 Gy the normal sensitive cells showed only sparse response compared to cells with increased sensitivity, which exhibited a strong response mainly of genes related to the senescence pathway. After exposure to 10 Gy the response of the normal sensitive cells was mainly associated with senescence and that of cells with increased sensitivity with apoptosis. We discuss these results in a clinical context and underline the impact of senescence-associated pathways in acute radiation response of normal

  5. Evaluation of random forest regression for prediction of breeding ...

    Indian Academy of Sciences (India)

    Model-based techniques have been widely used for prediction of breeding values of genotypes from genomewide association studies. However, application of the random forest (RF), a model-free ensemble learning method, is not widely used for prediction. In this study, the optimum values of tuning parameters of RF have ...

  6. Application of Random-Effects Probit Regression Models.

    Science.gov (United States)

    Gibbons, Robert D.; Hedeker, Donald

    1994-01-01

    Develops random-effects probit model for case in which outcome of interest is series of correlated binary responses, obtained as product of longitudinal response process where individual is repeatedly classified on binary outcome variable or in multilevel or clustered problems in which individuals within groups are considered to share…

  7. Random Decrement and Regression Analysis of Traffic Responses of Bridges

    DEFF Research Database (Denmark)

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

    1996-01-01

    The topic of this paper is the estimation of modal parameters from ambient data by applying the Random Decrement technique. The data fro the Queensborough Bridge over the Fraser River in Vancouver, Canada have been applied. The loads producing the dynamic response are ambient, e. g. wind, traffic...... and small ground motion. The random Decrement technique is used to estimate the correlation function or the free decays from the ambient data. From these functions, the modal parameters are extracted using the Ibrahim Time domain method. The possible influence of the traffic mass load on the bridge...... is investigated by assuming that the response level of the bridge is dependent on the mass of the vehicle load. The eigenfrequencies of the bridge is estimated as a function of the response level. This indicates the degree of influence of the mass load on the estimated eigenfrequencies. The results...

  8. Random Decrement and Regression Analysis of Traffic Responses of Bridges

    DEFF Research Database (Denmark)

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

    The topic of this paper is the estimation of modal parameters from ambient data by applying the Random Decrement technique. The data from the Queensborough Bridge over the Fraser River in Vancouver, Canada have been applied. The loads producing the dynamic response are ambient, e.g. wind, traffic...... and small ground motion. The Random Decrement technique is used to estimate the correlation function or the free decays from the ambient data. From these functions, the modal parameters are extracted using the Ibrahim Time Domain method. The possible influence of the traffic mass load on the bridge...... is investigated by assuming that the response level of the bridge is dependent on the mass of the vehicle load. The eigenfrequencies of the bridge are estimated as a function of the response level. This indicates the degree of influence of the mass load on the estimated eigenfrequencies. The results...

  9. Deriving Genomic Breeding Values for Residual Feed Intake from Covariance Functions of Random Regression Models

    DEFF Research Database (Denmark)

    Strathe, Anders B; Mark, Thomas; Nielsen, Bjarne

    Random regression models were used to estimate covariance functions between cumulated feed intake (CFI) and body weight (BW) in 8424 Danish Duroc pigs. Random regressions on second order Legendre polynomials of age were used to describe genetic and permanent environmental curves in BW and CFI. Ba...

  10. Technology diffusion in hospitals : A log odds random effects regression model

    NARCIS (Netherlands)

    Blank, J.L.T.; Valdmanis, V.G.

    2013-01-01

    This study identifies the factors that affect the diffusion of hospital innovations. We apply a log odds random effects regression model on hospital micro data. We introduce the concept of clustering innovations and the application of a log odds random effects regression model to describe the

  11. Technology diffusion in hospitals: A log odds random effects regression model

    NARCIS (Netherlands)

    J.L.T. Blank (Jos); V.G. Valdmanis (Vivian G.)

    2015-01-01

    textabstractThis study identifies the factors that affect the diffusion of hospital innovations. We apply a log odds random effects regression model on hospital micro data. We introduce the concept of clustering innovations and the application of a log odds random effects regression model to

  12. Random regression test-day model for the analysis of dairy cattle ...

    African Journals Online (AJOL)

    Random regression test-day model for the analysis of dairy cattle production data in South Africa: Creating the framework. EF Dzomba, KA Nephawe, AN Maiwashe, SWP Cloete, M Chimonyo, CB Banga, CJC Muller, K Dzama ...

  13. Random regression models in the evaluation of the growth curve of Simbrasil beef cattle

    NARCIS (Netherlands)

    Mota, M.; Marques, F.A.; Lopes, P.S.; Hidalgo, A.M.

    2013-01-01

    Random regression models were used to estimate the types and orders of random effects of (co)variance functions in the description of the growth trajectory of the Simbrasil cattle breed. Records for 7049 animals totaling 18,677 individual weighings were submitted to 15 models from the third to the

  14. Prediction models for clustered data: comparison of a random intercept and standard regression model.

    Science.gov (United States)

    Bouwmeester, Walter; Twisk, Jos W R; Kappen, Teus H; van Klei, Wilton A; Moons, Karel G M; Vergouwe, Yvonne

    2013-02-15

    When study data are clustered, standard regression analysis is considered inappropriate and analytical techniques for clustered data need to be used. For prediction research in which the interest of predictor effects is on the patient level, random effect regression models are probably preferred over standard regression analysis. It is well known that the random effect parameter estimates and the standard logistic regression parameter estimates are different. Here, we compared random effect and standard logistic regression models for their ability to provide accurate predictions. Using an empirical study on 1642 surgical patients at risk of postoperative nausea and vomiting, who were treated by one of 19 anesthesiologists (clusters), we developed prognostic models either with standard or random intercept logistic regression. External validity of these models was assessed in new patients from other anesthesiologists. We supported our results with simulation studies using intra-class correlation coefficients (ICC) of 5%, 15%, or 30%. Standard performance measures and measures adapted for the clustered data structure were estimated. The model developed with random effect analysis showed better discrimination than the standard approach, if the cluster effects were used for risk prediction (standard c-index of 0.69 versus 0.66). In the external validation set, both models showed similar discrimination (standard c-index 0.68 versus 0.67). The simulation study confirmed these results. For datasets with a high ICC (≥15%), model calibration was only adequate in external subjects, if the used performance measure assumed the same data structure as the model development method: standard calibration measures showed good calibration for the standard developed model, calibration measures adapting the clustered data structure showed good calibration for the prediction model with random intercept. The models with random intercept discriminate better than the standard model only

  15. Regression of left ventricular mass by antihypertensive treatment: a meta-analysis of randomized comparative studies.

    Science.gov (United States)

    Fagard, Robert H; Celis, Hilde; Thijs, Lutgarde; Wouters, Stijn

    2009-11-01

    Blood pressure-lowering therapy reduces left ventricular mass, but the question of whether differences exist among drug classes has not been fully resolved. Our aim was to compare the effects of diuretics, beta-blockers, calcium channel blockers, angiotensin-converting enzyme inhibitors, and angiotensin receptor blockers on left ventricular mass regression in patients with hypertension on the basis of prospective, randomized comparative studies. We performed meta-analyses, involving pooled pairwise comparisons of the drug classes and of each class versus other classes statistically combined, and meta-regression analyses to identify the determinants of the regression. The 75 relevant publications involved 84 pairwise comparisons and 6001 patients. Regression of left ventricular mass was significantly less (P=0.01) with beta-blockers (9.8%) than with angiotensin receptor blockers (12.5%), but none of the other analyzable pairwise comparisons between drug classes revealed significant differences (P>0.10). In addition, beta-blockers showed less regression than the other 4 classes statistically combined (Pmeta-regression analysis on all of the treatment arms, beta-blocker treatment was a significant and negative predictor of the regression (-3.6%; Pclasses, including angiotensin receptor blockers. In conclusion, beta-blockers show less regression of left ventricular mass, whereas angiotensin receptor blockers may induce larger regression. The inferiority of beta-blockers appears to be more convincing than the superiority of angiotensin receptor blockers.

  16. A random regression model in analysis of litter size in pigs | Lukovi& ...

    African Journals Online (AJOL)

    Dispersion parameters for number of piglets born alive (NBA) were estimated using a random regression model (RRM). Two data sets of litter records from the Nemščak farm in Slovenia were used for analyses. The first dataset (DS1) included records from the first to the sixth parity. The second dataset (DS2) was extended ...

  17. Subpixel urban land cover estimation: comparing cubist, random forests, and support vector regression

    Science.gov (United States)

    Jeffrey T. Walton

    2008-01-01

    Three machine learning subpixel estimation methods (Cubist, Random Forests, and support vector regression) were applied to estimate urban cover. Urban forest canopy cover and impervious surface cover were estimated from Landsat-7 ETM+ imagery using a higher resolution cover map resampled to 30 m as training and reference data. Three different band combinations (...

  18. Random regression models for daily feed intake in Danish Duroc pigs

    DEFF Research Database (Denmark)

    Strathe, Anders Bjerring; Mark, Thomas; Jensen, Just

    The objective of this study was to develop random regression models and estimate covariance functions for daily feed intake (DFI) in Danish Duroc pigs. A total of 476201 DFI records were available on 6542 Duroc boars between 70 to 160 days of age. The data originated from the National test statio...

  19. Semi-parametric estimation of random effects in a logistic regression model using conditional inference

    DEFF Research Database (Denmark)

    Petersen, Jørgen Holm

    2016-01-01

    This paper describes a new approach to the estimation in a logistic regression model with two crossed random effects where special interest is in estimating the variance of one of the effects while not making distributional assumptions about the other effect. A composite likelihood is studied...

  20. Genetic analysis of tolerance to infections using random regressions: a simulation study

    NARCIS (Netherlands)

    Kause, A.

    2011-01-01

    Tolerance to infections is the ability of a host to limit the impact of a given pathogen burden on host performance. This simulation study demonstrated the merit of using random regressions to estimate unbiased genetic variances for tolerance slope and its genetic correlations with other traits,

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

    Science.gov (United States)

    Wang, Wei; Griswold, Michael E.

    2016-01-01

    The random effect Tobit model is a regression model that accommodates both left- and/or right-censoring and within-cluster dependence of the outcome variable. Regression coefficients of random effect Tobit models have conditional interpretations on a constructed latent dependent variable and do not provide inference of overall exposure effects on the original outcome scale. Marginalized random effects model (MREM) permits likelihood-based estimation of marginal mean parameters for the clustered data. For random effect Tobit models, we extend the MREM to marginalize over both the random effects and the normal space and boundary components of the censored response to estimate overall exposure effects at population level. We also extend the ‘Average Predicted Value’ method to estimate the model-predicted marginal means for each person under different exposure status in a designated reference group by integrating over the random effects and then use the calculated difference to assess the overall exposure effect. The maximum likelihood estimation is proposed utilizing a quasi-Newton optimization algorithm with Gauss-Hermite quadrature to approximate the integration of the random effects. We use these methods to carefully analyze two real datasets. PMID:27449636

  2. Multiple Imputation of a Randomly Censored Covariate Improves Logistic Regression Analysis.

    Science.gov (United States)

    Atem, Folefac D; Qian, Jing; Maye, Jacqueline E; Johnson, Keith A; Betensky, Rebecca A

    2016-01-01

    Randomly censored covariates arise frequently in epidemiologic studies. The most commonly used methods, including complete case and single imputation or substitution, suffer from inefficiency and bias. They make strong parametric assumptions or they consider limit of detection censoring only. We employ multiple imputation, in conjunction with semi-parametric modeling of the censored covariate, to overcome these shortcomings and to facilitate robust estimation. We develop a multiple imputation approach for randomly censored covariates within the framework of a logistic regression model. We use the non-parametric estimate of the covariate distribution or the semiparametric Cox model estimate in the presence of additional covariates in the model. We evaluate this procedure in simulations, and compare its operating characteristics to those from the complete case analysis and a survival regression approach. We apply the procedures to an Alzheimer's study of the association between amyloid positivity and maternal age of onset of dementia. Multiple imputation achieves lower standard errors and higher power than the complete case approach under heavy and moderate censoring and is comparable under light censoring. The survival regression approach achieves the highest power among all procedures, but does not produce interpretable estimates of association. Multiple imputation offers a favorable alternative to complete case analysis and ad hoc substitution methods in the presence of randomly censored covariates within the framework of logistic regression.

  3. Vacancy-related diffusion correlation effects in a simple cubic random alloy and on the Na-K sublattice of alkali feldspar

    Science.gov (United States)

    Wilangowski, F.; Stolwijk, N. A.

    2015-07-01

    Motivated by the need to analyse experimental data on ionic conductivity in alkali feldspar, we performed Monte Carlo (MC) simulations of vacancy diffusion in random binary systems. We employed an efficient procedure for the calculation of the vacancy correlation factor ?, which includes the computation of the associated partial correlation factors (PCFs) ? and ?. Test simulations on a simple cubic lattice show the improvements compared to previous MC data and the discrepancies with the Manning model. Vacancy correlation factors on the Na-K sublattice in the monoclinic structure of alkali feldspar proved to be dependent on crystal orientation. For the ?-direction, PCFs related to the four different jump types were calculated. We also examined the percolation behaviour for extreme ratios of the atomic jump frequencies. The results are found to agree with known data for the simple cubic lattice. In the case of feldspar, we provide the first useful estimates for the percolation threshold and the associated critical exponent using a simplified set of jump frequencies.

  4. The limiting behavior of the estimated parameters in a misspecified random field regression model

    DEFF Research Database (Denmark)

    Dahl, Christian Møller; Qin, Yu

    This paper examines the limiting properties of the estimated parameters in the random field regression model recently proposed by Hamilton (Econometrica, 2001). Though the model is parametric, it enjoys the flexibility of the nonparametric approach since it can approximate a large collection......, as a consequence the random field model specification introduces non-stationarity and non-ergodicity in the misspecified model and it becomes non-trivial, relative to the existing literature, to establish the limiting behavior of the estimated parameters. The asymptotic results are obtained by applying some...

  5. Random Regression Models Based On The Skew Elliptically Contoured Distribution Assumptions With Applications To Longitudinal Data *

    Science.gov (United States)

    Zheng, Shimin; Rao, Uma; Bartolucci, Alfred A.; Singh, Karan P.

    2011-01-01

    Bartolucci et al.(2003) extended the distribution assumption from the normal (Lyles et al., 2000) to the elliptical contoured distribution (ECD) for random regression models used in analysis of longitudinal data accounting for both undetectable values and informative drop-outs. In this paper, the random regression models are constructed on the multivariate skew ECD. A real data set is used to illustrate that the skew ECDs can fit some unimodal continuous data better than the Gaussian distributions or more general continuous symmetric distributions when the symmetric distribution assumption is violated. Also, a simulation study is done for illustrating the model fitness from a variety of skew ECDs. The software we used is SAS/STAT, V. 9.13. PMID:21637734

  6. Maternal Smoking During Pregnancy and Childhood Growth Trajectory: A Random Effects Regression Analysis

    OpenAIRE

    Suzuki, Kohta; Kondo, Naoki; Sato, Miri; Tanaka, Taichiro; Ando, Daisuke; Yamagata, Zentaro

    2012-01-01

    Background Although maternal smoking during pregnancy has been reported to have an effect on childhood overweight/obesity, the impact of maternal smoking on the trajectory of the body mass of their offspring is not very clear. Previously, we investigated this effect by using a fixed-effect model. However, this analysis was limited because it rounded and categorized the age of the children. Therefore, we used a random-effects hierarchical linear regression model in the present study. Methods T...

  7. Weight evaluation of Tabapuã cattle raised in northeastern Brazil using random-regression models

    Directory of Open Access Journals (Sweden)

    M.R. Oliveira

    Full Text Available ABSTRACT The objective of this study is to compare random-regression models used to describe changes in evaluation parameters for growth in Tabapuã bovine raised in the Northeast of Brazilian. The M4532-5 random-regression model was found to be best for estimating the variation and heritability of growth characteristics in the animals evaluated. Estimates of direct additive genetic variance increased with age, while the maternal additive genetic variance demonstrated growth from birth to up to nearly 420 days of age. The genetic correlations between the first four characteristics were positive with moderate to large ranges. The greatest genetic correlation was observed between birth weight and at 240 days of age (0.82. The phenotypic correlation between birth weight and other characteristics was low. The M4532-5 random-regression model with 39 parameters was found to be best for describing the growth curve of the animals evaluated providing improved selection for heavier animals when performed after weaning. The interpretation of genetic parameters to predict the growth curve of cattle may allow the selection of animals to accelerate slaughter procedures.

  8. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression.

    Science.gov (United States)

    Bowden, Jack; Davey Smith, George; Burgess, Stephen

    2015-04-01

    The number of Mendelian randomization analyses including large numbers of genetic variants is rapidly increasing. This is due to the proliferation of genome-wide association studies, and the desire to obtain more precise estimates of causal effects. However, some genetic variants may not be valid instrumental variables, in particular due to them having more than one proximal phenotypic correlate (pleiotropy). We view Mendelian randomization with multiple instruments as a meta-analysis, and show that bias caused by pleiotropy can be regarded as analogous to small study bias. Causal estimates using each instrument can be displayed visually by a funnel plot to assess potential asymmetry. Egger regression, a tool to detect small study bias in meta-analysis, can be adapted to test for bias from pleiotropy, and the slope coefficient from Egger regression provides an estimate of the causal effect. Under the assumption that the association of each genetic variant with the exposure is independent of the pleiotropic effect of the variant (not via the exposure), Egger's test gives a valid test of the null causal hypothesis and a consistent causal effect estimate even when all the genetic variants are invalid instrumental variables. We illustrate the use of this approach by re-analysing two published Mendelian randomization studies of the causal effect of height on lung function, and the causal effect of blood pressure on coronary artery disease risk. The conservative nature of this approach is illustrated with these examples. An adaption of Egger regression (which we call MR-Egger) can detect some violations of the standard instrumental variable assumptions, and provide an effect estimate which is not subject to these violations. The approach provides a sensitivity analysis for the robustness of the findings from a Mendelian randomization investigation. © The Author 2015; Published by Oxford University Press on behalf of the International Epidemiological Association.

  9. Selection of locations of knots for linear splines in random regression test-day models.

    Science.gov (United States)

    Jamrozik, J; Bohmanova, J; Schaeffer, L R

    2010-04-01

    Using spline functions (segmented polynomials) in regression models requires the knowledge of the location of the knots. Knots are the points at which independent linear segments are connected. Optimal positions of knots for linear splines of different orders were determined in this study for different scenarios, using existing estimates of covariance functions and an optimization algorithm. The traits considered were test-day milk, fat and protein yields, and somatic cell score (SCS) in the first three lactations of Canadian Holsteins. Two ranges of days in milk (from 5 to 305 and from 5 to 365) were taken into account. In addition, four different populations of Holstein cows, from Australia, Canada, Italy and New Zealand, were examined with respect to first lactation (305 days) milk only. The estimates of genetic and permanent environmental covariance functions were based on single- and multiple-trait test-day models, with Legendre polynomials of order 4 as random regressions. A differential evolution algorithm was applied to find the best location of knots for splines of orders 4 to 7 and the criterion for optimization was the goodness-of-fit of the spline covariance function. Results indicated that the optimal position of knots for linear splines differed between genetic and permanent environmental effects, as well as between traits and lactations. Different populations also exhibited different patterns of optimal knot locations. With linear splines, different positions of knots should therefore be used for different effects and traits in random regression test-day models when analysing milk production traits.

  10. Random-effects regression analysis of correlated grouped-time survival data.

    Science.gov (United States)

    Hedeker, D; Siddiqui, O; Hu, F B

    2000-04-01

    Random-effects regression modelling is proposed for analysis of correlated grouped-time survival data. Two analysis approaches are considered. The first treats survival time as an ordinal outcome, which is either right-censored or not. The second approach treats survival time as a set of dichotomous indicators of whether the event occurred for time periods up to the period of the event or censor. For either approach both proportional hazards and proportional odds versions of the random-effects model are developed, while partial proportional hazards and odds generalizations are described for the latter approach. For estimation, a full-information maximum marginal likelihood solution is implemented using numerical quadrature to integrate over the distribution of multiple random effects. The quadrature solution allows some flexibility in the choice of distributions for the random effects; both normal and rectangular distributions are considered in this article. An analysis of a dataset where students are clustered within schools is used to illustrate features of random-effects analysis of clustered grouped-time survival data.

  11. Multiplicative random regression model for heterogeneous variance adjustment in genetic evaluation for milk yield in Simmental.

    Science.gov (United States)

    Lidauer, M H; Emmerling, R; Mäntysaari, E A

    2008-06-01

    A multiplicative random regression (M-RRM) test-day (TD) model was used to analyse daily milk yields from all available parities of German and Austrian Simmental dairy cattle. The method to account for heterogeneous variance (HV) was based on the multiplicative mixed model approach of Meuwissen. The variance model for the heterogeneity parameters included a fixed region x year x month x parity effect and a random herd x test-month effect with a within-herd first-order autocorrelation between test-months. Acceleration of variance model solutions after each multiplicative model cycle enabled fast convergence of adjustment factors and reduced total computing time significantly. Maximum Likelihood estimation of within-strata residual variances was enhanced by inclusion of approximated information on loss in degrees of freedom due to estimation of location parameters. This improved heterogeneity estimates for very small herds. The multiplicative model was compared with a model that assumed homogeneous variance. Re-estimated genetic variances, based on Mendelian sampling deviations, were homogeneous for the M-RRM TD model but heterogeneous for the homogeneous random regression TD model. Accounting for HV had large effect on cow ranking but moderate effect on bull ranking.

  12. Longitudinal Analysis of Residual Feed Intake in Mink using Random Regression with Heterogeneous Residual Variance

    DEFF Research Database (Denmark)

    Shirali, Mahmoud; Nielsen, Vivi Hunnicke; Møller, Steen Henrik

    at the end compared to the early growing period suggesting that heterogeneous residual variance should be considered for analyzing feed efficiency data in mink. This study suggests random regression methods are suitable for analyzing feed efficiency and that genetic selection for RFI in mink is promising.......Heritability of residual feed intake (RFI) increased from low to high over the growing period in male and female mink. The lowest heritability for RFI (male: 0.04 ± 0.01 standard deviation (SD); female: 0.05 ± 0.01 SD) was in early and the highest heritability (male: 0.33 ± 0.02; female: 0.34 ± 0...

  13. Predicting longitudinal trajectories of health probabilities with random-effects multinomial logit regression.

    Science.gov (United States)

    Liu, Xian; Engel, Charles C

    2012-12-20

    Researchers often encounter longitudinal health data characterized with three or more ordinal or nominal categories. Random-effects multinomial logit models are generally applied to account for potential lack of independence inherent in such clustered data. When parameter estimates are used to describe longitudinal processes, however, random effects, both between and within individuals, need to be retransformed for correctly predicting outcome probabilities. This study attempts to go beyond existing work by developing a retransformation method that derives longitudinal growth trajectories of unbiased health probabilities. We estimated variances of the predicted probabilities by using the delta method. Additionally, we transformed the covariates' regression coefficients on the multinomial logit function, not substantively meaningful, to the conditional effects on the predicted probabilities. The empirical illustration uses the longitudinal data from the Asset and Health Dynamics among the Oldest Old. Our analysis compared three sets of the predicted probabilities of three health states at six time points, obtained from, respectively, the retransformation method, the best linear unbiased prediction, and the fixed-effects approach. The results demonstrate that neglect of retransforming random errors in the random-effects multinomial logit model results in severely biased longitudinal trajectories of health probabilities as well as overestimated effects of covariates on the probabilities. Copyright © 2012 John Wiley & Sons, Ltd.

  14. Performance evaluation of random forest and support vector regressions in natural hazard change detection

    Science.gov (United States)

    Eisavi, Vahid; Homayouni, Saeid

    2016-10-01

    Information on land use and land cover changes is considered as a foremost requirement for monitoring environmental change. Developing change detection methodology in the remote sensing community is an active research topic. However, to the best of our knowledge, no research has been conducted so far on the application of random forest regression (RFR) and support vector regression (SVR) for natural hazard change detection from high-resolution optical remote sensing observations. Hence, the objective of this study is to examine the use of RFR and SVR to discriminate between changed and unchanged areas after a tsunami. For this study, RFR and SVR were applied to two different pilot coastlines in Indonesia and Japan. Two different remotely sensed data sets acquired by Quickbird and Ikonos sensors were used for efficient evaluation of the proposed methodology. The results demonstrated better performance of SVM compared to random forest (RF) with an overall accuracy higher by 3% to 4% and kappa coefficient by 0.05 to 0.07. Using McNemar's test, statistically significant differences (Z≥1.96), at the 5% significance level, between the confusion matrices of the RF classifier and the support vector classifier were observed in both study areas. The high accuracy of change detection obtained in this study confirms that these methods have the potential to be used for detecting changes due to natural hazards.

  15. Maternal smoking during pregnancy and childhood growth trajectory: a random effects regression analysis.

    Science.gov (United States)

    Suzuki, Kohta; Kondo, Naoki; Sato, Miri; Tanaka, Taichiro; Ando, Daisuke; Yamagata, Zentaro

    2012-01-01

    Although maternal smoking during pregnancy has been reported to have an effect on childhood overweight/obesity, the impact of maternal smoking on the trajectory of the body mass of their offspring is not very clear. Previously, we investigated this effect by using a fixed-effect model. However, this analysis was limited because it rounded and categorized the age of the children. Therefore, we used a random-effects hierarchical linear regression model in the present study. The study population comprised children born between 1 April 1991 and 31 March 1999 in Koshu City, Japan and their mothers. Maternal smoking during early pregnancy was the exposure studied. The body mass index (BMI) z-score trajectory of children born to smoking and non-smoking mothers, by gender, was used as the outcome. We modeled BMI trajectory using a 2-level random intercept and slope regression. The participating mothers delivered 1619 babies during the study period. For male children, there was very strong evidence that the effect of age in months on the increase in BMI z-score was enhanced by maternal smoking during pregnancy (P smoking during pregnancy (P = 0.054), which suggests that the effect of maternal smoking during pregnancy on the early-life BMI trajectory of offspring differed by gender. These results may be valuable for exploring the mechanism of fetal programming and might therefore be clinically important.

  16. Technology diffusion in hospitals: a log odds random effects regression model.

    Science.gov (United States)

    Blank, Jos L T; Valdmanis, Vivian G

    2015-01-01

    This study identifies the factors that affect the diffusion of hospital innovations. We apply a log odds random effects regression model on hospital micro data. We introduce the concept of clustering innovations and the application of a log odds random effects regression model to describe the diffusion of technologies. We distinguish a number of determinants, such as service, physician, and environmental, financial and organizational characteristics of the 60 Dutch hospitals in our sample. On the basis of this data set on Dutch general hospitals over the period 1995-2002, we conclude that there is a relation between a number of determinants and the diffusion of innovations underlining conclusions from earlier research. Positive effects were found on the basis of the size of the hospitals, competition and a hospital's commitment to innovation. It appears that if a policy is developed to further diffuse innovations, the external effects of demand and market competition need to be examined, which would de facto lead to an efficient use of technology. For the individual hospital, instituting an innovations office appears to be the most prudent course of action. © 2013 The Authors. International Journal of Health Planning and Management published by John Wiley & Sons, Ltd.

  17. Genetic evaluation of egg production curve in Thai native chickens by random regression and spline models.

    Science.gov (United States)

    Mookprom, S; Boonkum, W; Kunhareang, S; Siripanya, S; Duangjinda, M

    2017-02-01

    The objective of this research is to investigate appropriate random regression models with various covariance functions, for the genetic evaluation of test-day egg production. Data included 7,884 monthly egg production records from 657 Thai native chickens (Pradu Hang Dam) that were obtained during the first to sixth generation and were born during 2007 to 2014 at the Research and Development Network Center for Animal Breeding (Native Chickens), Khon Kaen University. Average annual and monthly egg productions were 117 ± 41 and 10.20 ± 6.40 eggs, respectively. Nine random regression models were analyzed using the Wilmink function (WM), Koops and Grossman function (KG), Legendre polynomials functions with second, third, and fourth orders (LG2, LG3, LG4), and spline functions with 4, 5, 6, and 8 knots (SP4, SP5, SP6, and SP8). All covariance functions were nested within the same additive genetic and permanent environmental random effects, and the variance components were estimated by Restricted Maximum Likelihood (REML). In model comparisons, mean square error (MSE) and the coefficient of detemination (R2) calculated the goodness of fit; and the correlation between observed and predicted values [Formula: see text] was used to calculate the cross-validated predictive abilities. We found that the covariance functions of SP5, SP6, and SP8 proved appropriate for the genetic evaluation of the egg production curves for Thai native chickens. The estimated heritability of monthly egg production ranged from 0.07 to 0.39, and the highest heritability was found during the first to third months of egg production. In conclusion, the spline functions within monthly egg production can be applied to breeding programs for the improvement of both egg number and persistence of egg production. © 2016 Poultry Science Association Inc.

  18. Is pancreaticogastrostomy safer than pancreaticojejunostomy after pancreaticoduodenectomy? A meta-regression analysis of randomized clinical trials.

    Science.gov (United States)

    Ricci, Claudio; Casadei, Riccardo; Taffurelli, Giovanni; Pacilio, Carlo Alberto; Beltrami, Denis; Minni, Francesco

    To evaluate the clinically relevant POPF rate between Pancreatogastrostomy (PG) and pancreaticojejunostomy (PJ) after pancreaticoduodenectomy (PD). To evaluate the confounding factors affecting meta-analytic results. A systematic literature search of randomized clinical trials (RCTs) comparing PG to PJ with an International Study Group of Pancreatic Fistula (ISGPF) definition of postoperative pancreatic fistula (POPF). Risk difference (RD) and number needed to treat or harm (NNT and NNH) were used. Fixed and random-effect models were applied. Impact of confounding covariates on the meta-analytic results was evaluated using meta-regression analysis, reporting β coefficient ± standard error (SE). Seven RCTs were identified involving 1184 patients: 603 PG and 581 PJ. RD in the fixed model of clinically relevant POPFs suggested that PG was superior to PJ (RD-0.07; 95% CI: -0.11 to -0.03) with an NNT of 14 (95% CI: 9 to 33). In random model, PG was not superior to PJ (RD-0.06; 95% CI: -0.13 to 0.01) with an NNT of 17 and a possibility of harm in some cases (NNH = 100). Meta-regression suggested that the increase in the proportion of "soft pancreas" in the PG arm corresponded to a more positive value of RD (β = 0.47 ± 0.19; P value: 0.045 ± 0.003). A PG could be slightly superior to PJ in the prevention of clinically relevant POPF. The presence of high risk pancreatic remnant remains the main limitation of PG. Copyright © 2017. Published by Elsevier B.V.

  19. A review of R-packages for random-intercept probit regression in small clusters

    Directory of Open Access Journals (Sweden)

    Haeike Josephy

    2016-10-01

    Full Text Available Generalized Linear Mixed Models (GLMMs are widely used to model clustered categorical outcomes. To tackle the intractable integration over the random effects distributions, several approximation approaches have been developed for likelihood-based inference. As these seldom yield satisfactory results when analyzing binary outcomes from small clusters, estimation within the Structural Equation Modeling (SEM framework is proposed as an alternative. We compare the performance of R-packages for random-intercept probit regression relying on: the Laplace approximation, adaptive Gaussian quadrature (AGQ, penalized quasi-likelihood, an MCMC-implementation, and integrated nested Laplace approximation within the GLMM-framework, and a robust diagonally weighted least squares estimation within the SEM-framework. In terms of bias for the fixed and random effect estimators, SEM usually performs best for cluster size two, while AGQ prevails in terms of precision (mainly because of SEM's robust standard errors. As the cluster size increases, however, AGQ becomes the best choice for both bias and precision.

  20. Random regression models for milk, fat and protein in Colombian Buffaloes

    Directory of Open Access Journals (Sweden)

    Naudin Hurtado-Lugo

    2015-01-01

    Full Text Available Objective. Covariance functions for additive genetic and permanent environmental effects and, subsequently, genetic parameters for test-day milk (MY, fat (FY protein (PY yields and mozzarella cheese (MP in buffaloes from Colombia were estimate by using Random regression models (RRM with Legendre polynomials (LP. Materials and Methods. Test-day records of MY, FY, PY and MP from 1884 first lactations of buffalo cows from 228 sires were analyzed. The animals belonged to 14 herds in Colombia between 1995 and 2011. Ten monthly classes of days in milk were considered for test-day yields. The contemporary groups were defined as herd-year-month of milk test-day. Random additive genetic, permanent environmental and residual effects were included in the model. Fixed effects included the contemporary group, linear and quadratic effects of age at calving, and the average lactation curve of the population, which was modeled by third-order LP. Random additive genetic and permanent environmental effects were estimated by RRM using third- to- sixth-order LP. Residual variances were modeled using homogeneous and heterogeneous structures. Results. The heritabilities for MY, FY, PY and MP ranged from 0.38 to 0.05, 0.67 to 0.11, 0.50 to 0.07 and 0.50 to 0.11, respectively. Conclusions. In general, the RRM are adequate to describe the genetic variation in test-day of MY, FY, PY and MP in Colombian buffaloes.

  1. Treatment comparison in randomized clinical trials with nonignorable missingness: A reverse regression approach.

    Science.gov (United States)

    Zhang, Zhiwei; Cheon, Kyeongmi

    2017-04-01

    A common problem in randomized clinical trials is nonignorable missingness, namely that the clinical outcome(s) of interest can be missing in a way that is not fully explained by the observed quantities. This happens when the continued participation of patients depends on the current outcome after adjusting for the observed history. Standard methods for handling nonignorable missingness typically require specification of the response mechanism, which can be difficult in practice. This article proposes a reverse regression approach that does not require a model for the response mechanism. Instead, the proposed approach relies on the assumption that missingness is independent of treatment assignment upon conditioning on the relevant outcome(s). This conditional independence assumption is motivated by the observation that, when patients are effectively masked to the assigned treatment, their decision to either stay in the trial or drop out cannot depend on the assigned treatment directly. Under this assumption, one can estimate parameters in the reverse regression model, test for the presence of a treatment effect, and in some cases estimate the outcome distributions. The methodology can be extended to longitudinal outcomes under natural conditions. The proposed approach is illustrated with real data from a cardiovascular study.

  2. A general instrumental variable framework for regression analysis with outcome missing not at random.

    Science.gov (United States)

    Tchetgen Tchetgen, Eric J; Wirth, Kathleen E

    2017-02-23

    The instrumental variable (IV) design is a well-known approach for unbiased evaluation of causal effects in the presence of unobserved confounding. In this article, we study the IV approach to account for selection bias in regression analysis with outcome missing not at random. In such a setting, a valid IV is a variable which (i) predicts the nonresponse process, and (ii) is independent of the outcome in the underlying population. We show that under the additional assumption (iii) that the IV is independent of the magnitude of selection bias due to nonresponse, the population regression in view is nonparametrically identified. For point estimation under (i)-(iii), we propose a simple complete-case analysis which modifies the regression of primary interest by carefully incorporating the IV to account for selection bias. The approach is developed for the identity, log and logit link functions. For inferences about the marginal mean of a binary outcome assuming (i) and (ii) only, we describe novel and approximately sharp bounds which unlike Robins-Manski bounds, are smooth in model parameters, therefore allowing for a straightforward approach to account for uncertainty due to sampling variability. These bounds provide a more honest account of uncertainty and allows one to assess the extent to which a violation of the key identifying condition (iii) might affect inferences. For illustration, the methods are used to account for selection bias induced by HIV testing nonparticipation in the evaluation of HIV prevalence in the Zambian Demographic and Health Surveys. © 2017, The International Biometric Society.

  3. Genetic evaluation for persistency of lactation in Holstein cows using a random regression model

    Directory of Open Access Journals (Sweden)

    Jaime Araujo Cobuci

    2007-03-01

    Full Text Available A model for analyzing test day records including both fixed and random coefficients was applied to the genetic evaluation of first lactation data for Holstein cows. Data comprising 87045 test-day milk yield records from calving between 1997 and 2001 from Holstein herds in 10 regions of the Brazilian state of Minas Gerais. Six persistency of lactation measures were evaluated using breeding values obtained by random regression analyses. The Wilmink function was used to model the additive genetic and permanent environmental effects. Residual variance was constant throughout lactation. Ranking for animals did not change among criteria for persistency measurements, but ranking changes were observed when the estimated breeding value (EBV for persistency of lactation was contrasted with those estimated for 305-day milk yield (305MY. The rank correlation estimates for persistency of lactation and 305MY were practically the same for sire and cows, and ranged from -0.45 to 0.69. The EBVs for milk yield during lactation for sires producing daughters with superior 305MY indicate genetic differences between sires regarding their ability to transmit desirable persistency of lactation traits. This suggests that selection for total lactation milk yield does not identify sires or cows that are genetically superior in regard to persistency of lactation. Genetic evaluation for persistency of lactation is important for improving the efficiency of the milk production capacity of Holstein cows.

  4. Systematic review of treatment modalities for gingival depigmentation: a random-effects poisson regression analysis.

    Science.gov (United States)

    Lin, Yi Hung; Tu, Yu Kang; Lu, Chun Tai; Chung, Wen Chen; Huang, Chiung Fang; Huang, Mao Suan; Lu, Hsein Kun

    2014-01-01

    Repigmentation variably occurs with different treatment methods in patients with gingival pigmentation. A systemic review was conducted of various treatment modalities for eliminating melanin pigmentation of the gingiva, comprising bur abrasion, scalpel surgery, cryosurgery, electrosurgery, gingival grafts, and laser techniques, to compare the recurrence rates (Rrs) of these treatment procedures. Electronic databases, including PubMed, Web of Science, Google, and Medline were comprehensively searched, and manual searches were conducted for studies published from January 1951 to June 2013. After applying inclusion and exclusion criteria, the final list of articles was reviewed in depth to achieve the objectives of this review. A Poisson regression was used to analyze the outcome of depigmentation using the various treatment methods. The systematic review was based on case reports mainly. In total, 61 eligible publications met the defined criteria. The various therapeutic procedures showed variable clinical results with a wide range of Rrs. A random-effects Poisson regression showed that cryosurgery (Rr = 0.32%), electrosurgery (Rr = 0.74%), and laser depigmentation (Rr = 1.16%) yielded superior result, whereas bur abrasion yielded the highest Rr (8.89%). Within the limit of the sampling level, the present evidence-based results show that cryosurgery exhibits the optimal predictability for depigmentation of the gingiva among all procedures examined, followed by electrosurgery and laser techniques. It is possible to treat melanin pigmentation of the gingiva with various methods and prevent repigmentation. Among those treatment modalities, cryosurgery, electrosurgery, and laser surgery appear to be the best choices for treating gingival pigmentation. © 2014 Wiley Periodicals, Inc.

  5. Milk yield persistency in Brazilian Gyr cattle based on a random regression model.

    Science.gov (United States)

    Pereira, R J; Verneque, R S; Lopes, P S; Santana, M L; Lagrotta, M R; Torres, R A; Vercesi Filho, A E; Machado, M A

    2012-06-15

    With the objective of evaluating measures of milk yield persistency, 27,000 test-day milk yield records from 3362 first lactations of Brazilian Gyr cows that calved between 1990 and 2007 were analyzed with a random regression model. Random, additive genetic and permanent environmental effects were modeled using Legendre polynomials of order 4 and 5, respectively. Residual variance was modeled using five classes. The average lactation curve was modeled using a fourth-order Legendre polynomial. Heritability estimates for measures of persistency ranged from 0.10 to 0.25. Genetic correlations between measures of persistency and 305-day milk yield (Y305) ranged from -0.52 to 0.03. At high selection intensities for persistency measures and Y305, few animals were selected in common. As the selection intensity for the two traits decreased, a higher percentage of animals were selected in common. The average predicted breeding values for Y305 according to year of birth of the cows had a substantial annual genetic gain. In contrast, no improvement in the average persistency breeding value was observed. We conclude that selection for total milk yield during lactation does not identify bulls or cows that are genetically superior in terms of milk yield persistency. A measure of persistency represented by the sum of deviations of estimated breeding value for days 31 to 280 in relation to estimated breeding value for day 30 should be preferred in genetic evaluations of this trait in the Gyr breed, since this measure showed a medium heritability and a genetic correlation with 305-day milk yield close to zero. In addition, this measure is more adequate at the time of peak lactation, which occurs between days 25 and 30 after calving in this breed.

  6. Multi-fidelity Gaussian process regression for prediction of random fields

    Energy Technology Data Exchange (ETDEWEB)

    Parussini, L. [Department of Engineering and Architecture, University of Trieste (Italy); Venturi, D., E-mail: venturi@ucsc.edu [Department of Applied Mathematics and Statistics, University of California Santa Cruz (United States); Perdikaris, P. [Department of Mechanical Engineering, Massachusetts Institute of Technology (United States); Karniadakis, G.E. [Division of Applied Mathematics, Brown University (United States)

    2017-05-01

    We propose a new multi-fidelity Gaussian process regression (GPR) approach for prediction of random fields based on observations of surrogate models or hierarchies of surrogate models. Our method builds upon recent work on recursive Bayesian techniques, in particular recursive co-kriging, and extends it to vector-valued fields and various types of covariances, including separable and non-separable ones. The framework we propose is general and can be used to perform uncertainty propagation and quantification in model-based simulations, multi-fidelity data fusion, and surrogate-based optimization. We demonstrate the effectiveness of the proposed recursive GPR techniques through various examples. Specifically, we study the stochastic Burgers equation and the stochastic Oberbeck–Boussinesq equations describing natural convection within a square enclosure. In both cases we find that the standard deviation of the Gaussian predictors as well as the absolute errors relative to benchmark stochastic solutions are very small, suggesting that the proposed multi-fidelity GPR approaches can yield highly accurate results.

  7. Combinations of Stressors in Midlife: Examining Role and Domain Stressors Using Regression Trees and Random Forests

    Science.gov (United States)

    2013-01-01

    Objectives. Global perceptions of stress (GPS) have major implications for mental and physical health, and stress in midlife may influence adaptation in later life. Thus, it is important to determine the unique and interactive effects of diverse influences of role stress (at work or in personal relationships), loneliness, life events, time pressure, caregiving, finances, discrimination, and neighborhood circumstances on these GPS. Method. Exploratory regression trees and random forests were used to examine complex interactions among myriad events and chronic stressors in middle-aged participants’ (N = 410; mean age = 52.12) GPS. Results. Different role and domain stressors were influential at high and low levels of loneliness. Varied combinations of these stressors resulting in similar levels of perceived stress are also outlined as examples of equifinality. Loneliness emerged as an important predictor across trees. Discussion. Exploring multiple stressors simultaneously provides insights into the diversity of stressor combinations across individuals—even those with similar levels of global perceived stress—and answers theoretical mandates to better understand the influence of stress by sampling from many domain and role stressors. Further, the unique influences of each predictor relative to the others inform theory and applied work. Finally, examples of equifinality and multifinality call for targeted interventions. PMID:23341437

  8. Box-Cox Transformation and Random Regression Models for Fecal egg Count Data.

    Science.gov (United States)

    da Silva, Marcos Vinícius Gualberto Barbosa; Van Tassell, Curtis P; Sonstegard, Tad S; Cobuci, Jaime Araujo; Gasbarre, Louis C

    2011-01-01

    Accurate genetic evaluation of livestock is based on appropriate modeling of phenotypic measurements. In ruminants, fecal egg count (FEC) is commonly used to measure resistance to nematodes. FEC values are not normally distributed and logarithmic transformations have been used in an effort to achieve normality before analysis. However, the transformed data are often still not normally distributed, especially when data are extremely skewed. A series of repeated FEC measurements may provide information about the population dynamics of a group or individual. A total of 6375 FEC measures were obtained for 410 animals between 1992 and 2003 from the Beltsville Agricultural Research Center Angus herd. Original data were transformed using an extension of the Box-Cox transformation to approach normality and to estimate (co)variance components. We also proposed using random regression models (RRM) for genetic and non-genetic studies of FEC. Phenotypes were analyzed using RRM and restricted maximum likelihood. Within the different orders of Legendre polynomials used, those with more parameters (order 4) adjusted FEC data best. Results indicated that the transformation of FEC data utilizing the Box-Cox transformation family was effective in reducing the skewness and kurtosis, and dramatically increased estimates of heritability, and measurements of FEC obtained in the period between 12 and 26 weeks in a 26-week experimental challenge period are genetically correlated.

  9. BOX-COX transformation and random regression models for fecal egg count data

    Directory of Open Access Journals (Sweden)

    Marcos Vinicius Silva

    2012-01-01

    Full Text Available Accurate genetic evaluation of livestock is based on appropriate modeling of phenotypic measurements. In ruminants fecal egg count (FEC is commonly used to measure resistance to nematodes. FEC values are not normally distributed and logarithmic transformations have been used to achieve normality before analysis. However, the transformed data are often not normally distributed, especially when data are extremely skewed. A series of repeated FEC measurements may provide information about the population dynamics of a group or individual. A total of 6,375 FEC measures were obtained for 410 animals between 1992 and 2003 from the Beltsville Agricultural Research Center Angus herd. Original data were transformed using an extension of the Box-Cox transformation to approach normality and to estimate (covariance components. We also proposed using random regression models (RRM for genetic and non-genetic studies of FEC. Phenotypes were analyzed using RRM and restricted maximum likelihood. Within the different orders of Legendre polynomials used, those with more parameters (order 4 adjusted FEC data best. Results indicated that the transformation of FEC data utilizing the Box-Cox transformation family was effective in reducing the skewness and kurtosis, and dramatically increased estimates of heritability, and measurements of FEC obtained in the period between 12 and 26 weeks in a 26-week experimental challenge period are genetically correlated.

  10. Genetic Parameters for Milk Yield and Lactation Persistency Using Random Regression Models in Girolando Cattle

    Directory of Open Access Journals (Sweden)

    Ali William Canaza-Cayo

    2015-10-01

    Full Text Available A total of 32,817 test-day milk yield (TDMY records of the first lactation of 4,056 Girolando cows daughters of 276 sires, collected from 118 herds between 2000 and 2011 were utilized to estimate the genetic parameters for TDMY via random regression models (RRM using Legendre’s polynomial functions whose orders varied from 3 to 5. In addition, nine measures of persistency in milk yield (PSi and the genetic trend of 305-day milk yield (305MY were evaluated. The fit quality criteria used indicated RRM employing the Legendre’s polynomial of orders 3 and 5 for fitting the genetic additive and permanent environment effects, respectively, as the best model. The heritability and genetic correlation for TDMY throughout the lactation, obtained with the best model, varied from 0.18 to 0.23 and from −0.03 to 1.00, respectively. The heritability and genetic correlation for persistency and 305MY varied from 0.10 to 0.33 and from −0.98 to 1.00, respectively. The use of PS7 would be the most suitable option for the evaluation of Girolando cattle. The estimated breeding values for 305MY of sires and cows showed significant and positive genetic trends. Thus, the use of selection indices would be indicated in the genetic evaluation of Girolando cattle for both traits.

  11. Microbiome Data Accurately Predicts the Postmortem Interval Using Random Forest Regression Models

    Directory of Open Access Journals (Sweden)

    Aeriel Belk

    2018-02-01

    Full Text Available Death investigations often include an effort to establish the postmortem interval (PMI in cases in which the time of death is uncertain. The postmortem interval can lead to the identification of the deceased and the validation of witness statements and suspect alibis. Recent research has demonstrated that microbes provide an accurate clock that starts at death and relies on ecological change in the microbial communities that normally inhabit a body and its surrounding environment. Here, we explore how to build the most robust Random Forest regression models for prediction of PMI by testing models built on different sample types (gravesoil, skin of the torso, skin of the head, gene markers (16S ribosomal RNA (rRNA, 18S rRNA, internal transcribed spacer regions (ITS, and taxonomic levels (sequence variants, species, genus, etc.. We also tested whether particular suites of indicator microbes were informative across different datasets. Generally, results indicate that the most accurate models for predicting PMI were built using gravesoil and skin data using the 16S rRNA genetic marker at the taxonomic level of phyla. Additionally, several phyla consistently contributed highly to model accuracy and may be candidate indicators of PMI.

  12. Prediction of residual feed intake for first-lactation dairy cows using orthogonal polynomial random regression.

    Science.gov (United States)

    Manafiazar, G; McFadden, T; Goonewardene, L; Okine, E; Basarab, J; Li, P; Wang, Z

    2013-01-01

    Residual Feed Intake (RFI) is a measure of energy efficiency. Developing an appropriate model to predict expected energy intake while accounting for multifunctional energy requirements of metabolic body weight (MBW), empty body weight (EBW), milk production energy requirements (MPER), and their nonlinear lactation profiles, is the key to successful prediction of RFI in dairy cattle. Individual daily actual energy intake and monthly body weight of 281 first-lactation dairy cows from 1 to 305 d in milk were recorded at the Dairy Research and Technology Centre of the University of Alberta (Edmonton, AB, Canada); individual monthly milk yield and compositions were obtained from the Dairy Herd Improvement Program. Combinations of different orders (1-5) of fixed (F) and random (R) factors were fitted using Legendre polynomial regression to model the nonlinear lactation profiles of MBW, EBW, and MPER over 301 d. The F5R3, F5R3, and F5R2 (subscripts indicate the order fitted) models were selected, based on the combination of the log-likelihood ratio test and the Bayesian information criterion, as the best prediction equations for MBW, EBW, and MPER, respectively. The selected models were used to predict daily individual values for these traits. To consider the body reserve changes, the differences of predicted EBW between 2 consecutive days were considered as the EBW change between these days. The smoothed total 301-d actual energy intake was then linearly regressed on the total 301-d predicted traits of MBW, EBW change, and MPER to obtain the first-lactation RFI (coefficient of determination=0.68). The mean of predicted daily average lactation RFI was 0 and ranged from -6.58 to 8.64 Mcal of NE(L)/d. Fifty-one percent of the animals had an RFI value below the mean (efficient) and 49% of them had an RFI value above the mean (inefficient). These results indicate that the first-lactation RFI can be predicted from its component traits with a reasonable coefficient of

  13. Appraisal, coping, emotion, and performance during elite fencing matches: a random coefficient regression model approach.

    Science.gov (United States)

    Doron, J; Martinent, G

    2017-09-01

    Understanding more about the stress process is important for the performance of athletes during stressful situations. Grounded in Lazarus's (1991, 1999, 2000) CMRT of emotion, this study tracked longitudinally the relationships between cognitive appraisal, coping, emotions, and performance in nine elite fencers across 14 international matches (representing 619 momentary assessments) using a naturalistic, video-assisted methodology. A series of hierarchical linear modeling analyses were conducted to: (a) explore the relationships between cognitive appraisals (challenge and threat), coping strategies (task- and disengagement oriented coping), emotions (positive and negative) and objective performance; (b) ascertain whether the relationship between appraisal and emotion was mediated by coping; and (c) examine whether the relationship between appraisal and objective performance was mediated by emotion and coping. The results of the random coefficient regression models showed: (a) positive relationships between challenge appraisal, task-oriented coping, positive emotions, and performance, as well as between threat appraisal, disengagement-oriented coping and negative emotions; (b) that disengagement-oriented coping partially mediated the relationship between threat and negative emotions, whereas task-oriented coping partially mediated the relationship between challenge and positive emotions; and (c) that disengagement-oriented coping mediated the relationship between threat and performance, whereas task-oriented coping and positive emotions partially mediated the relationship between challenge and performance. As a whole, this study furthered knowledge during sport performance situations of Lazarus's (1999) claim that these psychological constructs exist within a conceptual unit. Specifically, our findings indicated that the ways these constructs are inter-related influence objective performance within competitive settings. © 2016 John Wiley & Sons A/S. Published by

  14. Comparing cluster-level dynamic treatment regimens using sequential, multiple assignment, randomized trials: Regression estimation and sample size considerations.

    Science.gov (United States)

    NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel

    2017-08-01

    Cluster-level dynamic treatment regimens can be used to guide sequential treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level dynamic treatment regimen, the treatment is potentially adapted and re-adapted over time based on changes in the cluster that could be impacted by prior intervention, including aggregate measures of the individuals or patients that compose it. Cluster-randomized sequential multiple assignment randomized trials can be used to answer multiple open questions preventing scientists from developing high-quality cluster-level dynamic treatment regimens. In a cluster-randomized sequential multiple assignment randomized trial, sequential randomizations occur at the cluster level and outcomes are observed at the individual level. This manuscript makes two contributions to the design and analysis of cluster-randomized sequential multiple assignment randomized trials. First, a weighted least squares regression approach is proposed for comparing the mean of a patient-level outcome between the cluster-level dynamic treatment regimens embedded in a sequential multiple assignment randomized trial. The regression approach facilitates the use of baseline covariates which is often critical in the analysis of cluster-level trials. Second, sample size calculators are derived for two common cluster-randomized sequential multiple assignment randomized trial designs for use when the primary aim is a between-dynamic treatment regimen comparison of the mean of a continuous patient-level outcome. The methods are motivated by the Adaptive Implementation of Effective Programs Trial which is, to our knowledge, the first-ever cluster-randomized sequential multiple assignment randomized trial in psychiatry.

  15. Predicting attention-deficit/hyperactivity disorder severity from psychosocial stress and stress-response genes: a random forest regression approach

    NARCIS (Netherlands)

    Meer, D. van der; Hoekstra, P.J.; Donkelaar, M.M.J. van; Bralten, J.B.; Oosterlaan, J.; Heslenfeld, D.; Faraone, S.V; Franke, B.; Buitelaar, J.K.; Hartman, C.A.

    2017-01-01

    Identifying genetic variants contributing to attention-deficit/hyperactivity disorder (ADHD) is complicated by the involvement of numerous common genetic variants with small effects, interacting with each other as well as with environmental factors, such as stress exposure. Random forest regression

  16. Genetic Parameters for Body condition score, Body weigth, Milk yield and Fertility estimated using random regression models

    NARCIS (Netherlands)

    Berry, D.P.; Buckley, F.; Dillon, P.; Evans, R.D.; Rath, M.; Veerkamp, R.F.

    2003-01-01

    Genetic (co)variances between body condition score (BCS), body weight (BW), milk yield, and fertility were estimated using a random regression animal model extended to multivariate analysis. The data analyzed included 81,313 BCS observations, 91,937 BW observations, and 100,458 milk test-day yields

  17. Variances in the projections, resulting from CLIMEX, Boosted Regression Trees and Random Forests techniques

    Science.gov (United States)

    Shabani, Farzin; Kumar, Lalit; Solhjouy-fard, Samaneh

    2017-08-01

    The aim of this study was to have a comparative investigation and evaluation of the capabilities of correlative and mechanistic modeling processes, applied to the projection of future distributions of date palm in novel environments and to establish a method of minimizing uncertainty in the projections of differing techniques. The location of this study on a global scale is in Middle Eastern Countries. We compared the mechanistic model CLIMEX (CL) with the correlative models MaxEnt (MX), Boosted Regression Trees (BRT), and Random Forests (RF) to project current and future distributions of date palm ( Phoenix dactylifera L.). The Global Climate Model (GCM), the CSIRO-Mk3.0 (CS) using the A2 emissions scenario, was selected for making projections. Both indigenous and alien distribution data of the species were utilized in the modeling process. The common areas predicted by MX, BRT, RF, and CL from the CS GCM were extracted and compared to ascertain projection uncertainty levels of each individual technique. The common areas identified by all four modeling techniques were used to produce a map indicating suitable and unsuitable areas for date palm cultivation for Middle Eastern countries, for the present and the year 2100. The four different modeling approaches predict fairly different distributions. Projections from CL were more conservative than from MX. The BRT and RF were the most conservative methods in terms of projections for the current time. The combination of the final CL and MX projections for the present and 2100 provide higher certainty concerning those areas that will become highly suitable for future date palm cultivation. According to the four models, cold, hot, and wet stress, with differences on a regional basis, appears to be the major restrictions on future date palm distribution. The results demonstrate variances in the projections, resulting from different techniques. The assessment and interpretation of model projections requires reservations

  18. Novel head and neck cancer survival analysis approach: random survival forests versus Cox proportional hazards regression.

    Science.gov (United States)

    Datema, Frank R; Moya, Ana; Krause, Peter; Bäck, Thomas; Willmes, Lars; Langeveld, Ton; Baatenburg de Jong, Robert J; Blom, Henk M

    2012-01-01

    Electronic patient files generate an enormous amount of medical data. These data can be used for research, such as prognostic modeling. Automatization of statistical prognostication processes allows automatic updating of models when new data is gathered. The increase of power behind an automated prognostic model makes its predictive capability more reliable. Cox proportional hazard regression is most frequently used in prognostication. Automatization of a Cox model is possible, but we expect the updating process to be time-consuming. A possible solution lies in an alternative modeling technique called random survival forests (RSFs). RSF is easily automated and is known to handle the proportionality assumption coherently and automatically. Performance of RSF has not yet been tested on a large head and neck oncological dataset. This study investigates performance of head and neck overall survival of RSF models. Performances are compared to a Cox model as the "gold standard." RSF might be an interesting alternative modeling approach for automatization when performances are similar. RSF models were created in R (Cox also in SPSS). Four RSF splitting rules were used: log-rank, conservation of events, log-rank score, and log-rank approximation. Models were based on historical data of 1371 patients with primary head-and-neck cancer, diagnosed between 1981 and 1998. Models contain 8 covariates: tumor site, T classification, N classification, M classification, age, sex, prior malignancies, and comorbidity. Model performances were determined by Harrell's concordance error rate, in which 33% of the original data served as a validation sample. RSF and Cox models delivered similar error rates. The Cox model performed slightly better (error rate, 0.2826). The log-rank splitting approach gave the best RSF performance (error rate, 0.2873). In accord with Cox and RSF models, high T classification, high N classification, and severe comorbidity are very important covariates in the

  19. Genetic evaluation and selection response for growth in meat-type quail through random regression models using B-spline functions and Legendre polynomials.

    Science.gov (United States)

    Mota, L F M; Martins, P G M A; Littiere, T O; Abreu, L R A; Silva, M A; Bonafé, C M

    2017-08-14

    The objective was to estimate (co)variance functions using random regression models (RRM) with Legendre polynomials, B-spline function and multi-trait models aimed at evaluating genetic parameters of growth traits in meat-type quail. A database containing the complete pedigree information of 7000 meat-type quail was utilized. The models included the fixed effects of contemporary group and generation. Direct additive genetic and permanent environmental effects, considered as random, were modeled using B-spline functions considering quadratic and cubic polynomials for each individual segment, and Legendre polynomials for age. Residual variances were grouped in four age classes. Direct additive genetic and permanent environmental effects were modeled using 2 to 4 segments and were modeled by Legendre polynomial with orders of fit ranging from 2 to 4. The model with quadratic B-spline adjustment, using four segments for direct additive genetic and permanent environmental effects, was the most appropriate and parsimonious to describe the covariance structure of the data. The RRM using Legendre polynomials presented an underestimation of the residual variance. Lesser heritability estimates were observed for multi-trait models in comparison with RRM for the evaluated ages. In general, the genetic correlations between measures of BW from hatching to 35 days of age decreased as the range between the evaluated ages increased. Genetic trend for BW was positive and significant along the selection generations. The genetic response to selection for BW in the evaluated ages presented greater values for RRM compared with multi-trait models. In summary, RRM using B-spline functions with four residual variance classes and segments were the best fit for genetic evaluation of growth traits in meat-type quail. In conclusion, RRM should be considered in genetic evaluation of breeding programs.

  20. PREDICTING LONGITUDINAL TRAJECTORIES OF HEALTH PROBABILITIES WITH RANDOM-EFFECTS MULTINOMIAL LOGIT REGRESSION

    OpenAIRE

    Liu, Xian; Engel, Charles C.

    2012-01-01

    Researchers often encounter longitudinal health data characterized with three or more ordinal or nominal categories. Random-effects multinomial logit models are generally applied to account for potential lack of independence inherent in such clustered data. When parameter estimates are used to describe longitudinal processes, however, random effects, both between and within individuals, need to be retransformed for correctly predicting outcome probabilities. This study attempts to go beyond e...

  1. Feed efficiency and body weight growth throughout growing-furring period in mink using random regression method

    DEFF Research Database (Denmark)

    Shirali, Mahmoud; Nielsen, Vivi Hunnicke; Møller, Steen Henrik

    2014-01-01

    be obtained by only considering RFI estimate and BW at pelting, however, lower genetic correlations than unity indicate that extra genetic gain can be obtained by including estimates of these traits at the growing period. This study suggests random regression methods are suitable for analysing feed efficiency......The aim of this study was to determine genetic background of longitudinal residual feed intake (RFI) and body weight (BW) growth in farmed mink using random regression methods considering heterogeneous residual variances. Eight BW measures for each mink was recorded every three weeks from 63 to 210...... days of age for 2139 male mink and the same number of females. Cumulative feed intake was calculated six times with three weeks interval based on daily feed consumption between weighing’s from 105 to 210 days of age. Heritability estimates for RFI increased by age from 0.18 (0.03, standard deviation...

  2. A Comparative Assessment of the Influences of Human Impacts on Soil Cd Concentrations Based on Stepwise Linear Regression, Classification and Regression Tree, and Random Forest Models.

    Science.gov (United States)

    Qiu, Lefeng; Wang, Kai; Long, Wenli; Wang, Ke; Hu, Wei; Amable, Gabriel S

    2016-01-01

    Soil cadmium (Cd) contamination has attracted a great deal of attention because of its detrimental effects on animals and humans. This study aimed to develop and compare the performances of stepwise linear regression (SLR), classification and regression tree (CART) and random forest (RF) models in the prediction and mapping of the spatial distribution of soil Cd and to identify likely sources of Cd accumulation in Fuyang County, eastern China. Soil Cd data from 276 topsoil (0-20 cm) samples were collected and randomly divided into calibration (222 samples) and validation datasets (54 samples). Auxiliary data, including detailed land use information, soil organic matter, soil pH, and topographic data, were incorporated into the models to simulate the soil Cd concentrations and further identify the main factors influencing soil Cd variation. The predictive models for soil Cd concentration exhibited acceptable overall accuracies (72.22% for SLR, 70.37% for CART, and 75.93% for RF). The SLR model exhibited the largest predicted deviation, with a mean error (ME) of 0.074 mg/kg, a mean absolute error (MAE) of 0.160 mg/kg, and a root mean squared error (RMSE) of 0.274 mg/kg, and the RF model produced the results closest to the observed values, with an ME of 0.002 mg/kg, an MAE of 0.132 mg/kg, and an RMSE of 0.198 mg/kg. The RF model also exhibited the greatest R2 value (0.772). The CART model predictions closely followed, with ME, MAE, RMSE, and R2 values of 0.013 mg/kg, 0.154 mg/kg, 0.230 mg/kg and 0.644, respectively. The three prediction maps generally exhibited similar and realistic spatial patterns of soil Cd contamination. The heavily Cd-affected areas were primarily located in the alluvial valley plain of the Fuchun River and its tributaries because of the dramatic industrialization and urbanization processes that have occurred there. The most important variable for explaining high levels of soil Cd accumulation was the presence of metal smelting industries. The

  3. A Comparative Assessment of the Influences of Human Impacts on Soil Cd Concentrations Based on Stepwise Linear Regression, Classification and Regression Tree, and Random Forest Models.

    Directory of Open Access Journals (Sweden)

    Lefeng Qiu

    Full Text Available Soil cadmium (Cd contamination has attracted a great deal of attention because of its detrimental effects on animals and humans. This study aimed to develop and compare the performances of stepwise linear regression (SLR, classification and regression tree (CART and random forest (RF models in the prediction and mapping of the spatial distribution of soil Cd and to identify likely sources of Cd accumulation in Fuyang County, eastern China. Soil Cd data from 276 topsoil (0-20 cm samples were collected and randomly divided into calibration (222 samples and validation datasets (54 samples. Auxiliary data, including detailed land use information, soil organic matter, soil pH, and topographic data, were incorporated into the models to simulate the soil Cd concentrations and further identify the main factors influencing soil Cd variation. The predictive models for soil Cd concentration exhibited acceptable overall accuracies (72.22% for SLR, 70.37% for CART, and 75.93% for RF. The SLR model exhibited the largest predicted deviation, with a mean error (ME of 0.074 mg/kg, a mean absolute error (MAE of 0.160 mg/kg, and a root mean squared error (RMSE of 0.274 mg/kg, and the RF model produced the results closest to the observed values, with an ME of 0.002 mg/kg, an MAE of 0.132 mg/kg, and an RMSE of 0.198 mg/kg. The RF model also exhibited the greatest R2 value (0.772. The CART model predictions closely followed, with ME, MAE, RMSE, and R2 values of 0.013 mg/kg, 0.154 mg/kg, 0.230 mg/kg and 0.644, respectively. The three prediction maps generally exhibited similar and realistic spatial patterns of soil Cd contamination. The heavily Cd-affected areas were primarily located in the alluvial valley plain of the Fuchun River and its tributaries because of the dramatic industrialization and urbanization processes that have occurred there. The most important variable for explaining high levels of soil Cd accumulation was the presence of metal smelting industries

  4. Review Random regression test-day model for the analysis of dairy ...

    African Journals Online (AJOL)

    jannes

    Abstract. Genetic evaluation of dairy cattle using test-day models is now common internationally. In South. Africa a fixed regression test-day model is used to generate breeding values for dairy animals on a routine basis. The model is, however, often criticized for erroneously assuming a standard lactation curve for cows.

  5. Random regression test-day model for the analysis of dairy cattle ...

    African Journals Online (AJOL)

    Genetic evaluation of dairy cattle using test-day models is now common internationally. In South Africa a fixed regression test-day model is used to generate breeding values for dairy animals on a routine basis. The model is, however, often criticized for erroneously assuming a standard lactation curve for cows in similar ...

  6. Appropriate assessment of neighborhood effects on individual health: integrating random and fixed effects in multilevel logistic regression

    DEFF Research Database (Denmark)

    Larsen, Klaus; Merlo, Juan

    2005-01-01

    The logistic regression model is frequently used in epidemiologic studies, yielding odds ratio or relative risk interpretations. Inspired by the theory of linear normal models, the logistic regression model has been extended to allow for correlated responses by introducing random effects. However......, the model does not inherit the interpretational features of the normal model. In this paper, the authors argue that the existing measures are unsatisfactory (and some of them are even improper) when quantifying results from multilevel logistic regression analyses. The authors suggest a measure...... of heterogeneity, the median odds ratio, that quantifies cluster heterogeneity and facilitates a direct comparison between covariate effects and the magnitude of heterogeneity in terms of well-known odds ratios. Quantifying cluster-level covariates in a meaningful way is a challenge in multilevel logistic...

  7. Evaluating an Organizational-Level Occupational Health Intervention in a Combined Regression Discontinuity and Randomized Control Design.

    Science.gov (United States)

    Sørensen, By Ole H

    2016-10-01

    Organizational-level occupational health interventions have great potential to improve employees' health and well-being. However, they often compare unfavourably to individual-level interventions. This calls for improving methods for designing, implementing and evaluating organizational interventions. This paper presents and discusses the regression discontinuity design because, like the randomized control trial, it is a strong summative experimental design, but it typically fits organizational-level interventions better. The paper explores advantages and disadvantages of a regression discontinuity design with an embedded randomized control trial. It provides an example from an intervention study focusing on reducing sickness absence in 196 preschools. The paper demonstrates that such a design fits the organizational context, because it allows management to focus on organizations or workgroups with the most salient problems. In addition, organizations may accept an embedded randomized design because the organizations or groups with most salient needs receive obligatory treatment as part of the regression discontinuity design. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  8. Multiple trait model combining random regressions for daily feed intake with single measured performance traits of growing pigs

    Directory of Open Access Journals (Sweden)

    Künzi Niklaus

    2002-01-01

    Full Text Available Abstract A random regression model for daily feed intake and a conventional multiple trait animal model for the four traits average daily gain on test (ADG, feed conversion ratio (FCR, carcass lean content and meat quality index were combined to analyse data from 1 449 castrated male Large White pigs performance tested in two French central testing stations in 1997. Group housed pigs fed ad libitum with electronic feed dispensers were tested from 35 to 100 kg live body weight. A quadratic polynomial in days on test was used as a regression function for weekly means of daily feed intake and to escribe its residual variance. The same fixed (batch and random (additive genetic, pen and individual permanent environmental effects were used for regression coefficients of feed intake and single measured traits. Variance components were estimated by means of a Bayesian analysis using Gibbs sampling. Four Gibbs chains were run for 550 000 rounds each, from which 50 000 rounds were discarded from the burn-in period. Estimates of posterior means of covariance matrices were calculated from the remaining two million samples. Low heritabilities of linear and quadratic regression coefficients and their unfavourable genetic correlations with other performance traits reveal that altering the shape of the feed intake curve by direct or indirect selection is difficult.

  9. Star points on cubic surfaces

    NARCIS (Netherlands)

    Nguyen, T.C.

    2000-01-01

    A cubic surface in P 3 is given by a non-zero cubic homogeneous polynomial in 4 variables. Fixing an ordering of monomials of degree 3 in the polynomial ring k[x0; x1; x2; x3 ], each cubic surface denes a point in P 19 . The locus P 19 of singular cubic surfaces is a closed subset of

  10. 3D statistical shape models incorporating 3D random forest regression voting for robust CT liver segmentation

    Science.gov (United States)

    Norajitra, Tobias; Meinzer, Hans-Peter; Maier-Hein, Klaus H.

    2015-03-01

    During image segmentation, 3D Statistical Shape Models (SSM) usually conduct a limited search for target landmarks within one-dimensional search profiles perpendicular to the model surface. In addition, landmark appearance is modeled only locally based on linear profiles and weak learners, altogether leading to segmentation errors from landmark ambiguities and limited search coverage. We present a new method for 3D SSM segmentation based on 3D Random Forest Regression Voting. For each surface landmark, a Random Regression Forest is trained that learns a 3D spatial displacement function between the according reference landmark and a set of surrounding sample points, based on an infinite set of non-local randomized 3D Haar-like features. Landmark search is then conducted omni-directionally within 3D search spaces, where voxelwise forest predictions on landmark position contribute to a common voting map which reflects the overall position estimate. Segmentation experiments were conducted on a set of 45 CT volumes of the human liver, of which 40 images were randomly chosen for training and 5 for testing. Without parameter optimization, using a simple candidate selection and a single resolution approach, excellent results were achieved, while faster convergence and better concavity segmentation were observed, altogether underlining the potential of our approach in terms of increased robustness from distinct landmark detection and from better search coverage.

  11. Auto Regressive Moving Average (ARMA) Modeling Method for Gyro Random Noise Using a Robust Kalman Filter.

    Science.gov (United States)

    Huang, Lei

    2015-09-30

    To solve the problem in which the conventional ARMA modeling methods for gyro random noise require a large number of samples and converge slowly, an ARMA modeling method using a robust Kalman filtering is developed. The ARMA model parameters are employed as state arguments. Unknown time-varying estimators of observation noise are used to achieve the estimated mean and variance of the observation noise. Using the robust Kalman filtering, the ARMA model parameters are estimated accurately. The developed ARMA modeling method has the advantages of a rapid convergence and high accuracy. Thus, the required sample size is reduced. It can be applied to modeling applications for gyro random noise in which a fast and accurate ARMA modeling method is required.

  12. Solution of the Cubic

    Indian Academy of Sciences (India)

    to solving a cubic equation. Thus Cardano's formula filled the essential gap in our understanding of the so- lu tions of polynomial equations. The purpose of this .... great influence on Euler. Finally, it was Euler who uti- lized these symbols throughout his writings and made them the language of mathematics. Thus the mathe-.

  13. Evaluation of alternative schemes for recording body weights in meat-type quails by using random regression.

    Science.gov (United States)

    Silva, L P; Ribeiro, J C; Leite, C D S; Sousa, M F; Bonafé, C M; Caetano, G C; Crispim, A C; Torres, R A

    2013-05-13

    Data from 8759 meat-type quails from the UFV1 strain and 9128 from the UFV2 strain were used to assess the possibility of reducing the number of body weight records in genetic evaluations. The evaluated animals were weighed weekly since hatching to the 6th week of life, with up to 7 records of body weight for each bird. The data were evaluated by random regression models, with 9 alternative schemes of data recording, which included 4 records for each scheme and their covariance functions for additive and permanent environmental effects of order 3, fitting 4 intervals for residual variance, and a complete scheme, with 7 records, order of fit 6 for additive and permanent environmental effects and 7 intervals for residual variance. Estimates of heritability for body weight at the 6th week varied from 0.45 to 0.53 for the UFV1 strain and from 0.28 to 0.54 for UFV2 strain. The schemes that had more records in points at the final extreme of the age range showed better estimates, which was likely due to certain properties of polynomial regression that led to biased results in the final extreme of the age range when data are unbalanced. The reduction of the number of body weight records taken during the growth phase is feasible, with little change to breeding value estimates, when 4 body weight records are used in random regression models.

  14. Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

    Directory of Open Access Journals (Sweden)

    Maria Gabriela Campolina Diniz Peixoto

    2014-05-01

    Full Text Available The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524 of test-day milk yield (TDMY from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects, whereas the contemporary group, calving age (linear and quadratic effects and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

  15. A note on Using regression models to analyze randomized trials: asymptotically valid hypothesis tests despite incorrectly specified models.

    Science.gov (United States)

    Kim, Jane Paik

    2013-03-01

    In the context of randomized trials, Rosenblum and van der Laan (2009, Biometrics 63, 937-945) considered the null hypothesis of no treatment effect on the mean outcome within strata of baseline variables. They showed that hypothesis tests based on linear regression models and generalized linear regression models are guaranteed to have asymptotically correct Type I error regardless of the actual data generating distribution, assuming the treatment assignment is independent of covariates. We consider another important outcome in randomized trials, the time from randomization until failure, and the null hypothesis of no treatment effect on the survivor function conditional on a set of baseline variables. By a direct application of arguments in Rosenblum and van der Laan (2009), we show that hypothesis tests based on multiplicative hazards models with an exponential link, i.e., proportional hazards models, and multiplicative hazards models with linear link functions where the baseline hazard is parameterized, are asymptotically valid under model misspecification provided that the censoring distribution is independent of the treatment assignment given the covariates. In the case of the Cox model and linear link model with unspecified baseline hazard function, the arguments in Rosenblum and van der Laan (2009) cannot be applied to show the robustness of a misspecified model. Instead, we adopt an approach used in previous literature (Struthers and Kalbfleisch, 1986, Biometrika 73, 363-369) to show that hypothesis tests based on these models, including models with interaction terms, have correct type I error. Copyright © 2013, The International Biometric Society.

  16. Genetic analysis of production traits of Holstein cows in the Mediterranean climate of Iran using random regression and animal model

    Directory of Open Access Journals (Sweden)

    Mohammad Jabarzadeh Ivrigh

    2016-04-01

    Full Text Available Introduction Productive traits such as milk production and fat and protein percentage have economic importance in the livestock industry. Accurate prediction of breeding value of animals is one of the best tools available for maximizing response to selection program. It is a fact that the main objective of the breeding program, is to achieve the maximum economic benefit. For breeders of dairy cattle, milk, fat, and protein are the main sources of income that are the most important traits in the firm goals. For evaluating the dairy cattle based on these traits (milk production, fat, and protein percentage, prediction of breeding values is essential. The present study was performed in order to estimate the genetic and phenotypic parameters and genetic and phenotypic trends of production traits in the Mediterranean climate of Iran (including; Ardebil, Hamadan, East and West Azerbaijan and Zanjan provinces using 105118 records for Test Day and 30985 records for 305-day lactation records Related 8808 Herd of first lactation Holstein Cattle calving between 2003 to 2013. All records collected by Animal Breeding Center of Iran. Materials and Methods Records were edited using Fox pro 8.0 and ACCESS 2010 software and the wrong and unusual records were removed from the dataset. All analyses were performed using the RR (random regression routine of the WOMBAT software package using AIREML algorithm on Linux operation system. Test day records were analyzed with the following random regression model (RRM: Where; Pk; kth fixed effect of province, YSl; lth fixed effect of year-season of calving, Yklimnptv; test day record i obtained at dimt of cow p calved at the nth age group in herd-test day m, HTDm; fixed effect of mth herd-test date, Cf; The fth fixed regression coefficient for calving age, agen; The nth calving age, k; The order of fit for fixed regression coefficients (k=4, βr; The rth fixed regression coefficient, ka; The order of fit for additive

  17. Comparison of Logistic Regression and Random Forests techniques for shallow landslide susceptibility assessment in Giampilieri (NE Sicily, Italy)

    Science.gov (United States)

    Trigila, Alessandro; Iadanza, Carla; Esposito, Carlo; Scarascia-Mugnozza, Gabriele

    2015-11-01

    The aim of this work is to define reliable susceptibility models for shallow landslides using Logistic Regression and Random Forests multivariate statistical techniques. The study area, located in North-East Sicily, was hit on October 1st 2009 by a severe rainstorm (225 mm of cumulative rainfall in 7 h) which caused flash floods and more than 1000 landslides. Several small villages, such as Giampilieri, were hit with 31 fatalities, 6 missing persons and damage to buildings and transportation infrastructures. Landslides, mainly types such as earth and debris translational slides evolving into debris flows, were triggered on steep slopes and involved colluvium and regolith materials which cover the underlying metamorphic bedrock. The work has been carried out with the following steps: i) realization of a detailed event landslide inventory map through field surveys coupled with observation of high resolution aerial colour orthophoto; ii) identification of landslide source areas; iii) data preparation of landslide controlling factors and descriptive statistics based on a bivariate method (Frequency Ratio) to get an initial overview on existing relationships between causative factors and shallow landslide source areas; iv) choice of criteria for the selection and sizing of the mapping unit; v) implementation of 5 multivariate statistical susceptibility models based on Logistic Regression and Random Forests techniques and focused on landslide source areas; vi) evaluation of the influence of sample size and type of sampling on results and performance of the models; vii) evaluation of the predictive capabilities of the models using ROC curve, AUC and contingency tables; viii) comparison of model results and obtained susceptibility maps; and ix) analysis of temporal variation of landslide susceptibility related to input parameter changes. Models based on Logistic Regression and Random Forests have demonstrated excellent predictive capabilities. Land use and wildfire

  18. Connected Cubic Network Graph

    Directory of Open Access Journals (Sweden)

    Burhan Selçuk

    2017-06-01

    Full Text Available Hypercube is a popular interconnection network. Due to the popularity of hypercube, more researchers pay a great effort to develop the different variants of hypercube. In this paper, we have proposed a variant of hypercube which is called as “Connected Cubic Network Graphs”, and have investigated the Hamilton-like properties of Connected Cubic Network Graphs (CCNG. Firstly, we defined CCNG and showed the characteristic analyses of CCNG. Then, we showed that the CCNG has the properties of Hamilton graph, and can be labeled using a Gray coding based recursive algorithm. Finally, we gave the comparison results, a routing algorithm and a bitonic sort algorithm for CCNG. In case of sparsity and cost, CCNG is better than Hypercube.

  19. Guarded Cubical Type Theory

    DEFF Research Database (Denmark)

    Birkedal, Lars; Bizjak, Aleš; Clouston, Ranald

    2016-01-01

    terms. CTT provides a computational interpretation of functional extensionality, enjoys canonicity for the natural numbers type, and is conjectured to support decidable type-checking. Our new type theory, guarded cubical type theory (GCTT), provides a computational interpretation of extensionality......This paper improves the treatment of equality in guarded dependent type theory (GDTT), by combining it with cubical type theory (CTT). GDTT is an extensional type theory with guarded recursive types, which are useful for building models of program logics, and for programming and reasoning...... with coinductive types. We wish to implement GDTT with decidable type checking, while still supporting non-trivial equality proofs that reason about the extensions of guarded recursive constructions. CTT is a variation of Martin-L\\"of type theory in which the identity type is replaced by abstract paths between...

  20. Recurrence of random walks with long-range steps generated by fractional Laplacian matrices on regular networks and simple cubic lattices

    Science.gov (United States)

    Michelitsch, T. M.; Collet, B. A.; Riascos, A. P.; Nowakowski, A. F.; Nicolleau, F. C. G. A.

    2017-12-01

    We analyze a Markovian random walk strategy on undirected regular networks involving power matrix functions of the type L\\frac{α{2}} where L indicates a ‘simple’ Laplacian matrix. We refer to such walks as ‘fractional random walks’ with admissible interval 0 α (recurrent for d≤slantα ) of the lattice. As a consequence, for 0global mean first passage times (Kemeny constant) for the fractional random walk. For an infinite 1D lattice (infinite ring) we obtain for the transient regime 0world properties with the emergence of Lévy flights on large (infinite) lattices.

  1. A Logistic Regression Model with a Hierarchical Random Error Term for Analyzing the Utilization of Public Transport

    Directory of Open Access Journals (Sweden)

    Chong Wei

    2015-01-01

    Full Text Available Logistic regression models have been widely used in previous studies to analyze public transport utilization. These studies have shown travel time to be an indispensable variable for such analysis and usually consider it to be a deterministic variable. This formulation does not allow us to capture travelers’ perception error regarding travel time, and recent studies have indicated that this error can have a significant effect on modal choice behavior. In this study, we propose a logistic regression model with a hierarchical random error term. The proposed model adds a new random error term for the travel time variable. This term structure enables us to investigate travelers’ perception error regarding travel time from a given choice behavior dataset. We also propose an extended model that allows constraining the sign of this error in the model. We develop two Gibbs samplers to estimate the basic hierarchical model and the extended model. The performance of the proposed models is examined using a well-known dataset.

  2. Estimation of genetic parameters for electrical conductivity of milk for Holstein breed using random regression

    Directory of Open Access Journals (Sweden)

    Diego Augusto Campos da Cruz

    2012-12-01

    Full Text Available The electrical conductivity of milk is an indirect method of mastitis diagnosis and can be used as selection criterion in breeding programs to obtain resistant animals to infection. For the present study data from 9,302 milk electrical conductivity measurements in the morning (ECM, from 1,129 Holstein cows in first lactation, calving between 2001 and 2011, belonging to eight herds in the Southeast of Brazil, obtained from automated milking equipment WESTFALIA® with system management "Dairyplan" was utilized. Classes of ECM were formed at weekly intervals, representing a total of 42 classes. The model included direct additive genetic, permanent environmental and residual effects as random and the fixed effects of contemporary group (herd - year and season of the control, age at calving as a covariate (linear and quadratic. Mean trends were modeled by an orthogonal Legendre polynomial with three coefficients of days in milk. The residual variance was considered homogeneous throughout lactation. Variance components were estimated by restricted maximum likelihood method (REML, using the statistical package Wombat (Meyer, 2006. The mean and standard deviation of the electrical conductivity of milk were 4.799 ± 0.543 ms/cm. The heritability for ECM were increased from the beginning to the middle of lactation (154 days, when it reached the maximum value (0.44, decreasing thereafter and reaching its minimum value at 300 days (0.17. Genetic correlations between the ECM at different periods of lactation were high and positive across the course of lactation, ranging from 0.73 to 0.99. It was observed that the correlation estimates were considerably lower when compared to the ECM 300 days with those of other periods. The data suggest that significant gains can be obtained via selection when using the ECM as selection criterion aimed at resistance to mastitis. It was verified also, that the selection for this trait in the early period of lactation, to

  3. Random regression analysis of test-day milk yields in the first and second lactations of Brazilian Gyr cows.

    Science.gov (United States)

    Gonzalez-Herrera, L G; El Faro, L; Bignardi, A B; Pereira, R J; Machado, C H C; Albuquerque, L G

    2015-12-09

    The objective of the present study was to estimate the genetic parameters for test-day milk yields (TDMY) in the first and second lactations using random regression models (RRM) in order to contribute to the application of these models in genetic evaluation of milk yield in Gyr cattle. A total of 53,328 TDMY records from 7118 lactations of 5853 Gyr cows were analyzed. The model included the direct additive, permanent environmental, and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cows at calving were included as fixed effects. A random regression model fitting fourth-order Legendre polynomials for additive genetic and permanent environmental effects, with five classes of residual variance, was applied. In the first lactation, the heritabilities increased from early lactation (0.26) until TDMY3 (0.38), followed by a decrease until the end of lactation. In the second lactation, the estimates increased from the first (0.29) to the fifth test day (0.36), with a slight decrease thereafter, and again increased on the last two test days (0.34 and 0.41). There were positive and high genetic correlations estimated between first-lactation TDMY and the remaining TDMY of the two lactations. The moderate heritability estimates, as well as the high genetic correlations between half the first-lactation TDMY and all TDMY of the two lactations, suggest that the selection based only on first lactation TDMY is the best selection strategy to increase milk production across first and second lactations of Gyr cows.

  4. Multivariate random-parameters zero-inflated negative binomial regression model: an application to estimate crash frequencies at intersections.

    Science.gov (United States)

    Dong, Chunjiao; Clarke, David B; Yan, Xuedong; Khattak, Asad; Huang, Baoshan

    2014-09-01

    Crash data are collected through police reports and integrated with road inventory data for further analysis. Integrated police reports and inventory data yield correlated multivariate data for roadway entities (e.g., segments or intersections). Analysis of such data reveals important relationships that can help focus on high-risk situations and coming up with safety countermeasures. To understand relationships between crash frequencies and associated variables, while taking full advantage of the available data, multivariate random-parameters models are appropriate since they can simultaneously consider the correlation among the specific crash types and account for unobserved heterogeneity. However, a key issue that arises with correlated multivariate data is the number of crash-free samples increases, as crash counts have many categories. In this paper, we describe a multivariate random-parameters zero-inflated negative binomial (MRZINB) regression model for jointly modeling crash counts. The full Bayesian method is employed to estimate the model parameters. Crash frequencies at urban signalized intersections in Tennessee are analyzed. The paper investigates the performance of MZINB and MRZINB regression models in establishing the relationship between crash frequencies, pavement conditions, traffic factors, and geometric design features of roadway intersections. Compared to the MZINB model, the MRZINB model identifies additional statistically significant factors and provides better goodness of fit in developing the relationships. The empirical results show that MRZINB model possesses most of the desirable statistical properties in terms of its ability to accommodate unobserved heterogeneity and excess zero counts in correlated data. Notably, in the random-parameters MZINB model, the estimated parameters vary significantly across intersections for different crash types. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. Multivariate random regression analysis for body weight and main morphological traits in genetically improved farmed tilapia (Oreochromis niloticus).

    Science.gov (United States)

    He, Jie; Zhao, Yunfeng; Zhao, Jingli; Gao, Jin; Han, Dandan; Xu, Pao; Yang, Runqing

    2017-11-02

    Because of their high economic importance, growth traits in fish are under continuous improvement. For growth traits that are recorded at multiple time-points in life, the use of univariate and multivariate animal models is limited because of the variable and irregular timing of these measures. Thus, the univariate random regression model (RRM) was introduced for the genetic analysis of dynamic growth traits in fish breeding. We used a multivariate random regression model (MRRM) to analyze genetic changes in growth traits recorded at multiple time-point of genetically-improved farmed tilapia. Legendre polynomials of different orders were applied to characterize the influences of fixed and random effects on growth trajectories. The final MRRM was determined by optimizing the univariate RRM for the analyzed traits separately via penalizing adaptively the likelihood statistical criterion, which is superior to both the Akaike information criterion and the Bayesian information criterion. In the selected MRRM, the additive genetic effects were modeled by Legendre polynomials of three orders for body weight (BWE) and body length (BL) and of two orders for body depth (BD). By using the covariance functions of the MRRM, estimated heritabilities were between 0.086 and 0.628 for BWE, 0.155 and 0.556 for BL, and 0.056 and 0.607 for BD. Only heritabilities for BD measured from 60 to 140 days of age were consistently higher than those estimated by the univariate RRM. All genetic correlations between growth time-points exceeded 0.5 for either single or pairwise time-points. Moreover, correlations between early and late growth time-points were lower. Thus, for phenotypes that are measured repeatedly in aquaculture, an MRRM can enhance the efficiency of the comprehensive selection for BWE and the main morphological traits.

  6. Isolating the cow-specific part of residual energy intake in lactating dairy cows using random regressions.

    Science.gov (United States)

    Fischer, A; Friggens, N C; Berry, D P; Faverdin, P

    2017-12-11

    The ability to properly assess and accurately phenotype true differences in feed efficiency among dairy cows is key to the development of breeding programs for improving feed efficiency. The variability among individuals in feed efficiency is commonly characterised by the residual intake approach. Residual feed intake is represented by the residuals of a linear regression of intake on the corresponding quantities of the biological functions that consume (or release) energy. However, the residuals include both, model fitting and measurement errors as well as any variability in cow efficiency. The objective of this study was to isolate the individual animal variability in feed efficiency from the residual component. Two separate models were fitted, in one the standard residual energy intake (REI) was calculated as the residual of a multiple linear regression of lactation average net energy intake (NEI) on lactation average milk energy output, average metabolic BW, as well as lactation loss and gain of body condition score. In the other, a linear mixed model was used to simultaneously fit fixed linear regressions and random cow levels on the biological traits and intercept using fortnight repeated measures for the variables. This method split the predicted NEI in two parts: one quantifying the population mean intercept and coefficients, and one quantifying cow-specific deviations in the intercept and coefficients. The cow-specific part of predicted NEI was assumed to isolate true differences in feed efficiency among cows. NEI and associated energy expenditure phenotypes were available for the first 17 fortnights of lactation from 119 Holstein cows; all fed a constant energy-rich diet. Mixed models fitting cow-specific intercept and coefficients to different combinations of the aforementioned energy expenditure traits, calculated on a fortnightly basis, were compared. The variance of REI estimated with the lactation average model represented only 8% of the variance of

  7. Genetic analysis of milk solid no-fat percentage by fixed and random regression models in Kurdi sheep of Shirvan

    Directory of Open Access Journals (Sweden)

    fatemh kazemi borzel abad

    2016-08-01

    Full Text Available Introduction Milk solid no-fat is economically very important in cheese industry. Compared to the other kinds of milk, ewe’s milk contains higher amount of milk solids no-fat. Milk solids no-fat (MSNF contains lactose, caseins, whey proteins, and minerals. The use of test day records in random regression method has several benefits including flexibility to account for the environmental and genetic components of the shape of lactation, reducing generation interval and cost of recording by making fewer measurements, increasing the accuracy of genetic evaluation and direct correction for fixed effects. Therefore, the objective of the present study was to estimate genetic parameters for test-day milk solid no-fat percentage in Kurdi sheep of Shirvan using fixed and random regression models. Materials and methods In the present investigation, genetic analysis of milk solid no-fat percentage was carried out using fixed and random regression models by Wombat software. Data included 1094 test day records of milk solid no-fat percentage collected from 250 ewes in Hossien Abad Kurdi sheep breeding station. Milking was carried out by hand milking combined with lamb suckling at 14 days interval starting from May to August 2012. Then, 50 ml of milk samples were immediately analysed by Ecomilk total to determine the milk solid no-fat percentage. Fixed effects of litter size, parity, month of recording and days in milk as covariate and random effects of direct genetic and permanent environmental effects were included in the models. General linear model was used to identify effective fixed effects on the trait by SAS 9.1 software. Variance and covariance components were estimated using restricted maximum likelihood procedure. In random regression model, orthogonal Legendre polynomials of order 2 for permanent environmental and additive genetic effects was fitted. Results and Discussion Average milk solid no-fat percentage of Kurdi ewes was 11.83. Average

  8. Spatial prediction of landslides using a hybrid machine learning approach based on Random Subspace and Classification and Regression Trees

    Science.gov (United States)

    Pham, Binh Thai; Prakash, Indra; Tien Bui, Dieu

    2018-02-01

    A hybrid machine learning approach of Random Subspace (RSS) and Classification And Regression Trees (CART) is proposed to develop a model named RSSCART for spatial prediction of landslides. This model is a combination of the RSS method which is known as an efficient ensemble technique and the CART which is a state of the art classifier. The Luc Yen district of Yen Bai province, a prominent landslide prone area of Viet Nam, was selected for the model development. Performance of the RSSCART model was evaluated through the Receiver Operating Characteristic (ROC) curve, statistical analysis methods, and the Chi Square test. Results were compared with other benchmark landslide models namely Support Vector Machines (SVM), single CART, Naïve Bayes Trees (NBT), and Logistic Regression (LR). In the development of model, ten important landslide affecting factors related with geomorphology, geology and geo-environment were considered namely slope angles, elevation, slope aspect, curvature, lithology, distance to faults, distance to rivers, distance to roads, and rainfall. Performance of the RSSCART model (AUC = 0.841) is the best compared with other popular landslide models namely SVM (0.835), single CART (0.822), NBT (0.821), and LR (0.723). These results indicate that performance of the RSSCART is a promising method for spatial landslide prediction.

  9. Random regression models to estimate genetic parameters for test-day milk yield in Brazilian Murrah buffaloes.

    Science.gov (United States)

    Sesana, R C; Bignardi, A B; Borquis, R R A; El Faro, L; Baldi, F; Albuquerque, L G; Tonhati, H

    2010-10-01

    The objective of this work was to estimate covariance functions for additive genetic and permanent environmental effects and, subsequently, to obtain genetic parameters for buffalo's test-day milk production using random regression models on Legendre polynomials (LPs). A total of 17 935 test-day milk yield (TDMY) from 1433 first lactations of Murrah buffaloes, calving from 1985 to 2005 and belonging to 12 herds located in São Paulo state, Brazil, were analysed. Contemporary groups (CGs) were defined by herd, year and month of milk test. Residual variances were modelled through variance functions, from second to fourth order and also by a step function with 1, 4, 6, 22 and 42 classes. The model of analyses included the fixed effect of CGs, number of milking, age of cow at calving as a covariable (linear and quadratic) and the mean trend of the population. As random effects were included the additive genetic and permanent environmental effects. The additive genetic and permanent environmental random effects were modelled by LP of days in milk from quadratic to seventh degree polynomial functions. The model with additive genetic and animal permanent environmental effects adjusted by quintic and sixth order LP, respectively, and residual variance modelled through a step function with six classes was the most adequate model to describe the covariance structure of the data. Heritability estimates decreased from 0.44 (first week) to 0.18 (fourth week). Unexpected negative genetic correlation estimates were obtained between TDMY records at first weeks with records from middle to the end of lactation, being the values varied from -0.07 (second with eighth week) to -0.34 (1st with 42nd week). TDMY heritability estimates were moderate in the course of the lactation, suggesting that this trait could be applied as selection criteria in milking buffaloes. Copyright 2010 Blackwell Verlag GmbH.

  10. Guarded Cubical Type Theory

    DEFF Research Database (Denmark)

    Birkedal, Lars; Bizjak, Aleš; Clouston, Ranald

    2016-01-01

    types. This further expands the foundations of CTT as a basis for formalisation in mathematics and computer science. We present examples to demonstrate the expressivity of our type theory, all of which have been checked using a prototype type-checker implementation, and present semantics in a presheaf......This paper improves the treatment of equality in guarded dependent type theory (GDTT), by combining it with cubical type theory (CTT). GDTT is an extensional type theory with guarded recursive types, which are useful for building models of program logics, and for programming and reasoning...... with coinductive types. We wish to implement GDTT with decidable type-checking, while still supporting non-trivial equality proofs that reason about the extensions of guarded recursive constructions. CTT is a variation of Martin-L\\"of type theory in which the identity type is replaced by abstract paths between...

  11. A review of regression procedures for randomized response data, including univariate and multivariate logistic regression, the proportional odds model and item response model, and self-protective responses

    NARCIS (Netherlands)

    Cruyff, M.; Böckenholt, U.; van der Heijden, P.G.M.; Frank, L.E.

    2016-01-01

    In survey research, it is often problematic to ask people sensitive questions because they may refuse to answer or they may provide a socially desirable answer that does not reveal their true status on the sensitive question. To solve this problem Warner (1965) proposed randomized response (RR).

  12. Methods for calculating confidence and credible intervals for the residual between-study variance in random effects meta-regression models

    Science.gov (United States)

    2014-01-01

    Background Meta-regression is becoming increasingly used to model study level covariate effects. However this type of statistical analysis presents many difficulties and challenges. Here two methods for calculating confidence intervals for the magnitude of the residual between-study variance in random effects meta-regression models are developed. A further suggestion for calculating credible intervals using informative prior distributions for the residual between-study variance is presented. Methods Two recently proposed and, under the assumptions of the random effects model, exact methods for constructing confidence intervals for the between-study variance in random effects meta-analyses are extended to the meta-regression setting. The use of Generalised Cochran heterogeneity statistics is extended to the meta-regression setting and a Newton-Raphson procedure is developed to implement the Q profile method for meta-analysis and meta-regression. WinBUGS is used to implement informative priors for the residual between-study variance in the context of Bayesian meta-regressions. Results Results are obtained for two contrasting examples, where the first example involves a binary covariate and the second involves a continuous covariate. Intervals for the residual between-study variance are wide for both examples. Conclusions Statistical methods, and R computer software, are available to compute exact confidence intervals for the residual between-study variance under the random effects model for meta-regression. These frequentist methods are almost as easily implemented as their established counterparts for meta-analysis. Bayesian meta-regressions are also easily performed by analysts who are comfortable using WinBUGS. Estimates of the residual between-study variance in random effects meta-regressions should be routinely reported and accompanied by some measure of their uncertainty. Confidence and/or credible intervals are well-suited to this purpose. PMID:25196829

  13. Substituting random forest for multiple linear regression improves binding affinity prediction of scoring functions: Cyscore as a case study.

    Science.gov (United States)

    Li, Hongjian; Leung, Kwong-Sak; Wong, Man-Hon; Ballester, Pedro J

    2014-08-27

    State-of-the-art protein-ligand docking methods are generally limited by the traditionally low accuracy of their scoring functions, which are used to predict binding affinity and thus vital for discriminating between active and inactive compounds. Despite intensive research over the years, classical scoring functions have reached a plateau in their predictive performance. These assume a predetermined additive functional form for some sophisticated numerical features, and use standard multivariate linear regression (MLR) on experimental data to derive the coefficients. In this study we show that such a simple functional form is detrimental for the prediction performance of a scoring function, and replacing linear regression by machine learning techniques like random forest (RF) can improve prediction performance. We investigate the conditions of applying RF under various contexts and find that given sufficient training samples RF manages to comprehensively capture the non-linearity between structural features and measured binding affinities. Incorporating more structural features and training with more samples can both boost RF performance. In addition, we analyze the importance of structural features to binding affinity prediction using the RF variable importance tool. Lastly, we use Cyscore, a top performing empirical scoring function, as a baseline for comparison study. Machine-learning scoring functions are fundamentally different from classical scoring functions because the former circumvents the fixed functional form relating structural features with binding affinities. RF, but not MLR, can effectively exploit more structural features and more training samples, leading to higher prediction performance. The future availability of more X-ray crystal structures will further widen the performance gap between RF-based and MLR-based scoring functions. This further stresses the importance of substituting RF for MLR in scoring function development.

  14. Estimação de funções de covariância para características de crescimento da raça Tabapuã utilizando modelos de regressão aleatória Estimation of covariance functions for growth traits in Tabapuã cattle using random regression models

    Directory of Open Access Journals (Sweden)

    Severino Cavalcante de Sousa Júnior

    2010-05-01

    were included as fixed effects; and as covariables, animal age at weighing and age of dam at calving (linear and quadratic effects and on age at weighing,, the orthogonal Legendre polynomial (cubic regression was considered to model the mean curve of the population. Residuals effects were modeled considering seven classes of variance. The models were compared by Akaike criterion and Bayesian information criterion. The best model showed orders 4, 3, 6, and 3 for maternal and direct additive genetic effect, and maternal and animal permanent enviroment, respectively. Estimates of (covariance and heritability obtained with the bi-trait and random regression models were similar. The heritability estimates for direct additive genetic effect obtained by the random regression models increased from birth (0.15 to 660 days of age (0.45. The greatest estimates of maternal heritability were obtained for weights measured right after birth. In general, the genetic correlation estimates were moderate to high, and they decreased as the distance between weights increased. Selection for higher weights at any age will promote weight gain from birth to 660 days of age.

  15. Dropout from exercise randomized controlled trials among people with depression: A meta-analysis and meta regression.

    Science.gov (United States)

    Stubbs, Brendon; Vancampfort, Davy; Rosenbaum, Simon; Ward, Philip B; Richards, Justin; Soundy, Andrew; Veronese, Nicola; Solmi, Marco; Schuch, Felipe B

    2016-01-15

    Exercise has established efficacy in improving depressive symptoms. Dropouts from randomized controlled trials (RCT's) pose a threat to the validity of this evidence base, with dropout rates varying across studies. We conducted a systematic review and meta-analysis to investigate the prevalence and predictors of dropout rates among adults with depression participating in exercise RCT's. Three authors identified RCT's from a recent Cochrane review and conducted updated searches of major electronic databases from 01/2013 to 08/2015. We included RCT's of exercise interventions in people with depression (including major depressive disorder (MDD) and depressive symptoms) that reported dropout rates. A random effects meta-analysis and meta regression were conducted. Overall, 40 RCT's were included reporting dropout rates across 52 exercise interventions including 1720 people with depression (49.1 years (range=19-76 years), 72% female (range=0-100)). The trim and fill adjusted prevalence of dropout across all studies was 18.1% (95%CI=15.0-21.8%) and 17.2% (95%CI=13.5-21.7, N=31) in MDD only. In MDD participants, higher baseline depressive symptoms (β=0.0409, 95%CI=0.0809-0.0009, P=0.04) predicted greater dropout, whilst supervised interventions delivered by physiotherapists (β=-1.2029, 95%CI=-2.0967 to -0.3091, p=0.008) and exercise physiologists (β=-1.3396, 95%CI=-2.4478 to -0.2313, p=0.01) predicted lower dropout. A comparative meta-analysis (N=29) established dropout was lower in exercise than control conditions (OR=0.642, 95%CI=0.43-0.95, p=0.02). Exercise is well tolerated by people with depression and drop out in RCT's is lower than control conditions. Thus, exercise is a feasible treatment, in particular when delivered by healthcare professionals with specific training in exercise prescription. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. Test day-milk yields variance component estimation using repeatability or random regression models in the Rendena breed

    Directory of Open Access Journals (Sweden)

    Roberto Mantovani

    2010-01-01

    Full Text Available This study has aimed to compare Repeatability (RP-TDm and Random-Regression Test Day models (RR-TDm in genetic evaluations of milk (M, fat (F and protein (P yields in Rendena breed. Variance estimations for Milk (M, Fat (F and Protein (P were obtained on a sample of 43,842 TD belonging to 2,692 animals controlled over 15 years (1990-2005. RP-TDm estimates of h2 were of 0.21 for M and 0.17 for both F and P, whereas RR-TDM provided a trend of h2 ranging from 0.15-0.34 for M, 0.15-0.31 for F and 0.10-0.24 for P. Both RP-TDm and RR-TDm results agreed with literature, even though RR-TDm provided a pattern of h2 along the lactation different from other studies, with the lowest h2 at the beginning and at the end of lactation. PSB, MAD and -2Log L parameters revealed lower power of RP-TDm as compare with the RR-TDm.

  17. Application of random regression models for genetic analysis of 305-d milk yield over different lactations of Iranian Holsteins

    Directory of Open Access Journals (Sweden)

    Mahdi Elahi Torshizi

    2017-10-01

    Full Text Available Objective During the last decade, genetic evaluation of dairy cows using longitudinal data (test day milk yield or 305- day milk yield using random regression method has been officially adopted in several countries. The objectives of this study were to estimate covariance functions for genetic and permanent environmental effects and to obtain genetic parameters of 305-day milk yield over seven parities. Methods Data including 60,279 total 305–day milk yield of 17,309 Iranian Holstein dairy cows in 7 parities calved between 20 to 140 months between 2004 and 2011. Residual variances were modeled by homogeneous and step functions with 7 and 10 classes. Results The results showed that a third order polynomial for additive genetic and permanent environmental effects plus a step function with 10 classes for the residual variance was the most adequate and parsimonious model to describe the covariance structure of the data. Heritability estimates obtained by this model varied from 0.17 to 0.28. The performance of this model was better than repeatability model. Moreover, 10 classes of residual variance produce the more accurate result than 7 classes or homogeneous residual effect. Conclusion A quadratic Legendre polynomial for additive genetic and permanent environmental effects with 10 step function residual classes are sufficient to produce a parsimonious model that explained the change in 305-day milk yield over consecutive parities of Iranian Holstein cows.

  18. Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield.

    Science.gov (United States)

    Sun, Jin; Rutkoski, Jessica E; Poland, Jesse A; Crossa, José; Jannink, Jean-Luc; Sorrells, Mark E

    2017-07-01

    High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat ( L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect selection for grain yield. In this study, we evaluated three statistical models, simple repeatability (SR), multitrait (MT), and random regression (RR), for the longitudinal data of secondary traits and compared the impact of the proposed models for secondary traits on their predictive abilities for grain yield. Grain yield and secondary traits, canopy temperature (CT) and normalized difference vegetation index (NDVI), were collected in five diverse environments for 557 wheat lines with available pedigree and genomic information. A two-stage analysis was applied for pedigree and genomic selection (GS). First, secondary traits were fitted by SR, MT, or RR models, separately, within each environment. Then, best linear unbiased predictions (BLUPs) of secondary traits from the above models were used in the multivariate prediction models to compare predictive abilities for grain yield. Predictive ability was substantially improved by 70%, on average, from multivariate pedigree and genomic models when including secondary traits in both training and test populations. Additionally, (i) predictive abilities slightly varied for MT, RR, or SR models in this data set, (ii) results indicated that including BLUPs of secondary traits from the MT model was the best in severe drought, and (iii) the RR model was slightly better than SR and MT models under drought environment. Copyright © 2017 Crop Science Society of America.

  19. Placebo and nocebo reactions in randomized trials of pharmacological treatments for persistent depressive disorder. A meta-regression analysis.

    Science.gov (United States)

    Meister, Ramona; Jansen, Alessa; Härter, Martin; Nestoriuc, Yvonne; Kriston, Levente

    2017-06-01

    We aimed to investigate placebo and nocebo reactions in randomized controlled trials (RCT) of pharmacological treatments for persistent depressive disorder (PDD). We conducted a systematic electronic search and included RCTs investigating antidepressants for the treatment of PDD. Outcomes were the number of patients experiencing response and remission in placebo arms (=placebo reaction). Additional outcomes were the incidence of patients experiencing adverse events and related discontinuations in placebo arms (=nocebo reaction). A priori defined effect modifiers were analyzed using a series of meta-regression analyses. Twenty-three trials were included in the analyses. We found a pooled placebo response rate of 31% and a placebo remission rate of 22%. The pooled adverse event rate and related discontinuations were 57% and 4%, respectively. All placebo arm outcomes were positively associated with the corresponding medication arm outcomes. Placebo response rate was associated with a greater proportion of patients with early onset depression, a smaller chance to receive placebo and a larger sample size. The adverse event rate in placebo arms was associated with a greater proportion of patients with early onset depression, a smaller proportion of females and a more recent publication. Pooled placebo and nocebo reaction rates in PDD were comparable to those in episodic depression. The identified effect modifiers should be considered to assess unbiased effects in RCTs, to influence placebo and nocebo reactions in practice. Limitations result from the methodology applied, the fact that we conducted only univariate analyses, and the number and quality of included trials. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. 3D Statistical Shape Models Incorporating Landmark-Wise Random Regression Forests for Omni-Directional Landmark Detection.

    Science.gov (United States)

    Norajitra, Tobias; Maier-Hein, Klaus H

    2017-01-01

    3D Statistical Shape Models (3D-SSM) are widely used for medical image segmentation. However, during segmentation, they typically perform a very limited unidirectional search for suitable landmark positions in the image, relying on weak learners or use-case specific appearance models that solely take local image information into account. As a consequence, segmentation errors arise, and results in general depend on the accuracy of a previous model initialization. Furthermore, these methods become subject to a tedious and use-case dependent parameter tuning in order to obtain optimized results. To overcome these limitations, we propose an extension of 3D-SSM by landmark-wise random regression forests that perform an enhanced omni-directional search for landmark positions, thereby taking rich non-local image information into account. In addition, we provide a long distance model fitting based on a multi-scale approach, that allows an accurate and reproducible segmentation even from distant image positions, thus enabling an application without model initialization. Finally, translation of the proposed method to different organs is straightforward and requires no adaptation of the training process. In segmentation experiments on 45 clinical CT volumes, the proposed omni-directional search significantly increased accuracy and displayed great precision regardless of model initialization. Furthermore, for liver, spleen and kidney segmentation in a competitive multi-organ labeling challenge on publicly available data, the proposed method achieved similar or better results than the state of the art. Finally, liver segmentation results were obtained that successfully compete with specialized state-of-the-art methods from the well-known liver segmentation challenge SLIVER.

  1. Groundwater potential mapping using C5.0, random forest, and multivariate adaptive regression spline models in GIS.

    Science.gov (United States)

    Golkarian, Ali; Naghibi, Seyed Amir; Kalantar, Bahareh; Pradhan, Biswajeet

    2018-02-17

    Ever increasing demand for water resources for different purposes makes it essential to have better understanding and knowledge about water resources. As known, groundwater resources are one of the main water resources especially in countries with arid climatic condition. Thus, this study seeks to provide groundwater potential maps (GPMs) employing new algorithms. Accordingly, this study aims to validate the performance of C5.0, random forest (RF), and multivariate adaptive regression splines (MARS) algorithms for generating GPMs in the eastern part of Mashhad Plain, Iran. For this purpose, a dataset was produced consisting of spring locations as indicator and groundwater-conditioning factors (GCFs) as input. In this research, 13 GCFs were selected including altitude, slope aspect, slope angle, plan curvature, profile curvature, topographic wetness index (TWI), slope length, distance from rivers and faults, rivers and faults density, land use, and lithology. The mentioned dataset was divided into two classes of training and validation with 70 and 30% of the springs, respectively. Then, C5.0, RF, and MARS algorithms were employed using R statistical software, and the final values were transformed into GPMs. Finally, two evaluation criteria including Kappa and area under receiver operating characteristics curve (AUC-ROC) were calculated. According to the findings of this research, MARS had the best performance with AUC-ROC of 84.2%, followed by RF and C5.0 algorithms with AUC-ROC values of 79.7 and 77.3%, respectively. The results indicated that AUC-ROC values for the employed models are more than 70% which shows their acceptable performance. As a conclusion, the produced methodology could be used in other geographical areas. GPMs could be used by water resource managers and related organizations to accelerate and facilitate water resource exploitation.

  2. Octanuclear cubic coordination cages.

    Science.gov (United States)

    Tidmarsh, Ian S; Faust, Thomas B; Adams, Harry; Harding, Lindsay P; Russo, Luca; Clegg, William; Ward, Michael D

    2008-11-12

    Two new bis-bidentate bridging ligands have been prepared, L (naph) and L (anth), which contain two chelating pyrazolyl-pyridine units connected to an aromatic spacer (naphthalene-1,5-diyl and anthracene-9,10-diyl respectively) via methylene connectors. Each of these reacts with transition metal dications having a preference for octahedral coordination geometry to afford {M 8L 12} (16+) cages (for L (anth), M = Cu, Zn; for L (naph), M = Co, Ni, Cd) which have an approximately cubic arrangement of metal ions with a bridging ligand spanning each of the twelve edges, and a large central cavity containing a mixture of anions and/or solvent molecules. The cages based on L (anth) have two cyclic helical {M 4L 4} faces, of opposite chirality, connected by four additional L (anth) ligands as "pillars"; all metal centers have a meridional tris-chelate configuration. In contrast the cages based on L (naph) have (noncrystallographic) S 6 symmetry, with a diagonally opposite pair of corners having a facial tris-chelate configuration with the other six being meridional. An additional significant difference between the two types of structure is that the cubes containing L (anth) do not show significant interligand aromatic stacking interactions. However, in the cages based on L (naph), there are six five-membered stacks of aromatic ligand fragments around the periphery, each based on an alternating array of electron-rich (naphthyl) and electron-deficient (pyrazolyl-pyridine, coordinated to M (2+)) aromatic units. A consequence of this is that the cages {M 8(L (naph)) 12} (16+) retain their structural integrity in polar solvents, in contrast to the cages {M 8(L (anth)) 12} (16+) which dissociate in polar solvents. Consequently, the cages {M 8(L (naph)) 12} (16+) give NMR spectra in agreement with the symmetry observed in the solid state, and their fluorescence spectra (for M = Cd) display (in addition to the normal naphthalene-based pi-pi* fluorescence) a lower-energy exciplex

  3. FUZZY MATHEMATICS AND CUBICAL COMPLEXES

    Directory of Open Access Journals (Sweden)

    ADOLFO MACEDA MENDEZ

    2017-07-01

    applications in digital image processing and in the study of dynamical systems, but in the actual literature there is not an extension of their properties using fuzzy sets. In this paper is proposed a generalization of the concept of cubical complex and of some of their properties, such as connectedness, polyhedral realization, connected component and holes, using fuzzy sets. The upper and lower trees of a fuzzy cubical complex are defined, which give information about the way in which its regional extrema are related. The homology groups of a fuzzy cubical complex are defined and it is shown that the rank of the 0-homology group of a given level is equal with the number of regional maxima of that level. Finally, it is shown how to associate a fuzzy cubical complex with a bidimensional digital grayscale image in order to study somo of its topological properties.

  4. Estimation of genotype X environment interactions, in a grassbased system, for milk yield, body condition score,and body weight using random regression models

    NARCIS (Netherlands)

    Berry, D.P.; Buckley, F.; Dillon, P.; Evans, R.D.; Rath, M.; Veerkamp, R.F.

    2003-01-01

    (Co)variance components for milk yield, body condition score (BCS), body weight (BW), BCS change and BW change over different herd-year mean milk yields (HMY) and nutritional environments (concentrate feeding level, grazing severity and silage quality) were estimated using a random regression model.

  5. New machine learning tools for predictive vegetation mapping after climate change: Bagging and Random Forest perform better than Regression Tree Analysis

    Science.gov (United States)

    L.R. Iverson; A.M. Prasad; A. Liaw

    2004-01-01

    More and better machine learning tools are becoming available for landscape ecologists to aid in understanding species-environment relationships and to map probable species occurrence now and potentially into the future. To thal end, we evaluated three statistical models: Regression Tree Analybib (RTA), Bagging Trees (BT) and Random Forest (RF) for their utility in...

  6. Using Logistic Regression and Random Forests multivariate statistical methods for landslide spatial probability assessment in North-Est Sicily, Italy

    Science.gov (United States)

    Trigila, Alessandro; Iadanza, Carla; Esposito, Carlo; Scarascia-Mugnozza, Gabriele

    2015-04-01

    first phase of the work addressed to identify the spatial relationships between the landslides location and the 13 related factors by using the Frequency Ratio bivariate statistical method. The analysis was then carried out by adopting a multivariate statistical approach, according to the Logistic Regression technique and Random Forests technique that gave best results in terms of AUC. The models were performed and evaluated with different sample sizes and also taking into account the temporal variation of input variables such as burned areas by wildfire. The most significant outcome of this work are: the relevant influence of the sample size on the model results and the strong importance of some environmental factors (e.g. land use and wildfires) for the identification of the depletion zones of extremely rapid shallow landslides.

  7. Application of random forest time series, support vector regression and multivariate adaptive regression splines models in prediction of snowfall (a case study of Alvand in the middle Zagros, Iran)

    Science.gov (United States)

    Hamidi, Omid; Tapak, Leili; Abbasi, Hamed; Maryanaji, Zohreh

    2017-10-01

    We have conducted a case study to investigate the performance of support vector machine, multivariate adaptive regression splines, and random forest time series methods in snowfall modeling. These models were applied to a data set of monthly snowfall collected during six cold months at Hamadan Airport sample station located in the Zagros Mountain Range in Iran. We considered monthly data of snowfall from 1981 to 2008 during the period from October/November to April/May as the training set and the data from 2009 to 2015 as the testing set. The root mean square errors (RMSE), mean absolute errors (MAE), determination coefficient (R 2), coefficient of efficiency (E%), and intra-class correlation coefficient (ICC) statistics were used as evaluation criteria. Our results indicated that the random forest time series model outperformed the support vector machine and multivariate adaptive regression splines models in predicting monthly snowfall in terms of several criteria. The RMSE, MAE, R 2, E, and ICC for the testing set were 7.84, 5.52, 0.92, 0.89, and 0.93, respectively. The overall results indicated that the random forest time series model could be successfully used to estimate monthly snowfall values. Moreover, the support vector machine model showed substantial performance as well, suggesting it may also be applied to forecast snowfall in this area.

  8. Genetic parameters for milk production by using random regression models with different alternatives of fixed regression modeling Parâmetros genéticos para produção de leite usando modelos de regressão aleatória com diferentes alternativas de modelagem da regressão fixa

    Directory of Open Access Journals (Sweden)

    Jaime Araújo Cobuci

    2011-03-01

    Full Text Available Records of test-day milk yields of the first three lactations of 25,500 Holstein cows were used to estimate genetic parameters for milk yield by using two alternatives of definition of fixed regression of the random regression models (RRM. Legendre polynomials of fourth and fifth orders were used to model regression of fixed curve (defined based on averages of the populations or multiple sub-populations formed by grouping animals which calved at the same age and in the same season of the year or random lactation curves (additive genetic and permanent enviroment. Akaike information criterion (AIC and Bayesian information criterion (BIC indicated that the models which used multiple regression of fixed lactation curves of lactation multiple regression model with fixed lactation curves had the best fit for the first lactation test-day milk yields and the models which used a single regression of fixed curve had the best fit for the second and third lactations. Heritability for milk yield during lactation estimates did not vary among models but ranged from 0.22 to 0.34, from 0.11 to 0.21, and from 0.10 to 0.20, respectively, in the first three lactations. Similarly to heridability estimates of genetic correlations did not vary among models. The use of single or multiple fixed regressions for fixed lactation curves by RRM does not influence the estimates of genetic parameters for test-day milk yield across lactations.Os registros de produção de leite no dia do controle das três primeiras lactações de 25,5 mil vacas da raça Holandesa foram utilizados para estimar parâmetros genéticos para produção de leite usando duas alternativas de definição da regressão fixa dos modelos de regressão aleatória (MRA. Os polinômios de Legendre de ordens 4 e 5 foram usados para modelar as regressões das curvas fixas (definidas com base nas médias das produções de leite no dia do controle da população ou de múltiplas sub-populações formadas pelo

  9. Canopy Height Estimation in French Guiana with LiDAR ICESat/GLAS Data Using Principal Component Analysis and Random Forest Regressions

    Directory of Open Access Journals (Sweden)

    Ibrahim Fayad

    2014-11-01

    Full Text Available Estimating forest canopy height from large-footprint satellite LiDAR waveforms is challenging given the complex interaction between LiDAR waveforms, terrain, and vegetation, especially in dense tropical and equatorial forests. In this study, canopy height in French Guiana was estimated using multiple linear regression models and the Random Forest technique (RF. This analysis was either based on LiDAR waveform metrics extracted from the GLAS (Geoscience Laser Altimeter System spaceborne LiDAR data and terrain information derived from the SRTM (Shuttle Radar Topography Mission DEM (Digital Elevation Model or on Principal Component Analysis (PCA of GLAS waveforms. Results show that the best statistical model for estimating forest height based on waveform metrics and digital elevation data is a linear regression of waveform extent, trailing edge extent, and terrain index (RMSE of 3.7 m. For the PCA based models, better canopy height estimation results were observed using a regression model that incorporated both the first 13 principal components (PCs and the waveform extent (RMSE = 3.8 m. Random Forest regressions revealed that the best configuration for canopy height estimation used all the following metrics: waveform extent, leading edge, trailing edge, and terrain index (RMSE = 3.4 m. Waveform extent was the variable that best explained canopy height, with an importance factor almost three times higher than those for the other three metrics (leading edge, trailing edge, and terrain index. Furthermore, the Random Forest regression incorporating the first 13 PCs and the waveform extent had a slightly-improved canopy height estimation in comparison to the linear model, with an RMSE of 3.6 m. In conclusion, multiple linear regressions and RF regressions provided canopy height estimations with similar precision using either LiDAR metrics or PCs. However, a regression model (linear regression or RF based on the PCA of waveform samples with waveform

  10. Cryptographic Analysis in Cubic Time

    DEFF Research Database (Denmark)

    Nielson, Flemming; Nielson, Hanne Riis; Seidl, H.

    2004-01-01

    The spi-calculus is a variant of the polyadic pi-calculus that admits symmetric cryptography and that admits expressing communication protocols in a precise though still abstract way. This paper shows that context-independent control flow analysis can be calculated in cubic time despite the fact...... that the spi-calculus operates over an infinite universe of values. Our approach is based on Horn Clauses with Sharing and we develop transformations to pass from the infinite to the finite and to deal with the polyadic nature of input and output. We prove that this suffices for obtaining a cubic time...

  11. Canopy height estimation in French Guiana with LiDAR ICESat/GLAS data using principal component analysis and random forest regressions

    OpenAIRE

    Ibrahim Fayad; Nicolas Baghdadi; Jean-Stéphane Bailly; Nicolas Barbier; Valéry Gond; Mahmoud El Hajj; Frédéric Fabre; Bernard Bourgine

    2014-01-01

    International audience; Estimating forest canopy height from large-footprint satellite LiDAR waveforms is challenging given the complex interaction between LiDAR waveforms, terrain, and vegetation, especially in dense tropical and equatorial forests. In this study, canopy height in French Guiana was estimated using multiple linear regression models and the Random Forest technique (RF). This analysis was either based on LiDAR waveform metrics extracted from the GLAS (Geoscience Laser Altimeter...

  12. Modelos de regressão aleatória com diferentes estruturas de variância residual para descrever o tamanho da leitegada Random regression models with different residual variance structures for describing litter size in swine

    Directory of Open Access Journals (Sweden)

    Aderbal Cavalcante-Neto

    2011-12-01

    Full Text Available Objetivou-se comparar modelos de regressão aleatória com diferentes estruturas de variância residual, a fim de se buscar a melhor modelagem para a característica tamanho da leitegada ao nascer (TLN. Utilizaram-se 1.701 registros de TLN, que foram analisados por meio de modelo animal, unicaracterística, de regressão aleatória. As regressões fixa e aleatórias foram representadas por funções contínuas sobre a ordem de parto, ajustadas por polinômios ortogonais de Legendre de ordem 3. Para averiguar a melhor modelagem para a variância residual, considerou-se a heterogeneidade de variância por meio de 1 a 7 classes de variância residual. O modelo geral de análise incluiu grupo de contemporâneo como efeito fixo; os coeficientes de regressão fixa para modelar a trajetória média da população; os coeficientes de regressão aleatória do efeito genético aditivo-direto, do comum-de-leitegada e do de ambiente permanente de animal; e o efeito aleatório residual. O teste da razão de verossimilhança, o critério de informação de Akaike e o critério de informação bayesiano de Schwarz apontaram o modelo que considerou homogeneidade de variância como o que proporcionou melhor ajuste aos dados utilizados. As herdabilidades obtidas foram próximas a zero (0,002 a 0,006. O efeito de ambiente permanente foi crescente da 1ª (0,06 à 5ª (0,28 ordem, mas decrescente desse ponto até a 7ª ordem (0,18. O comum-de-leitegada apresentou valores baixos (0,01 a 0,02. A utilização de homogeneidade de variância residual foi mais adequada para modelar as variâncias associadas à característica tamanho da leitegada ao nascer nesse conjunto de dado.The objective of this work was to compare random regression models with different residual variance structures, so as to obtain the best modeling for the trait litter size at birth (LSB in swine. One thousand, seven hundred and one records of LSB were analyzed. LSB was analyzed by means of a

  13. The use of a random regression model on the estimation of genetic parameters for weight at performance test in Appenninica sheep breed

    Directory of Open Access Journals (Sweden)

    Francesca M. Sarti

    2015-07-01

    Full Text Available The Appenninica breed is an Italian meat sheep; the rams are approved according to a phenotypic index that is based on an average daily gain at performance test. The 8546 live weights of 1930 Appenninica male lambs tested in the performance station of the ASSONAPA (National Sheep Breeders Association, Italy from 1986 to 2010 showed a great variability in age at weighing and in number of records by year. The goal of the study is to verify the feasibility of the estimation of a genetic index for weight in the Appenninica sheep by a mixed model, and to explore the use of random regression to avoid the corrections for weighing at different ages. The heritability and repeatability (mean±SE of the average live weight were 0.27±0.04 and 0.54±0.08 respectively; the heritabilities of weights recorded at different weighing days ranged from 0.27 to 0.58, while the heritabilities of weights at different ages showed a narrower variability (0.29÷0.41. The estimates of live weight heritability by random regressions ranged between 0.34 at 123 d of age and 0.52 at 411 d. The results proved that the random regression model is the most adequate to analyse the data of Appenninica breed.

  14. Cubication of Conservative Nonlinear Oscillators

    Science.gov (United States)

    Belendez, Augusto; Alvarez, Mariela L.; Fernandez, Elena; Pascual, Immaculada

    2009-01-01

    A cubication procedure of the nonlinear differential equation for conservative nonlinear oscillators is analysed and discussed. This scheme is based on the Chebyshev series expansion of the restoring force, and this allows us to approximate the original nonlinear differential equation by a Duffing equation in which the coefficients for the linear…

  15. Acupuncture for musculoskeletal pain: A meta-analysis and meta-regression of sham-controlled randomized clinical trials

    OpenAIRE

    Qi-ling Yuan; Peng Wang; Liang Liu; Fu Sun; Yong-song Cai; Wen-tao Wu; Mao-lin Ye; Jiang-tao Ma; Bang-bang Xu; Yin-gang Zhang

    2016-01-01

    The aims of this systematic review were to study the analgesic effect of real acupuncture and to explore whether sham acupuncture (SA) type is related to the estimated effect of real acupuncture for musculoskeletal pain. Five databases were searched. The outcome was pain or disability immediately (?1 week) following an intervention. Standardized mean differences (SMDs) with 95% confidence intervals were calculated. Meta-regression was used to explore possible sources of heterogeneity. Sixty-t...

  16. Utilização de modelos de regressão aleatória para produção de leite no dia do controle, com diferentes estruturas de variâncias residuais Random regression test-day models for milk yield records, with different structure of residual variances

    Directory of Open Access Journals (Sweden)

    Lenira El Faro

    2003-10-01

    Full Text Available Foram utilizados quatorze modelos de regressão aleatória, para ajustar 86.598 dados de produção de leite no dia do controle de 2.155 primeiras lactações de vacas Caracu, truncadas aos 305 dias. Os modelos incluíram os efeitos fixos de grupo contemporâneo e a covariável idade da vaca ao parto. Uma regressão ortogonal de ordem cúbica foi usada para modelar a trajetória média da população. Os efeitos genéticos aditivos e de ambiente permanente foram modelados por meio de regressões aleatórias, usando polinômios ortogonais de Legendre, de ordens cúbicas. Diferentes estruturas de variâncias residuais foram testadas e consideradas por meio de classes contendo 1, 10, 15 e 43 variâncias residuais e de funções de variâncias (FV usando polinômios ordinários e ortogonais, cujas ordens variaram de quadrática até sêxtupla. Os modelos foram comparados usando o teste da razão de verossimilhança, o Critério de Informação de Akaike e o Critério de Informação Bayesiano de Schwar. Os testes indicaram que, quanto maior a ordem da função de variâncias, melhor o ajuste. Dos polinômios ordinários, a função de sexta ordem foi superior. Os modelos com classes de variâncias residuais foram aparentemente superiores àqueles com funções de variância. O modelo com homogeneidade de variâncias foi inadequado. O modelo com 15 classes heterogêneas foi o que melhor ajustou às variâncias residuais, entretanto, os parâmetros genéticos estimados foram muito próximos para os modelos com 10, 15 ou 43 classes de variâncias ou com FV de sexta ordem.Fourteen random regression models were used to adjust 86,595 test-day milk records of 2,155 first lactation of native Caracu cows. The models include fixed effects of contemporary group and age of cow as covariable. A cubic regression on Legendre orthogonal polynomial of days in milk was used to model the mean trend and the additive genetic and permanent environmental regressions

  17. Advances in SCA and RF-DNA Fingerprinting Through Enhanced Linear Regression Attacks and Application of Random Forest Classifiers

    Science.gov (United States)

    2014-09-18

    when 3 or more images were used for classification. All three easily outperform the Naive Bayes Maximum Likelihood method. In [85], the Random Forest is...Maximum Likelihood (MDA/ML) . . . . . . . . . . . . . . . . . . . . . . . . 22 2.5.1.2 Naive Bayes . . . . . . . . . . . . . . . . . . . . . . . . 24...probabilities [59], log-likelihood is used here. Given a known distribution, ML provides optimal classification performance [125]. 2.5.1.2 Naive Bayes If N

  18. Comparing cluster-level dynamic treatment regimens using sequential, multiple assignment, randomized trials: Regression estimation and sample size considerations

    OpenAIRE

    NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel

    2016-01-01

    Cluster-level dynamic treatment regimens can be used to guide sequential, intervention or treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level DTR, the intervention or treatment is potentially adapted and re-adapted over time based on changes in the cluster that could be impacted by prior intervention, including based on aggregate measures of the individuals or patients that comprise it. Cluster-randomized sequentia...

  19. Acupuncture for musculoskeletal pain: A meta-analysis and meta-regression of sham-controlled randomized clinical trials.

    Science.gov (United States)

    Yuan, Qi-Ling; Wang, Peng; Liu, Liang; Sun, Fu; Cai, Yong-Song; Wu, Wen-Tao; Ye, Mao-Lin; Ma, Jiang-Tao; Xu, Bang-Bang; Zhang, Yin-Gang

    2016-07-29

    The aims of this systematic review were to study the analgesic effect of real acupuncture and to explore whether sham acupuncture (SA) type is related to the estimated effect of real acupuncture for musculoskeletal pain. Five databases were searched. The outcome was pain or disability immediately (≤1 week) following an intervention. Standardized mean differences (SMDs) with 95% confidence intervals were calculated. Meta-regression was used to explore possible sources of heterogeneity. Sixty-three studies (6382 individuals) were included. Eight condition types were included. The pooled effect size was moderate for pain relief (59 trials, 4980 individuals, SMD -0.61, 95% CI -0.76 to -0.47; P meta-regression model, sham needle location and/or depth could explain most or all heterogeneities for some conditions (e.g., shoulder pain, low back pain, osteoarthritis, myofascial pain, and fibromyalgia); however, the interactions between subgroups via these covariates were not significant (P < 0.05). Our review provided low-quality evidence that real acupuncture has a moderate effect (approximate 12-point reduction on the 100-mm visual analogue scale) on musculoskeletal pain. SA type did not appear to be related to the estimated effect of real acupuncture.

  20. Application of single-step genomic best linear unbiased prediction with a multiple-lactation random regression test-day model for Japanese Holsteins.

    Science.gov (United States)

    Baba, Toshimi; Gotoh, Yusaku; Yamaguchi, Satoshi; Nakagawa, Satoshi; Abe, Hayato; Masuda, Yutaka; Kawahara, Takayoshi

    2017-08-01

    This study aimed to evaluate a validation reliability of single-step genomic best linear unbiased prediction (ssGBLUP) with a multiple-lactation random regression test-day model and investigate an effect of adding genotyped cows on the reliability. Two data sets for test-day records from the first three lactations were used: full data from February 1975 to December 2015 (60 850 534 records from 2 853 810 cows) and reduced data cut off in 2011 (53 091 066 records from 2 502 307 cows). We used marker genotypes of 4480 bulls and 608 cows. Genomic enhanced breeding values (GEBV) of 305-day milk yield in all the lactations were estimated for at least 535 young bulls using two marker data sets: bull genotypes only and both bulls and cows genotypes. The realized reliability (R 2 ) from linear regression analysis was used as an indicator of validation reliability. Using only genotyped bulls, R 2 was ranged from 0.41 to 0.46 and it was always higher than parent averages. The very similar R 2 were observed when genotyped cows were added. An application of ssGBLUP to a multiple-lactation random regression model is feasible and adding a limited number of genotyped cows has no significant effect on reliability of GEBV for genotyped bulls. © 2016 Japanese Society of Animal Science.

  1. Cubication of conservative nonlinear oscillators

    Energy Technology Data Exchange (ETDEWEB)

    Belendez, Augusto; Alvarez, Mariela L [Departamento de Fisica, Ingenieria de Sistemas y Teoria de la Senal, Universidad de Alicante, Apartado 99, E-03080 Alicante (Spain); Fernandez, Elena; Pascual, Inmaculada [Departamento de Optica, FarmacologIa y Anatomia, Universidad de Alicante, Apartado 99, E-03080 Alicante (Spain)], E-mail: a.belendez@ua.es

    2009-09-15

    A cubication procedure of the nonlinear differential equation for conservative nonlinear oscillators is analysed and discussed. This scheme is based on the Chebyshev series expansion of the restoring force, and this allows us to approximate the original nonlinear differential equation by a Duffing equation in which the coefficients for the linear and cubic terms depend on the initial amplitude, A, while in a Taylor expansion of the restoring force these coefficients are independent of A. The replacement of the original nonlinear equation by an approximate Duffing equation allows us to obtain an approximate frequency-amplitude relation as a function of the complete elliptic integral of the first kind. Some conservative nonlinear oscillators are analysed to illustrate the usefulness and effectiveness of this scheme.

  2. Numbers for reducible cubic scrolls

    Directory of Open Access Journals (Sweden)

    Israel Vainsencher

    2004-12-01

    Full Text Available We show how to compute the number of reducible cubic scrolls of codimension 2 in (math blackboard symbol Pn incident to the appropriate number of linear spaces.Mostramos como calcular o número de rolos cúbicos redutíveis de codimensão 2 em (math blackboard symbol Pn incidentes a espaços lineares apropriados.

  3. Cubic Matrix, Nambu Mechanics and Beyond

    OpenAIRE

    Yoshiharu, KAWAMURA; Department of Physics, Shinshu University

    2003-01-01

    We propose a generalization of cubic matrix mechanics by introducing a canonical triplet and study its relation to Nambu mechanics. The generalized cubic matrix mechanics we consider can be interpreted as a 'quantum' generalization of Nambu mechanics.

  4. Cubic Matrix, Nambu Mechanics and Beyond

    OpenAIRE

    Kawamura, Y.

    2002-01-01

    We propose a generalization of cubic matrix mechanics by introducing a canonical triplet and study its relation to Nambu mechanics. The generalized cubic matrix mechanics we consider can be interpreted as a “quantum” generalization of Nambu mechanics.

  5. Estimation of genetic parameters for racing speed at different distances in young and adult Spanish Trotter horses using the random regression model.

    Science.gov (United States)

    Gómez, M D; Menendez-Buxadera, A; Valera, M; Molina, A

    2010-10-01

    A total of 71 522 records (from 3154 horses) with the times per kilometre (TPK), recorded in Spanish Trotter horses (individual races) from racing performances held from 1991 to 2007, were available for this study. The TPK values for the different age groups (young and adult horses) and different distances (1600-2700 m) were considered as different traits, and a bi character random regression model (RRM) was applied to estimate the (co)variance components throughout the trajectory of age groups and distances. The following effects were considered as fixed: the combination of hippodrome-date of race (404 levels); sex of the animals (3 levels); type of start (2 levels) and a fixed regression of Legendre polynomials (order 2). Those considered as random effects were the random regression Legendre polynomial (order 1) for animals (9201 animals in the pedigree); the individual environment permanent (3154 animals with data) and the driver (n = 957 levels). The residual variance was considered as heterogeneous with two classes (ages). The heritability estimated by distance ranged from 0.12 to 0.34, with a different trajectory for the two age groups. Within each age group, the genetic correlations between adjacent distances were high (>0.90), but decreased when the differences between them were over 400 metres for both age groups. The genetic correlations for the same distance across the age groups ranged from 0.47 to 0.78. Accordingly, the analysed trait (TPK) can be considered as positive genetic correlated but as different traits along the trajectory of distance and age. Therefore, some re-ranking should be expected in the breeding value of the horses at different characteristics of the racing. The use of RRM is recommended because it allows us to estimate the breeding value along the whole trajectory of race competition. Copyright 2010 Blackwell Verlag GmbH.

  6. Solving Cubic Equations by Polynomial Decomposition

    Science.gov (United States)

    Kulkarni, Raghavendra G.

    2011-01-01

    Several mathematicians struggled to solve cubic equations, and in 1515 Scipione del Ferro reportedly solved the cubic while participating in a local mathematical contest, but did not bother to publish his method. Then it was Cardano (1539) who first published the solution to the general cubic equation in his book "The Great Art, or, The Rules of…

  7. Cubic colloids : Synthesis, functionalization and applications

    NARCIS (Netherlands)

    Castillo, S.I.R.

    2015-01-01

    This thesis is a study on cubic colloids: micron-sized cubic particles with rounded corners (cubic superballs). Owing to their shape, particle packing for cubes is more efficient than for spheres and results in fascinating phase and packing behavior. For our cubes, the particle volume fraction when

  8. Modelos de regressão aleatória para avaliação da curva de crescimento em matrizes de codorna de corte Random regression models for growth evaluation of meat-type quail hens

    Directory of Open Access Journals (Sweden)

    Bruno Bastos Teixeira

    2012-09-01

    Full Text Available Objetivou-se comparar diferentes modelos de regressão aleatória por meio de funções polinomiais de Legendre de diferentes ordens, para avaliar o que melhor se ajusta ao estudo genético da curva de crescimento de codornas de corte. Foram avaliados dados de 2136 matrizes de codorna de corte, dos quais 1026 pertenciam ao grupo genético UFV1 e 1110 ao grupo UFV2. As codornas foram pesadas nos 1°, 7°, 14°, 21°, 28°, 35°, 42°, 77°, 112° e 147° dias de idade e seus pesos utilizados para a análise. Foram testadas duas possíveis modelagens de variância residual heterogênea, sendo agrupadas em 3 e 5 classes de idade. Após, foi realizado o estudo do modelo de regressão aleatória que melhor aplica-se à curva de crescimento das codornas. A comparação entre os modelos foi feita pelo Critério de Informação de Akaike (AIC, Critério de Informação Bayesiano de Schwarz (BIC, Logaritmo da função de verossimilhança (Log e L e teste da razão de verossimilhança (LRT, ao nível de 1%. O modelo que considerou a heterogeneidade de variância residual CL3 mostrou-se adequado à linhagem UFV1, e o modelo CL5 à linhagem UFV2. Uma função polinomial de Legendre com ordem 5, para efeito genético aditivo direto e 5 para efeito permanente de animal, para a linhagem UFV1 e, com ordem 3, para efeito genético aditivo direto e 5 para efeito permanente de animal para a linhagem UFV2, deve ser utilizada na avaliação genética da curva de crescimento das codornas de corte.The objective was to compare different random regression models using Legendre polynomial functions of different orders, to evaluate what best fits the genetic study of the growth curve of meat quails. It was evaluated data from 2136 cut dies quail, of which 1026 belonged to genetic group UFV1 and 1110 the group UFV2. Quail were weighed at 10, 70, 140, 210, 280, 350, 420, 770, 1120 and 1470 days of age, and weights used for the analysis. It was tested two possible modeling

  9. Underemployment and mental health: comparing fixed-effects and random-effects regression approaches in an Australian working population cohort.

    Science.gov (United States)

    Milner, Allison; LaMontagne, Anthony D

    2017-05-01

    Underemployment occurs when workers are available for more hours of work than offered. It is a serious problem in many Organisation for Economic Co-operation and Development (OECD) countries, and particularly in Australia, where it affects about 8% of the employed population. This paper seeks to answer the question: does an increase in underemployment have an influence on mental health? The current paper uses data from an Australian cohort of working people (2001-2013) to investigate both within-person and between-person differences in mental health associated with being underemployed compared with being fully employed. The main exposure was underemployment (not underemployed, underemployed 1-5, 6-10, 11-20 and over 21 hours), and the outcome was the five-item Mental Health Inventory. Results suggest that stepwise declines in mental health are associated with an increasing number of hours underemployed. Results were stronger in the random-effects (11-20 hours =-1.53, 95% CI -2.03 to -1.03, p<0.001; 21 hours and over -2.24, 95% CI -3.06 to -1.43, p<0.001) than fixed-effects models (11-20 hours =-1.11, 95% CI -1.63 to -0.58, p<0.001; 21 hours and over -1.19, 95% CI -2.06 to -0.32, p=0.008). This likely reflects the fact that certain workers were more likely to suffer the negative effects of underemployment than others (eg, women, younger workers, workers in lower-skilled jobs and who were casually employed). We suggest underemployment to be a target of future workplace prevention strategies. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  10. Effect of intensive statin therapy on regression of carotid intima-media thickness in patients with subclinical carotid atherosclerosis (a prospective, randomized trial: PEACE (Pitavastatin Evaluation of Atherosclerosis Regression by Intensive Cholesterol-lowering Therapy) study).

    Science.gov (United States)

    Ikeda, Koji; Takahashi, Tomosaburo; Yamada, Hiroyuki; Matsui, Kiyoaki; Sawada, Takahisa; Nakamura, Takashi; Matsubara, Hiroaki

    2013-12-01

    Atherosclerosis often advances before symptoms appear. It remains uncertain whether intensive cholesterol-lowering therapy with statin is beneficial when compared with moderate cholesterol-lowering therapy in patients with subclinical carotid atherosclerosis. The PEACE study was a prospective, randomized, open-labeled, blinded end points, two-arm parallel treatment group comparison study conducted at 15 centers in Japan. A total of 303 patients with carotid intima-media thickness (CIMT) thickening (>1.1 mm) whose low-density lipoprotein cholesterol (LDL-C) level was more than 100 mg/dl were enrolled, in which 223 patients completed the 12 months' follow-up study. Patients were randomly assigned to receive either moderate (target LDL-C; 100 mg/dl) or intensive (target LDL-C; 80 mg/dl) cholesterol-lowering therapy with pitavastatin. The primary end point was the change in mean far wall common CIMT. LDL-C level declined to 89.4 ± 20 mg/dl in the intensive group, while it declined to 95.1 ± 22.5 mg/dl in the moderate group at 12 months' follow-up (p confidence interval -0.046 to -0.0014) mm/year (p confidence interval -0.028 to 0.012) mm/year (p = 0.4406 vs. baseline) in the moderate group. However, there was no significant difference in the change in mean far wall common CIMT between the groups (p = 0.29). Intensive cholesterol-lowering therapy did not show superior effects on the progression of CIMT to moderate cholesterol-lowering therapy, whereas only intensive cholesterol-lowering therapy regressed the carotid atherosclerosis over one year.

  11. Estimation of Genetic Parameters for First Lactation Monthly Test-day Milk Yields using Random Regression Test Day Model in Karan Fries Cattle

    Directory of Open Access Journals (Sweden)

    Ajay Singh

    2016-06-01

    Full Text Available A single trait linear mixed random regression test-day model was applied for the first time for analyzing the first lactation monthly test-day milk yield records in Karan Fries cattle. The test-day milk yield data was modeled using a random regression model (RRM considering different order of Legendre polynomial for the additive genetic effect (4th order and the permanent environmental effect (5th order. Data pertaining to 1,583 lactation records spread over a period of 30 years were recorded and analyzed in the study. The variance component, heritability and genetic correlations among test-day milk yields were estimated using RRM. RRM heritability estimates of test-day milk yield varied from 0.11 to 0.22 in different test-day records. The estimates of genetic correlations between different test-day milk yields ranged 0.01 (test-day 1 [TD-1] and TD-11 to 0.99 (TD-4 and TD-5. The magnitudes of genetic correlations between test-day milk yields decreased as the interval between test-days increased and adjacent test-day had higher correlations. Additive genetic and permanent environment variances were higher for test-day milk yields at both ends of lactation. The residual variance was observed to be lower than the permanent environment variance for all the test-day milk yields.

  12. Vitamin A supplementation and neonatal mortality in the developing world: a meta-regression of cluster-randomized trials.

    Science.gov (United States)

    Rotondi, Michael Anthony; Khobzi, Nooshin

    2010-09-01

    To assess the relationship between the prevalence of vitamin A deficiency among pregnant women and the effect of neonatal vitamin A supplementation on infant mortality. Studies of neonatal supplementation with vitamin A have yielded contradictory findings with regard to its effect on the risk of infant death, possibly owing to heterogeneity between studies. One source of that heterogeneity is the prevalence of vitamin A deficiency among pregnant women, which we examined using meta-regression techniques on eligible individual and cluster-randomized trials. Adapting standard techniques to control for the inclusion of a cluster-randomized trial, we modelled the logarithm of the relative risk of infant death comparing vitamin A supplementation at birth to a standard treatment, as a linear function of the prevalence of vitamin A deficiency in pregnant women. Meta-regression analysis revealed a statistically significant linear relationship between the prevalence of vitamin A deficiency in pregnant women and the observed effectiveness of vitamin A supplementation at birth. In regions where at least 22% of pregnant women have vitamin A deficiency, giving neonates vitamin A supplements will have a protective effect against infant death. A meta-regression analysis is observational in nature and may suffer from confounding bias. Nevertheless, our study suggests that vitamin A supplementation can reduce infant mortality in regions where this micronutrient deficiency is common. Thus, neonatal supplementation programmes may prove most beneficial in regions where the prevalence of vitamin A deficiency among pregnant women is high.

  13. Genetic analysis of the cumulative pseudo-survival rate during lactation of Holstein cattle in Japan by using random regression models.

    Science.gov (United States)

    Sasaki, O; Aihara, M; Nishiura, A; Takeda, H; Satoh, M

    2015-08-01

    Longevity is a crucial economic trait in the dairy farming industry. In this study, our objective was to develop a random regression model for genetic evaluation of survival. For the analysis, we used test-day records obtained for the first 5 lactations of 380,252 cows from 1,296 herds in Japan between 2001 and 2010; this data set was randomly divided into 7 subsets. The cumulative pseudo-survival rate (PSR) was determined according to whether a cow was alive (1) or absent (0) in her herd on the test day within each lactation group. Each lactation number was treated as an independent trait in a random regression multiple-trait model (MTM) or as a repeated measure in a random regression single-trait repeatability model (STRM). A proportional hazard model (PHM) was also developed as a piecewise-hazards model. The average (± standard deviation) heritability estimates of the PSR at 365 d in milk (DIM) among the 7 data sets in the first (LG1), second (LG2), and third to fifth lactations (LG3) of the MTM were 0.042±0.007, 0.070±0.012, and 0.084±0.007, respectively. The heritability estimate of the STRM was 0.038±0.004. The genetic correlations of PSR between distinct DIM within or between lactation groups were high when the interval between DIM was short. These results indicated that whereas the genetic factors contributing to the PSR between closely associated DIM would be similar even for different lactation numbers, the genetic factors contributing to PSR would differ between distinct lactation periods. The average (± standard deviation) effective heritability estimate based on the relative risk of the PHM among the 7 data sets was 0.068±0.009. The estimated breeding values (EBV) in LG1, LG2, LG3, the STRM, and the PHM were unbiased estimates of the genetic trend. The absolute values of the Spearman's rank correlation coefficients between the EBV of the relative risk of the PHM and the EBV of PSR at 365 DIM for LG1, LG2, LG3, and the STRM were 0.75, 0.87, 0

  14. Heat and moisture exchangers (HMEs) and heated humidifiers (HHs) in adult critically ill patients: a systematic review, meta-analysis and meta-regression of randomized controlled trials.

    Science.gov (United States)

    Vargas, Maria; Chiumello, Davide; Sutherasan, Yuda; Ball, Lorenzo; Esquinas, Antonio M; Pelosi, Paolo; Servillo, Giuseppe

    2017-05-29

    The aims of this systematic review and meta-analysis of randomized controlled trials are to evaluate the effects of active heated humidifiers (HHs) and moisture exchangers (HMEs) in preventing artificial airway occlusion and pneumonia, and on mortality in adult critically ill patients. In addition, we planned to perform a meta-regression analysis to evaluate the relationship between the incidence of artificial airway occlusion, pneumonia and mortality and clinical features of adult critically ill patients. Computerized databases were searched for randomized controlled trials (RCTs) comparing HHs and HMEs and reporting artificial airway occlusion, pneumonia and mortality as predefined outcomes. Relative risk (RR), 95% confidence interval for each outcome and I 2 were estimated for each outcome. Furthermore, weighted random-effect meta-regression analysis was performed to test the relationship between the effect size on each considered outcome and covariates. Eighteen RCTs and 2442 adult critically ill patients were included in the analysis. The incidence of artificial airway occlusion (RR = 1.853; 95% CI 0.792-4.338), pneumonia (RR = 932; 95% CI 0.730-1.190) and mortality (RR = 1.023; 95% CI 0.878-1.192) were not different in patients treated with HMEs and HHs. However, in the subgroup analyses the incidence of airway occlusion was higher in HMEs compared with HHs with non-heated wire (RR = 3.776; 95% CI 1.560-9.143). According to the meta-regression, the effect size in the treatment group on artificial airway occlusion was influenced by the percentage of patients with pneumonia (β = -0.058; p = 0.027; favors HMEs in studies with high prevalence of pneumonia), and a trend was observed for an effect of the duration of mechanical ventilation (MV) (β = -0.108; p = 0.054; favors HMEs in studies with longer MV time). In this meta-analysis we found no superiority of HMEs and HHs, in terms of artificial airway occlusion, pneumonia and

  15. A matrix-based method of moments for fitting the multivariate random effects model for meta-analysis and meta-regression.

    Science.gov (United States)

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

    2013-03-01

    Multivariate meta-analysis is becoming more commonly used. Methods for fitting the multivariate random effects model include maximum likelihood, restricted maximum likelihood, Bayesian estimation and multivariate generalisations of the standard univariate method of moments. Here, we provide a new multivariate method of moments for estimating the between-study covariance matrix with the properties that (1) it allows for either complete or incomplete outcomes and (2) it allows for covariates through meta-regression. Further, for complete data, it is invariant to linear transformations. Our method reduces to the usual univariate method of moments, proposed by DerSimonian and Laird, in a single dimension. We illustrate our method and compare it with some of the alternatives using a simulation study and a real example. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. A matrix-based method of moments for fitting the multivariate random effects model for meta-analysis and meta-regression

    Science.gov (United States)

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

    2013-01-01

    Multivariate meta-analysis is becoming more commonly used. Methods for fitting the multivariate random effects model include maximum likelihood, restricted maximum likelihood, Bayesian estimation and multivariate generalisations of the standard univariate method of moments. Here, we provide a new multivariate method of moments for estimating the between-study covariance matrix with the properties that (1) it allows for either complete or incomplete outcomes and (2) it allows for covariates through meta-regression. Further, for complete data, it is invariant to linear transformations. Our method reduces to the usual univariate method of moments, proposed by DerSimonian and Laird, in a single dimension. We illustrate our method and compare it with some of the alternatives using a simulation study and a real example. PMID:23401213

  17. Efficacy of cognitive behavioral therapy for anxiety disorders in older people: a meta-analysis and meta-regression of randomized controlled trials.

    Science.gov (United States)

    Gould, Rebecca L; Coulson, Mark C; Howard, Robert J

    2012-02-01

    To review the magnitude and duration of and factors associated with effects of cognitive behavioral therapy (CBT) for anxiety disorders in older people. Electronic literature databases and the Cochrane Trials Registry were searched for articles. A systematic critical review, random-effects meta-analysis, and meta-regression of randomized controlled trials were conducted. Community outpatient clinics. People with diagnoses of anxiety disorders. Outcome measures of anxiety and depression. Twelve studies were included. CBT was significantly more effective than treatment as usual or being on a waiting list at reducing anxiety symptoms at 0-month follow-up, with the effect size being moderate, but when CBT was compared with an active control condition, the between-group difference in favor of CBT was not statistically significant, and the effect size was small. At 6- but not 3- or 12-month follow-up, CBT was significantly more effective at reducing anxiety symptoms than an active control condition, although the effect size was again small. Meta-regression analyses revealed only one factor (type of control group) to be significantly associated with the magnitude of effect sizes. The review confirms the effectiveness of CBT for anxiety disorders in older people but is suggestive of lower efficacy in older than working-age people. The small effect sizes in favor of CBT over an active control condition illustrate the need to investigate other treatment approaches that may be used to substitute or augment CBT to increase the effectiveness of treatment of anxiety disorders in older people. © 2012, Copyright the Authors Journal compilation © 2012, The American Geriatrics Society.

  18. Cubical local partial orders on cubically subdivided spaces - existence and construction

    DEFF Research Database (Denmark)

    Fajstrup, Lisbeth

    The geometric models of Higher Dimensional Automata and Dijkstra's PV-model are cubically subdivided topological spaces with a local partial order. If a cubicalization of a topological space is free of immersed cubic Möbius bands, then there are consistent choices of direction in all cubes, such ...

  19. Topics in Cubic Special Geometry

    CERN Document Server

    Bellucci, Stefano; Roychowdhury, Raju

    2011-01-01

    We reconsider the sub-leading quantum perturbative corrections to N=2 cubic special Kaehler geometries. Imposing the invariance under axion-shifts, all such corrections (but the imaginary constant one) can be introduced or removed through suitable, lower unitriangular symplectic transformations, dubbed Peccei-Quinn (PQ) transformations. Since PQ transformations do not belong to the d=4 U-duality group G4, in symmetric cases they generally have a non-trivial action on the unique quartic invariant polynomial I4 of the charge representation R of G4. This leads to interesting phenomena in relation to theory of extremal black hole attractors; namely, the possibility to make transitions between different charge orbits of R, with corresponding change of the supersymmetry properties of the supported attractor solutions. Furthermore, a suitable action of PQ transformations can also set I4 to zero, or vice versa it can generate a non-vanishing I4: this corresponds to transitions between "large" and "small" charge orbit...

  20. (real and complex) of the general cubic

    African Journals Online (AJOL)

    ES Obe

    + cx + d = 0 have been formulated and presented. The explicit hyperbolic expressions for the complex roots have been developed for the first time in history thereby enabling the establishment of harmony in the solution of cubic equations. Also, four alternative expressions for the only real root of the cubic have also been ...

  1. Regression Basics

    CERN Document Server

    Kahane, Leo H

    2007-01-01

    Using a friendly, nontechnical approach, the Second Edition of Regression Basics introduces readers to the fundamentals of regression. Accessible to anyone with an introductory statistics background, this book builds from a simple two-variable model to a model of greater complexity. Author Leo H. Kahane weaves four engaging examples throughout the text to illustrate not only the techniques of regression but also how this empirical tool can be applied in creative ways to consider a broad array of topics. New to the Second Edition Offers greater coverage of simple panel-data estimation:

  2. Enhancement of regression of cervical intraepithelial neoplasia II (moderate dysplasia) with topically applied all-trans-retinoic acid: a randomized trial.

    Science.gov (United States)

    Meyskens, F L; Surwit, E; Moon, T E; Childers, J M; Davis, J R; Dorr, R T; Johnson, C S; Alberts, D S

    1994-04-06

    Retinoids enhance differentiation of most epithelial tissues. Epidemiologic studies have shown an inverse relationship between dietary intake or serum levels of vitamin A and the development of cervical dysplasia and/or cervical cancer. Pilot and phase I investigations demonstrated the feasibility of the local delivery of all-trans-retinoic acid (RA) to the cervix using a collagen sponge insert and cervical cap. A phase II trial produced a clinical complete response rate of 50%. This randomized phase III trial was designed to determine whether topically applied RA reversed moderate cervical intraepithelial neoplasia (CIN) II or severe CIN. Analyses were based on 301 women with CIN (moderate dysplasia, 151 women; severe dysplasia, 150 women), evaluated by serial colposcopy, Papanicolaou cytology, and cervical biopsy. Cervical caps with sponges containing either 1.0 mL of 0.372% beta-trans-RA or a placebo were inserted daily for 4 days when women entered the trial, and for 2 days at months 3 and 6. Patients receiving treatment and those receiving placebo were similar with respect to age, ethnicity, birth-control methods, histologic features of the endocervical biopsy specimen and koilocytotic atypia, and percentage of involvement of the cervix at study. Treatment effects were compared using Fisher's exact test and logistic regression methods. Side effects were recorded, and differences were compared using Fisher's exact test. RA increased the complete histologic regression rate of CIN II from 27% in the placebo group to 43% in the retinoic acid treatment group (P = .041). No treatment difference between the two arms was evident in the severe dysplasia group. More vaginal and vulvar side effects were seen in the patients receiving RA, but these effects were mild and reversible. A short course of locally applied RA can reverse CIN II, but not more advanced dysplasia, with acceptable local side effects. A derivative of vitamin A can reverse or suppress an epithelial

  3. Exposure assessment models for elemental components of particulate matter in an urban environment: A comparison of regression and random forest approaches

    Science.gov (United States)

    Brokamp, Cole; Jandarov, Roman; Rao, M. B.; LeMasters, Grace; Ryan, Patrick

    2017-02-01

    Exposure assessment for elemental components of particulate matter (PM) using land use modeling is a complex problem due to the high spatial and temporal variations in pollutant concentrations at the local scale. Land use regression (LUR) models may fail to capture complex interactions and non-linear relationships between pollutant concentrations and land use variables. The increasing availability of big spatial data and machine learning methods present an opportunity for improvement in PM exposure assessment models. In this manuscript, our objective was to develop a novel land use random forest (LURF) model and compare its accuracy and precision to a LUR model for elemental components of PM in the urban city of Cincinnati, Ohio. PM smaller than 2.5 μm (PM2.5) and eleven elemental components were measured at 24 sampling stations from the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). Over 50 different predictors associated with transportation, physical features, community socioeconomic characteristics, greenspace, land cover, and emission point sources were used to construct LUR and LURF models. Cross validation was used to quantify and compare model performance. LURF and LUR models were created for aluminum (Al), copper (Cu), iron (Fe), potassium (K), manganese (Mn), nickel (Ni), lead (Pb), sulfur (S), silicon (Si), vanadium (V), zinc (Zn), and total PM2.5 in the CCAAPS study area. LURF utilized a more diverse and greater number of predictors than LUR and LURF models for Al, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all showed a decrease in fractional predictive error of at least 5% compared to their LUR models. LURF models for Al, Cu, Fe, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all had a cross validated fractional predictive error less than 30%. Furthermore, LUR models showed a differential exposure assessment bias and had a higher prediction error variance. Random forest and other machine learning methods may provide more accurate exposure assessment.

  4. Effect of Daily Caper Fruit Pickle Consumption on Disease Regression in Patients with Non-Alcoholic Fatty Liver Disease: a Double-Blinded Randomized Clinical Trial

    Directory of Open Access Journals (Sweden)

    Narjes Khavasi

    2017-12-01

    Full Text Available Purpose: Despite numerous studies on the effects of complementary medicine, to our knowledge, there is no study on the effects of Capparis spinosa on disease regression in non-alcoholic fatty liver disease (NAFLD patients. We compared the effects of caper fruit pickle consumption, as an Iranian traditional medicine product, on the anthropometric measures and biochemical parameters in different NAFLD patients. Methods: A 12-weeks randomized, controlled, double-blind trial was designed in 44 NAFLD patients randomly categorized for the control (n=22 or caper (n=22. The caper group received 40-50 gr of caper fruit pickles with meals daily. Before and after treatment, we assessed anthropometric measures, grade of fatty liver, serum lipoproteins and liver enzymes. Results: Weight and BMI were significantly decreased in the caper (p<0.001 and p<0.001 and control group (p=0.001 and p=0.001, respectively. Serum TG, TC and LDL.C just were significantly decreased in the control group (p=0.01, p<0.001 and p<0.001, respectively. Adjusted to the baseline measures, serum ALT and AST reduction were significantly higher in the caper than control group from baseline up to the end of the study (p<0.001 and p=0.02, respectively. After weeks 12, disease severity was significantly decreased in the caper group (p <0.001. Conclusion: Our results suggest that daily caper fruit pickle consumption for 12 weeks may be potentially effective on improving the biochemical parameters in NAFLD patients. Further, additional larger controlled trials are needed for the verification of these results.

  5. Pre-hospital electrocardiogram triage with telemedicine near halves time to treatment in STEMI: A meta-analysis and meta-regression analysis of non-randomized studies.

    Science.gov (United States)

    Brunetti, Natale Daniele; De Gennaro, Luisa; Correale, Michele; Santoro, Francesco; Caldarola, Pasquale; Gaglione, Antonio; Di Biase, Matteo

    2017-04-01

    A shorter time to treatment has been shown to be associated with lower mortality rates in acute myocardial infarction (AMI). Several strategies have been adopted with the aim to reduce any delay in diagnosis of AMI: pre-hospital triage with telemedicine is one of such strategies. We therefore aimed to measure the real effect of pre-hospital triage with telemedicine in case of AMI in a meta-analysis study. We performed a meta-analysis of non-randomized studies with the aim to quantify the exact reduction of time to treatment achieved by pre-hospital triage with telemedicine. Data were pooled and compared by relative time reduction and 95% C.I.s. A meta-regression analysis was performed in order to find possible predictors of shorter time to treatment. Eleven studies were selected and finally evaluated in the study. The overall relative reduction of time to treatment with pre-hospital triage and telemedicine was -38/-40% (ptriage with telemedicine is associated with a near halved time to treatment in AMI. The benefit is larger in terms of absolute time to treatment reduction in populations with larger delays to treatment. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Quadratic-like dynamics of cubic polynomials

    OpenAIRE

    Blokh, Alexander; Oversteegen, Lex; Ptacek, Ross; Timorin, Vladlen

    2013-01-01

    A small perturbation of a quadratic polynomial with a non-repelling fixed point gives a polynomial with an attracting fixed point and a Jordan curve Julia set, on which the perturbed polynomial acts like angle doubling. However, there are cubic polynomials with a non-repelling fixed point, for which no perturbation results into a polynomial with Jordan curve Julia set. Motivated by the study of the closure of the Cubic Principal Hyperbolic Domain, we describe such polynomials in terms of thei...

  7. Heisenberg antiferromagnets with exchange and cubic anisotropies

    Energy Technology Data Exchange (ETDEWEB)

    Bannasch, G [MPI fuer Physik komplexer Systeme, 01187 Dresden (Germany); Selke, W, E-mail: selke@physik.rwth-aachen.d [Institut fuer Theoretische Physik, RWTH Aachen University and JARA-SIM, 52056 Aachen (Germany)

    2010-01-01

    We study classical Heisenberg antiferromagnets with uniaxial exchange anisotropy and a cubic anisotropy term on simple cubic lattices in an external magnetic field using ground state considerations and extensive Monte Carlo simulations. In addition to the antiferromagnetic phase field-induced spin-flop and non-collinear, biconical phases may occur. Phase diagrams and critical as well as multicritical phenomena are discussed. Results are compared to previous findings.

  8. Segmented Regression Based on B-Splines with Solved Examples

    Directory of Open Access Journals (Sweden)

    Miloš Kaňka

    2015-12-01

    Full Text Available The subject of the paper is segmented linear, quadratic, and cubic regression based on B-spline basis functions. In this article we expose the formulas for the computation of B-splines of order one, two, and three that is needed to construct linear, quadratic, and cubic regression. We list some interesting properties of these functions. For a clearer understanding we give the solutions of a couple of elementary exercises regarding these functions.

  9. Genetic Analysis of Milk Yield in First-Lactation Holstein Friesian in Ethiopia: A Lactation Average vs Random Regression Test-Day Model Analysis

    Directory of Open Access Journals (Sweden)

    S. Meseret

    2015-09-01

    Full Text Available The development of effective genetic evaluations and selection of sires requires accurate estimates of genetic parameters for all economically important traits in the breeding goal. The main objective of this study was to assess the relative performance of the traditional lactation average model (LAM against the random regression test-day model (RRM in the estimation of genetic parameters and prediction of breeding values for Holstein Friesian herds in Ethiopia. The data used consisted of 6,500 test-day (TD records from 800 first-lactation Holstein Friesian cows that calved between 1997 and 2013. Co-variance components were estimated using the average information restricted maximum likelihood method under single trait animal model. The estimate of heritability for first-lactation milk yield was 0.30 from LAM whilst estimates from the RRM model ranged from 0.17 to 0.29 for the different stages of lactation. Genetic correlations between different TDs in first-lactation Holstein Friesian ranged from 0.37 to 0.99. The observed genetic correlation was less than unity between milk yields at different TDs, which indicated that the assumption of LAM may not be optimal for accurate evaluation of the genetic merit of animals. A close look at estimated breeding values from both models showed that RRM had higher standard deviation compared to LAM indicating that the TD model makes efficient utilization of TD information. Correlations of breeding values between models ranged from 0.90 to 0.96 for different group of sires and cows and marked re-rankings were observed in top sires and cows in moving from the traditional LAM to RRM evaluations.

  10. Comparing the effect of aromatase inhibitor (letrozole) + cabergoline (Dostinex) and letrozole alone on uterine myoma regression,a randomized clinical trial.

    Science.gov (United States)

    Sayyah-Melli, M; Mobasseri, M; Gharabaghi, P M; Ouladsahebmadarek, E; Rahmani, V

    2017-03-01

    To evaluate the effect of letrozole in combination with cabergoline and letrozole alone on regression of symptomatic uterine myomas in women of reproductive age. Randomized controlled clinical trial. University hospital. Ninety-one women of reproductive age were enrolled in the study and 88 women were eligible. Eight participants were excluded from the study. Eighty women of reproductive age with symptomatic myomas >4cm were evaluated in two groups. Participants in Group 1 received 2.5mg letrozole once daily and cabergoline 0.5mg/week from the first day of the menstrual cycle for 12 weeks, and participants in Group 2 received letrozole alone. Changes in uterine size and volume; myoma size, volume and number; and side effects of treatment. Overall, 76 patients completed the study. Compared with baseline values, mean uterine volume was reduced significantly in both groups (p=0.01), and there was no significant difference between groups (p=0.99). The mean number of dominant myomas was reduced significantly in both groups (p=0.03), with no significant difference between groups (p=0.6). The mean volume of myomas was reduced significantly in both groups (p=0.01), with no significant difference between groups (p=0.45). Although a significant decrease in number and volume of myomas was documented in each group (pcabergoline group (nine vs two cases, p=0.02), but the two groups were comparable for the remaining minor side effects. This study showed that 12 weeks of treatment with letrozole with and without cabergoline improved the size and volume of the uterus and myomas, led to symptom improvement, and could be used for short-term treatment prior to surgery or fertility programmes. Condensation letrozole in combination with cabergoline in the management of uterine fibroids. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  11. Genetic Analysis of Milk Yield in First-Lactation Holstein Friesian in Ethiopia: A Lactation Average vs Random Regression Test-Day Model Analysis

    Science.gov (United States)

    Meseret, S.; Tamir, B.; Gebreyohannes, G.; Lidauer, M.; Negussie, E.

    2015-01-01

    The development of effective genetic evaluations and selection of sires requires accurate estimates of genetic parameters for all economically important traits in the breeding goal. The main objective of this study was to assess the relative performance of the traditional lactation average model (LAM) against the random regression test-day model (RRM) in the estimation of genetic parameters and prediction of breeding values for Holstein Friesian herds in Ethiopia. The data used consisted of 6,500 test-day (TD) records from 800 first-lactation Holstein Friesian cows that calved between 1997 and 2013. Co-variance components were estimated using the average information restricted maximum likelihood method under single trait animal model. The estimate of heritability for first-lactation milk yield was 0.30 from LAM whilst estimates from the RRM model ranged from 0.17 to 0.29 for the different stages of lactation. Genetic correlations between different TDs in first-lactation Holstein Friesian ranged from 0.37 to 0.99. The observed genetic correlation was less than unity between milk yields at different TDs, which indicated that the assumption of LAM may not be optimal for accurate evaluation of the genetic merit of animals. A close look at estimated breeding values from both models showed that RRM had higher standard deviation compared to LAM indicating that the TD model makes efficient utilization of TD information. Correlations of breeding values between models ranged from 0.90 to 0.96 for different group of sires and cows and marked re-rankings were observed in top sires and cows in moving from the traditional LAM to RRM evaluations. PMID:26194217

  12. Linear regression

    CERN Document Server

    Olive, David J

    2017-01-01

    This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response trans...

  13. Fraktal Regress

    Directory of Open Access Journals (Sweden)

    Igor K. Kochanenko

    2013-01-01

    Full Text Available Procedures of construction of curve regress by criterion of the least fractals, i.e. the greatest probability of the sums of degrees of the least deviations measured intensity from their modelling values are proved. The exponent is defined as fractal dimension of a time number. The difference of results of a well-founded method and a method of the least squares is quantitatively estimated.

  14. Packing of nonoverlapping cubic particles: Computational algorithms and microstructural characteristics

    Science.gov (United States)

    Malmir, Hessam; Sahimi, Muhammad; Tabar, M. Reza Rahimi

    2016-12-01

    Packing of cubic particles arises in a variety of problems, ranging from biological materials to colloids and the fabrication of new types of porous materials with controlled morphology. The properties of such packings may also be relevant to problems involving suspensions of cubic zeolites, precipitation of salt crystals during CO2 sequestration in rock, and intrusion of fresh water in aquifers by saline water. Not much is known, however, about the structure and statistical descriptors of such packings. We present a detailed simulation and microstructural characterization of packings of nonoverlapping monodisperse cubic particles, following up on our preliminary results [H. Malmir et al., Sci. Rep. 6, 35024 (2016), 10.1038/srep35024]. A modification of the random sequential addition (RSA) algorithm has been developed to generate such packings, and a variety of microstructural descriptors, including the radial distribution function, the face-normal correlation function, two-point probability and cluster functions, the lineal-path function, the pore-size distribution function, and surface-surface and surface-void correlation functions, have been computed, along with the specific surface and mean chord length of the packings. The results indicate the existence of both spatial and orientational long-range order as the the packing density increases. The maximum packing fraction achievable with the RSA method is about 0.57, which represents the limit for a structure similar to liquid crystals.

  15. Genetic correlations between the cumulative pseudo-survival rate, milk yield, and somatic cell score during lactation in Holstein cattle in Japan using a random regression model.

    Science.gov (United States)

    Sasaki, O; Aihara, M; Nishiura, A; Takeda, H

    2017-09-01

    Trends in genetic correlations between longevity, milk yield, and somatic cell score (SCS) during lactation in cows are difficult to trace. In this study, changes in the genetic correlations between milk yield, SCS, and cumulative pseudo-survival rate (PSR) during lactation were examined, and the effect of milk yield and SCS information on the reliability of estimated breeding value (EBV) of PSR were determined. Test day milk yield, SCS, and PSR records were obtained for Holstein cows in Japan from 2004 to 2013. A random subset of the data was used for the analysis (825 herds, 205,383 cows). This data set was randomly divided into 5 subsets (162-168 herds, 83,389-95,854 cows), and genetic parameters were estimated in each subset independently. Data were analyzed using multiple-trait random regression animal models including either the residual effect for the whole lactation period (H0), the residual effects for 5 lactation stages (H5), or both of these residual effects (HD). Milk yield heritability increased until 310 to 351 d in milk (DIM) and SCS heritability increased until 330 to 344 DIM. Heritability estimates for PSR increased with DIM from 0.00 to 0.05. The genetic correlation between milk yield and SCS increased negatively to under -0.60 at 455 DIM. The genetic correlation between milk yield and PSR increased until 342 to 355 DIM (0.53-0.57). The genetic correlation between the SCS and PSR was -0.82 to -0.83 at around 180 DIM, and decreased to -0.65 to -0.71 at 455 DIM. The reliability of EBV of PSR for sires with 30 or more recorded daughters was 0.17 to 0.45 when the effects of correlated traits were ignored. The maximum reliability of EBV was observed at 257 (H0) or 322 (HD) DIM. When the correlations of PSR with milk yield and SCS were considered, the reliabilities of PSR estimates increased to 0.31-0.76. The genetic parameter estimates of H5 were the same as those for HD. The rank correlation coefficients of the EBV of PSR between H0 and H5 or HD were

  16. Landslide Susceptibility Analysis by the comparison and integration of Random Forest and Logistic Regression methods; application to the disaster of Nova Friburgo - Rio de Janeiro, Brasil (January 2011)

    Science.gov (United States)

    Esposito, Carlo; Barra, Anna; Evans, Stephen G.; Scarascia Mugnozza, Gabriele; Delaney, Keith

    2014-05-01

    The study of landslide susceptibility by multivariate statistical methods is based on finding a quantitative relationship between controlling factors and landslide occurrence. Such studies have become popular in the last few decades thanks to the development of geographic information systems (GIS) software and the related improved data management. In this work we applied a statistical approach to an area of high landslide susceptibility mainly due to its tropical climate and geological-geomorphological setting. The study area is located in the south-east region of Brazil that has frequently been affected by flood and landslide hazard, especially because of heavy rainfall events during the summer season. In this work we studied a disastrous event that occurred on January 11th and 12th of 2011, which involved Região Serrana (the mountainous region of Rio de Janeiro State) and caused more than 5000 landslides and at least 904 deaths. In order to produce susceptibility maps, we focused our attention on an area of 93,6 km2 that includes Nova Friburgo city. We utilized two different multivariate statistic methods: Logistic Regression (LR), already widely used in applied geosciences, and Random Forest (RF), which has only recently been applied to landslide susceptibility analysis. With reference to each mapping unit, the first method (LR) results in a probability of landslide occurrence, while the second one (RF) gives a prediction in terms of % of area susceptible to slope failure. With this aim in mind, a landslide inventory map (related to the studied event) has been drawn up through analyses of high-resolution GeoEye satellite images, in a GIS environment. Data layers of 11 causative factors have been created and processed in order to be used as continuous numerical or discrete categorical variables in statistical analysis. In particular, the logistic regression method has frequent difficulties in managing numerical continuous and discrete categorical variables

  17. Pennies for Milk: Using a First-Hand Descent into Randomness to Illustrate the Risks of Regression to the Mean for Marketing Researchers and Managers

    Science.gov (United States)

    Posavac, Steven S.; Posavac, Emil J.

    2017-01-01

    The authors describe the Pennies for Milk exercise, a participative classroom experience in which students generate a regression to the mean effect within the context of simulated household milk purchases. Regression to the mean is a ubiquitous threat for marketing researchers and managers but is often hard for students to understand. The Pennies…

  18. Uso de funções ortogonais para descrever a produção de leite no dia de controle por meio de modelos de regressão aleatória Genetic modelling of daily milk yield using orthogonal polynomials in random regression

    Directory of Open Access Journals (Sweden)

    Cláudio Vieira de Araújo

    2006-06-01

    Full Text Available Registros de produção de leite de 68.523 controles leiteiros de 8.536 vacas da raça Holandesa, filhas de 537 reprodutores, distribuídas em 266 rebanhos, com parições nos anos de 1996 a 2001, foram utilizados na comparação de modelos de regressão aleatória, para estimação de componentes de variância. Os modelos de regressão aleatória diferiram entre si pelo grau do polinômio de Legendre utilizado para descrever a trajetória da curva de lactação dos animais. Os modelos incluíram os efeitos rebanho-mês-ano do controle, composição genética dos animais, freqüência de ordenhas diárias, regressão polinomial em cada classe de idade-estação de parto para descrever a parte fixa da lactação e regressão polinomial aleatória relacionadas aos efeitos genético direto e de ambiente permanente. As estimativas de herdabilidade obtidas oscilaram de 0,122 a 0,291. Verificou-se que o modelo de regressão aleatória que utilizou a maior ordem para os polinômios de Legendre descreveu melhor a variação genética da produção de leite, de acordo com o critério de Akaike.Data comprising 68,523 test day milk yield of 8,536 cows of the Holstein breed, daughters of 537 sires, distributed in 266 herds, calving from 1996 to 2001, were used to compare random regression models, for estimating variance. Test day records (TD were analyzed by different random regression models regarding the function used to describe the trajectory of the lactation curve of the animals. Legendre orthogonal polynomials function of second, third and fourth order were used. The random regression models included the effects of herd-month-year of the control, genetic group of the animals; the frequency of the daily milk; regression coefficients for each class of age-season (in order to describe the fixed part of the lactation curve and random regression coefficients related to the direct genetic and the permanent environmental effects. The heritability estimates

  19. Estimação de parâmetros genéticos para peso do nascimento aos 550 dias de idade para animais da raça Tabapuã utilizando-se modelos de regressão aleatória Genetic parameters for weights from birth to 550 days of age of Tabapuã cattle using random regression models

    Directory of Open Access Journals (Sweden)

    Laila Talarico Dias

    2006-10-01

    , consisting of 21,762 records from 4,221 animals of Tabapuã cattle, weighted from birth to 550 days of age, were used to estimate covariance functions by random regression models using Legendre polynomials of order two to five. Models included the direct and maternal genetic, animal and maternal permanent environmental random effects and compared by Schwarz´s Bayesian information criteria (BIC and Akaike´s information criteria (AIC. Both criterions suggested the model including direct genetic, maternal genetic, animal permanent and maternal permanent environmental effects respectively adjusted by cubic, quadratic, fourth order and linear polynomials, and residual variances adjusted by fifth order variance function as the best one to describe the covariance structure of the used database. Direct heritability estimates were higher at the beginning and at the end of the growth trajectory. Maternal heritability estimates increased from birth to 160 days of age and decreased thereafter. In general, genetic correlation estimates decreased as age between weights increased. Efficiency of selection may be improved by using weights of the post weaning period because of their higher genetic variance and heritability estimates.

  20. Purely cubic action for string field theory

    Science.gov (United States)

    Horowitz, G. T.; Lykken, J.; Rohm, R.; Strominger, A.

    1986-01-01

    It is shown that Witten's (1986) open-bosonic-string field-theory action and a closed-string analog can be written as a purely cubic interaction term. The conventional form of the action arises by expansion around particular solutions of the classical equations of motion. The explicit background dependence of the conventional action via the Becchi-Rouet-Stora-Tyutin operator is eliminated in the cubic formulation. A closed-form expression is found for the full nonlinear gauge-transformation law.

  1. The Exact Limit of Some Cubic Towers

    DEFF Research Database (Denmark)

    Anbar Meidl, Nurdagül; Beelen, Peter; Nguyen, Nhut

    2017-01-01

    Recently, a new explicit tower of function fields was introduced by Bassa, Beelen, Garcia and Stichtenoth (BBGS). This resulted in currently the best known lower bound for Ihara’s constant in the case of non-prime finite fields. In particular over cubic fields, the tower’s limit is at least as good...

  2. A look through 'lens' cubic mitochondria.

    Science.gov (United States)

    Almsherqi, Zakaria; Margadant, Felix; Deng, Yuru

    2012-10-06

    Cell membranes may fold up into three-dimensional nanoperiodic cubic structures in biological systems. Similar geometries are well studied in other disciplines such as mathematics, physics and polymer chemistry. The fundamental function of cubic membranes in biological systems has not been uncovered yet; however, their appearance in specialized cell types indicates a role as structural templates or perhaps direct physical entities with specialized biophysical properties. The mitochondria located at the inner segment of the retinal cones of tree shrew (Tupaia glis and Tupaia belangeri) contain unique patterns of concentric cristae with a highly ordered membrane arrangement in three dimensions similar to the photonic nanostructures observed in butterfly wing scales. Using a direct template matching method, we show that the inner mitochondrial membrane folds into multi-layered (8 to 12 layers) gyroid cubic membrane arrangements in the photoreceptor cells. Three-dimensional simulation data demonstrate that such multi-layer gyroid membrane arrangements in the retinal cones of a tree shrew's eye can potentially function as: (i) multi-focal lens; (ii) angle-independent interference filters to block UV light; and (iii) a waveguide photonic crystal. These theoretical results highlight for the first time the significance of multi-layer cubic membrane arrangements to achieve near-quasi-photonic crystal properties through the simple and reversible biological process of continuous membrane folding.

  3. A monotonicity conjecture for real cubic maps

    Energy Technology Data Exchange (ETDEWEB)

    Dawson, S.P. [Los Alamos National Lab., NM (United States); Galeeva, R. [Northwestern Univ., Evanston, IL (United States); Milnor, J. [State Univ. of New York, Stony Brook, NY (United States); Tresser, C. [International Business Machines Corp., Yorktown Heights, NY (United States)

    1993-12-01

    This will be an outline of work in progress. We study the conjecture that the topological entropy of a real cubic map depends ``monotonely`` on its parameters, in the sense that each locus of constant entropy in parameter space is a connected set. This material will be presented in more detail in a later paper.

  4. Cubical version of combinatorial differential forms

    DEFF Research Database (Denmark)

    Kock, Anders

    2010-01-01

    The theory of combinatorial differential forms is usually presented in simplicial terms. We present here a cubical version; it depends on the possibility of forming affine combinations of mutual neighbour points in a manifold, in the context of synthetic differential geometry....

  5. Uso de modelos de regressão aleatória para descrever a variação genética da produção de leite na raça Holandesa Random regressions models to describe the genetic variation of milk yield in Holstein breed

    Directory of Open Access Journals (Sweden)

    Cláudio Vieira de Araújo

    2006-06-01

    Full Text Available Registros de produção de leite de 68.523 controles leiteiros de 8.536 vacas da raça Holandesa, com parições nos anos de 1996 a 2001, foram utilizados na comparação entre modelos de regressão aleatória para estimação de componentes de variância. Os registros de controle leiteiro foram analisados como características múltiplas, considerando cada controle uma característica distinta. Os mesmos registros de controle leiteiro foram analisados como dados longitudinais, por meio de modelos de regressão aleatória, que diferiram entre si pela função utilizada para descrever a trajetória da curva de lactação dos animais. As funções utilizadas foram a exponencial de Wilmink, a função de Ali e Schaeffer e os polinômios de Legendre de segundo e quarto graus. A comparação entre modelos foi realizada com base nos seguintes critérios: estimativas de componentes de variância, obtidas no modelo multicaractístico e por regressão aleatória; valores da variância residual; e valores do logaritmo da função de verossimilhança. As estimativas de herdabilidade obtidas por meio dos modelos de características múltiplas variaram de 0,110 a 0,244. Para os modelos de regressão aleatória, esses valores oscilaram de 0,127 a 0,301, observando-se as maiores estimativas nos modelos com maior número de parâmetros. Verificou-se que os modelos de regressão aleatória que utilizaram os polinômios de Legendre descreveram melhor a variação genética da produção de leite.Data comprising 68,523 test day milk yield of 8,536 cows of the Holstein breed, calving from 1996 to 2001, were used to compare random regression models, for estimating variance components. Test day records (TD were analyzed as multiple traits, considering each TD as a different trait. The test day records were analyzed as longitudinal traits by different random regression models regarding the function used to describe the trajectory of the lactation curve of the animals

  6. Estimação de parâmetros genéticos em caprinos leiteiros por meio de análise de regressão aleatória utilizando-se a Amostragem de Gibbs Estimation of genetic parameters for milk yield of dairy goats by random regression analysis using Gibbs Sampling

    Directory of Open Access Journals (Sweden)

    Giselle Mariano Lessa de Assis

    2006-06-01

    Full Text Available Modelos de regressão aleatória foram utilizados neste estudo para estimar parâmetros genéticos da produção de leite no dia do controle (PLDC em caprinos leiteiros da raça Alpina, por meio da metodologia Bayesiana. As estimativas geradas foram comparadas às obtidas com análise de regressão aleatória, utilizando-se o REML. As herdabilidades encontradas pela análise Bayesiana variaram de 0,18 a 0,37, enquanto, pelo REML, variaram de 0,09 a 0,32. As correlações genéticas entre dias de controle próximos se aproximaram da unidade, decrescendo gradualmente conforme a distância entre os dias de controle aumentou. Os resultados obtidos indicam que: a estrutura de covariâncias da PLDC em caprinos ao longo da lactação pode ser modelada adequadamente por meio da regressão aleatória; a predição de ganhos genéticos e a seleção de animais geneticamente superiores é viável ao longo de toda a trajetória da lactação; os resultados gerados pelas análises de regressão aleatória utilizando-se a Amostragem de Gibbs e o REML foram semelhantes, embora as estimativas das variâncias genéticas e das herdabilidades tenham sido levemente superiores na análise Bayesiana, utilizando-se a Amostragem de Gibbs.Random regression models were used to estimate genetic parameters for test-day milk yield (PLDC of Alpine dairy goats, implemented by Bayesian methods with Gibbs Sampling. The estimates were compared with those obtained by random regression analysis, using REML. Heritability estimates obtained by Bayesian analysis ranged from 0.18 to 0.37, while those obtained by REML ranged from 0.09 to 0.32. Genetic correlations between yields of close test days approached the unit, but decreased gradually as the interval between test days increased. Results indicated that random regression models are appropriate to model the covariance structure of PLDC and to predict genetic gains and select animals along the lactation trajectory of dairy goats

  7. Electronic levels of cubic quantum dots

    Energy Technology Data Exchange (ETDEWEB)

    Aristone, Flavio [Federal De Mato Grosso Do Sul Univ., Campo Grande (Brazil); Sanchez-Dehesa, Jose [Autonoma De Madrid Univ., Madrid (Spain); Marques, Gilmar E. [Federal De Sao Carlos Univ., Sao Carlos (Brazil)

    2003-09-01

    We introduce an efficient variational method to solve the three-dimensional Schroedinger equation for any arbitrary potential V(x,y,z). The method uses a basis set of localized functions which are build up as products of one-dimensional cubic {beta}-splines. We calculated the energy levels of GaAs/AlGaAs cubic quantum dots and make a comparison with the results from two well-known simplification schemes based on a decomposition of the full potential problem into three separate one-dimensional problems. We show that the scheme making a sequential decomposition gives eigenvalues in better agreement with the ones obtained variationally, but an exact solution is necessary when looking for highly precise values.

  8. Linearizability conditions of quasi-cubic systems

    Directory of Open Access Journals (Sweden)

    Wentao Huang

    2012-09-01

    Full Text Available In this paper we study the linearizability problem of the two-dimensional complex quasi-cubic system $\\dot{z}=z+(zw^{d}(a_{30}z^{3}+a_{21}z^{2}w+a_{12}zw^2+a_{03}w^{3},~\\dot{w}=-w-(zw^{d}(b_{30}w^{3}+b_{21}w^{2}z+b_{12}wz^2+b_{03}z^{3}$, where $z, w, a_{ij}, b_{ij}\\in \\mathbb{C}$ and $d$ is a real number. We find a transformation to change the quasi-cubic system into an equivalent quintic system and then obtain the necessary and sufficient linearizability conditions by the Darboux linearization method or by proving the existence of linearizing transformations.

  9. Development of Technology Parameter Towards Shipbuilding Productivity Predictor Using Cubic Spline Approach

    Directory of Open Access Journals (Sweden)

    Bagiyo Suwasono

    2011-05-01

    Full Text Available Ability of production processes associated with state-of-the-art technology, which allows the shipbuilding, is customized with modern equipment. It will give impact to level of productivity and competitiveness. This study proposes a nonparametric regression cubic spline approach with 1 knot, 2 knots, and 3 knots. The application programs Tibco Spotfire S+ showed that a cubic spline with 2 knots (4.25 and 4.50 gave the best result with the value of GCV = 56.21556, and R2 = 94.03%.Estimation result of cubic spline with 2 knots for the PT. Batamec shipyard = 35.61 MH/CGT, PT. Dok & Perkapalan Surabaya = 27.49 MH/CGT, PT. Karimun Sembawang Shipyard = 27.49 MH/CGT, and PT. PAL Indonesia = 19.89 MH/CGT.

  10. Neutrosophic Cubic MCGDM Method Based on Similarity Measure

    Directory of Open Access Journals (Sweden)

    Surapati Pramanik

    2017-06-01

    Full Text Available The notion of neutrosophic cubic set is originated from the hybridization of the concept of neutrosophic set and interval valued neutrosophic set. We define similarity measure for neutrosophic cubic sets and prove some of its basic properties.

  11. Spherical model provides visual aid for cubic crystal study

    Science.gov (United States)

    Bacigalupi, R. J.; Spakowski, A. E.

    1965-01-01

    Transparent sphere of polymethylmethacrylate with major zones and poles of cubic crystals is used to make crystallographic visualizations and to interpret Laue X ray diffraction of single cubic crystals.

  12. Repeated measurements of blood lactate concentration as a prognostic marker in horses with acute colitis evaluated with classification and regression trees (CART) and random forest analysis

    DEFF Research Database (Denmark)

    Petersen, Mette Bisgaard; Tolver, Anders; Husted, Louise

    2016-01-01

    -off value of 7 mmol/L had a sensitivity of 0.66 and a specificity of 0.92 in predicting survival. In independent test data, the sensitivity was 0.69 and the specificity was 0.76. At the observed survival rate (38%), the optimal decision tree identified horses as non-survivors when the Lac at admission...... admitted with acute colitis (trees, as well as random...

  13. Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part I: Effects of Random Error

    Science.gov (United States)

    Duda, David P.; Minnis, Patrick

    2009-01-01

    Straightforward application of the Schmidt-Appleman contrail formation criteria to diagnose persistent contrail occurrence from numerical weather prediction data is hindered by significant bias errors in the upper tropospheric humidity. Logistic models of contrail occurrence have been proposed to overcome this problem, but basic questions remain about how random measurement error may affect their accuracy. A set of 5000 synthetic contrail observations is created to study the effects of random error in these probabilistic models. The simulated observations are based on distributions of temperature, humidity, and vertical velocity derived from Advanced Regional Prediction System (ARPS) weather analyses. The logistic models created from the simulated observations were evaluated using two common statistical measures of model accuracy, the percent correct (PC) and the Hanssen-Kuipers discriminant (HKD). To convert the probabilistic results of the logistic models into a dichotomous yes/no choice suitable for the statistical measures, two critical probability thresholds are considered. The HKD scores are higher when the climatological frequency of contrail occurrence is used as the critical threshold, while the PC scores are higher when the critical probability threshold is 0.5. For both thresholds, typical random errors in temperature, relative humidity, and vertical velocity are found to be small enough to allow for accurate logistic models of contrail occurrence. The accuracy of the models developed from synthetic data is over 85 percent for both the prediction of contrail occurrence and non-occurrence, although in practice, larger errors would be anticipated.

  14. Concepts for a theoretical and experimental study of lifting rotor random loads and vibrations. Phase 6-B: Experiments with progressing/regressing forced rotor flapping modes

    Science.gov (United States)

    Hohenemser, K. H.; Crews, S. T.

    1972-01-01

    A two bladed 16-inch hingeless rotor model was built and tested outside and inside a 24 by 24 inch wind tunnel test section at collective pitch settings up to 5 deg and rotor advance ratios up to .4. The rotor model has a simple eccentric mechanism to provide progressing or regressing cyclic pitch excitation. The flapping responses were compared to analytically determined responses which included flap-bending elasticity but excluded rotor wake effects. Substantial systematic deviations of the measured responses from the computed responses were found, which were interpreted as the effects of interaction of the blades with a rotating asymmetrical wake.

  15. Cubic-spline interpolation to estimate effects of inbreeding on milk yield in first lactation Holstein cows

    Directory of Open Access Journals (Sweden)

    Makram J. Geha

    2011-01-01

    Full Text Available Milk yield records (305d, 2X, actual milk yield of 123,639 registered first lactation Holstein cows were used to compare linear regression (y = β0 + β1X + e ,quadratic regression, (y = β0 + β1X + β2X2 + e cubic regression (y = β0 + β1X + β2X2 + β3X3 + e and fixed factor models, with cubic-spline interpolation models, for estimating the effects of inbreeding on milk yield. Ten animal models, all with herd-year-season of calving as fixed effect, were compared using the Akaike corrected-Information Criterion (AICc. The cubic-spline interpolation model with seven knots had the lowest AICc, whereas for all those labeled as "traditional", AICc was higher than the best model. Results from fitting inbreeding using a cubic-spline with seven knots were compared to results from fitting inbreeding as a linear covariate or as a fixed factor with seven levels. Estimates of inbreeding effects were not significantly different between the cubic-spline model and the fixed factor model, but were significantly different from the linear regression model. Milk yield decreased significantly at inbreeding levels greater than 9%. Variance component estimates were similar for the three models. Ranking of the top 100 sires with daughter records remained unaffected by the model used.

  16. Cubic-spline interpolation to estimate effects of inbreeding on milk yield in first lactation Holstein cows.

    Science.gov (United States)

    Geha, Makram J; Keown, Jeffrey F; Van Vleck, L Dale

    2011-07-01

    Milk yield records (305d, 2X, actual milk yield) of 123,639 registered first lactation Holstein cows were used to compare linear regression (y = β(0) + β(1)X + e), quadratic regression, (y = β(0) + β(1)X + β(2)X(2) + e) cubic regression (y = β(0) + β(1)X + β(2)X(2) + β(3)X(3) +e) and fixed factor models, with cubic-spline interpolation models, for estimating the effects of inbreeding on milk yield. Ten animal models, all with herd-year-season of calving as fixed effect, were compared using the Akaike corrected-Information Criterion (AICc). The cubic-spline interpolation model with seven knots had the lowest AICc, whereas for all those labeled as "traditional", AICc was higher than the best model. Results from fitting inbreeding using a cubic-spline with seven knots were compared to results from fitting inbreeding as a linear covariate or as a fixed factor with seven levels. Estimates of inbreeding effects were not significantly different between the cubic-spline model and the fixed factor model, but were significantly different from the linear regression model. Milk yield decreased significantly at inbreeding levels greater than 9%. Variance component estimates were similar for the three models. Ranking of the top 100 sires with daughter records remained unaffected by the model used.

  17. Topologically correct cortical segmentation using Khalimsky's cubic complex framework

    Science.gov (United States)

    Cardoso, Manuel J.; Clarkson, Matthew J.; Modat, Marc; Talbot, Hugues; Couprie, Michel; Ourselin, Sébastien

    2011-03-01

    Automatic segmentation of the cerebral cortex from magnetic resonance brain images is a valuable tool for neuroscience research. Due to the presence of noise, intensity non-uniformity, partial volume effects, the limited resolution of MRI and the highly convoluted shape of the cerebral cortex, segmenting the brain in a robust, accurate and topologically correct way still poses a challenge. In this paper we describe a topologically correct Expectation Maximisation based Maximum a Posteriori segmentation algorithm formulated within the Khalimsky cubic complex framework, where both the solution of the EM algorithm and the information derived from a geodesic distance function are used to locally modify the weighting of a Markov Random Field and drive the topology correction operations. Experiments performed on 20 Brainweb datasets show that the proposed method obtains a topologically correct segmentation without significant loss in accuracy when compared to two well established techniques.

  18. Early management of type 2 diabetes based on a SMBG strategy: the way to diabetes regression--the St Carlos study : a 3-year, prospective, randomized, clinic-based, interventional study with parallel groups.

    Science.gov (United States)

    García de la Torre, Nuria; Durán, Alejandra; Del Valle, Laura; Fuentes, Manuel; Barca, Idoya; Martín, Patricia; Montañez, Carmen; Perez-Ferre, Natalia; Abad, Rosario; Sanz, Fuencisla; Galindo, Mercedes; Rubio, Miguel A; Calle-Pascual, Alfonso L

    2013-08-01

    The aims are to define the regression rate in newly diagnosed type 2 diabetes after lifestyle intervention and pharmacological therapy based on a SMBG (self-monitoring of blood glucose) strategy in routine practice as compared to standard HbA1c-based treatment and to assess whether a supervised exercise program has additional effects. St Carlos study is a 3-year, prospective, randomized, clinic-based, interventional study with three parallel groups. Hundred and ninety-five patients were randomized to the SMBG intervention group [I group; n = 130; Ia: SMBG (n = 65) and Ib: SMBG + supervised exercise (n = 65)] and to the HbA1c control group (C group) (n = 65). The primary outcome was to estimate the regression rate of type 2 diabetes (HbA1c 4 kg was 3.6 (1.8-7); p < 0.001. This study shows that the use of SMBG in an educational program effectively increases the regression rate in newly diagnosed type 2 diabetic patients after 3 years of follow-up. These data suggest that SMBG-based programs should be extended to primary care settings where diabetic patients are usually attended.

  19. Concepts for a theoretical and experimental study of lifting rotor random loads and vibrations (further experiments with progressing/regressing rotor flapping modes), Phase 7-C

    Science.gov (United States)

    Hohenemser, K. H.; Crews, S. T.

    1973-01-01

    The experiments with progressing/regressing forced rotor flapping modes have been extended in several directions and the data processing method has been considerably refined. The 16 inch hingeless 2-bladed rotor model was equipped with a new set of high precision blades which removed previously encountered tracking difficulties at high advance ratio, so that tests up to .8 rotor advance ratio could be conducted. In addition to data with 1.20 blade natural flapping frequency data at 1.10 flapping frequency were obtained. Outside the wind tunnel, tests with a ground plate located at different distances below the rotor were conducted while recording the dynamic downflow at a station .2R below the rotor plane with a hot wire anemometer.

  20. Time-varying Markov regression random-effect model with Bayesian estimation procedures: Application to dynamics of functional recovery in patients with stroke.

    Science.gov (United States)

    Pan, Shin-Liang; Chen, Hsiu-Hsi

    2010-09-01

    The rates of functional recovery after stroke tend to decrease with time. Time-varying Markov processes (TVMP) may be more biologically plausible than time-invariant Markov process for modeling such data. However, analysis of such stochastic processes, particularly tackling reversible transitions and the incorporation of random effects into models, can be analytically intractable. We make use of ordinary differential equations to solve continuous-time TVMP with reversible transitions. The proportional hazard form was used to assess the effects of an individual's covariates on multi-state transitions with the incorporation of random effects that capture the residual variation after being explained by measured covariates under the concept of generalized linear model. We further built up Bayesian directed acyclic graphic model to obtain full joint posterior distribution. Markov chain Monte Carlo (MCMC) with Gibbs sampling was applied to estimate parameters based on posterior marginal distributions with multiple integrands. The proposed method was illustrated with empirical data from a study on the functional recovery after stroke. Copyright 2010 Elsevier Inc. All rights reserved.

  1. The special symplectic structure of binary cubics

    OpenAIRE

    Slupinski, Marcus J.; Stanton, Robert

    2009-01-01

    Let $k$ be a field of characteristic not $2$ or $3$. Let $V$ be the $k$-space of binary cubic polynomials. The natural symplectic structure on $k^2$ promotes to a symplectic structure $\\omega$ on $V$ and from the natural symplectic action of $\\textrm{Sl}(2,k)$ one obtains the symplectic module $(V,\\omega)$. We give a complete analysis of this symplectic module from the point of view of the associated moment map, its norm square $Q$ (essentially the classical discriminant) and the symplectic g...

  2. Magnetoelastic oscillations in ferromagnets with cubic symmetry

    Science.gov (United States)

    Baryakhtar, V. G.; Danilevich, A. G.

    2017-03-01

    This is a study of the influence of magnetoelastic interactions on the properties of ferromagnets with cubic symmetry. The dispersion relations for coupled magnetoelastic waves are calculated for all the ground states of a ferromagnet with cubic symmetry. It is shown that the magnetoelastic interaction coefficient depends on the directions of the magnetic moment of the ferromagnet and the external magnetic field, as well as on the direction of the wave vector of the collective oscillations. These results are used as the basis for quantitative calculations of the dispersion relations for an NiMnGa alloy with shape memory. The features of the magnetoelastic interaction owing to martensite phase transitions in which one of the elastic moduli becomes anomalously small are discussed. These calculations show that a reduction in the elastic moduli of the crystal causes a substantial increase in the magnetoelastic interaction. It is also shown that the existence of a magnetoelastic interaction leads to a decrease in the experimentally determined elastic moduli.

  3. Regression of lumbar disc herniation by physiotherapy. Does non-surgical spinal decompression therapy make a difference? Double-blind randomized controlled trial.

    Science.gov (United States)

    Demirel, Aynur; Yorubulut, Mehmet; Ergun, Nevin

    2017-09-22

    The aim of the study determining whether or not Non-invasive Spinal Decompression Therapy (NSDT) was effective in resorption of herniation, increasing disc height in patients with lumbar disc herniation (LHNP). A total of twenty patients diagnosed as LHNP and suffering from pain at least 8 weeks were enrolled to the study. Patients were allocated in study (SG) and control groups (CG) randomly. Both groups received combination of electrotherapy, deep friction massage and stabilization exercise for fifteen session. SG received additionally NSDT different from CG. Numeric Anolog Scale, Straight leg raise test, Oswestry Disability Index (ODI) were applied at baseline and after treatment. Disc height and herniation thickness were measured on Magnetic Resonance Imagination which performed at baseline and three months after therapy. Both treatments had positive effect for improving pain, functional restoration and reduction in thickness of herniation. Although reduction of herniation size was higher in SG than CG, no significant differences were found between groups and any superiority to each other (p> 0.05). This study showed that patients with LHNP received physiotherapy had improvement based on clinical and radiologic evidence. NSDT can be used as assistive agent for other physiotherapy methods in treatment of lumbar disc herniation.

  4. Genetic evaluation of partial growth trajectory of Santa Inês breed using random regression models Avaliação genética de parte da trajetória de crescimento em ovinos da raça Santa Inês utilizando modelos de regressão aleatória

    Directory of Open Access Journals (Sweden)

    Kassiana Adriano Pinto de Oliveira

    2010-05-01

    Full Text Available It was evaluated data set of 19,303 weight records of Santa Inês sheep in order to evaluate distinct polynomial functions with different order for better adjustements of fixed and random regressions of growth trajectory and to estimate (covariances components and genetic parameters of this trajectory. Fixed effects used in analysis were contemporary group, sex and birth type. Ordinary and Legendre polynomials, ranging from two to four orders, were evaluated for fixed regression of average growth trajectory. Legendre and quadratic b-spline functions, ranging from three to four orders, were evaluated for random regressions. Legendre polynomials of order fourth were suitable to fit random regression, while ordinary polynomials of third order were the best for fixed trajectory. Direct heritabilities on days 1, 50, 150, 250 and 411 were 0.24, 0.12, 0.44, 0.84, and 0.96, respectively, while maternal heritabilities for the same ages were 0.24, 0.19, 0.09, 0.02, and 0.01, respectively. Genetic correlations among weights in subsequent ages were high, tending to unity, and there were negative correlations between weights at early ages and weights at late ages. It is possible to modify the growth trajectory by selection with the observed genetic variability. Genetic control of weights at initial ages is not the same in late ages. So, selection of animals for slaughter in early age must be different from that of replacement animals.Foram utilizados 19.303 registros de peso de ovinos da raça Santa Inês com os objetivos de avaliar funções polinomiais com diferentes ordens para melhor ajuste das regressões fixas e aleatórias da trajetória de crescimento e estimar os componentes de covariância e os parâmetros genéticos desta trajetória. Os efeitos fixos utilizados nas análises foram grupo de contemporâneos, sexo e tipo de nascimento. Para ajuste da regressão fixa da trajetória média de crescimento, foram avaliados polinômios ordinários e de

  5. Differentiating regressed melanoma from regressed lichenoid keratosis.

    Science.gov (United States)

    Chan, Aegean H; Shulman, Kenneth J; Lee, Bonnie A

    2017-04-01

    Distinguishing regressed lichen planus-like keratosis (LPLK) from regressed melanoma can be difficult on histopathologic examination, potentially resulting in mismanagement of patients. We aimed to identify histopathologic features by which regressed melanoma can be differentiated from regressed LPLK. Twenty actively inflamed LPLK, 12 LPLK with regression and 15 melanomas with regression were compared and evaluated by hematoxylin and eosin staining as well as Melan-A, microphthalmia transcription factor (MiTF) and cytokeratin (AE1/AE3) immunostaining. (1) A total of 40% of regressed melanomas showed complete or near complete loss of melanocytes within the epidermis with Melan-A and MiTF immunostaining, while 8% of regressed LPLK exhibited this finding. (2) Necrotic keratinocytes were seen in the epidermis in 33% regressed melanomas as opposed to all of the regressed LPLK. (3) A dense infiltrate of melanophages in the papillary dermis was seen in 40% of regressed melanomas, a feature not seen in regressed LPLK. In summary, our findings suggest that a complete or near complete loss of melanocytes within the epidermis strongly favors a regressed melanoma over a regressed LPLK. In addition, necrotic epidermal keratinocytes and the presence of a dense band-like distribution of dermal melanophages can be helpful in differentiating these lesions. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  6. Better Autologistic Regression

    Directory of Open Access Journals (Sweden)

    Mark A. Wolters

    2017-11-01

    Full Text Available Autologistic regression is an important probability model for dichotomous random variables observed along with covariate information. It has been used in various fields for analyzing binary data possessing spatial or network structure. The model can be viewed as an extension of the autologistic model (also known as the Ising model, quadratic exponential binary distribution, or Boltzmann machine to include covariates. It can also be viewed as an extension of logistic regression to handle responses that are not independent. Not all authors use exactly the same form of the autologistic regression model. Variations of the model differ in two respects. First, the variable coding—the two numbers used to represent the two possible states of the variables—might differ. Common coding choices are (zero, one and (minus one, plus one. Second, the model might appear in either of two algebraic forms: a standard form, or a recently proposed centered form. Little attention has been paid to the effect of these differences, and the literature shows ambiguity about their importance. It is shown here that changes to either coding or centering in fact produce distinct, non-nested probability models. Theoretical results, numerical studies, and analysis of an ecological data set all show that the differences among the models can be large and practically significant. Understanding the nature of the differences and making appropriate modeling choices can lead to significantly improved autologistic regression analyses. The results strongly suggest that the standard model with plus/minus coding, which we call the symmetric autologistic model, is the most natural choice among the autologistic variants.

  7. Cathodoluminescence of cubic GaN epilayers

    Energy Technology Data Exchange (ETDEWEB)

    Wang, C.; As, D.J.; Schikora, D.; Schoettker, B.; Lischka, K. [Paderborn Univ. (Gesamthochschule) (Germany). Fachbereich 6 - Physik

    1998-08-01

    Cathodoluminescence (CL) of MBE grown cubic GaN epilayers has been studied as a function of the e-beam excitation intensity. The room temperature CL-spectrum is dominated by a near edge band with a FWHM as narrow as 55 meV at high excitation. It consists of an excitonic and a band-acceptor transition. A broad emission band peaked at 2.4 eV is observed at low excitation. Using a simple model based on bimolecular rate equations the concentration of defects involved in this transition is estimated to be about 10{sup 15} cm{sup -3}. CL-measurements with varying excitation intensity reveal that these recombination levels have only minor influence on the performance of high injection optoelectronic devices like laser diodes. Our CL-measurements show also that the deep centres are homogeneously distributed within the epilayer. (orig.) 11 refs.

  8. Triangulation of cubic panorama for view synthesis.

    Science.gov (United States)

    Zhang, Chunxiao; Zhao, Yan; Wu, Falin

    2011-08-01

    An unstructured triangulation approach, new to our knowledge, is proposed to apply triangular meshes for representing and rendering a scene on a cubic panorama (CP). It sophisticatedly converts a complicated three-dimensional triangulation into a simple three-step triangulation. First, a two-dimensional Delaunay triangulation is individually carried out on each face. Second, an improved polygonal triangulation is implemented in the intermediate regions of each of two faces. Third, a cobweblike triangulation is designed for the remaining intermediate regions after unfolding four faces to the top/bottom face. Since the last two steps well solve the boundary problem arising from cube edges, the triangulation with irregular-distribution feature points is implemented in a CP as a whole. The triangular meshes can be warped from multiple reference CPs onto an arbitrary viewpoint by face-to-face homography transformations. The experiments indicate that the proposed triangulation approach provides a good modeling for the scene with photorealistic rendered CPs.

  9. Cubic nonlinear Schroedinger equation with vorticity

    Energy Technology Data Exchange (ETDEWEB)

    Caliari, M; Morato, L M; Zuccher, S [Dipartimento di Informatica, Universita di Verona, Ca' Vignal 2, Strada Le Grazie 15, 37134 Verona (Italy); Loffredo, M I [Dipartimento di Scienze Matematiche ed Informatiche, Universita di Siena, Pian dei Mantellini 44, 53100 Siena (Italy)], E-mail: marco.caliari@univr.it, E-mail: loffredo@unisi.it, E-mail: laura.morato@univr.it, E-mail: zuccher@sci.univr.it

    2008-12-15

    In this paper, we introduce a new class of nonlinear Schroedinger equations (NLSEs), with an electromagnetic potential (A,{phi}), both depending on the wavefunction {psi}. The scalar potential {phi} depends on |{psi}|{sup 2}, whereas the vector potential A satisfies the equation of magnetohydrodynamics with coefficient depending on {psi}. In Madelung variables, the velocity field comes to be not irrotational in general and we prove that the vorticity induces dissipation, until the dynamical equilibrium is reached. The expression of the rate of dissipation is common to all NLSEs in the class. We show that they are a particular case of the one-particle dynamics out of dynamical equilibrium for a system of N identical interacting Bose particles, as recently described within stochastic quantization by Lagrangian variational principle. The cubic case is discussed in particular. Results of numerical experiments for rotational excitations of the ground state in a finite two-dimensional trap with harmonic potential are reported.

  10. Shape preserving rational cubic spline for positive and convex data

    Directory of Open Access Journals (Sweden)

    Malik Zawwar Hussain

    2011-11-01

    Full Text Available In this paper, the problem of shape preserving C2 rational cubic spline has been proposed. The shapes of the positive and convex data are under discussion of the proposed spline solutions. A C2 rational cubic function with two families of free parameters has been introduced to attain the C2 positive curves from positive data and C2 convex curves from convex data. Simple data dependent constraints are derived on free parameters in the description of rational cubic function to obtain the desired shape of the data. The rational cubic schemes have unique representations.

  11. Solving Buckmaster equation using cubic B-spline and cubic trigonometric B-spline collocation methods

    Science.gov (United States)

    Chanthrasuwan, Maveeka; Asri, Nur Asreenawaty Mohd; Hamid, Nur Nadiah Abd; Majid, Ahmad Abd.; Azmi, Amirah

    2017-08-01

    The cubic B-spline and cubic trigonometric B-spline functions are used to set up the collocation in finding solutions for the Buckmaster equation. These splines are applied as interpolating functions in the spatial dimension while the finite difference method (FDM) is used to discretize the time derivative. The Buckmaster equation is linearized using Taylor's expansion and solved using two schemes, namely Crank-Nicolson and fully implicit. The von Neumann stability analysis is carried out on the two schemes and they are shown to be conditionally stable. In order to demonstrate the capability of the schemes, some problems are solved and compared with analytical and FDM solutions. The proposed methods are found to generate more accurate results than the FDM.

  12. Estimação de parâmetros genéticos para produção de leite de vacas da raça Holandesa via regressão aleatória Estimation of genetic parameters for Holstein cows milk production by random regression

    Directory of Open Access Journals (Sweden)

    C.K.P. Dorneles

    2009-04-01

    Full Text Available Foram utilizados 21.702 registros de produção de leite no dia do controle de 2.429 vacas primíparas da raça Holandesa, filhas de 233 touros, coletados em 33 rebanhos do Estado do Rio Grande do Sul, para estimar parâmetros genéticos para produção de leite no dia do controle. O modelo de regressão aleatória ajustado aos controles leiteiros entre o sexto e o 305º dia de lactação incluiu o efeito de rebanho-ano-mês do controle, idade da vaca no parto e os parâmetros do polinômio de Legendre de ordem quatro, para modelar a curva média da produção de leite da população e parâmetros do mesmo polinômio, para modelar os efeitos aleatórios genético-aditivo e de ambiente permanente. As variâncias genéticas e de ambiente permanente para produção de leite no dia do controle variaram, respectivamente, de 2,38 a 3,14 e de 7,55 a 10,35. As estimativas de herdabilidade aumentaram gradativamente do início (0,14 para o final do período de lactação (0,20, indicando ser uma característica de moderada herdabilidade. As correlações genéticas entre as produções de leite de diferentes estágios leiteiros variaram de 0,33 a 0,99 e foram maiores entre os controles adjacentes. As correlações de ambiente permanente seguiram a mesma tendência das correlações genéticas. O modelo de regressão aleatória com polinômio de Legendre de ordem quatro pode ser considerado como uma boa ferramenta para estimação de parâmetros genéticos para a produção de leite ao longo da lactação.A total of 21,702 records of milk production from 2,429 first-lactation Holstein cows, sired by 233 bulls, collected in 33 herds in the State of Rio Grande do Sul from 1991 to 2003, were used to estimate genetic parameters for that characteristic. The random regression model adjusted to test day from the 6th and the 305th lactation day included the effect of herd-year-month of the test day, the age of the cow at parturition, and the order fourth Legendre

  13. Regression analysis by example

    National Research Council Canada - National Science Library

    Chatterjee, Samprit; Hadi, Ali S

    2012-01-01

    .... The emphasis continues to be on exploratory data analysis rather than statistical theory. The coverage offers in-depth treatment of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression...

  14. Topological Oxide Insulator in Cubic Perovskite Structure

    Science.gov (United States)

    Jin, Hosub; Rhim, Sonny H.; Im, Jino; Freeman, Arthur J.

    2013-01-01

    The emergence of topologically protected conducting states with the chiral spin texture is the most prominent feature at the surface of topological insulators. On the application side, large band gap and high resistivity to distinguish surface from bulk degrees of freedom should be guaranteed for the full usage of the surface states. Here, we suggest that the oxide cubic perovskite YBiO3, more than just an oxide, defines itself as a new three-dimensional topological insulator exhibiting both a large bulk band gap and a high resistivity. Based on first-principles calculations varying the spin-orbit coupling strength, the non-trivial band topology of YBiO3 is investigated, where the spin-orbit coupling of the Bi 6p orbital plays a crucial role. Taking the exquisite synthesis techniques in oxide electronics into account, YBiO3 can also be used to provide various interface configurations hosting exotic topological phenomena combined with other quantum phases. PMID:23575973

  15. The square of a planar cubic graph is 7-colorable

    DEFF Research Database (Denmark)

    Thomassen, Carsten

    2017-01-01

    We prove the conjecture made by G. Wegner in 1977 that the square of every planar, cubic graph is 7-colorable. Here, 7 cannot be replaced by 6.......We prove the conjecture made by G. Wegner in 1977 that the square of every planar, cubic graph is 7-colorable. Here, 7 cannot be replaced by 6....

  16. Ultrasonic harmonic generation from materials with up to cubic nonlinearity.

    Science.gov (United States)

    Kube, Christopher M; Arguelles, Andrea P

    2017-08-01

    This letter considers the combined effects of quadratic and cubic nonlinearity on plane wave propagation in generally anisotropic elastic solids. Displacement solutions are derived that represent the fundamental, second-, and third-harmonic waves. In arriving at the solutions, the quadratic and cubic nonlinearity parameters for generally anisotropic materials are defined. The effects of quadratic and cubic nonlinearity are shown to influence the amplitude and phase of the fundamental wave. In addition, the phase of the third-harmonic depends on a simple combination of the quadratic and cubic nonlinearity parameters. Nonlinearity parameters are given explicitly for materials having isotropic and cubic symmetry. Lastly, acoustic nonlinearity surfaces are introduced, which illustrate the nonlinearity parameters as a function of various propagation directions in anisotropic materials.

  17. Robustness of Multiple High Speed TCP CUBIC Connections Under Severe Operating Conditions

    DEFF Research Database (Denmark)

    Pilimon, Artur; Ruepp, Sarah Renée; Berger, Michael Stübert

    2015-01-01

    on and supported by packet-level simulations. The results show that the aggressive nature of CUBIC’s nonlinear congestion window control principle causes a degradation of the time-average throughput at the moderate level of random packet loss even under increasing Round-Trip-Time of the flow. However......We study the adaptation capabilities and robustness of the high-speed TCP CUBIC algorithm. For this purpose we consider a network environment with variable and high random packet loss and a large Bandwidth-Delay product, shared by multiple heterogeneous TCP connections. The analysis is based...

  18. Exact diagonalization of cubic lattice models in commensurate Abelian magnetic fluxes and translational invariant non-Abelian potentials

    DEFF Research Database (Denmark)

    Burrello, M.; Fulga, Ion Cosma; Lepori, L.

    2017-01-01

    We present a general analytical formalism to determine the energy spectrum of a quantum particle in a cubic lattice subject to translationally invariant commensurate magnetic fluxes and in the presence of a general spaceindependent non-Abelian gauge potential. We first review and analyze the case....... Finally, we numerically study the effect of random flux perturbations....

  19. Serial femtosecond crystallography of soluble proteins in lipidic cubic phase

    Energy Technology Data Exchange (ETDEWEB)

    Fromme, Raimund; Ishchenko, Andrii; Metz, Markus; Chowdhury, Shatabdi Roy; Basu, Shibom; Boutet, Sébastien; Fromme, Petra; White, Thomas A.; Barty, Anton; Spence, John C. H.; Weierstall, Uwe; Liu, Wei; Cherezov, Vadim

    2015-08-04

    Serial femtosecond crystallography (SFX) at X-ray free-electron lasers (XFELs) enables high-resolution protein structure determination using micrometre-sized crystals at room temperature with minimal effects from radiation damage. SFX requires a steady supply of microcrystals intersecting the XFEL beam at random orientations. An LCP–SFX method has recently been introduced in which microcrystals of membrane proteins are grown and delivered for SFX data collection inside a gel-like membrane-mimetic matrix, known as lipidic cubic phase (LCP), using a special LCP microextrusion injector. Here, it is demonstrated that LCP can also be used as a suitable carrier medium for microcrystals of soluble proteins, enabling a dramatic reduction in the amount of crystallized protein required for data collection compared with crystals delivered by liquid injectors. High-quality LCP–SFX data sets were collected for two soluble proteins, lysozyme and phycocyanin, using less than 0.1 mg of each protein.

  20. Persistência na lactação para vacas da raça Holandesa criadas no Estado do Rio Grande do Sul via modelos de regressão aleatória Lactation persistency for Holstein cows raised in the State of Rio Grande do Sul using a random regression model

    Directory of Open Access Journals (Sweden)

    Cristian Kelen Pinto Dorneles

    2009-08-01

    Full Text Available Foram utilizados 21.702 registros de produção de leite no dia do controle de 2.429 vacas primíparas da raça Holandesa, filhas de 233 touros, coletados em 33 rebanhos do Estado do Rio Grande do Sul, entre 1992 e 2003, para estimar parâmetros genéticos, para três medidas de persistência (PS1, PS2 e PS3 e para a produção de leite até 305 dias (P305 de lactação. Os modelos de regressão aleatória ajustados aos controles leiteiros entre o sexto e o 300o dia de lactação incluíram o efeito de rebanho-ano-mês do controle, a idade da vaca ao parto e os parâmetros do polinômio de Legendre de ordem quatro, para modelar a curva média da produção de leite da população e os parâmetros do mesmo polinômio, para modelar os efeitos aleatórios genético-aditivo direto e de ambiente permanente. As estimativas de herdabilidade obtidas foram 0,05, 0,08 e 0,19, respectivamente, para PS1, PS2 e PS3 e 0,25, para P305 sugerindo a possibilidade de ganho genético por meio da seleção para PS3 e para P305. As correlações genéticas entre as três medidas de persistência e P305, variaram de -0,05 a 0,07, indicando serem persistência e produção, características determinadas por grupos de genes diferentes. Assim, consequentemente, a seleção para P305, geralmente praticada, não promove progresso genético para a persistência.There were used 21,702 test day milk yields from 2,429 first parity Holstein breed cows, daughters of 2,031 dams and 233 sires, distributed over 33 herds in the state of Rio Grande do Sul, from 1992 to 2003. Genetic parameters for three measures of lactation persistency (PS1, PS2 e PS3 and for milk production to 305 days (P305 were evaluated. A random regression model adjusted by fourth order Legendre polynomial was used. The random regression model adjusted to test day between the sixth and the 305th lactation day included the herd-year-season of the test day, the age of the cow at the parturition effects and the

  1. Estimação de componentes de co-variância para pesos corporais do nascimento aos 365 dias de idade de bovinos Guzerá empregando-se modelos de regressão aleatória Estimates of covariance components for body weights from birth to 365 days of age in Guzera cattle, using random regression models

    Directory of Open Access Journals (Sweden)

    Luciele Cristina Pelicioni

    2009-01-01

    permanent environmental effects, using random regression models. The random effects included were modeled by regression on Legendre Polynomials with orders ranging from linear to quartic. The models were compared through the likelihood ratio test, Akaike's information criterion and the Schwarz's Bayesian information criterion. The model with 18 heterogeneous classes was the one that best fitted the residual variances, according to the statistical tests; however, the model with variance function of 5th order also showed to be appropriate. The direct heritability estimates were higher than those found in literature, ranging from 0.04 to 0.53, showing similar trends when compared to those estimated using univariate models. Selection on body weight in any age should improve the body weight in all ages in the studied interval.

  2. Genetic evaluation for large data sets by random regression models in Nellore cattle Avaliação genética para grandes massas de dados por meio de modelos de regressão aleatória em gado Nelore

    Directory of Open Access Journals (Sweden)

    P.R.C. Nobre

    2009-08-01

    Full Text Available Expected progeny differences (EPD of Nellore cattle estimated by random regression model (RRM and multiple trait model (MTM were compared. Genetic evaluation data included 3,819,895 records of up nine sequential weights of 963,227 animals measured at ages ranging from one day (birth weight to 733 days. Traits considered were weights at birth, ten to 110-day old, 102 to 202-day old, 193 to 293-day old, 283 to 383-day old, 376 to 476-day old, 551 to 651-day old, and 633 to 733-day old. Seven data samples were created. Because the parameters estimates biologically were better, two of them were chosen: one with 84,426 records and another with 72,040. Records preadjusted to a fixed age were analyzed by a MTM, which included the effects of contemporary group, age of dam class, additive direct, additive maternal, and maternal permanent environment. Analyses were carried out by REML, with five traits at a time. The RRM included the effects of age of animal, contemporary group, age of dam class, additive direct, permanent environment, additive maternal, and maternal permanent environment. Different degree of Legendre polynomials were used to describe random effects. MTM estimated covariance components and genetic parameters for weight at birth and sequential weights and RRM for all ages. Due to the fact that correlation among the estimates EPD from MTM and all the tested RM were not equal to 1.0, it is not possible to recommend RRM to genetic evaluation to large data sets.Compararam-se as diferenças esperadas nas progênies (DEPs de gado Nelore, estimadas por meio de um modelo de características múltiplas (MTM, com um modelo de regressão aleatória (RRM. Foram utilizados 3.819.895 dados de peso corporal sequenciais para a avaliação genética de 963.227 animais, coletados do nascer aos 733 dias de idade. As características consideradas foram: peso ao nascer e pesos dos 10 aos 110, dos 102 aos 202, dos 193 aos 293, dos 283 aos 383, dos 376 aos 476

  3. Avaliação da persistência na lactação da raça Guzerá, utilizando modelos de regressão aleatória Evaluation of lactation persistency of Guzerat cows using random regression models

    Directory of Open Access Journals (Sweden)

    L.S. Freitas

    2010-04-01

    Full Text Available Estimaram-se a herdabilidade e as correlações genéticas e de ambiente permanente entre seis medidas de persistência da lactação de vacas da raça Guzerá, utilizando modelo de regressão aleatória. Foram considerados 8276 registros de produção de leite no dia do controle, na primeira lactação, de 1021 vacas. A regressão aleatória foi calculada pela função logarítmica de Ali e Schaeffer e pelo polinômio de Legendre, obtendo-se os coeficientes para os efeitos fixos, genético aditivo e de ambiente permanente. A função que mais se adequou aos dados foi a de Ali e Schaeffer, mas apresentou problemas de convergência. Os resultados evidenciaram que a persistência é uma característica com herdabilidade de valor moderado e de baixa correlação com o valor genético para produção de leite aos 305 dias, indicando a possibilidade de se obter resposta à seleção para mudança na curva de lactação sem afetar negativamente a produção total de leite na lactação. A medida de persistência que calcula a diferença de produção de leite entre as fases intermediária e inicial da lactação apresentou alta correlação com a produção aos 305 dias.The heritability and the genetic and permanent environment correlations were estimated among six different measures of persistency in the lactation of Guzerat cow, using the Random Regression Model. A total of 8,403 records from 1,034 first lactation cows were evaluated. The Random Regression Model was calculated by the logarithmic function of Ali and Schaeffer and Legendre polynomials to get coefficients for fixed, additive genetic and permanent environment effects. Ali and Schaeffer was the function that better fit to the data, but it had convergence problems. The results showed that persistence is a trait with moderate heritability, and low correlation with genetic value for 305-d milk production which allows to select animals in order to alter the format of the curve of production

  4. Polyimide nanocomposites based on cubic zirconium tungstate

    Science.gov (United States)

    Ramasubramanian Sharma, Gayathri

    2009-12-01

    In this research, cubic zirconium tungstate (ZrW2O8) was used as a filler to reduce the CTE of polyimides (PI), and the effect of ZrW2O8 nanoparticles on the bulk polymer properties was studied. Polyimides are high performance polymers with exceptional thermal stability, and there is a need for PIs with low CTEs for high temperature applications. The nanofiller, cubic ZrW2O8, is well known for its isotropic negative thermal expansion (NTE) over a wide temperature range from -272.7 to 777°C. The preparation of nanocomposites involved the synthesis of ZrW 2O8 nanofiller, engineering the polymer-filler interface using linker groups and optimization of processing strategies to prepare free-standing PI nanocomposite films. A hydrothermal method was used to synthesize ZrW 2O8 nanoparticles. Polyimide-ZrW2O8 interface interaction was enhanced by covalently bonding linker moieties to the surface of ZrW2O8 nanoparticles. Specifically, ZrW 2O8 nanoparticles were functionalized with two different linker groups: (1) a short aliphatic silane, and (2) low molecular weight PI. The surface functionalization was confirmed using X-ray photoelectron spectroscopy and thermal gravimetric analysis (TGA). Reprecipitation blending was used to prepare the freestanding PI-ZrW2O8 nanocomposite films with up to 15 volume% filler loading. SEM images showed the improvements in polymer-filler wetting behavior achieved using interface engineering. SEM images indicated that there was better filler dispersion in the PI matrix using reprecipitation blending, compared to the filler dispersion achieved in the nanocomposites prepared using conventional blending technique. The structure-property relationships in PI-ZrW2O8 nanocomposites were investigated by studying the thermal degradation, glass transition, tensile and thermal expansion properties of the nanocomposites. The properties were studied as a function of filler loading and interface linker groups. Addition of ZrW2O8 nanoparticles did not

  5. Reduced Rank Regression

    DEFF Research Database (Denmark)

    Johansen, Søren

    2008-01-01

    The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating e...... eigenvalues and eigenvectors. We give a number of different applications to regression and time series analysis, and show how the reduced rank regression estimator can be derived as a Gaussian maximum likelihood estimator. We briefly mention asymptotic results......The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

  6. Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests.

    Science.gov (United States)

    Maroco, João; Silva, Dina; Rodrigues, Ana; Guerreiro, Manuela; Santana, Isabel; de Mendonça, Alexandre

    2011-08-17

    Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI), but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests) were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression) in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test. Press' Q test showed that all classifiers performed better than chance alone (p classification accuracy (Median (Me) = 0.76) an area under the ROC (Me = 0.90). However this method showed high specificity (Me = 1.0) but low sensitivity (Me = 0.3). Random Forest ranked second in overall accuracy (Me = 0.73) with high area under the ROC (Me = 0.73) specificity (Me = 0.73) and sensitivity (Me = 0.64). Linear Discriminant Analysis also showed acceptable overall accuracy (Me = 0.66), with acceptable area under the ROC (Me = 0.72) specificity (Me = 0.66) and sensitivity (Me = 0.64). The remaining classifiers showed overall classification accuracy above a median value of 0.63, but for most

  7. The compressibility of cubic white and orthorhombic, rhombohedral, and simple cubic black phosphorus

    Energy Technology Data Exchange (ETDEWEB)

    Clark, Simon M; Zaug, Joseph

    2010-03-10

    The effect of pressure on the crystal structure of white phosphorus has been studied up to 22.4 GPa. The ?alpha phase was found to transform into the alpha' phase at 0.87 +- 0.04 GPa with a volume change of 0.1 +- 0.3 cc/mol. A fit of a second order Birch- Murnaghan equation to the data gave Vo = 16.94 ? 0.08 cc/mol and Ko = 6.7 +- 0.5 GPa for the alpha phase and Vo = 16.4 +- 0.1 cc/mol and Ko = 9.1 +- 0.3 GPa for the alpha' phase. The alpha' phase was found to transform to the A17 phase of black phosphorus at 2.68 +- 0.34 GPa and then with increasing pressure to the A7 and then simple cubic phase of black phosphorus. A fit of a second order Birch-Murnaghan equation to our data combined with previous measurements gave Vo = 11.43 +- 0.05 cc/mol and Ko = 34.7 +- 0.5 GPa for the A17 phase, Vo = 9.62 +- 0.01 cc/mol and Ko = 65.0 +- 0.6 GPa for the A7 phase and , Vo = 9.23 +- 0.01 cc/mol and Ko = 72.5 +- 0.3 GPa for the simple cubic phase.

  8. Hardness and thermal stability of cubic silicon nitride

    DEFF Research Database (Denmark)

    Jiang, Jianzhong; Kragh, Flemming; Frost, D. J.

    2001-01-01

    The hardness and thermal stability of cubic spinel silicon nitride (c-Si3N4), synthesized under high-pressure and high-temperature conditions, have been studied by microindentation measurements, and x-ray powder diffraction and scanning electron microscopy, respectively The phase at ambient...... temperature has an average hardness of 35.31 GPa, slightly larger than SiO2 stishovite, which is often referred to as the third hardest material after diamond and cubic boron nitride. The cubic phase is stable up to 1673 K in air. At 1873 K, alpha -and beta -Si3N4 phases are observed, indicating a phase...

  9. On q-power cycles in cubic graphs

    DEFF Research Database (Denmark)

    Bensmail, Julien

    2017-01-01

    In the context of a conjecture of Erdos and Gyárfás, we consider, for any q ≥ 2, the existence of q-power cycles (i.e. with length a power of q) in cubic graphs. We exhibit constructions showing that, for every q ≥ 3, there exist arbitrarily large cubic graphs with no q-power cycles. Concerning...... the remaining case q = 2 (which corresponds to the conjecture of Erdos and Gyárfás), we show that there exist arbitrarily large cubic graphs whose only 2-power cycles have length 4 only, or 8 only....

  10. On q-Power Cycles in Cubic Graphs

    OpenAIRE

    Bensmail Julien

    2017-01-01

    International audience; In the context of a conjecture of Erdős and Gyárfás, we consider, for any $q ≥ 2$, the existence of q-power cycles (i.e. with length a power of q) in cubic graphs. We exhibit constructions showing that, for every $q ≥ 3$, there exist arbitrarily large cubic graphs with no q-power cycles. Concerning the remaining case $q = 2$ (which corresponds to the conjecture of Erdős and Gyárfás), we show that there exist arbitrarily large cubic graphs whose only 2-power cycles have...

  11. Virologic response to tipranavir-ritonavir or darunavir-ritonavir based regimens in antiretroviral therapy experienced HIV-1 patients: a meta-analysis and meta-regression of randomized controlled clinical trials.

    Directory of Open Access Journals (Sweden)

    Asres Berhan

    Full Text Available The development of tipranavir and darunavir, second generation non-peptidic HIV protease inhibitors, with marked improved resistance profiles, has opened a new perspective on the treatment of antiretroviral therapy (ART experienced HIV patients with poor viral load control. The aim of this study was to determine the virologic response in ART experienced patients to tipranavir-ritonavir and darunavir-ritonavir based regimens.A computer based literature search was conducted in the databases of HINARI (Health InterNetwork Access to Research Initiative, Medline and Cochrane library. Meta-analysis was performed by including randomized controlled studies that were conducted in ART experienced patients with plasma viral load above 1,000 copies HIV RNA/ml. The odds ratios and 95% confidence intervals (CI for viral loads of <50 copies and <400 copies HIV RNA/ml at the end of the intervention were determined by the random effects model. Meta-regression, sensitivity analysis and funnel plots were done. The number of HIV-1 patients who were on either a tipranavir-ritonavir or darunavir-ritonavir based regimen and achieved viral load less than 50 copies HIV RNA/ml was significantly higher (overall OR = 3.4; 95% CI, 2.61-4.52 than the number of HIV-1 patients who were on investigator selected boosted comparator HIV-1 protease inhibitors (CPIs-ritonavir. Similarly, the number of patients with viral load less than 400 copies HIV RNA/ml was significantly higher in either the tipranavir-ritonavir or darunavir-ritonavir based regimen treated group (overall OR = 3.0; 95% CI, 2.15-4.11. Meta-regression showed that the viral load reduction was independent of baseline viral load, baseline CD4 count and duration of tipranavir-ritonavir or darunavir-ritonavir based regimen.Tipranavir and darunavir based regimens were more effective in patients who were ART experienced and had poor viral load control. Further studies are required to determine their consistent

  12. Monotonicity preserving splines using rational cubic Timmer interpolation

    Science.gov (United States)

    Zakaria, Wan Zafira Ezza Wan; Alimin, Nur Safiyah; Ali, Jamaludin Md

    2017-08-01

    In scientific application and Computer Aided Design (CAD), users usually need to generate a spline passing through a given set of data, which preserves certain shape properties of the data such as positivity, monotonicity or convexity. The required curve has to be a smooth shape-preserving interpolant. In this paper a rational cubic spline in Timmer representation is developed to generate interpolant that preserves monotonicity with visually pleasing curve. To control the shape of the interpolant three parameters are introduced. The shape parameters in the description of the rational cubic interpolant are subjected to monotonicity constrained. The necessary and sufficient conditions of the rational cubic interpolant are derived and visually the proposed rational cubic Timmer interpolant gives very pleasing results.

  13. Bicontinuous cubic liquid crystalline nanoparticles for oral delivery of Doxorubicin

    DEFF Research Database (Denmark)

    Swarnakar, Nitin K; Thanki, Kaushik; Jain, Sanyog

    2014-01-01

    PURPOSE: The present study explores the potential of bicontinous cubic liquid crystalline nanoparticles (LCNPs) for improving therapeutic potential of doxorubicin. METHODS: Phytantriol based Dox-LCNPs were prepared using hydrotrope method, optimized for various formulation components, process var...

  14. The First Derivative of Ramanujans Cubic Continued Fraction

    OpenAIRE

    Bagis, Nikos

    2011-01-01

    We give the complete evaluation of the first derivative of the Ramanujans cubic continued fraction using Elliptic functions. The Elliptic functions are easy to handle and give the results in terms of Gamma functions and radicals from tables.

  15. Elastic properties of cubic crystals: Every's versus Blackman's diagram

    OpenAIRE

    Paszkiewicz, T.; Wolski, S.

    2007-01-01

    Blackman's diagram of two dimensionless ratios of elastic constants is frequently used to correlate elastic properties of cubic crystals with interatomic bondings. Every's diagram of a different set of two dimensionless variables was used by us for classification of various properties of such crystals. We compare these two ways of characterization of elastic properties of cubic materials and consider the description of various groups of materials, e.g. simple metals, oxides, and alkali halide...

  16. Generalized Born--Infeld Actions and Projective Cubic Curves

    CERN Document Server

    Ferrara, S; Sagnotti, A; Stora, R; Yeranyan, A

    2015-01-01

    We investigate $U(1)^{\\,n}$ supersymmetric Born-Infeld Lagrangians with a second non-linearly realized supersymmetry. The resulting non-linear structure is more complex than the square root present in the standard Born-Infeld action, and nonetheless the quadratic constraints determining these models can be solved exactly in all cases containing three vector multiplets. The corresponding models are classified by cubic holomorphic prepotentials. Their symmetry structures are associated to projective cubic varieties.

  17. On the Rank of Elliptic Curves in Elementary Cubic Extensions

    Directory of Open Access Journals (Sweden)

    Rintaro Kozuma

    2015-01-01

    Full Text Available We give a method for explicitly constructing an elementary cubic extension L over which an elliptic curve ED:y2+Dy=x3  (D∈Q∗ has Mordell-Weil rank of at least a given positive integer by finding a close connection between a 3-isogeny of ED and a generic polynomial for cyclic cubic extensions. In our method, the extension degree [L:Q] often becomes small.

  18. Regression analysis by example

    CERN Document Server

    Chatterjee, Samprit

    2012-01-01

    Praise for the Fourth Edition: ""This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable."" -Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded

  19. Particle Swarm Optimization and regression analysis I

    Science.gov (United States)

    Mohanty, Souyma D.

    2012-04-01

    Particle Swarm Optimization (PSO) is now widely used in many problems that require global optimization of high-dimensional and highly multi-modal functions. However, PSO has not yet seen widespread use in astronomical data analysis even though optimization problems in this field have become increasingly complex. In this two-part article, we first provide an overview of the PSO method in the concrete context of a ubiquitous problem in astronomy, namely, regression analysis. In particular, we consider the problem of optimizing the placement of knots in regression based on cubic splines (spline smoothing). The second part will describe an in-depth investigation of PSO in some realistic data analysis challenges.

  20. Flexible survival regression modelling

    DEFF Research Database (Denmark)

    Cortese, Giuliana; Scheike, Thomas H; Martinussen, Torben

    2009-01-01

    Regression analysis of survival data, and more generally event history data, is typically based on Cox's regression model. We here review some recent methodology, focusing on the limitations of Cox's regression model. The key limitation is that the model is not well suited to represent time-varyi...

  1. TOPICAL REVIEW: Nonlinear photonic crystals: III. Cubic nonlinearity

    Science.gov (United States)

    Babin, Anatoli; Figotin, Alexander

    2003-10-01

    Weakly nonlinear interactions between wavepackets in a lossless periodic dielectric medium are studied based on the classical Maxwell equations with a cubic nonlinearity. We consider nonlinear processes such that: (i) the amplitude of the wave component due to the nonlinearity does not exceed the amplitude of its linear component; (ii) the spatial range of a probing wavepacket is much smaller than the dimension of the medium sample, and it is not too small compared with the dimension of the primitive cell. These nonlinear processes are naturally described in terms of the cubic interaction phase function based on the dispersion relations of the underlying linear periodic medium. It turns out that only a few quadruplets of modes have significant nonlinear interactions. They are singled out by a system of selection rules including the group velocity, frequency and phase matching conditions. It turns out that the intrinsic symmetries of the cubic interaction phase stemming from assumed inversion symmetry of the dispersion relations play a significant role in the cubic nonlinear interactions. We also study canonical forms of the cubic interaction phase leading to a complete quantitative classification of all possible significant cubic interactions. The classification is ultimately based on a universal system of indices reflecting the intensity of nonlinear interactions.

  2. Análises da persistência na lactação de vacas da raça Holandesa, usando produção no dia do controle e modelo de regressão aleatória Analysis of persistency in the lactation of Holstein cows using test-day yield and random regression model

    Directory of Open Access Journals (Sweden)

    Jaime Araujo Cobuci

    2004-06-01

    Full Text Available Foram utilizados 87.045 registros de produção de leite, na primeira lactação, de 11.023 vacas da raça Holandesa, obtidos nos anos de 1997 a 2001, em diferentes rebanhos distribuídos em dez núcleos do Estado de Minas Gerais. Foram avaliados seis tipos de mensuração da persistência na lactação utilizando-se os valores genéticos da produção de leite, obtidos por meio do modelo de regressão aleatória - MRA. Utilizou-se a função de Wilmink na descrição dos efeitos aleatórios e fixos, pelo MRA. As estimativas de herdabilidade e de correlação genética, para as várias mensurações da persistência na lactação, variaram em decorrência da definição da persistência. As estimativas de herdabilidade para persistência na lactação variaram de 0,11 a 0,27 e as estimativas de correlação genética entre as mensurações da persistência na lactação e produção de leite até 305 dias, de -0,31 a 0,55, indicando que a persistência na lactação é uma característica de moderada herdabilidade e pouco correlacionada com a produção de leite até 305 dias. A seleção de animais para persistência na lactação, com o objetivo de alterar a forma da curva de lactação, pode ser eficiente.A total of 87,045 milk yield records of 11,023 first-parity Holstein cows was utilized, obtained from 1997 to 2001 from different herds of 10 Minas Gerais locations. Six types of persistency measures in lactation were evaluated using milk yield breeding values, obtained by means of Random Regression Model - RRM. The Wilmink function was used to describe the random and fixed effects by RRM. Heritability estimates and genetic correlations for various persistency measures in lactation were dependent on the definition of persistency. The heritability estimates for persistency in lactation ranged from 0.11 to 0.27 and the genetic variations among persistency measures in lactation and milk yield up to d 305 ranged from -0.31 to 0.55, showing that

  3. Parâmetros genéticos para a produção de leite de controles individuais de vacas da raça Gir estimados com modelos de repetibilidade e regressão aleatória Estimation of genetic parameters for test day milk records of first lactation Gyr cows using repeatability and random regression animal models

    Directory of Open Access Journals (Sweden)

    Claudio Napolis Costa

    2005-10-01

    número de estimativas negativas entre as PLC do início e fim da lactação do que a FAS. Exceto para a FAS, observou-se redução das estimativas de correlação genética próximas à unidade entre as PLC adjacentes para valores negativos entre as PLC no início e no fim da lactação. Entre os polinômios de Legendre, o de quinta ordem apresentou um melhor o ajuste das PLC. Os resultados indicam o potencial de uso de regressão aleatória, com os modelos LP5 e a FAS apresentando-se como os mais adequados para a modelagem das variâncias genética e de efeito permanente das PLC da raça Gir.Data comprising 8,183 test day records of 1,273 first lactations of Gyr cows from herds supervised by ABCZ were used to estimate variance components and genetic parameters for milk yield using repeatability and random regression animal models by REML. Genetic modelling of logarithmic (FAS, exponential (FW curves was compared to orthogonal Legendre polynomials (LP of order 3 to 5. Residual variance was assumed to be constant in all (ME=1 or some periods of lactation (ME=4. Lactation milk yield in 305-d was also adjusted by an animal model. Genetic variance, heritability and repeatability for test day milk yields estimated by a repeatability animal model were 1.74 kg2, 0.27, and 0.76, respectively. Genetic variance and heritability estimates for lactation milk yield were respectively 121,094.6 and 0.22. Heritability estimates from FAS and FW, respectively, decreased from 0,59 and 0.74 at the beginning of lactation to 0.20 at the end of the period. Except for a fifth-order LP with ME=1, heritability estimates decreased from around 0,70 at early lactation to 0,30 at the end of lactation. Residual variance estimates were slightly smaller for logarithimic than for exponential curves both for homogeneous and heterogeneous variance assumptions. Estimates of residual variance in all stages of lactation decreased as the order of LP increased and depended on the assumption about ME

  4. Short Duration vs Standard Duration of Dual-Antiplatelet Therapy After Percutaneous Coronary Intervention With Second-Generation Drug-Eluting Stents - A Systematic Review, Meta-Analysis, and Meta-Regression Analysis of Randomized Controlled Trials.

    Science.gov (United States)

    Wassef, Anthony W A; Khafaji, Hadi; Syed, Ishba; Yan, Andrew T; Udell, Jacob A; Goodman, Shaun G; Cheema, Asim N; Bagai, Akshay

    2016-12-01

    Current guidelines recommend 12 months of dual-antiplatelet therapy (DAPT) after percutaneous coronary intervention (PCI) with drug-eluting stent (DES) implantation. Whether the duration of DAPT can be safely shortened with use of second-generation DESs is unclear. We conducted a meta-analysis of randomized controlled trials comparing short duration (SD) (3-6 months) with standard longer duration (LD) (≥12 months) DAPT in patients treated with primarily second-generation DES implantation. Meta-regression was performed to explore the relationship between acute coronary syndrome (ACS) and the effect of DAPT duration. Six studies were included, with 12,752/13,928 (91.5%) patients receiving second-generation DESs. A total of 5367 patients (39%) had PCI in the setting of ACS. There was no difference in all-cause mortality (1.1% vs 1.2%; odds ratio [OR], 0.86; 95% confidence interval [CI], 0.63-1.18; P=.36) or cardiac mortality (0.9% vs 1.0%; OR, 0.92; 95% CI, 0.61-1.39; P=.69) with SD-DAPT vs LD-DAPT, respectively. Definite/probable stent thrombosis (0.5% vs 0.3%; OR, 1.33; 95% CI, 0.75-2.34; P=.51), myocardial infarction (1.5% vs 1.3%; OR, 1.17; 95% CI, 0.88-1.56; P=.29), and stroke (0.4% vs 0.4%; OR, 1.04; 95% CI, 0.60-1.81; P=.88) were similar between the groups. Compared with LD-DAPT, SD-DAPT was associated with lower clinically significant bleeding (0.9% vs 1.4%; OR, 0.64; 95% CI, 0.46-0.89; P=.01). Meta-regression analysis showed no significant association between the proportion of ACS patients in trials and duration of DAPT for the outcomes of mortality (P=.95), myocardial infarction (P=.98), or stent thrombosis (P=.89). In low-risk patients treated with contemporary second-generation DES implantation, SD-DAPT has similar rates of mortality, myocardial infarction, and stent thrombosis, with lower rates of bleeding compared with LD-DAPT.

  5. Glycemic Control During Continuous Subcutaneous Insulin Infusion Versus Multiple Daily Insulin Injections in Type 2 Diabetes: Individual Patient Data Meta-analysis and Meta-regression of Randomized Controlled Trials.

    Science.gov (United States)

    Pickup, John C; Reznik, Yves; Sutton, Alex J

    2017-05-01

    To compare glycemic control during continuous subcutaneous insulin infusion (CSII) and multiple daily insulin injections (MDI) in people with type 2 diabetes to identify patient characteristics that determine those best treated by CSII. Randomized controlled trials were selected comparing HbA1c during CSII versus MDI in people with type 2 diabetes. Data sources included Cochrane database and Ovid Medline. We explored patient-level determinants of final HbA1c level and insulin dose using Bayesian meta-regression models of individual patient data and summary effects using two-step meta-analysis. Hypoglycemia data were unavailable. Five trials were identified, with 287 patients randomized to receive MDI and 303 to receive CSII. Baseline HbA1c was the best determinant of final HbA1c: HbA1c difference (%) = 1.575 - (0.216 [95% credible interval 0.371-0.043] × baseline HbA1c) for all trials, but with largest effect in the trial with prerandomization optimization of control. Baseline insulin dose was best predictor of final insulin dose: insulin dose difference (units/kg) = 0.1245 - (0.382 [0.510-0.254] × baseline insulin dose). Overall HbA1c difference was -0.40% (-0.86 to 0.05 [-4.4 mmol/mol (-9.4 to 0.6)]). Overall insulin dose was reduced by -0.25 units/kg (-0.31 to -0.19) (26% reduction on CSII), and by -24.0 units/day (-30.6 to -17.5). Mean weight did not differ between treatments (0.08 kg [-0.33 to 0.48]). CSII achieves better glycemic control than MDI in people with poorly controlled type 2 diabetes, with ∼26% reduction in insulin requirements and no weight change. The best effect is in those worst controlled and with the highest insulin dose at baseline. © 2017 by the American Diabetes Association.

  6. Neurocognitive deficits in schizophrenia are associated with alterations in blood levels of neurosteroids: a multiple regression analysis of findings from a double-blind, randomized, placebo-controlled, crossover trial with DHEA.

    Science.gov (United States)

    Ritsner, Michael S; Strous, Rael D

    2010-01-01

    While neurosteroids exert multiple effects in the central nervous system, their associations with neurocognitive deficits in schizophrenia are not yet fully understood. The purpose of this study was to identify the contribution of circulating levels of dehydroepiandrosterone (DHEA), its sulfate (DHEAS), androstenedione, and cortisol to neurocognitive deficits through DHEA administration in schizophrenia. Data regarding cognitive function, symptom severity, daily doses, side effects of antipsychotic agents and blood levels of DHEA, DHEAS, androstenedione and cortisol were collected among 55 schizophrenia patients in a double-blind, randomized, placebo-controlled, crossover trial with DHEA at three intervals: upon study entry, after 6weeks of DHEA administration (200mg/d), and after 6weeks of a placebo period. Multiple regression analysis was applied for predicting sustained attention, memory, and executive function scores across three examinations controlling for clinical, treatment and background covariates. Findings indicated that circulating DHEAS and androstenedione levels are shown as positive predictors of cognitive functioning, while DHEA level as negative predictor. Overall, blood neurosteroid levels and their molar ratios accounted for 16.5% of the total variance in sustained attention, 8-13% in visual memory tasks, and about 12% in executive functions. In addition, effects of symptoms, illness duration, daily doses of antipsychotic agents, side effects, education, and age of onset accounted for variability in cognitive functioning in schizophrenia. The present study suggests that alterations in circulating levels of neurosteroids and their molar ratios may reflect pathophysiological processes, which, at least partially, underlie cognitive dysfunction in schizophrenia. Copyright 2009 Elsevier Ltd. All rights reserved.

  7. Visualisation of Regression Trees

    OpenAIRE

    Brunsdon, Chris

    2007-01-01

    he regression tree [1] has been used as a tool for exploring multivariate data sets for some time. As in multiple linear regression, the technique is applied to a data set consisting of a contin- uous response variable y and a set of predictor variables { x 1 ,x 2 ,...,x k } which may be continuous or categorical. However, instead of modelling y as a linear function of the predictors, regression trees model y as a series of ...

  8. Smoothed Cox regression

    OpenAIRE

    Dabrowska, Dorota M.

    1997-01-01

    Nonparametric regression was shown by Beran and McKeague and Utikal to provide a flexible method for analysis of censored failure times and more general counting processes models in the presence of covariates. We discuss application of kernel smoothing towards estimation in a generalized Cox regression model with baseline intensity dependent on a covariate. Under regularity conditions we show that estimates of the regression parameters are asymptotically normal at rate root-n, and we also dis...

  9. Introduction to regression graphics

    CERN Document Server

    Cook, R Dennis

    2009-01-01

    Covers the use of dynamic and interactive computer graphics in linear regression analysis, focusing on analytical graphics. Features new techniques like plot rotation. The authors have composed their own regression code, using Xlisp-Stat language called R-code, which is a nearly complete system for linear regression analysis and can be utilized as the main computer program in a linear regression course. The accompanying disks, for both Macintosh and Windows computers, contain the R-code and Xlisp-Stat. An Instructor's Manual presenting detailed solutions to all the problems in the book is ava

  10. Alternative Methods of Regression

    CERN Document Server

    Birkes, David

    2011-01-01

    Of related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald G. Watts ".an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models.highly recommend[ed].for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models." --Technometrics This book provides a balance between theory and practice supported by extensive displays of instructive geometrical constructs. Numerous in-depth case studies illustrate the use of nonlinear regression analysis--with all data s

  11. Local optimality of cubic lattices for interaction energies

    Science.gov (United States)

    Bétermin, Laurent

    2017-12-01

    We study the local optimality of simple cubic, body-centred-cubic and face-centred-cubic lattices among Bravais lattices of fixed density for some finite energy per point. Following the work of Ennola (Math Proc Camb 60:855-875, 1964), we prove that these lattices are critical points of all the energies, we write the second derivatives in a simple way and we investigate the local optimality of these lattices for the theta function and the Lennard-Jones-type energies. In particular, we prove the local minimality of the FCC lattice (resp. BCC lattice) for large enough (resp. small enough) values of its scaling parameter and we also prove the fact that the simple cubic lattice is a saddle point of the energy. Furthermore, we prove the local minimality of the FCC and the BCC lattices at high density (with an optimal explicit bound) and its local maximality at low density in the Lennard-Jones-type potential case. We then show the local minimality of FCC and BCC lattices among all the Bravais lattices (without a density constraint). The largest possible open interval of density's values where the simple cubic lattice is a local minimizer is also computed.

  12. Estimativas de parâmetros genéticos para produção de leite e persistência da lactação em vacas Gir, aplicando modelos de regressão aleatória Estimates of genetic parameters for milk yield and persistency of lactation of Gyr cows, applying random regression models

    Directory of Open Access Journals (Sweden)

    Luis Gabriel González Herrera

    2008-09-01

    of Gyr cows calving between 1990 and 2005 were used to estimate genetic parameters of monthly test-day milk yield (TDMY. Records were analyzed by random regression models (MRA that included the additive genetic and permanent environmental random effects and the contemporary group, age of cow at calving (linear and quadratic components and the average trend of the population as fixed effects. Random trajectories were fitted by Wilmink's (WIL and Ali & Schaeffer's (AS parametric functions. Residual variances were fitted by step functions with 1, 4, 6 or 10 classes. The contemporary group was defined by herd-year-season of test-day and included at least three animals. Models were compared by Akaike's and Schwarz's Bayesian (BIC information criterion. The AS function used for modeling the additive genetic and permanent environmental effects with heterogeneous residual variances adjusted with a step function with four classes was the best fitted model. Heritability estimates ranged from 0.21 to 0.33 for the AS function and from 0.17 to 0.30 for WIL function and were larger in the first half of the lactation period. Genetic correlations between TDMY were high and positive for adjacent test-days and decreased as days between records increased. Predicted breeding values for total 305-day milk yield (MRA305 and specific periods of lactation (obtained by the mean of all breeding values in the periods using the AS function were compared with that predicted by a standard model using accumulated 305-day milk yield (PTA305 by rank correlation. The magnitude of correlations suggested differences may be observed in ranking animals by using the different criteria which were compared in this study.

  13. Dias ao Parto de Fêmeas Nelore de um Experimento de Seleção para Crescimento: II - Modelo de Regressão Aleatória Days to Calving of Nelore Cows from a Selection Experiment for Growth: II - Random Regression Model

    Directory of Open Access Journals (Sweden)

    Maria Eugênia Zerlotti Mercadante

    2002-07-01

    Full Text Available Os parâmetros genéticos para dias ao parto foram estimados usando um modelo de regressão aleatória, com polinômios ortogonais da idade na monta (em anos como covariável. Os registros de dias ao parto (4.118 foram provenientes de 926 vacas de três rebanhos Nelore experimentais, sendo os rebanhos seleção e tradicional selecionados para maior peso ao sobreano, e o rebanho controle selecionado para a média do peso ao sobreano. As variâncias genética aditiva e permanente de ambiente foram descritas por uma função polinomial de ordem 4, com nove medidas de erro, resultando em variâncias fenotípica e genética aditiva altas nas idades mais avançadas, principalmente após a 6ª monta. As herdabilidades estimadas aumentaram de 0,08 a 0,28 da 1ª à 6ª monta. As correlações genéticas foram médias entre o primeiro desempenho e os demais (0,32 a 0,66, altas entre os desempenhos adjacentes (0,98 a 0,99, e um pouco menores entre os não adjacentes (0,63 a 0,98. A seleção para peso não alterou o valor genético médio das vacas dos rebanhos selecionados, entretanto, os valores genéticos médios das vacas do rebanho controle mostraram tendência de queda no decorrer dos anos.Genetic parameters for days to calving were estimated using a random regression model, with orthogonal polynomials of age at breeding season (in years as covariable. The records of days to calving (4,118 came from 929 cows from three experimental Nelore herds, been the selection and traditional herds selected for higher yearling weight and the control herd selected for the mean of yearling weight. Genetic and permanent environmental variances were described by a fourth order polynomial function, with 9 measures of error. The phenotypic and additive genetic variances were high in late records, especially after the 6th breeding season. Heritabilities estimates increased from 0.08 to 0.28, from first up to 6th breeding season. Genetic correlations were moderate

  14. Avaliação de medidas da persistência da lactação de cabras da raça Saanen sob modelo de regressão aleatória Evaluation of persistency lactation measures of Saanen goats under random regression model

    Directory of Open Access Journals (Sweden)

    Gilberto Romeiro de Oliveira Menezes

    2010-08-01

    Full Text Available Utilizaram-se 10.238 registros semanais de produção de leite no dia do controle, provenientes de 388 primeiras lactações de cabras da raça Saanen, na avaliação de seis medidas da persistência da lactação, a fim de verificar qual a mais adequada para o uso em avaliações genéticas para a característica. As seis medidas avaliadas são adaptações de medidas utilizadas em bovinos de leite, obtidas por substituir, nas fórmulas, os valores de referência de bovinos pelos de caprinos. Os valores usados nos cálculos foram obtidos de modelos de regressão aleatória. As estimativas de herdabilidade para as medidas de persistência variaram entre 0,03 e 0,09. As correlações genéticas entre medidas de persistência e produção de leite até 268 dias variaram entre -0,64 e 0,67. Por apresentar a menor correlação genética com produção aos 268 dias (0,14, a medida de persistência PS4, obtida pelo somatório dos valores do 41º ao 240º dia de lactação como desvios da produção aos 40 dias de lactação, é a mais indicada em avaliações genéticas para persistência da lactação em cabras da raça Saanen. Assim, a seleção de cabras de melhor persistência da lactação não altera a produção aos 268 dias. Em razão da baixa herdabilidade dessa medida (0,03, pequenas respostas à seleção são esperadas neste rebanho.It was used 10,238 weekly milk production records on the control day from the first 388 lactations of Saanen goats on the evalution of six lactation persistency measures in order to find out which was the best fitted for using in genetic evaluations on this trait. These six evaluated measures are adaptations from those used on dairy cattle, obtained by replacing, in the formula, bovine reference values by the goat ones. The values used in the calculations were obtained from random regression models. Heritability estimates for persistency measures ranged from 0.03 to 0.09. Genetic correlations between

  15. Off-pump versus on-pump coronary artery bypass surgery: meta-analysis and meta-regression of 13,524 patients from randomized trials Cirurgia de revascularização miocárdica com CEC versus sem CEC: meta-análise e meta-regressão de 13.524 pacientes de estudos randomizados

    Directory of Open Access Journals (Sweden)

    Michel Pompeu Barros de Oliveira Sá

    2012-12-01

    Full Text Available BACKGROUND: Most recent published meta-analysis of randomized controlled trials (RCTs showed that off-pump coronary artery bypass graft surgery (CABG reduces incidence of stroke by 30% compared with on-pump CABG, but showed no difference in other outcomes. New RCTs were published, indicating need of new meta-analysis to investigate pooled results adding these further studies. METHODS: MEDLINE, EMBASE, CENTRAL/CCTR, SciELO, LILACS, Google Scholar and reference lists of relevant articles were searched for RCTs that compared outcomes (30-day mortality for all-cause, myocardial infarction or stroke between off-pump versus on-pump CABG until May 2012. The principal summary measures were relative risk (RR with 95% Confidence Interval (CI and P values (considered statistically significant when INTRODUÇÃO: A meta-análise mais recente de estudos randomizados controlados (ERC mostrou que cirurgia de revascularização (CRM sem circulação extracorpórea (CEC reduz a incidência de acidente vascular cerebral em 30% em comparação com CRM com CEC, mas não mostrou diferença em outros resultados. Novos ERCs foram publicados, indicando necessidade de nova meta-análise para investigar resultados agrupados adicionando esses estudos. MÉTODOS: MEDLINE, EMBASE, CENTRAL / CCTR, SciELO, LILACS, Google Scholar e listas de referências de artigos relevantes foram pesquisados para ERCs que compararam os resultados de 30 dias (mortalidade por todas as causas, infarto do miocárdio ou acidente vascular cerebral - AVC entre CRM com CEC versus sem CEC até maio de 2012. As medidas sumárias principais foram o risco relativo (RR com intervalo de confiança de 95% (IC e os valores de P (considerado estatisticamente significativo quando <0,05. Os RR foram combinados entre os estudos usando modelo de efeito randômico de DerSimonian-Laird. Meta-análise e meta-regressão foram concluídas usando o software versão Meta-Análise Abrangente 2 (Biostat Inc., Englewood

  16. Morse–Smale Regression

    Energy Technology Data Exchange (ETDEWEB)

    Gerber, Samuel [Univ. of Utah, Salt Lake City, UT (United States); Rubel, Oliver [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bremer, Peer -Timo [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pascucci, Valerio [Univ. of Utah, Salt Lake City, UT (United States); Whitaker, Ross T. [Univ. of Utah, Salt Lake City, UT (United States)

    2012-01-19

    This paper introduces a novel partition-based regression approach that incorporates topological information. Partition-based regression typically introduces a quality-of-fit-driven decomposition of the domain. The emphasis in this work is on a topologically meaningful segmentation. Thus, the proposed regression approach is based on a segmentation induced by a discrete approximation of the Morse–Smale complex. This yields a segmentation with partitions corresponding to regions of the function with a single minimum and maximum that are often well approximated by a linear model. This approach yields regression models that are amenable to interpretation and have good predictive capacity. Typically, regression estimates are quantified by their geometrical accuracy. For the proposed regression, an important aspect is the quality of the segmentation itself. Thus, this article introduces a new criterion that measures the topological accuracy of the estimate. The topological accuracy provides a complementary measure to the classical geometrical error measures and is very sensitive to overfitting. The Morse–Smale regression is compared to state-of-the-art approaches in terms of geometry and topology and yields comparable or improved fits in many cases. Finally, a detailed study on climate-simulation data demonstrates the application of the Morse–Smale regression. Supplementary Materials are available online and contain an implementation of the proposed approach in the R package msr, an analysis and simulations on the stability of the Morse–Smale complex approximation, and additional tables for the climate-simulation study.

  17. Quantile Regression Methods

    DEFF Research Database (Denmark)

    Fitzenberger, Bernd; Wilke, Ralf Andreas

    2015-01-01

    Quantile regression is emerging as a popular statistical approach, which complements the estimation of conditional mean models. While the latter only focuses on one aspect of the conditional distribution of the dependent variable, the mean, quantile regression provides more detailed insights...

  18. Dimension Reduction and Discretization in Stochastic Problems by Regression Method

    DEFF Research Database (Denmark)

    Ditlevsen, Ove Dalager

    1996-01-01

    The chapter mainly deals with dimension reduction and field discretizations based directly on the concept of linear regression. Several examples of interesting applications in stochastic mechanics are also given.Keywords: Random fields discretization, Linear regression, Stochastic interpolation...

  19. Comparison of electron bands of hexagonal and cubic diamond

    Science.gov (United States)

    Salehpour, M. R.; Satpathy, S.

    1990-02-01

    Using the local-density-theory and the linear-muffin-tin-orbitals method, we calculate the electron band structures of hexagonal (lonsdaleite) and cubic diamond. Even though the arrangement of atoms is very similar between the two crystal structures, we find significant differences in the electron bands, especially in the conduction bands. In particular, including estimated corrections on top of the local-density results, we find the lowest theoretical gap of hexagonal diamond to be 4.5 eV, i.e., a remarkable 1.1-eV drop as compared to that of cubic diamond. The lowest gap in the hexagonal structure is still indirect as in the cubic structure, but the gap is now from Γ to K. The reduction of the band gap should be observable in optical-absorption or reflectivity experiments.

  20. Mechanisms of optical gain in cubic gallium nitrite

    Science.gov (United States)

    Holst, J.; Eckey, L.; Hoffmann, A.; Broser, I.; Schöttker, B.; As, D. J.; Schikora, D.; Lischka, K.

    1998-03-01

    We report on the mechanisms of optical gain in cubic GaN. Intensity-dependent gain spectra allow a distinction of the processes involved in providing optical amplification. For moderate excitation levels, the biexciton decay is responsible for a gain structure at 3.265 eV. With increasing excitation densities, gain is observed on the high energy side of the cubic band gap due to band filling processes. For the highest pump intensities, the electron-hole plasma is the dominant gain process. Gain values up to 210 cm-1 were obtained, indicating the high potential of cubic GaN for device applications. The observed gain mechanisms are similar to those of hexagonal GaN.

  1. Deformation of the cubic open string field theory

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Taejin, E-mail: taejin@kangwon.ac.kr

    2017-05-10

    We study a consistent deformation of the cubic open bosonic string theory in such a way that the non-planar world sheet diagrams of the perturbative string theory are mapped onto their equivalent planar diagrams of the light-cone string field theory with some length parameters fixed. An explicit evaluation of the cubic string vertex in the zero-slope limit yields the correct relationship between the string coupling constant and the Yang–Mills coupling constant. The deformed cubic open string field theory is shown to produce the non-Abelian Yang–Mills action in the zero-slope limit if it is defined on multiple D-branes. Applying the consistent deformation systematically to multi-string world sheet diagrams, we may be able to calculate scattering amplitudes with an arbitrary number of external open strings.

  2. Deformation of the cubic open string field theory

    Directory of Open Access Journals (Sweden)

    Taejin Lee

    2017-05-01

    Full Text Available We study a consistent deformation of the cubic open bosonic string theory in such a way that the non-planar world sheet diagrams of the perturbative string theory are mapped onto their equivalent planar diagrams of the light-cone string field theory with some length parameters fixed. An explicit evaluation of the cubic string vertex in the zero-slope limit yields the correct relationship between the string coupling constant and the Yang–Mills coupling constant. The deformed cubic open string field theory is shown to produce the non-Abelian Yang–Mills action in the zero-slope limit if it is defined on multiple D-branes. Applying the consistent deformation systematically to multi-string world sheet diagrams, we may be able to calculate scattering amplitudes with an arbitrary number of external open strings.

  3. Tetragonal and cubic zirconia multilayered ceramic constructs created by EPD.

    Science.gov (United States)

    Mochales, Carolina; Frank, Stefan; Zehbe, Rolf; Traykova, Tania; Fleckenstein, Christine; Maerten, Anke; Fleck, Claudia; Mueller, Wolf-Dieter

    2013-02-14

    The interest in electrophoretic deposition (EPD) for nanomaterials and ceramics production has widely increased due to the versatility of this technique to effectively combine different materials in unique shapes and structures. We successfully established an EPD layering process with submicrometer sized powders of Y-TZP with different mol percentages of yttrium oxide (3 and 8%) and produced multilayers of alternating tetragonal and cubic phases with a clearly defined interface. The rationale behind the design of these multilayer constructs was to optimize the properties of the final ceramic by combining the high mechanical toughness of the tetragonal phase of zirconia together with the high ionic conductivity of its cubic phase. In this work, a preliminary study of the mechanical properties of these constructs proved the good mechanical integrity of the multilayered constructs obtained as well as crack deflection in the interface between tetragonal and cubic zirconia layers.

  4. On Compatible Normal Odd Partitions in Cubic Graphs

    CERN Document Server

    Fouquet, Jean-Luc

    2012-01-01

    A normal odd partition T of the edges of a cubic graph is a partition into trails of odd length (no repeated edge) such that each vertex is the end vertex of exactly one trail of the partition and internal in some trail. For each vertex v, we can distinguish the edge for which this vertex is pending. Three normal odd partitions are compatible whenever these distinguished edges are distinct for each vertex. We examine this notion and show that a cubic 3 edge-colorable graph can always be provided with three compatible normal odd partitions. The Petersen graph has this property and we can construct other cubic graphs with chromatic index four with the same property. Finally, we propose a new conjecture which, if true, would imply the well known Fan and Raspaud Conjecture

  5. Regression to Causality

    DEFF Research Database (Denmark)

    Bordacconi, Mats Joe; Larsen, Martin Vinæs

    2014-01-01

    Humans are fundamentally primed for making causal attributions based on correlations. This implies that researchers must be careful to present their results in a manner that inhibits unwarranted causal attribution. In this paper, we present the results of an experiment that suggests regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...

  6. 3D confocal imaging in CUBIC-cleared mouse heart

    Energy Technology Data Exchange (ETDEWEB)

    Nehrhoff, I.; Bocancea, D.; Vaquero, J.; Vaquero, J.J.; Lorrio, M.T.; Ripoll, J.; Desco, M.; Gomez-Gaviro, M.V.

    2016-07-01

    Acquiring high resolution 3D images of the heart enables the ability to study heart diseases more in detail. Here, the CUBIC (clear, unobstructed brain imaging cocktails and computational analysis) clearing protocol was adapted for thick mouse heart sections to increase the penetration depth of the confocal microscope lasers into the tissue. The adapted CUBIC clearing of the heart lets the antibody penetrate deeper into the tissue by a factor of five. The here shown protocol enables deep 3D highresolution image acquisition in the heart. This allows a much more accurate assessment of the cellular and structural changes that underlie heart diseases. (Author)

  7. Trace spaces in a pre-cubical complex

    DEFF Research Database (Denmark)

    Raussen, Martin

    arc length which moreover is shown to be invariant under directed homotopies. D-paths up to reparametrization (called traces) can thus be represented by arc length parametrized d-paths. Under weak additional conditions,it is shown that trace spaces in a pre-cubical complex are separable metric spaces......In directed algebraic topology, (spaces of) directed irreversible (d)-paths are studied from a topological and from a categorical point of view. Motivated by models for concurrent computation, we study in this paper spaces of d-paths in a pre-cubical complex. Such paths are equipped with a natural...

  8. Applied linear regression

    CERN Document Server

    Weisberg, Sanford

    2013-01-01

    Praise for the Third Edition ""...this is an excellent book which could easily be used as a course text...""-International Statistical Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples. Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illus

  9. Applied logistic regression

    CERN Document Server

    Hosmer, David W; Sturdivant, Rodney X

    2013-01-01

     A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-

  10. Three contributions to robust regression diagnostics

    Directory of Open Access Journals (Sweden)

    Kalina J.

    2015-12-01

    Full Text Available Robust regression methods have been developed not only as a diagnostic tool for standard least squares estimation in statistical and econometric applications, but can be also used as self-standing regression estimation procedures. Therefore, they need to be equipped by their own diagnostic tools. This paper is devoted to robust regression and presents three contributions to its diagnostic tools or estimating regression parameters under non-standard conditions. Firstly, we derive the Durbin-Watson test of independence of random regression errors for the regression median. The approach is based on the approximation to the exact null distribution of the test statistic. Secondly, we accompany the least trimmed squares estimator by a subjective criterion for selecting a suitable value of the trimming constant. Thirdly, we propose a robust version of the instrumental variables estimator. The new methods are illustrated on examples with real data and their advantages and limitations are discussed.

  11. Trapping of cubic ZnO nanocrystallites at ambient conditions

    DEFF Research Database (Denmark)

    Decremps, F.; Pellicer-Porres, J.; Datchi, F.

    2002-01-01

    Dense powder of nanocrystalline ZnO has been recovered at ambient conditions in the metastable cubic structure after a heat treatment at high pressure (15 GPa and 550 K). Combined x-ray diffraction (XRD) and x-ray absorption spectroscopy (XAS) experiments have been performed to probe both long...

  12. Aspects on mediated glucose oxidation at a supported cubic phase.

    Science.gov (United States)

    Aghbolagh, Mahdi Shahmohammadi; Khani Meynaq, Mohammad Yaser; Shimizu, Kenichi; Lindholm-Sethson, Britta

    2017-12-01

    A supported liquid crystalline cubic phase housing glucose oxidase on an electrode surface has been suggested as bio-anode in a biofuel. The purpose of this investigation is to clarify some aspect on the mediated enzymatic oxidation of glucose in such a bio-anode where the mediator ferrocene-carboxylic acid and glucose were dissolved in the solution. The enzyme glucose oxidase was housed in the water channels of the mono-olein cubic phase. The system was investigated with cyclic voltammetry at different scan rates and the temperature was varied between 15°C and 30°C. The diffusion coefficient of the mediator and also the film resistance was estimated showing a large decrease in the mass-transport properties as the temperature was decreased. The current from mediated oxidation of glucose at the electrode surface increased with decreasing film thickness. The transport of the mediator in the cubic phase was the rate-limiting step in the overall reaction, where the oxidation of glucose took place at the outer surface of the cubic phase. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Computation of conjugate depths in cubic-shape open channels ...

    African Journals Online (AJOL)

    For rectangular channels, an explicit equation for obtaining the conjugate depth has been derived and is available in any standard hydraulics text. This paper is to develop a procedure for computing the conjugate depth in cubic-shaped open channels, given an initial depth. This procedure involves the use of a table or a ...

  14. Global Well-Posedness for Cubic NLS with Nonlinear Damping

    KAUST Repository

    Antonelli, Paolo

    2010-11-04

    We study the Cauchy problem for the cubic nonlinear Schrödinger equation, perturbed by (higher order) dissipative nonlinearities. We prove global in-time existence of solutions for general initial data in the energy space. In particular we treat the energy-critical case of a quintic dissipation in three space dimensions. © Taylor & Francis Group, LLC.

  15. Occurrence of stable periodic modes in a pendulum with cubic ...

    Indian Academy of Sciences (India)

    Abstract. Dynamical systems with nonlinear damping show interesting behavior in the periodic and chaotic phases. The Froude pendulum with cubical and linear damping is a paradigm for such a system. In this work the driven Froude pendulum is studied by the harmonic balancing method; the resulting nonlinear response ...

  16. Occurrence of stable periodic modes in a pendulum with cubic ...

    Indian Academy of Sciences (India)

    Dynamical systems with nonlinear damping show interesting behavior in the periodic and chaotic phases. The Froude pendulum with cubical and linear damping is a paradigm for such a system. In this work the driven Froude pendulum is studied by the harmonic balancing method; the resulting nonlinear response curves ...

  17. A Unified Approach to Teaching Quadratic and Cubic Equations.

    Science.gov (United States)

    Ward, A. J. B.

    2003-01-01

    Presents a simple method for teaching the algebraic solution of cubic equations via completion of the cube. Shows that this method is readily accepted by students already familiar with completion of the square as a method for quadratic equations. (Author/KHR)

  18. computation of conjugate depths in cubic-shaped open channels

    African Journals Online (AJOL)

    channels, an explicit equation for obtaining the conjugate depth has been derived and is available in any standard hydraulics text. This paper is to develop a procedure for computing the conjugate depth in cubic-shaped open channels, given an initial depth. This procedure involves the use of a table or a chart and avoids ...

  19. A look through ‘lens’ cubic mitochondria

    Science.gov (United States)

    Almsherqi, Zakaria; Margadant, Felix; Deng, Yuru

    2012-01-01

    Cell membranes may fold up into three-dimensional nanoperiodic cubic structures in biological systems. Similar geometries are well studied in other disciplines such as mathematics, physics and polymer chemistry. The fundamental function of cubic membranes in biological systems has not been uncovered yet; however, their appearance in specialized cell types indicates a role as structural templates or perhaps direct physical entities with specialized biophysical properties. The mitochondria located at the inner segment of the retinal cones of tree shrew (Tupaia glis and Tupaia belangeri) contain unique patterns of concentric cristae with a highly ordered membrane arrangement in three dimensions similar to the photonic nanostructures observed in butterfly wing scales. Using a direct template matching method, we show that the inner mitochondrial membrane folds into multi-layered (8 to 12 layers) gyroid cubic membrane arrangements in the photoreceptor cells. Three-dimensional simulation data demonstrate that such multi-layer gyroid membrane arrangements in the retinal cones of a tree shrew's eye can potentially function as: (i) multi-focal lens; (ii) angle-independent interference filters to block UV light; and (iii) a waveguide photonic crystal. These theoretical results highlight for the first time the significance of multi-layer cubic membrane arrangements to achieve near-quasi-photonic crystal properties through the simple and reversible biological process of continuous membrane folding. PMID:24098837

  20. A simple method for indexing powder diffraction patterns of cubic ...

    African Journals Online (AJOL)

    A simple method for indexing powder diffraction patterns of cubic materials:(1) using the θ-values of reference. ... Tanzania Journal of Science ... Alternatively, you can download the PDF file directly to your computer, from where it can be ...

  1. Influence of strontium on the cubic to ordered hexagonal phase ...

    Indian Academy of Sciences (India)

    ... Lecture Workshops · Refresher Courses · Symposia. Home; Journals; Bulletin of Materials Science; Volume 23; Issue 6. Influence of strontium on the cubic to ordered hexagonal phase transformation in barium magnesium niobate. M Thirumal A K Ganguli. Phase Transitions Volume 23 Issue 6 December 2000 pp 495-498 ...

  2. Interaction of dispersed cubic phases with blood components

    DEFF Research Database (Denmark)

    Bode, J C; Kuntsche, Judith; Funari, S S

    2013-01-01

    The interaction of aqueous nanoparticle dispersions, e.g. based on monoolein/poloxamer 407, with blood components is an important topic concerning especially the parenteral way of administration. Therefore, the influence of human and porcine plasma on dispersed cubic phases was investigated. Part...

  3. Tangent Lines without Derivatives for Quadratic and Cubic Equations

    Science.gov (United States)

    Carroll, William J.

    2009-01-01

    In the quadratic equation, y = ax[superscript 2] + bx + c, the equation y = bx + c is identified as the equation of the line tangent to the parabola at its y-intercept. This is extended to give a convenient method of graphing tangent lines at any point on the graph of a quadratic or a cubic equation. (Contains 5 figures.)

  4. A cubic interpolation algorithm for solving non-linear equations ...

    African Journals Online (AJOL)

    A new Algorithm - based on cubic interpolation have been developed for solving non-linear algebraic equations. The Algorithm is derived from LaGrange's interpolation polynomial. The method discussed here is faster than the \\"Regular Falsi\\" which is based on linear interpolation. Since this new method does not involve ...

  5. Specific heat of the simple-cubic Ising model

    NARCIS (Netherlands)

    Feng, X.; Blöte, H.W.J.

    2010-01-01

    We provide an expression quantitatively describing the specific heat of the Ising model on the simple-cubic lattice in the critical region. This expression is based on finite-size scaling of numerical results obtained by means of a Monte Carlo method. It agrees satisfactorily with series expansions

  6. C2-rational cubic spline involving tension parameters

    Indian Academy of Sciences (India)

    http://www.ias.ac.in/article/fulltext/pmsc/110/03/0305-0314. Keywords. Interpolation; rational; spline; tension parameter; monotonicity; convexity; continuity. Abstract. In the present paper, 1-piecewise rational cubic spline function involving tension parameters is considered which produces a monotonic interpolant to a given ...

  7. The traveling salesman problem on cubic and subcubic graphs

    NARCIS (Netherlands)

    S. Boyd; R.A. Sitters (René); S.L. van der Ster; L. Stougie (Leen)

    2014-01-01

    htmlabstractWe study the traveling salesman problem (TSP) on the metric completion of cubic and subcubic graphs, which is known to be NP-hard. The problem is of interest because of its relation to the famous 4/3-conjecture for metric TSP, which says that the integrality gap, i.e., the worst case

  8. Semiparametric Regression Pursuit.

    Science.gov (United States)

    Huang, Jian; Wei, Fengrong; Ma, Shuangge

    2012-10-01

    The semiparametric partially linear model allows flexible modeling of covariate effects on the response variable in regression. It combines the flexibility of nonparametric regression and parsimony of linear regression. The most important assumption in the existing methods for the estimation in this model is to assume a priori that it is known which covariates have a linear effect and which do not. However, in applied work, this is rarely known in advance. We consider the problem of estimation in the partially linear models without assuming a priori which covariates have linear effects. We propose a semiparametric regression pursuit method for identifying the covariates with a linear effect. Our proposed method is a penalized regression approach using a group minimax concave penalty. Under suitable conditions we show that the proposed approach is model-pursuit consistent, meaning that it can correctly determine which covariates have a linear effect and which do not with high probability. The performance of the proposed method is evaluated using simulation studies, which support our theoretical results. A real data example is used to illustrated the application of the proposed method.

  9. Almost opposite regression dependence in bivariate distributions

    OpenAIRE

    Siburg, Karl Friedrich; Stoimenov, Pavel A.

    2014-01-01

    Let X,Y be two continuous random variables. Investigating the regression dependence of Y on X, respectively, of X on Y, we show that the two of them can have almost opposite behavior. Indeed, given any e > 0, we construct a bivariate random vector (X,Y) such that the respective regression dependence measures r2|1(X,Y), r1|2(X,Y) ∈ [0,1] introduced in Dette et al. (2013) satisfy r2|1(X,Y) = 1 as well as r1|2(X,Y)

  10. [Understanding logistic regression].

    Science.gov (United States)

    El Sanharawi, M; Naudet, F

    2013-10-01

    Logistic regression is one of the most common multivariate analysis models utilized in epidemiology. It allows the measurement of the association between the occurrence of an event (qualitative dependent variable) and factors susceptible to influence it (explicative variables). The choice of explicative variables that should be included in the logistic regression model is based on prior knowledge of the disease physiopathology and the statistical association between the variable and the event, as measured by the odds ratio. The main steps for the procedure, the conditions of application, and the essential tools for its interpretation are discussed concisely. We also discuss the importance of the choice of variables that must be included and retained in the regression model in order to avoid the omission of important confounding factors. Finally, by way of illustration, we provide an example from the literature, which should help the reader test his or her knowledge. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

  11. Descriptors for predicting the lattice constant of body centered cubic crystal

    Science.gov (United States)

    Takahashi, Keisuke; Takahashi, Lauren; Baran, Jakub D.; Tanaka, Yuzuru

    2017-05-01

    The prediction of the lattice constant of binary body centered cubic crystals is performed in terms of first principle calculations and machine learning. In particular, 1541 binary body centered cubic crystals are calculated using density functional theory. Results from first principle calculations, corresponding information from periodic table, and mathematically tailored data are stored as a dataset. Data mining reveals seven descriptors which are key to determining the lattice constant where the contribution of descriptors is also discussed and visualized. Support vector regression (SVR) technique is implemented to train the data where the predicted lattice constants have the mean score of 83.6% accuracy via cross-validation and maximum error of 4% when compared to experimentally determined lattice constants. In addition, trained SVR is successful in predicting material combinations from a desired lattice constant. Thus, a set of descriptors for determining the lattice constant is identified and can be used as a base descriptor for lattice constants of further complex crystals. This would allow for the acceleration of the search for lattice constants of desired atomic compositions as well as the prediction of new materials based on a specified lattice constant.

  12. Simultaneous Inference in Regression

    CERN Document Server

    Liu, Wei

    2010-01-01

    The use of simultaneous confidence bands in linear regression is a vibrant area of research. This book presents an overview of the methodology and applications, including necessary background material on linear models. A special chapter on logistic regression gives readers a glimpse into how these methods can be used for generalized linear models. The appendices provide computational tools for simulating confidence bands. The author also includes MATLAB[registered] programs for all examples on the web. With many numerical examples and software implementation, this text serves the needs of rese

  13. Regression Estimator Using Double Ranked Set Sampling

    Directory of Open Access Journals (Sweden)

    Hani M. Samawi

    2002-06-01

    Full Text Available The performance of a regression estimator based on the double ranked set sample (DRSS scheme, introduced by Al-Saleh and Al-Kadiri (2000, is investigated when the mean of the auxiliary variable X is unknown. Our primary analysis and simulation indicates that using the DRSS regression estimator for estimating the population mean substantially increases relative efficiency compared to using regression estimator based on simple random sampling (SRS or ranked set sampling (RSS (Yu and Lam, 1997 regression estimator.  Moreover, the regression estimator using DRSS is also more efficient than the naïve estimators of the population mean using SRS, RSS (when the correlation coefficient is at least 0.4 and DRSS for high correlation coefficient (at least 0.91. The theory is illustrated using a real data set of trees.

  14. Nonlinear Regression with R

    CERN Document Server

    Ritz, Christian; Parmigiani, Giovanni

    2009-01-01

    R is a rapidly evolving lingua franca of graphical display and statistical analysis of experiments from the applied sciences. This book provides a coherent treatment of nonlinear regression with R by means of examples from a diversity of applied sciences such as biology, chemistry, engineering, medicine and toxicology.

  15. Modern Regression Discontinuity Analysis

    Science.gov (United States)

    Bloom, Howard S.

    2012-01-01

    This article provides a detailed discussion of the theory and practice of modern regression discontinuity (RD) analysis for estimating the effects of interventions or treatments. Part 1 briefly chronicles the history of RD analysis and summarizes its past applications. Part 2 explains how in theory an RD analysis can identify an average effect of…

  16. Multiple linear regression analysis

    Science.gov (United States)

    Edwards, T. R.

    1980-01-01

    Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.

  17. Linear Regression Analysis

    CERN Document Server

    Seber, George A F

    2012-01-01

    Concise, mathematically clear, and comprehensive treatment of the subject.* Expanded coverage of diagnostics and methods of model fitting.* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models.* More than 200 problems throughout the book plus outline solutions for the exercises.* This revision has been extensively class-tested.

  18. Bayesian ARTMAP for regression.

    Science.gov (United States)

    Sasu, L M; Andonie, R

    2013-10-01

    Bayesian ARTMAP (BA) is a recently introduced neural architecture which uses a combination of Fuzzy ARTMAP competitive learning and Bayesian learning. Training is generally performed online, in a single-epoch. During training, BA creates input data clusters as Gaussian categories, and also infers the conditional probabilities between input patterns and categories, and between categories and classes. During prediction, BA uses Bayesian posterior probability estimation. So far, BA was used only for classification. The goal of this paper is to analyze the efficiency of BA for regression problems. Our contributions are: (i) we generalize the BA algorithm using the clustering functionality of both ART modules, and name it BA for Regression (BAR); (ii) we prove that BAR is a universal approximator with the best approximation property. In other words, BAR approximates arbitrarily well any continuous function (universal approximation) and, for every given continuous function, there is one in the set of BAR approximators situated at minimum distance (best approximation); (iii) we experimentally compare the online trained BAR with several neural models, on the following standard regression benchmarks: CPU Computer Hardware, Boston Housing, Wisconsin Breast Cancer, and Communities and Crime. Our results show that BAR is an appropriate tool for regression tasks, both for theoretical and practical reasons. Copyright © 2013 Elsevier Ltd. All rights reserved.

  19. Bounded Gaussian process regression

    DEFF Research Database (Denmark)

    Jensen, Bjørn Sand; Nielsen, Jens Brehm; Larsen, Jan

    2013-01-01

    We extend the Gaussian process (GP) framework for bounded regression by introducing two bounded likelihood functions that model the noise on the dependent variable explicitly. This is fundamentally different from the implicit noise assumption in the previously suggested warped GP framework. We...

  20. Mechanisms of neuroblastoma regression

    Science.gov (United States)

    Brodeur, Garrett M.; Bagatell, Rochelle

    2014-01-01

    Recent genomic and biological studies of neuroblastoma have shed light on the dramatic heterogeneity in the clinical behaviour of this disease, which spans from spontaneous regression or differentiation in some patients, to relentless disease progression in others, despite intensive multimodality therapy. This evidence also suggests several possible mechanisms to explain the phenomena of spontaneous regression in neuroblastomas, including neurotrophin deprivation, humoral or cellular immunity, loss of telomerase activity and alterations in epigenetic regulation. A better understanding of the mechanisms of spontaneous regression might help to identify optimal therapeutic approaches for patients with these tumours. Currently, the most druggable mechanism is the delayed activation of developmentally programmed cell death regulated by the tropomyosin receptor kinase A pathway. Indeed, targeted therapy aimed at inhibiting neurotrophin receptors might be used in lieu of conventional chemotherapy or radiation in infants with biologically favourable tumours that require treatment. Alternative approaches consist of breaking immune tolerance to tumour antigens or activating neurotrophin receptor pathways to induce neuronal differentiation. These approaches are likely to be most effective against biologically favourable tumours, but they might also provide insights into treatment of biologically unfavourable tumours. We describe the different mechanisms of spontaneous neuroblastoma regression and the consequent therapeutic approaches. PMID:25331179

  1. Affine equivalence of cubic homogeneous rotation symmetric Boolean functions

    CERN Document Server

    Cusick, Thomas W

    2010-01-01

    Homogeneous rotation symmetric Boolean functions have been extensively studied in recent years because of their applications in cryptography. Little is known about the basic question of when two such functions are affine equivalent. The simplest case of quadratic rotation symmetric functions which are generated by cyclic permutations of the variables in a single monomial was only settled in 2009. This paper studies the much more complicated cubic case for such functions. A new concept of \\emph{patterns} is introduced, by means of which the structure of the smallest group G_n, whose action on the set of all such cubic functions in $n$ variables gives the affine equivalence classes for these functions under permutation of the variables, is determined. We conjecture that the equivalence classes are the same if all nonsingular affine transformations, not just permutations, are allowed. This conjecture is verified if n < 22. Our method gives much more information about the equivalence classes; for example, in t...

  2. The Piecewise Cubic Method (PCM) for computational fluid dynamics

    Science.gov (United States)

    Lee, Dongwook; Faller, Hugues; Reyes, Adam

    2017-07-01

    We present a new high-order finite volume reconstruction method for hyperbolic conservation laws. The method is based on a piecewise cubic polynomial which provides its solutions a fifth-order accuracy in space. The spatially reconstructed solutions are evolved in time with a fourth-order accuracy by tracing the characteristics of the cubic polynomials. As a result, our temporal update scheme provides a significantly simpler and computationally more efficient approach in achieving fourth order accuracy in time, relative to the comparable fourth-order Runge-Kutta method. We demonstrate that the solutions of PCM converges at fifth-order in solving 1D smooth flows described by hyperbolic conservation laws. We test the new scheme on a range of numerical experiments, including both gas dynamics and magnetohydrodynamics applications in multiple spatial dimensions.

  3. Negative thermal expansion materials related to cubic zirconium tungstate

    Science.gov (United States)

    Lind, Cora

    2001-12-01

    A non-hydrolytic sol-gel method for the preparation of ZrW2O 8 was developed. A new trigonal polymorph was discovered, which is structurally related to trigonal ZrMO2O8 and MnRe2O 8 as evidenced by powder x-ray diffraction and EXAFS studies. Seeding of the starting mixtures with cubic ZrW2O8 promoted crystallization of the cubic phase instead of trigonal material. Dehydration of ZrW2O7(OH)2·2H 2O gave cubic ZrW2O8 at 650°C, and a modification of this route led to the discovery of the new NTE materials cubic ZrMo 2O8 and HfMo2O8. These compounds crystallize in the same temperature range as the more stable trigonal AMo2O 8 polymorphs. To facilitate preparation of phase pure cubic molybdates, the influence of precursor chemistry on the crystallization behavior was investigated. The synthesis was extended to the solid solution system ZrxHf 1-xMoyW2-yO8 (0 ≤ x ≤ 1, 0 ≤ y ≤ 2). All compounds showed negative thermal expansion between 77 and 573 K. High-pressure in situ diffraction experiments were conducted on several AM2O8 polymorphs. With the exception of monoclinic ZrMo2O8, all materials underwent at least one pressure induced phase transition. Quasi-hydrostatic experiments on cubic AMo 2O8 led to a reversible transition to a new high-pressure structure, while low-pressure amorphization was observed under non-hydrostatic conditions. Isothermal kinetic studies of the cubic to trigonal transformation for ZrMo2O8 were carried out on four samples. Apparent activation energies of 170--290 kJ/mol were obtained using an Avrami model in combination with an Arrhenius analysis. This corresponds to 5% conversion levels after one year at temperatures between 220 and 315°C. Ex situ studies showed that the conversion at lower temperatures was considerably slower than what would be expected from extrapolation of the kinetic data. Drop solution calorimetry was carried out on several polymorphs of ZrMo 2O8, HfMo2O8 and ZrW2O 8. Only monoclinic ZrMo2O8 was enthalpically

  4. Plasma simulation with the Differential Algebraic Cubic Interpolated Propagation scheme

    Energy Technology Data Exchange (ETDEWEB)

    Utsumi, Takayuki [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

    1998-03-01

    A computer code based on the Differential Algebraic Cubic Interpolated Propagation scheme has been developed for the numerical solution of the Boltzmann equation for a one-dimensional plasma with immobile ions. The scheme advects the distribution function and its first derivatives in the phase space for one time step by using a numerical integration method for ordinary differential equations, and reconstructs the profile in phase space by using a cubic polynomial within a grid cell. The method gives stable and accurate results, and is efficient. It is successfully applied to a number of equations; the Vlasov equation, the Boltzmann equation with the Fokker-Planck or the Bhatnagar-Gross-Krook (BGK) collision term and the relativistic Vlasov equation. The method can be generalized in a straightforward way to treat cases such as problems with nonperiodic boundary conditions and higher dimensional problems. (author)

  5. Structural and magnetic transitions in cubic Mn3Ga.

    Science.gov (United States)

    Kharel, P; Huh, Y; Al-Aqtash, N; Shah, V R; Sabirianov, R F; Skomski, R; Sellmyer, D J

    2014-03-26

    The structural, magnetic and electron-transport properties of cubic Mn3Ga have been investigated. The alloys prepared by arc melting and melt-spinning show an antiferromagnetic spin order at room temperature but undergo coupled structural and magnetic phase transitions at 600 and 800 K. First-principles calculations show that the observed magnetic properties are consistent with that of a cubic Mn3Ga crystallizing in the disordered Cu3Au-type structure. The samples exhibit metallic electron transport with a resistance minimum near 30 K, followed by a logarithmic upturn below the minimum. The observed anomaly in the low-temperature resistivity has been discussed as a consequence of electron scattering at the low-lying excitations of the structurally disordered Mn3Ga lattice.

  6. Experimental core electron density of cubic boron nitride

    DEFF Research Database (Denmark)

    Wahlberg, Nanna; Bindzus, Niels; Bjerg, Lasse

    candidate because of its many similarities with diamond: bonding pattern in the extended network structure, hardness, and the quality of the crystallites.3 However, some degree ionic interaction is a part of the bonding in boron nitride, which is not present in diamond. By investigating the core density...... beyond multipolar modeling of the valence density. As was recently shown in a benchmark study of diamond by Bindzus et al.1 The next step is to investigate more complicated chemical bonding motives, to determine the effect of bonding on the core density. Cubic boron nitride2 lends itself as a perfect...... in boron nitride we may obtain a deeper understanding of the effect of bonding on the total density. We report here a thorough investigation of the charge density of cubic boron nitride with a detailed modelling of the inner atom charge density. By combining high resolution powder X-ray diffraction data...

  7. Highly Aminated Mesoporous Silica Nanoparticles with Cubic Pore Structure

    KAUST Repository

    Suteewong, Teeraporn

    2011-01-19

    Mesoporous silica with cubic symmetry has attracted interest from researchers for some time. Here, we present the room temperature synthesis of mesoporous silica nanoparticles possessing cubic Pm3n symmetry with very high molar ratios (>50%) of 3-aminopropyl triethoxysilane. The synthesis is robust allowing, for example, co-condensation of organic dyes without loss of structure. By means of pore expander molecules, the pore size can be enlarged from 2.7 to 5 nm, while particle size decreases. Adding pore expander and co-condensing fluorescent dyes in the same synthesis reduces average particle size further down to 100 nm. After PEGylation, such fluorescent aminated mesoporous silica nanoparticles are spontaneously taken up by cells as demonstrated by fluorescence microscopy.

  8. Higher-Order Approximation of Cubic-Quintic Duffing Model

    DEFF Research Database (Denmark)

    Ganji, S. S.; Barari, Amin; Babazadeh, H.

    2011-01-01

    We apply an Artificial Parameter Lindstedt-Poincaré Method (APL-PM) to find improved approximate solutions for strongly nonlinear Duffing oscillations with cubic-quintic nonlinear restoring force. This approach yields simple linear algebraic equations instead of nonlinear algebraic equations...... without analytical solution which makes it a unique solution. It is demonstrated that this method works very well for the whole range of parameters in the case of the cubic-quintic oscillator, and excellent agreement of the approximate frequencies with the exact one has been observed and discussed...... this analytical solution with the Newton-Harmonic Balancing Approach. Results indicate that this technique is very effective and convenient for solving conservative truly nonlinear oscillatory systems. Utter simplicity of the solution procedure confirms that this method can be easily extended to other kinds...

  9. Dislocations in hexagonal and cubic GaN

    Science.gov (United States)

    Blumenau, A. T.; Elsner, J.; Jones, R.; Heggie, M. I.; Öberg, S.; Frauenheim, T.; Briddon, P. R.

    2000-12-01

    The structure and electronic activity of several types of dislocations in both hexagonal and cubic GaN are calculated using first-principles methods. Most of the stoichiometric dislocations investigated in hexagonal GaN do not induce deep acceptor states and thus cannot be responsible for the yellow luminescence. However, it is shown that electrically active point defects, in particular gallium vacancies and oxygen-related defect complexes, can be trapped at the stress field of the dislocations and may be responsible for this luminescence. For cubic GaN, we find the ideal stoichiometric 60° dislocation to be electrically active and the glide set to be more stable than the shuffle. The dissociation of the latter is considered.

  10. Cubic-phase GaN light-emitting diodes

    Science.gov (United States)

    Yang, Hui; Zheng, L. X.; Li, J. B.; Wang, X. J.; Xu, D. P.; Wang, Y. T.; Hu, X. W.; Han, P. D.

    1999-04-01

    The feasibility of growing device-quality cubic GaN/GaAs(001) films by metal organic chemical vapor deposition has been demonstrated. The optical quality of the GaN films was characterized by room-temperature photoluminescence measurements, which shows a full width at half maximum of 46 meV. The structural quality of the films was investigated by transmission electron microscopy. There are submicron-size grains free from threading dislocations and stacking faults. More importantly, a cubic-phase GaN blue light-emitting diode has been fabricated. The device process, which is very simple and compatible with current GaAs technology, indicates a promising future for the blue light-emitting diode.

  11. Anodic etching of p-type cubic silicon carbide

    Science.gov (United States)

    Harris, G. L.; Fekade, K.; Wongchotigul, K.

    1992-01-01

    p-Type cubic silicon carbide was anodically etched using an electrolyte of HF:HCl:H2O. The etching depth was determined versus time with a fixed current density of 96.4 mA/sq cm. It was found that the etching was very smooth and very uniform. An etch rate of 22.7 nm/s was obtained in a 1:1:50 HF:HCl:H2O electrolyte.

  12. Large scale structures and the cubic galileon model

    CERN Document Server

    Bhattacharya, Sourav; Tomaras, Theodore N

    2015-01-01

    The maximum size of a bound cosmic structure is computed perturbatively as a function of its mass in the framework of the cubic galileon, proposed recently to model the dark energy of our Universe. Comparison of our results with observations constrains the matter-galileon coupling of the model to $0.03\\lesssim \\alpha \\lesssim 0.17$, thus improving previous bounds based solely on solar system physics.

  13. Influence of strontium on the cubic to ordered hexagonal phase ...

    Indian Academy of Sciences (India)

    Unknown

    Abstract. Oxides of the type Ba3–xSrxMgNb2O9 were synthesized by the solid state route. The x = 0 compo- sition (Ba3MgNb2O9) was found to crystallize in a disordered (cubic) perovskite structure when sintered at. 1000C. For higher Sr doping (x ≥ 0⋅5), there was clearly the presence of an ordered hexagonal phase ...

  14. Dry Powder Precursors of Cubic Liquid Crystalline Nanoparticles (cubosomes)

    Science.gov (United States)

    Spicer, Patrick T.; Small, William B.; Small, William B.; Lynch, Matthew L.; Burns, Janet L.

    2002-08-01

    Cubosomes are dispersed nanostructured particles of cubic phase liquid crystal that have stimulated significant research interest because of their potential for application in controlled-release and drug delivery. Despite the interest, cubosomes can be difficult to fabricate and stabilize with current methods. Most of the current work is limited to liquid phase processes involving high shear dispersion of bulk cubic liquid crystalline material into sub-micron particles, limiting application flexibility. In this work, two types of dry powder cubosome precursors are produced by spray-drying: (1) starch-encapsulated monoolein is produced by spray-drying a dispersion of cubic liquid crystalline particles in an aqueous starch solution and (2) dextran-encapsulated monoolein is produced by spray-drying an emulsion formed by the ethanol-dextran-monoolein-water system. The encapsulants are used to decrease powder cohesion during drying and to act as a soluble colloidal stabilizer upon hydration of the powders. Both powders are shown to form (on average) 0.6 μm colloidally-stable cubosomes upon addition to water. However, the starch powders have a broader particle size distribution than the dextran powders because of the relative ease of spraying emulsions versus dispersions. The developed processes enable the production of nanostructured cubosomes by end-users rather than just specialized researchers and allow tailoring of the surface state of the cubosomes for broader application.

  15. Trace spaces in a pre-cubical complex

    DEFF Research Database (Denmark)

    Raussen, Martin

    2009-01-01

    In directed algebraic topology, directed irreversible (d)-paths and spaces consisting of d-paths are studied from a topological and from a categorical point of view. Motivated by models for concurrent computation, we study in this paper spaces of d-paths in a pre-cubical complex. Such paths are e...... are separable metric spaces which are locally contractible and locally compact. Moreover, they have the homotopy type of a CW-complex.......In directed algebraic topology, directed irreversible (d)-paths and spaces consisting of d-paths are studied from a topological and from a categorical point of view. Motivated by models for concurrent computation, we study in this paper spaces of d-paths in a pre-cubical complex. Such paths...... are equipped with a natural arc length which moreover is shown to be invariant under directed homotopies. D-paths up to reparametrization (called traces) can thus be represented by arc length parametrized d-paths. Under weak additional conditions, it is shown that trace spaces in a pre-cubical complex...

  16. Subset selection in regression

    CERN Document Server

    Miller, Alan

    2002-01-01

    Originally published in 1990, the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade. Thoroughly revised to reflect progress in theory, methods, and computing power, the second edition promises to continue that tradition. The author has thoroughly updated each chapter, incorporated new material on recent developments, and included more examples and references. New in the Second Edition:A separate chapter on Bayesian methodsComplete revision of the chapter on estimationA major example from the field of near infrared spectroscopyMore emphasis on cross-validationGreater focus on bootstrappingStochastic algorithms for finding good subsets from large numbers of predictors when an exhaustive search is not feasible Software available on the Internet for implementing many of the algorithms presentedMore examplesSubset Selection in Regression, Second Edition remains dedicated to the techniques for fitting...

  17. Classification and regression trees

    CERN Document Server

    Breiman, Leo; Olshen, Richard A; Stone, Charles J

    1984-01-01

    The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

  18. Aid and growth regressions

    DEFF Research Database (Denmark)

    Hansen, Henrik; Tarp, Finn

    2001-01-01

    . There are, however, decreasing returns to aid, and the estimated effectiveness of aid is highly sensitive to the choice of estimator and the set of control variables. When investment and human capital are controlled for, no positive effect of aid is found. Yet, aid continues to impact on growth via...... investment. We conclude by stressing the need for more theoretical work before this kind of cross-country regressions are used for policy purposes....

  19. Iron-substituted cubic silsesquioxane pillared clays : Synthesis, characterization and acid catalytic activity

    NARCIS (Netherlands)

    Potsi, Georgia; Ladavos, Athanasios K.; Petrakis, Dimitrios; Douvalis, Alexios P.; Sanakis, Yiannis; Katsiotis, Marios S.; Papavassiliou, Georgios; Alhassan, Saeed; Gournis, Dimitrios; Rudolf, Petra

    2018-01-01

    Novel pillared structures were developed from the intercalation of iron-substituted cubic silsesquioxanes in a sodium and an acid-activated montmorillonite nanoclay and evaluated as acid catalysts. Octameric cubic oligosiloxanes were formed upon controlled hydrolytic polycondensation of the

  20. Hierarchical Logistic Regression in Course Placement

    Science.gov (United States)

    Schulz, E. Matthew; Betebenner, Damian; Ahn, Meeyeon

    2004-01-01

    Whether hierarchical logistic regression can reduce the sample size requirement for estimating optimal cutoff scores in a course placement service where predictive validity is measured by a threshold utility function is explored. Data from courses with varying class size were randomly partitioned into two halves per course. Nonhierarchical and…

  1. Nonparametric and semiparametric dynamic additive regression models

    DEFF Research Database (Denmark)

    Scheike, Thomas Harder; Martinussen, Torben

    Dynamic additive regression models provide a flexible class of models for analysis of longitudinal data. The approach suggested in this work is suited for measurements obtained at random time points and aims at estimating time-varying effects. Both fully nonparametric and semiparametric models can...

  2. Complex Regression Functional And Load Tests Development

    Directory of Open Access Journals (Sweden)

    Anton Andreevich Krasnopevtsev

    2015-10-01

    Full Text Available The article describes practical approaches for realization of automatized regression functional and load testing on random software-hardware complex, based on «MARSh 3.0» sample. Testing automatization is being realized for «MARSh 3.0» information security increase.

  3. Logistic regression models

    CERN Document Server

    Hilbe, Joseph M

    2009-01-01

    This book really does cover everything you ever wanted to know about logistic regression … with updates available on the author's website. Hilbe, a former national athletics champion, philosopher, and expert in astronomy, is a master at explaining statistical concepts and methods. Readers familiar with his other expository work will know what to expect-great clarity.The book provides considerable detail about all facets of logistic regression. No step of an argument is omitted so that the book will meet the needs of the reader who likes to see everything spelt out, while a person familiar with some of the topics has the option to skip "obvious" sections. The material has been thoroughly road-tested through classroom and web-based teaching. … The focus is on helping the reader to learn and understand logistic regression. The audience is not just students meeting the topic for the first time, but also experienced users. I believe the book really does meet the author's goal … .-Annette J. Dobson, Biometric...

  4. Solving nonlinear Benjamin-Bona-Mahony equation using cubic B-spline and cubic trigonometric B-spline collocation methods

    Science.gov (United States)

    Rahan, Nur Nadiah Mohd; Ishak, Siti Noor Shahira; Hamid, Nur Nadiah Abd; Majid, Ahmad Abd.; Azmi, Amirah

    2017-04-01

    In this research, the nonlinear Benjamin-Bona-Mahony (BBM) equation is solved numerically using the cubic B-spline (CuBS) and cubic trigonometric B-spline (CuTBS) collocation methods. The CuBS and CuTBS are utilized as interpolating functions in the spatial dimension while the standard finite difference method (FDM) is applied to discretize the temporal space. In order to solve the nonlinear problem, the BBM equation is linearized using Taylor's expansion. Applying the von-Neumann stability analysis, the proposed techniques are shown to be unconditionally stable under the Crank-Nicolson scheme. Several numerical examples are discussed and compared with exact solutions and results from the FDM.

  5. Key parameters governing the densification of cubic-Li7La3Zr2O12 Li+ conductors

    Science.gov (United States)

    Yi, Eongyu; Wang, Weimin; Kieffer, John; Laine, Richard M.

    2017-06-01

    Cubic-Li7La3Zr2O12 (LLZO) is regarded as one of the most promising solid electrolytes for the construction of inherently safe, next generation all-solid-state Li batteries. Unfortunately, sintering these materials to full density with controlled grain sizes, mechanical and electrochemical properties relies on energy and equipment intensive processes. In this work, we elucidate key parameters dictating LLZO densification by tracing the compositional and structural changes during processing calcined and ball-milled Al3+ doped LLZO powders. We find that the powders undergo ion (Li+/H+) exchange during room temperature processing, such that on heating, the protonated LLZO lattice collapses and crystallizes to its constituent oxides, leading to reaction driven densification at ionic conductivity (1.3 ± 0.1 mS cm-1) and record low ionic area specific resistance (2 Ω cm2).

  6. Adaptive metric kernel regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    2000-01-01

    Kernel smoothing is a widely used non-parametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this contribution, we propose an algorithm that adapts the input metric used in multivariate...... regression by minimising a cross-validation estimate of the generalisation error. This allows to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms...

  7. Adaptive Metric Kernel Regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    1998-01-01

    Kernel smoothing is a widely used nonparametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this paper, we propose an algorithm that adapts the input metric used in multivariate regression...... by minimising a cross-validation estimate of the generalisation error. This allows one to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms the standard...

  8. Flow and dispersion in an urban cubical cavity

    Science.gov (United States)

    Ryu, Young-Hee; Baik, Jong-Jin

    Flow and dispersion in an urban cubical cavity are numerically investigated using a Reynolds-averaged Navier-Stokes equations (RANS) model with the renormalization group (RNG) k- ɛ turbulence closure model. The urban cubical cavity is surrounded by flank walls that are parallel to the streamwise direction, called end-walls, as well as upstream and downstream walls. A primary vortex and secondary vortices including end-wall vortices are formed in the cavity. Because of the end-wall drag effect, the averaged mean-flow kinetic energy in the cavity is smaller than that in an urban street canyon that is open in the along-canyon direction. A trajectory analysis shows that the end-wall vortices cause fluid particles to move in the spanwise direction, indicating that flow in the cavity is essentially three-dimensional. The iso-surfaces of the Okubo-Weiss criterion capture cavity vortices well. The pollutant concentration is high near the bottom of the upstream side in the case of continuous pollutant emission, whereas it is high near the center of the primary vortex in the case of instantaneous pollutant emission. To get some insight into the degree of pollutant escape from the cavity according to various meteorological factors, extensive numerical experiments with different ambient wind speeds and directions, inflow turbulence intensities, and cavity-bottom heating intensities are performed. For each experiment, we calculate the time constant, which is defined as the time taken for the pollutant concentration to decrease to e-1 of its initial value. The time constant decreases substantially with increasing ambient wind speed, and tends to decrease with increasing inflow turbulence intensity and cavity-bottom heating intensity. The time constant increases as the ambient wind direction becomes oblique. High ambient wind speed is found to be the most crucial factor for ventilating the cavity, thus improving air quality in an urban cubical cavity.

  9. Stress reduction of cubic boron nitride films by oxygen addition

    Energy Technology Data Exchange (ETDEWEB)

    Ye, J. [Forschungszentrum Karlsruhe, IMF I, Hermann-von-Helmholtz-Platz 1, D-76344 Eggenstein-Leopoldshafen (Germany)], E-mail: Jian.Ye@imf.fzk.de; Ulrich, S.; Ziebert, C.; Stueber, M. [Forschungszentrum Karlsruhe, IMF I, Hermann-von-Helmholtz-Platz 1, D-76344 Eggenstein-Leopoldshafen (Germany)

    2008-12-01

    Cubic boron nitride (c-BN) films with significantly reduced residual stresses were successfully grown onto silicon substrates by means of controlled oxygen addition into the films. The deposition was based on radio-frequency magnetron sputtering of a hexagonal boron nitride (h-BN) target, and was accomplished in a reactive mode using gas mixtures of argon, nitrogen, and oxygen at 0.3 Pa pressure, 400 deg. C growth temperature, and - 250 V substrate bias. Results of systematic investigations are shown in this article with respect to the critical influences of oxygen concentration during deposition upon the stress, cubic phase fraction, as well as nanohardness of the deposited films. Under the specified growth conditions, the formation of c-BN was generally completely hindered for oxygen concentrations above 1.5 vol.% in the gas mixture. At concentrations below approximately 1 vol.%, the added oxygen exhibits however marginal influences on the c-BN fraction, but on the other side a strong impact on the stress of the deposited films. Cubic-phase dominated films (containing 70-80 vol.% c-BN) with their compressive stress three times reduced were thus produced through careful control of oxygen fraction in the gas mixture, showing an excellent nanohardness of almost 60 GPa. For such films, a post-deposition thermal treatment at 900 deg. C led to an additional drastic stress reduction resulting in a final residual stress that is almost 10 times lower than that of as-deposited c-BN films without intentional oxygen addition.

  10. Cubic Phases, Cubosomes and Ethosomes for Cutaneous Application.

    Science.gov (United States)

    Esposito, Elisabetta; Drechsler, Markus; Nastruzzi, Claudio; Cortesi, Rita

    2016-01-01

    Cutaneous administration represents a good strategy to treat skin diseases, avoiding side effects related to systemic administration. Apart from conventional therapy, based on the use of semi-solid formulation such as gel, ointments and creams, recently the use of specialized delivery systems based on lipid has been taken hold. This review provides an overview about the use of cubic phases, cubosomes and ethosomes, as lipid systems recently proposed to treat skin pathologies. In addition in the final part of the review cubic phases, cubosomes and ethosomes are compared to solid lipid nanoparticles and lecithin organogel with respect to their potential as delivery systems for cutaneous application. It has been reported that lipid nanosystems are able to dissolve and deliver active molecules in a controlled fashion, thereby improving their bioavailability and reducing side-effects. Particularly lipid matrixes are characterized by skin affinity and biocompatibility allowing their application on skin. Indeed, after cutaneous administration, the lipid matrix of cubic phases and cubosomes coalesces with the lipids of the stratum comeum and leads to the formation of a lipid depot from which the drug associated to the nanosystem can be released in the deeper skin strata in a controlled manner. Ethosomes are characterized by a malleable structure that promotes their interaction with skin, improving their potential as skin delivery systems with respect to liposomes. Also in the case of solid lipid nanoparticles it has been suggested a deep interaction between lipid matrix and skin strata that endorses sustained and prolonged drug release. Concerning lecithin organogel, the peculiar structure of this system, where lecithin exerts a penetration enhancer role, allows a deep interaction with skin strata, promoting the transdermal absorption of the encapsulated drugs.

  11. Inhomogeneous atomic Bose-Fermi mixtures in cubic lattices.

    Science.gov (United States)

    Cramer, M; Eisert, J; Illuminati, F

    2004-11-05

    We determine the ground state properties of inhomogeneous mixtures of bosons and fermions in cubic lattices and parabolic confining potentials. For finite hopping we determine the domain boundaries between Mott-insulator plateaux and hopping-dominated regions for lattices of arbitrary dimension within mean-field and perturbation theory. The results are compared with a new numerical method that is based on a Gutzwiller variational approach for the bosons and an exact treatment for the fermions. The findings can be applied as a guideline for future experiments with trapped atomic Bose-Fermi mixtures in optical lattices.

  12. Compressibility and thermal expansion of cubic silicon nitride

    DEFF Research Database (Denmark)

    Jiang, Jianzhong; Lindelov, H.; Gerward, Leif

    2002-01-01

    The compressibility and thermal expansion of the cubic silicon nitride (c-Si3N4) phase have been investigated by performing in situ x-ray powder-diffraction measurements using synchrotron radiation, complemented with computer simulations by means of first-principles calculations. The bulk...... compressibility of the c-Si3N4 phase originates from the average of both Si-N tetrahedral and octahedral compressibilities where the octahedral polyhedra are less compressible than the tetrahedral ones. The origin of the unit cell expansion is revealed to be due to the increase of the octahedral Si-N and N-N bond...

  13. C2-rational cubic spline involving tension parameters

    Indian Academy of Sciences (India)

    iИ1 ИfЕ122Y 128Ж; Е122Y 156Ж; Е150Y 184Ж; Е178Y 184Ж;. Е206Y 156Ж; Е206Y 128Ж; Е178Y 100Ж; Е150Y 100Ж;. Е122Y 72Ж; Е122Y 44Ж; Е150Y 16Ж; Е178Y 16Ж;. Е206Y 44Ж; Е206Y 72ЖgY we obtain the C2-rational cubic spline interpolant. Thus for different values of the tension parameters r and t, ...

  14. Evidence for cubic phase in deposited germanium nanocrystals

    CERN Document Server

    Bostedt, C; Plitzko, J M; Möller, T; Terminello, L J

    2003-01-01

    Germanium nanocrystals with sizes ranging from 1 to 5 nm are condensed out of the gas phase in helium or argon buffer-gas atmospheres and subsequently deposited. The generated particle sizes are found to depend on the buffer gas, with helium yielding a narrower size distribution than argon and argon exhibiting a stronger pressure dependence of the produced particle sizes. Structural analysis of nanoparticles with average sizes around 5 nm reveals the bulklike cubic (diamond) phase - in contrast to recent experiments which suggest the tetragonal phase for similar-sized particles. These results are explained in terms of particle formation dynamics.

  15. Tensor tomography of stresses in cubic single crystals

    Directory of Open Access Journals (Sweden)

    Dmitry D. Karov

    2015-03-01

    Full Text Available The possibility of optical tomography applying to investigation of a two-dimensional and a three-dimensional stressed state in single cubic crystals has been studied. Stresses are determined within the framework of the Maxwell piezo-optic law (linear dependence of the permittivity tensor on stresses and weak optical anisotropy. It is shown that a complete reconstruction of stresses in a sample is impossible both by translucence it in the parallel planes system and by using of the elasticity theory equations. For overcoming these difficulties, it is offered to use a method of magnetophotoelasticity.

  16. Rotary Ultrasonic Machining of Poly-Crystalline Cubic Boron Nitride

    Directory of Open Access Journals (Sweden)

    Kuruc Marcel

    2014-12-01

    Full Text Available Poly-crystalline cubic boron nitride (PCBN is one of the hardest material. Generally, so hard materials could not be machined by conventional machining methods. Therefore, for this purpose, advanced machining methods have been designed. Rotary ultrasonic machining (RUM is included among them. RUM is based on abrasive removing mechanism of ultrasonic vibrating diamond particles, which are bonded on active part of rotating tool. It is suitable especially for machining hard and brittle materials (such as glass and ceramics. This contribution investigates this advanced machining method during machining of PCBN.

  17. An Introduction to Logistic Regression.

    Science.gov (United States)

    Cizek, Gregory J.; Fitzgerald, Shawn M.

    1999-01-01

    Where linearity cannot be assumed, logistic regression may be appropriate. This article describes conditions and tests for using logistic regression; introduces the logistic-regression model, the use of logistic-regression software, and some applications in published literature. Univariate and multiple independent-variable conditions and…

  18. Reciprocal Causation in Regression Analysis.

    Science.gov (United States)

    Wolfle, Lee M.

    1979-01-01

    With even the simplest bivariate regression, least-squares solutions are inappropriate unless one assumes a priori that reciprocal effects are absent, or at least implausible. While this discussion is limited to bivariate regression, the issues apply equally to multivariate regression, including stepwise regression. (Author/CTM)

  19. Bias-Robust Estimates of Regression Based on Projections

    OpenAIRE

    Maronna, Ricardo A.; Yohai, Victor J

    1993-01-01

    A new class of bias-robust estimates of multiple regression is introduced. If $y$ and $x$ are two real random variables, let $T(y, x)$ be a univariate robust estimate of regression of $y$ on $x$ through the origin. The regression estimate $\\mathbf{T}(y, \\mathbf{x})$ of a random variable $y$ on a random vector $\\mathbf{x} = (x_1,\\cdots, x_p)'$ is defined as the vector $\\mathbf{t} \\in \\mathfrak{R}^p$ which minimizes $\\sup_{\\|\\mathbf{\\lambda}\\| = 1} \\mid T(y - \\mathbf{t'x, \\lambda' x}) \\mid s(\\m...

  20. Four-dimensional black holes in Einsteinian cubic gravity

    Science.gov (United States)

    Bueno, Pablo; Cano, Pablo A.

    2016-12-01

    We construct static and spherically symmetric generalizations of the Schwarzschild- and Reissner-Nordström-(anti-)de Sitter [RN-(A)dS] black-hole solutions in four-dimensional Einsteinian cubic gravity (ECG). The solutions are characterized by a single function which satisfies a nonlinear second-order differential equation. Interestingly, we are able to compute independently the Hawking temperature T , the Wald entropy S and the Abbott-Deser mass M of the solutions analytically as functions of the horizon radius and the ECG coupling constant λ . Using these we show that the first law of black-hole mechanics is exactly satisfied. Some of the solutions have positive specific heat, which makes them thermodynamically stable, even in the uncharged and asymptotically flat case. Further, we claim that, up to cubic order in curvature, ECG is the most general four-dimensional theory of gravity which allows for nontrivial generalizations of Schwarzschild- and RN-(A)dS characterized by a single function which reduce to the usual Einstein gravity solutions when the corresponding higher-order couplings are set to zero.

  1. String scattering amplitudes and deformed cubic string field theory

    Science.gov (United States)

    Lai, Sheng-Hong; Lee, Jen-Chi; Lee, Taejin; Yang, Yi

    2018-01-01

    We study string scattering amplitudes by using the deformed cubic string field theory which is equivalent to the string field theory in the proper-time gauge. The four-string scattering amplitudes with three tachyons and an arbitrary string state are calculated. The string field theory yields the string scattering amplitudes evaluated on the world sheet of string scattering whereas the conventional method, based on the first quantized theory brings us the string scattering amplitudes defined on the upper half plane. For the highest spin states, generated by the primary operators, both calculations are in perfect agreement. In this case, the string scattering amplitudes are invariant under the conformal transformation, which maps the string world sheet onto the upper half plane. If the external string states are general massive states, generated by non-primary field operators, we need to take into account carefully the conformal transformation between the world sheet and the upper half plane. We show by an explicit calculation that the string scattering amplitudes calculated by using the deformed cubic string field theory transform into those of the first quantized theory on the upper half plane by the conformal transformation, generated by the Schwarz-Christoffel mapping.

  2. Elastic properties of cubic crystals: Every's versus Blackman's diagram

    Science.gov (United States)

    Paszkiewicz, T.; Wolski, S.

    2008-03-01

    Blackman's diagram of two dimensionless ratios of elastic constants is frequently used to correlate elastic properties of cubic crystals with interatomic bondings. Every's diagram of a different set of two dimensionless variables was used by us for classification of various properties of such crystals. We compare these two ways of characterization of elastic properties of cubic materials and consider the description of various groups of materials, e.g. simple metals, oxides, and alkali halides. With exception of intermediate valent compounds, the correlation coefficients for Every's diagrams of various groups of materials are greater than for Blackaman's diagrams, revealing the existence of a linear relationship between two dimensionless Every's variables. Alignment of elements and compounds along lines of constant Poisson's ratio v(lang100rang, m), (m arbitrary perpendicular to lang100rang) is observed. Division of the stability region in Blackman's diagram into region of complete auxetics, auxetics and non-auxetics is introduced. Correlations of a scaling and an acoustic anisotropy parameter are considered.

  3. Mixed convection in a double lid-driven cubic cavity

    Energy Technology Data Exchange (ETDEWEB)

    Nasreddine, Ouertatania; Nader, Ben Cheikha; Brahim, Ben Beyaa; Taieb, Lilia [Faculte des Sciences de Tunis, Dept. de Physique (Tunisia); Campo, A. [University of Texas at San Antonio, Dept. of Mechanical Engineering, San Antonio, TX (United States)

    2009-07-15

    To study the intricate three-dimensional flow structures and the companion heat transfer rates in double lid-driven cubic cavity heated from the top and cooled from below, a numerical methodology based on the finite volume method and a full multigrid acceleration is utilized in this paper. The four remaining walls forming the cubic cavity are adiabatic. The working fluid is air so that the Prandtl number equates to 0.71. Numerical solutions are generated for representative combinations of the controlling Reynolds number inside 100 {<=} Re {<=} 1000 and the Richardson numbers inside 0.001 {<=} Ri {<=} 10. Typical sets of streamlines and isotherms are presented to analyze the tortuous circulatory flow patterns set up by the competition between the forced flow created by the double driven walls and the buoyancy force of the fluid. For extreme combinations of high Ri and low Re, the heat transfer is essentially dominated by conduction. On the other hand, for extreme combinations of small Ri and high Re, the heat transfer becomes convective dominating. Numerical values of the overall Nusselt number in harmony with the Re- and Ri-intervals are presented and they are compared afterward against the standard case of a single lid driven cavity. It is discovered that a remarkable heat transfer improvement of up to 76% can be reached for the particular combination of Re=400 and Ri=1. (authors)

  4. Experimental investigation on water flow in cubic arrays of spheres

    Science.gov (United States)

    Huang, K.; Wan, J. W.; Chen, C. X.; He, L. Q.; Mei, W. B.; Zhang, M. Y.

    2013-06-01

    One-dimensional uniform flow in homogeneous porous media was experimentally investigated. Head drop experiments were conducted in four test tubes with cubic arrays of spheres in diameter 3 mm, 5 mm, 8 mm and 10 mm. The experimental results indicate that Darcy’s law should be an approximate expression by neglecting the inertial term for flow at low velocity. Nonlinearity is attributed to inertial term in porous medium before the turbulent flow emerges. Forchheimer equation with constant coefficients can well predict the flow in porous medium. The relationship between the diameter of the particles and the coefficients a and b in the equations were verified. Different Ergun type equations were used to predict the head drop and compared to the experimental data. It shows that the Irmay equation could well predict the fluid flow in cubic arrays of spheres, while the prediction of head drop by Ergun equation was much higher than observed data. It indicates that the coefficients α and β in the Ergun type equations have certain relations with porosity or the pore structure and would vary for different medium. The discontinuity observed was interpreted by transition from steady flow to weakly turbulence and compared with previous studies.

  5. On a family of cubic graphs containing the flower snarks

    CERN Document Server

    Fouquet, Jean-Luc; Vanherpe, Jean-Marie

    2010-01-01

    We consider cubic graphs formed with $k \\geq 2$ disjoint claws $C_i \\sim K_{1, 3}$ ($0 \\leq i \\leq k-1$) such that for every integer $i$ modulo $k$ the three vertices of degree 1 of $\\ C_i$ are joined to the three vertices of degree 1 of $C_{i-1}$ and joined to the three vertices of degree 1 of $C_{i+1}$. Denote by $t_i$ the vertex of degree 3 of $C_i$ and by $T$ the set $\\{t_1, t_2,..., t_{k-1}\\}$. In such a way we construct three distinct graphs, namely $FS(1,k)$, $FS(2,k)$ and $FS(3,k)$. The graph $FS(j,k)$ ($j \\in \\{1, 2, 3\\}$) is the graph where the set of vertices $\\cup_{i=0}^{i=k-1}V(C_i) \\setminus T$ induce $j$ cycles (note that the graphs $FS(2,2p+1)$, $p\\geq2$, are the flower snarks defined by Isaacs \\cite{Isa75}). We determine the number of perfect matchings of every $FS(j,k)$. A cubic graph $G$ is said to be {\\em 2-factor hamiltonian} if every 2-factor of $G$ is a hamiltonian cycle. We characterize the graphs $FS(j,k)$ that are 2-factor hamiltonian (note that FS(1,3) is the "Triplex Graph" of Robe...

  6. Symmetry group of an impenetrable cubic well potential

    Science.gov (United States)

    Hernández-Castillo, A. O.; Lemus, R.

    2013-11-01

    When the symmetry group of a quantum particle in an impenetrable cubic well potential is considered to be the O_h group, systematic accidental degeneracy appears. This degeneracy becomes natural when a new symmetry group, embedding the O_h group, is proposed. This new group turns out to be the semidirect product G=T \\wedge O_h, where T is a two-dimensional compact continuous group whose generators correspond to linear combinations of the one-dimensional Hamiltonians. The systematic degeneracy is studied in detail, the new group is identified and its irreducible representations are constructed by means of induction, an approach that allows the irreducibility and completeness to be assured. Similar to the hydrogen atom, we establish a one-to-one reciprocation between the energy and the new group irreducible representations. The impenetrable rectangular and square boxes are also analyzed as a reduction of symmetry from the cubic system. Pythagorean degeneracy as well as that due to commensurable sides is not considered.

  7. Modified Regression Correlation Coefficient for Poisson Regression Model

    Science.gov (United States)

    Kaengthong, Nattacha; Domthong, Uthumporn

    2017-09-01

    This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

  8. Insulin resistance: regression and clustering.

    Directory of Open Access Journals (Sweden)

    Sangho Yoon

    Full Text Available In this paper we try to define insulin resistance (IR precisely for a group of Chinese women. Our definition deliberately does not depend upon body mass index (BMI or age, although in other studies, with particular random effects models quite different from models used here, BMI accounts for a large part of the variability in IR. We accomplish our goal through application of Gauss mixture vector quantization (GMVQ, a technique for clustering that was developed for application to lossy data compression. Defining data come from measurements that play major roles in medical practice. A precise statement of what the data are is in Section 1. Their family structures are described in detail. They concern levels of lipids and the results of an oral glucose tolerance test (OGTT. We apply GMVQ to residuals obtained from regressions of outcomes of an OGTT and lipids on functions of age and BMI that are inferred from the data. A bootstrap procedure developed for our family data supplemented by insights from other approaches leads us to believe that two clusters are appropriate for defining IR precisely. One cluster consists of women who are IR, and the other of women who seem not to be. Genes and other features are used to predict cluster membership. We argue that prediction with "main effects" is not satisfactory, but prediction that includes interactions may be.

  9. Inter- and intraband transitions in cubic nitride quantum wells

    Energy Technology Data Exchange (ETDEWEB)

    Rodrigues, S.C.P. [Sao Paulo Univ. (Brazil). Inst. de Fisica de Sao Carlos; Sao Paulo Univ. (Brazil). Inst. de Fisica; Sipahi, G.M. [Sao Paulo Univ. (Brazil). Inst. de Fisica de Sao Carlos; Scolfaro, L.M.R.; Noriega, O.C.; Leite, J.R. [Sao Paulo Univ. (Brazil). Inst. de Fisica; Frey, T.; As, D.J.; Schikora, D.; Lischka, K. [Paderborn Univ. (Gesamthochschule) (Germany). Fachbereich 6 - Physik

    2002-03-16

    In this work we analyze the luminescence emissions from selected isolated GaN/InGaN quantum wells comparing measured and theoretical photoluminescence (PL) spectra. The calculations are performed within the k.p method by means of an 8 x 8 Kane Hamiltonian, generalized to treat different materials. Strain effects due to the large lattice mismatch between InN and GaN are taken into account. From the direct comparison with experimental results, we found evidence for transitions involving confined levels which, besides those related to quantum dots, may be ascribed to the first electron-heavy-hole transition in the quantum wells. Since the studies of optical properties of quantum wells based on cubic nitrides are at an early stage, the results reported here will provide guidelines for the interpretation of forthcoming experiments. (orig.)

  10. Surface irregularities of MBE grown cubic GaN layers

    Science.gov (United States)

    Lima, A. P.; Frey, T.; Köhler, U.; Wang, C.; As, D. J.; Schöttker, B.; Lischka, K.; Schikora, D.

    1999-02-01

    Cubic GaN layers are grown by molecular beam epitaxy on (0 0 1)GaAs substrates. The influence of intentional deviations from stoichiometric growth conditions on the structural homogeneity of the epitaxial layers and the GaN/GaAs interface was studied. Optical micrographs and AFM-images of the epilayers grown in a Ga-stabilised regime reveal the existence of different types of surface irregularities. We conclude that the irregularities observed are the result of successively melt-back etching in GaN and GaAs and solution growth within Ga-droplets due to the change of the saturation conditions of the liquid Ga-phase on the surface of the growing film.

  11. Linear electro-optic effect in cubic silicon carbide

    Science.gov (United States)

    Tang, Xiao; Irvine, Kenneth G.; Zhang, Dongping; Spencer, Michael G.

    1991-01-01

    The first observation is reported of the electrooptic effect of cubic silicon carbide (beta-SiC) grown by a low-pressure chemical vapor deposition reactor using the hydrogen, silane, and propane gas system. At a wavelength of 633 nm, the value of the electrooptic coefficient r41 in beta-SiC is determined to be 2.7 +/- 0.5 x 10 (exp-12) m/V, which is 1.7 times larger than that in gallium arsenide measured at 10.6 microns. Also, a half-wave voltage of 6.4 kV for beta-SiC is obtained. Because of this favorable value of electrooptic coefficient, it is believed that silicon carbide may be a promising candidate in electrooptic applications for high optical intensity in the visible region.

  12. Quantum corrections for the cubic Galileon in the covariant language

    Science.gov (United States)

    Saltas, Ippocratis D.; Vitagliano, Vincenzo

    2017-05-01

    We present for the first time an explicit exposition of quantum corrections within the cubic Galileon theory including the effect of quantum gravity, in a background- and gauge-invariant manner, employing the field-reparametrisation approach of the covariant effective action at 1-loop. We show that the consideration of gravitational effects in combination with the non-linear derivative structure of the theory reveals new interactions at the perturbative level, which manifest themselves as higher-operators in the associated effective action, which' relevance is controlled by appropriate ratios of the cosmological vacuum and the Galileon mass scale. The significance and concept of the covariant approach in this context is discussed, while all calculations are explicitly presented.

  13. A cubic autocatalytic reaction in a continuous stirred tank reactor

    Energy Technology Data Exchange (ETDEWEB)

    Yakubu, Aisha Aliyu; Yatim, Yazariah Mohd [School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM, Penang Malaysia (Malaysia)

    2015-10-22

    In the present study, the dynamics of the cubic autocatalytic reaction model in a continuous stirred tank reactor with linear autocatalyst decay is studied. This model describes the behavior of two chemicals (reactant and autocatalyst) flowing into the tank reactor. The behavior of the model is studied analytically and numerically. The steady state solutions are obtained for two cases, i.e. with the presence of an autocatalyst and its absence in the inflow. In the case with an autocatalyst, the model has a stable steady state. While in the case without an autocatalyst, the model exhibits three steady states, where one of the steady state is stable, the second is a saddle point while the last is spiral node. The last steady state losses stability through Hopf bifurcation and the location is determined. The physical interpretations of the results are also presented.

  14. Cubic nonlinear Schrödinger equation with vorticity

    Science.gov (United States)

    Caliari, M.; Loffredo, M. I.; Morato, L. M.; Zuccher, S.

    2008-12-01

    In this paper, we introduce a new class of nonlinear Schrödinger equations (NLSEs), with an electromagnetic potential (\\mathcal A,\\Phi) , both depending on the wavefunction Ψ. The scalar potential Φ depends on |Ψ|2, whereas the vector potential \\mathcal A satisfies the equation of magnetohydrodynamics with coefficient depending on Ψ. In Madelung variables, the velocity field comes to be not irrotational in general and we prove that the vorticity induces dissipation, until the dynamical equilibrium is reached. The expression of the rate of dissipation is common to all NLSEs in the class. We show that they are a particular case of the one-particle dynamics out of dynamical equilibrium for a system of N identical interacting Bose particles, as recently described within stochastic quantization by Lagrangian variational principle. The cubic case is discussed in particular. Results of numerical experiments for rotational excitations of the ground state in a finite two-dimensional trap with harmonic potential are reported.

  15. The electric field of a uniformly charged cubic shell

    Science.gov (United States)

    McCreery, Kaitlin; Greenside, Henry

    2018-01-01

    As an integrative and insightful example for undergraduates learning about electrostatics, we discuss how to use symmetry, Coulomb's law, superposition, Gauss's law, and visualization to understand the electric field E (x ,y ,z ) produced by a uniformly charged cubic shell. We first discuss how to deduce qualitatively, using freshman-level physics, the perhaps surprising fact that the interior electric field is nonzero and has a complex structure, pointing inwards from the middle of each face of the shell and pointing outwards towards each edge and corner. We then discuss how to understand the quantitative features of the electric field by plotting an analytical expression for E along symmetry lines and on symmetry surfaces of the shell.

  16. Photonic band gaps in body-centered-cubic structures

    Science.gov (United States)

    Hornreich, R. M.; Shtrikman, S.; Sommers, C.

    1994-04-01

    Photonic energy bands in body-centered-cubic bcc materials are analyzed by considering structures having O8 (I4132) space-group symmetry. Such structures can be realized physically by interlacing cylindrical elements oriented along crystallographic axes. In addition to heterogeneous systems composed entirely of dielectric materials, the possibility of using conducting materials (particularly at microwave frequencies) is studied. We find that (a) band gaps occur in heterogeneous dielectric systems when materials having a dielectric constant of 100 or more are properly placed in the O8 unit cell, and (b) utilizing conducting materials can significantly widen the excluded frequency band, the result being that band gaps of more than 20% should be attainable with O8 structures at microwave frequencies. Experimental verification of these results should be possible in this spectral region.

  17. Spatial 't Hooft loop to cubic order in hot QCD

    CERN Document Server

    Giovannangeli, P.

    2002-01-01

    Spatial 't Hooft loops of strength k measure the qualitative change in the behaviour of electric colour flux in confined and deconfined phase of SU (N) gauge theory. They show an area law in the deconfined phase, known analytica lly to two loop order with a ``k-scaling'' law k(N-k). In this paper we comput e the O(g^3) correction to the tension. It is due to neutral gluon fields that get their mass through interaction with the wall. The simple k-scaling is lost in cubic order. The generic problem of non-convexity shows up in this order an d the cure is provided. The result for large N is explicitely given. We show tha t nonperturbative effects appear at O(g^5).

  18. Bounce universe and black holes from critical Einsteinian cubic gravity

    Science.gov (United States)

    Feng, Xing-Hui; Huang, Hyat; Mai, Zhan-Feng; Lü, Hong

    2017-11-01

    We show that there exists a critical point for the coupling constants in Einsteinian cubic gravity in which the linearized equations on the maximally symmetric vacuum vanish identically. We construct an exact isotropic bounce universe in the critical theory in four dimensions. The comoving time runs from minus infinity to plus infinity, yielding a smooth universe bouncing between two de Sitter vacua. In five dimensions, we adopt a numerical approach to construct a bounce solution, in which a singularity occurs before the bounce takes place. We then construct exact anisotropic bounces that connect two isotropic de Sitter spacetimes with flat spatial sections. We further construct exact anti-de Sitter black holes in the critical theory in four and five dimensions and obtain an exact anti-de Sitter worm brane in four dimensions.

  19. Perbaikan Metode Penghitungan Debit Sungai Menggunakan Cubic Spline Interpolation

    Directory of Open Access Journals (Sweden)

    Budi I. Setiawan

    2007-09-01

    Full Text Available Makalah ini menyajikan perbaikan metode pengukuran debit sungai menggunakan fungsi cubic spline interpolation. Fungi ini digunakan untuk menggambarkan profil sungai secara kontinyu yang terbentuk atas hasil pengukuran jarak dan kedalaman sungai. Dengan metoda baru ini, luas dan perimeter sungai lebih mudah, cepat dan tepat dihitung. Demikian pula, fungsi kebalikannnya (inverse function tersedia menggunakan metode. Newton-Raphson sehingga memudahkan dalam perhitungan luas dan perimeter bila tinggi air sungai diketahui. Metode baru ini dapat langsung menghitung debit sungaimenggunakan formula Manning, dan menghasilkan kurva debit (rating curve. Dalam makalah ini dikemukaan satu canton pengukuran debit sungai Rudeng Aceh. Sungai ini mempunyai lebar sekitar 120 m dan kedalaman 7 m, dan pada saat pengukuran mempunyai debit 41 .3 m3/s, serta kurva debitnya mengikuti formula: Q= 0.1649 x H 2.884 , dimana Q debit (m3/s dan H tinggi air dari dasar sungai (m.

  20. Diamond and Cubic Boron Nitride: Properties, Growth and Applications

    Science.gov (United States)

    Soltani, A.; Talbi, A.; Mortet, V.; BenMoussa, A.; Zhang, W. J.; Gerbedoen, J.-C.; De Jaeger, J.-C.; Gokarna, A.; Haenen, K.; Wagner, P.

    2010-11-01

    Since their first synthesis, cubic boron nitride (c-BN) and diamond thin films have triggered a vivid interest in these wide band gap materials for many different applications. Because of superior properties, c-BN and diamond can be applied in optic, electronic and acoustic for high performances devices. In this discussion, we first describe briefly the properties of c-BN and diamond and we review both the growth techniques and the progresses achieved in the synthesis of c-BN and diamond, and in a second part, characteristics of new c-BN and diamond UV detectors for solar observation are reported. These photo-detectors present extremely low dark current, high breakdown voltage, high responsivity and stability under UV irradiation. Finally, diamond based acoustic devices and sensors are presented. High frequency acoustic wave devices can be design for high frequency filtering or sensing applications. Diamond/AlN micro-cantilevers are excellent platform for sensor applications.

  1. Modelling gravity on a hyper-cubic lattice

    CERN Document Server

    Tate, Kyle

    2012-01-01

    We present an elegant and simple dynamical model of symmetric, non-degenerate (n x n) matrices of fixed signature defined on a n-dimensional hyper-cubic lattice with nearest-neighbor interactions. We show how this model is related to General Relativity, and discuss multiple ways in which it can be useful for studying gravity, both classical and quantum. In particular, we show that the dynamics of the model when all matrices are close to the identity corresponds exactly to a finite-difference discretization of weak-field gravity in harmonic gauge. We also show that the action which defines the full dynamics of the model corresponds to the Einstein-Hilbert action to leading order in the lattice spacing, and use this observation to define a lattice analogue of the Ricci scalar and Einstein tensor. Finally, we perform a mean-field analysis of the statistical mechanics of this model.

  2. Lipidic cubic phase serial millisecond crystallography using synchrotron radiation

    Directory of Open Access Journals (Sweden)

    Przemyslaw Nogly

    2015-03-01

    Full Text Available Lipidic cubic phases (LCPs have emerged as successful matrixes for the crystallization of membrane proteins. Moreover, the viscous LCP also provides a highly effective delivery medium for serial femtosecond crystallography (SFX at X-ray free-electron lasers (XFELs. Here, the adaptation of this technology to perform serial millisecond crystallography (SMX at more widely available synchrotron microfocus beamlines is described. Compared with conventional microcrystallography, LCP-SMX eliminates the need for difficult handling of individual crystals and allows for data collection at room temperature. The technology is demonstrated by solving a structure of the light-driven proton-pump bacteriorhodopsin (bR at a resolution of 2.4 Å. The room-temperature structure of bR is very similar to previous cryogenic structures but shows small yet distinct differences in the retinal ligand and proton-transfer pathway.

  3. Computation of L ⊕ for several cubic Pisot numbers

    Directory of Open Access Journals (Sweden)

    Julien Bernat

    2007-05-01

    Full Text Available In this article, we are dealing with β-numeration, which is a generalization of numeration in a non-integer base. We consider the class of simple Parry numbers such that d β (1 = 0.k 1 d-1  k d with d ∈ ℕ, d ≥ 2 and k 1  ≥ k d  ≥ 1. We prove that these elements define Rauzy fractals that are stable under a central symmetry. We use this result to compute, for several cases of cubic Pisot units, the maximal length among the lengths of the finite β-fractional parts of sums of two β-integers, denoted by L ⊕. In particular, we prove that L ⊕  = 5 in the Tribonacci case.

  4. Electron spin dynamics in cubic GaN

    Science.gov (United States)

    Buß, J. H.; Schupp, T.; As, D. J.; Brandt, O.; Hägele, D.; Rudolph, J.

    2016-12-01

    The electron spin dynamics in cubic GaN is comprehensively investigated by time-resolved magneto-optical Kerr-rotation spectroscopy over a wide range of temperatures, magnetic fields, and doping densities. The spin dynamics is found to be governed by the interplay of spin relaxation of localized electrons and Dyakonov-Perel relaxation of delocalized electrons. Localized electrons significantly contribute to spin relaxation up to room temperature at moderate doping levels, while Dyakonov-Perel relaxation dominates for high temperatures or degenerate doping levels. Quantitative agreement to Dyakonov-Perel theory requires a larger value of the spin-splitting constant than theoretically predicted. Possible reasons for this discrepancy are discussed, including the role of charged dislocations.

  5. Preparation and pharmacokinetic study of fenofibrate cubic liquid crystalline

    Directory of Open Access Journals (Sweden)

    Shijie Wei

    2017-11-01

    Full Text Available An LCC delivery system for Fenofibrate (Fen was developed to improve its poorly oral bioavailability. Fen-LCC preparation methods were screened, and the prepared Fen-LCC was then characterized by a polarizing microscope and transmission electron microscopy (TEM. The spray drying technique was selected to dry and solidify particles into powder. The in vitro release of Fen-LCC was measured and in vivo pharmacokinetic experiments were carried out on rats after oral administration. Particles prepared through the high-temperature input method exhibited structural characteristics of LCC, and re-dissolved particles maintained the same features. The LCC delivery system can significantly improve in vitro release outcomes. After oral administration, AUCs of the suspension and LCC systems were measured at 131.6853 µg⋅h/ml and 1435.72893 µg⋅h/ml, respectively. The spray drying process presented here better maintains cubic structures, and the LCC system significantly improves bioavailability levels.

  6. A logistic regression estimating function for spatial Gibbs point processes

    DEFF Research Database (Denmark)

    Baddeley, Adrian; Coeurjolly, Jean-François; Rubak, Ege

    We propose a computationally efficient logistic regression estimating function for spatial Gibbs point processes. The sample points for the logistic regression consist of the observed point pattern together with a random pattern of dummy points. The estimating function is closely related...

  7. Population-Sample Regression in the Estimation of Population Proportions

    Science.gov (United States)

    Weitzman, R. A.

    2006-01-01

    Focusing on a single sample obtained randomly with replacement from a single population, this article examines the regression of population on sample proportions and develops an unbiased estimator of the square of the correlation between them. This estimator turns out to be the regression coefficient. Use of the squared-correlation estimator as a…

  8. Epitaxial growth and optical transitions of cubic GaN films

    Science.gov (United States)

    Schikora, D.; Hankeln, M.; As, D. J.; Lischka, K.; Litz, T.; Waag, A.; Buhrow, T.; Henneberger, F.

    1996-09-01

    Single-phase cubic GaN layers are grown by plasma-assisted molecular-beam epitaxy. The temperature dependence of the surface reconstruction is elaborated. The structural stability of the cubic growth in dependence of the growth stoichiometry is studied by RHEED measurements and numerical simulations of the experimental RHEED patterns. Growth oscillations on cubic GaN are recorded at higher substrate temperatures and nearly stoichiometric adatom coverage. Photoluminescence reveals the dominant optical transitions of cubic GaN and, by applying an external magnetic field, their characteristic g factors are determined.

  9. Subalgebras of BCK/BCI-Algebras Based on Cubic Soft Sets

    Directory of Open Access Journals (Sweden)

    G. Muhiuddin

    2014-01-01

    Full Text Available Operations of cubic soft sets including “AND” operation and “OR” operation based on P-orders and R-orders are introduced and some related properties are investigated. An example is presented to show that the R-union of two internal cubic soft sets might not be internal. A sufficient condition is provided, which ensure that the R-union of two internal cubic soft sets is also internal. Moreover, some properties of cubic soft subalgebras of BCK/BCI-algebras based on a given parameter are discussed.

  10. Cubic liquid crystalline nanoparticles: optimization and evaluation for ocular delivery of tropicamide.

    Science.gov (United States)

    Verma, Purnima; Ahuja, Munish

    2016-10-01

    The purpose of this study was to investigate the potential of cubic liquid crystalline nanoparticles for ocular delivery of tropicamide. Ultrasound-assisted fragmentation of cubic liquid crystalline bulk phases resulted in cubic liquid crystalline nanoparticles employing Pluronic F127 as dispersant. The effects of process variables such as sonication time, sonication amplitude, sonication depth, and pre-mixing time on particle size and polydispersity index was investigated using central composite design. The morphology of tropicamide-loaded nanoparticles was found to be nearly cubical in shape by transmission electron microscopy observation. Further, small angle X-ray scattering experiment confirmed the presence of D and P phase cubic structures in coexistence. The optimized tropicamide-loaded cubic nanoparticles showed in vitro corneal permeation of tropicamide across isolated porcine cornea comparable to its commercial preparation, Tropicacyl®. Ocular tolerance was evaluated by Hen's egg-chorioallantoic membrane test and histological studies. The results of in vivo mydriatic response study demonstrated a remarkably higher area under mydriatic response curve (AUC0→1440 min) values of cubic nanoparticles over Tropicacyl® indicating better therapeutic value of cubic nanoparticles. Furthermore, tropicamide-loaded cubic nanoparticles exhibited prolonged mydriatic effect on rabbits as compared to commercial conventional aqueous ophthalmic solution.

  11. Non-spherical micelles in an oil-in-water cubic phase

    DEFF Research Database (Denmark)

    Leaver, M.; Rajagopalan, V.; Ulf, O.

    2000-01-01

    The cubic phase formed between the microemulsion and hexagonal phases of the ternary pentaethylene glycol dodecyl ether (C12E5)-decane-water system and that doped with small amounts of sodium dodecylsulfate (SDS) have been investigated. The presence of discrete oil-swollen micelles in the cubic...... scattering experiments indicate that the lattice parameter for the cubic phase is inconsistent with a simple packing of micelles. Whilst insufficient reflections were observed to establish the space group of the cubic phase uniquely, those that were are consistent with two commonly observed space groups...

  12. Prediction of Gas Injection Effect on Asphaltene Precipitation Onset Using the Cubic and Cubic-Plus-Association Equations of State

    DEFF Research Database (Denmark)

    Arya, Alay; Liang, Xiaodong; von Solms, Nicolas

    2017-01-01

    precipitation onset condition during gas injection. The modeling approach is used with the Soave Redlich Kwong, Soave Redlich Kwong-Plus-Huron Vidal mixing rule and cubic-plus-association (CPA) equations of state (EoS). Six different reservoir fluids are studied with respect to asphaltene onset precipitation...... during nitrogen, hydrocarbon gas mixture, and carbon dioxide injection. It is also shown how to extend the modeling approach when the reservoir fluid is split into multiple pseudocomponents. It is observed that the modeling approach using any of the three models can predict the gas injection effect......Gas injection is a proven enhanced oil recovery technique. The gas injection changes the reservoir oil composition, temperature, and pressure conditions, which may result in asphaltene precipitation. In this work, we have used a modeling approach from the literature in order to predict asphaltene...

  13. Combining Alphas via Bounded Regression

    Directory of Open Access Journals (Sweden)

    Zura Kakushadze

    2015-11-01

    Full Text Available We give an explicit algorithm and source code for combining alpha streams via bounded regression. In practical applications, typically, there is insufficient history to compute a sample covariance matrix (SCM for a large number of alphas. To compute alpha allocation weights, one then resorts to (weighted regression over SCM principal components. Regression often produces alpha weights with insufficient diversification and/or skewed distribution against, e.g., turnover. This can be rectified by imposing bounds on alpha weights within the regression procedure. Bounded regression can also be applied to stock and other asset portfolio construction. We discuss illustrative examples.

  14. Characterization, Microstructure, and Dielectric properties of cubic pyrochlore structural ceramics

    KAUST Repository

    Li, Yangyang

    2013-05-01

    The (BMN) bulk materials were sintered at 1050°C, 1100°C, 1150°C, 1200°C by the conventional ceramic process, and their microstructure and dielectric properties were investigated by Scanning electron microscopy (SEM), X-ray diffraction (XRD), Raman spectroscopy, Transmission electron microscopy (TEM) (including the X-ray energy dispersive spectrometry EDS and high resolution transmission electron microscopy HRTEM) and dielectric impedance analyzer. We systematically investigated the structure, dielectric properties and voltage tunable property of the ceramics prepared at different sintering temperatures. The XRD patterns demonstrated that the synthesized BMN solid solutions had cubic phase pyrochlore-type structure when sintered at 1050°C or higher, and the lattice parameter (a) of the unit cell in BMN solid solution was calculated to be about 10.56Å. The vibrational peaks observed in the Raman spectra of BMN solid solutions also confirmed the cubic phase pyrochlore-type structure of the synthesized BMN. According to the Scanning Electron Microscope (SEM) images, the grain size increased with increasing sintering temperature. Additionally, it was shown that the densities of the BMN ceramic tablets vary with sintering temperature. The calculated theoretical density for the BMN ceramic tablets sintered at different temperatures is about 6.7521 . The density of the respective measured tablets is usually amounting more than 91% and 5 approaching a maximum value of 96.5% for sintering temperature of 1150°C. The microstructure was investigated by using Scanning Transmission Electron Microscope (STEM), X-ray diffraction (XRD). Combined with the results obtained from the STEM and XRD, the impact of sintering temperature on the macroscopic and microscopic structure was discussed. The relative dielectric constant ( ) and dielectric loss ( ) of the BMN solid solutions were measured to be 161-200 and (at room temperature and 100Hz-1MHz), respectively. The BMN solid

  15. Time-adaptive quantile regression

    DEFF Research Database (Denmark)

    Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg; Madsen, Henrik

    2008-01-01

    An algorithm for time-adaptive quantile regression is presented. The algorithm is based on the simplex algorithm, and the linear optimization formulation of the quantile regression problem is given. The observations have been split to allow a direct use of the simplex algorithm. The simplex method...... and an updating procedure are combined into a new algorithm for time-adaptive quantile regression, which generates new solutions on the basis of the old solution, leading to savings in computation time. The suggested algorithm is tested against a static quantile regression model on a data set with wind power...... production, where the models combine splines and quantile regression. The comparison indicates superior performance for the time-adaptive quantile regression in all the performance parameters considered....

  16. Mixed-effects regression models in linguistics

    CERN Document Server

    Heylen, Kris; Geeraerts, Dirk

    2018-01-01

    When data consist of grouped observations or clusters, and there is a risk that measurements within the same group are not independent, group-specific random effects can be added to a regression model in order to account for such within-group associations. Regression models that contain such group-specific random effects are called mixed-effects regression models, or simply mixed models. Mixed models are a versatile tool that can handle both balanced and unbalanced datasets and that can also be applied when several layers of grouping are present in the data; these layers can either be nested or crossed.  In linguistics, as in many other fields, the use of mixed models has gained ground rapidly over the last decade. This methodological evolution enables us to build more sophisticated and arguably more realistic models, but, due to its technical complexity, also introduces new challenges. This volume brings together a number of promising new evolutions in the use of mixed models in linguistics, but also addres...

  17. Evaluating Differential Effects Using Regression Interactions and Regression Mixture Models

    Science.gov (United States)

    Van Horn, M. Lee; Jaki, Thomas; Masyn, Katherine; Howe, George; Feaster, Daniel J.; Lamont, Andrea E.; George, Melissa R. W.; Kim, Minjung

    2015-01-01

    Research increasingly emphasizes understanding differential effects. This article focuses on understanding regression mixture models, which are relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their…

  18. Bias-corrected quantile regression estimation of censored regression models

    NARCIS (Netherlands)

    Cizek, Pavel; Sadikoglu, Serhan

    2018-01-01

    In this paper, an extension of the indirect inference methodology to semiparametric estimation is explored in the context of censored regression. Motivated by weak small-sample performance of the censored regression quantile estimator proposed by Powell (J Econom 32:143–155, 1986a), two- and

  19. Quantum assisted Gaussian process regression

    OpenAIRE

    Zhao, Zhikuan; Fitzsimons, Jack K.; Fitzsimons, Joseph F.

    2015-01-01

    Gaussian processes (GP) are a widely used model for regression problems in supervised machine learning. Implementation of GP regression typically requires $O(n^3)$ logic gates. We show that the quantum linear systems algorithm [Harrow et al., Phys. Rev. Lett. 103, 150502 (2009)] can be applied to Gaussian process regression (GPR), leading to an exponential reduction in computation time in some instances. We show that even in some cases not ideally suited to the quantum linear systems algorith...

  20. Liquid water in the domain of cubic crystalline ice Ic

    Science.gov (United States)

    Jenniskens, P.; Banham, S. F.; Blake, D. F.; McCoustra, M. R.

    1997-01-01

    Vapor-deposited amorphous water ice when warmed above the glass transition temperature (120-140 K), is a viscous liquid which exhibits a viscosity vs temperature relationship different from that of liquid water at room temperature. New studies of thin water ice films now demonstrate that viscous liquid water persists in the temperature range 140-210 K. where it coexists with cubic crystalline ice. The liquid character of amorphous water above the glass transition is demonstrated by (1) changes in the morphology of water ice films on a nonwetting surface observed in transmission electron microscopy (TEM) at around 175 K during slow warming, (2) changes in the binding energy of water molecules measured in temperature programmed desorption (TPD) studies, and (3) changes in the shape of the 3.07 micrometers absorption band observed in grazing angle reflection-absorption infrared spectroscopy (RAIRS) during annealing at high temperature. whereby the decreased roughness of the water surface is thought to cause changes in the selection rules for the excitation of O-H stretch vibrations. Because it is present over such a wide range of temperatures, we propose that this form of liquid water is a common material in nature. where it is expected to exist in the subsurface layers of comets and on the surfaces of some planets and satellites.

  1. STROPHOIDS, A FAMILY OF CUBIC CURVES WITH REMARKABLE PROPERTIES

    Directory of Open Access Journals (Sweden)

    STACHEL Hellmuth

    2015-06-01

    On each strophoid there is a symmetric relation of points, so-called ‘associated’ points, with a series of properties: The lines connecting associated points P and P’ are tangent of the negative pedal curve. Tangents at associated points intersect at a point which again lies on the cubic. For all pairs (P, P’ of associated points, the midpoints lie on a line through the node N. For any two pairs (P, P’ and (Q, Q’ of associated points, the points of intersection between the lines PQ and P’Q’ as well as between PQ’ and P’Q are again placed on the strophoid and mutually associated. The lines PQ and PQ’ are symmetric with respect to the line connecting P with the node. Thus, strophoids generalize Apollonian circles: For given non-collinear points A, A’ and N the locus of points X such that one angle bisector of the lines XA and XA’ passes through N is a strophoid.

  2. Cubic Phase Formation in Phospholipid and PEG-Lipid Mixtures

    Science.gov (United States)

    Murley, Kimberly; Cunningham, Beth; Wolfe, David; Williams, Patrick

    2005-03-01

    Lipid systems modeling cell membranes are capable of self-assembling into various liquid crystal mesophases with varying geometry and dimensions. We have suggested that it is possible to engineer the lipid systems through the incorporation of covalently attached polymer lipids to produce unique effects. The results of this engineering process include both the stabilization of lipid phases that normally exist over very limited temperature ranges and the induction of novel phases that are not normally present in the parent lipid. In this study, we used x-ray diffraction and NMR to investigate the phase behavior of the DOPE:PEG:MO and MO:PEG:D2O systems with varying molar ratios and PEG sizes. The phase diagram which we have generated indicates the conditions necessary to induce specific phase structures and sizes into three-dimensional cubic lipid systems. This information may be useful to create nanostructures which will be valuable in applications such as protein crystallization and protein biochip development.

  3. Research of Cubic Bezier Curve NC Interpolation Signal Generator

    Directory of Open Access Journals (Sweden)

    Shijun Ji

    2014-08-01

    Full Text Available Interpolation technology is the core of the computer numerical control (CNC system, and the precision and stability of the interpolation algorithm directly affect the machining precision and speed of CNC system. Most of the existing numerical control interpolation technology can only achieve circular arc interpolation, linear interpolation or parabola interpolation, but for the numerical control (NC machining of parts with complicated surface, it needs to establish the mathematical model and generate the curved line and curved surface outline of parts and then discrete the generated parts outline into a large amount of straight line or arc to carry on the processing, which creates the complex program and a large amount of code, so it inevitably introduce into the approximation error. All these factors affect the machining accuracy, surface roughness and machining efficiency. The stepless interpolation of cubic Bezier curve controlled by analog signal is studied in this paper, the tool motion trajectory of Bezier curve can be directly planned out in CNC system by adjusting control points, and then these data were put into the control motor which can complete the precise feeding of Bezier curve. This method realized the improvement of CNC trajectory controlled ability from the simple linear and circular arc to the complex project curve, and it provides a new way for economy realizing the curve surface parts with high quality and high efficiency machining.

  4. Time-dependent probability density function in cubic stochastic processes

    Science.gov (United States)

    Kim, Eun-jin; Hollerbach, Rainer

    2016-11-01

    We report time-dependent probability density functions (PDFs) for a nonlinear stochastic process with a cubic force using analytical and computational studies. Analytically, a transition probability is formulated by using a path integral and is computed by the saddle-point solution (instanton method) and a new nonlinear transformation of time. The predicted PDF p (x ,t ) in general involves a time integral, and useful PDFs with explicit dependence on x and t are presented in certain limits (e.g., in the short and long time limits). Numerical simulations of the Fokker-Planck equation provide exact time evolution of the PDFs and confirm analytical predictions in the limit of weak noise. In particular, we show that transient PDFs behave drastically differently from the stationary PDFs in regard to the asymmetry (skewness) and kurtosis. Specifically, while stationary PDFs are symmetric with the kurtosis smaller than 3, transient PDFs are skewed with the kurtosis larger than 3; transient PDFs are much broader than stationary PDFs. We elucidate the effect of nonlinear interaction on the strong fluctuations and intermittency in the relaxation process.

  5. Cubic mesoporous Ag@CN: a high performance humidity sensor.

    Science.gov (United States)

    Tomer, Vijay K; Thangaraj, Nishanthi; Gahlot, Sweta; Kailasam, Kamalakannan

    2016-12-01

    The fabrication of highly responsive, rapid response/recovery and durable relative humidity (%RH) sensors that can precisely monitor humidity levels still remains a considerable challenge for realizing the next generation humidity sensing applications. Herein, we report a remarkably sensitive and rapid %RH sensor having a reversible response using a nanocasting route for synthesizing mesoporous g-CN (commonly known as g-C3N4). The 3D replicated cubic mesostructure provides a high surface area thereby increasing the adsorption, transmission of charge carriers and desorption of water molecules across the sensor surfaces. Owing to its unique structure, the mesoporous g-CN functionalized with well dispersed catalytic Ag nanoparticles exhibits excellent sensitivity in the 11-98% RH range while retaining high stability, negligible hysteresis and superior real time %RH detection performances. Compared to conventional resistive sensors based on metal oxides, a rapid response time (3 s) and recovery time (1.4 s) were observed in the 11-98% RH range. Such impressive features originate from the planar morphology of g-CN as well as unique physical affinity and favourable electronic band positions of this material that facilitate water adsorption and charge transportation. Mesoporous g-CN with Ag nanoparticles is demonstrated to provide an effective strategy in designing high performance %RH sensors and show great promise for utilization of mesoporous 2D layered materials in the Internet of Things and next generation humidity sensing applications.

  6. Anti-phase domains in cubic GaN

    Energy Technology Data Exchange (ETDEWEB)

    Maria Kemper, Ricarda; Schupp, Thorsten; Haeberlen, Maik; Lindner, Joerg; Josef As, Donat [University of Paderborn, Department of Physics, Warburger Str. 100, D-33098 Paderborn (Germany); Niendorf, Thomas; Maier, Hans-Juergen [University of Paderborn, Lehrstuhl fuer Werkstoffkunde, Pohlweg 47-49, D-33098 Paderborn (Germany); Dempewolf, Anja; Bertram, Frank; Christen, Juergen [University of Magdeburg, Institut fuer Festkoerperphysik, P.O. Box 4120, D-39016 Magdeburg (Germany); Kirste, Ronny; Hoffmann, Axel [Technische Universitaet Berlin, Institute of Solid State Physics, Hardenbergstr. 36, D-10623 Berlin (Germany)

    2011-12-15

    The existence of anti-phase domains in cubic GaN grown on 3C-SiC/Si (001) substrates by plasma-assisted molecular beam epitaxy is reported. The influence of the 3C-SiC/Si (001) substrate morphology is studied with emphasis on the anti-phase domains (APDs). The GaN nucleation is governed by the APDs of the substrate, resulting in equal plane orientation and the same anti-phase boundaries. The presence of the APDs is independent of the GaN layer thickness. Atomic force microscopy surface analysis indicates lateral growth anisotropy of GaN facets in dependence of the APD orientation. This anisotropy can be linked to Ga and N face types of the {l_brace}111{r_brace} planes, similar to observations of anisotropic growth in 3C-SiC. In contrast to 3C-SiC, however, a difference in GaN phase composition for the two types of APDs can be measured by electron backscatter diffraction, {mu}-Raman and cathodoluminescence spectroscopy.

  7. Double-valued representations of the four-dimensional cubic lattice rotation group

    Energy Technology Data Exchange (ETDEWEB)

    Mandula, J.E.; Shpiz, E. (Washington Univ., St. Louis, MO (USA). Dept. of Physics)

    1984-01-23

    The double-valued representations of the rotation symmetry group of the four-dimensional cubic lattice are described. Their connections with double-valued representations of the three-dimensional cubic lattice rotation group and of the continuous O(3) and O(4) groups are given in detail.

  8. Double-valued representations of the four-dimensional cubic lattice rotation group

    Science.gov (United States)

    Mandula, Jeffrey E.; Shpiz, Edward

    1984-01-01

    The double-valued representations of the rotation symmetry group of the four-dimensional cubic lattice are described. Their connections with double-valued representations of the three-dimensional cubic lattice rotation group and of the continuous O(3) and O(4) groups are given in detail.

  9. Extending a Property of Cubic Polynomials to Higher-Degree Polynomials

    Science.gov (United States)

    Miller, David A.; Moseley, James

    2012-01-01

    In this paper, the authors examine a property that holds for all cubic polynomials given two zeros. This property is discovered after reviewing a variety of ways to determine the equation of a cubic polynomial given specific conditions through algebra and calculus. At the end of the article, they will connect the property to a very famous method…

  10. The double-end-pumped cubic Nd: YVO4 laser: Temperature ...

    Indian Academy of Sciences (India)

    2015-11-27

    Nov 27, 2015 ... Thermal effects of a double-end-pumped cubic Nd:YVO4 laser crystal are investigated in this paper. A detailed analysis of temperature distribution and thermal stress in cubic crystal with circular shape pumping is discussed. It has been shown that by considering the total input powers as constant, the ...

  11. On the dynamic buckling of a lightly damped elastic cubic model ...

    African Journals Online (AJOL)

    In this paper, we employ a generalization of Lindsted-Poincare technique to determine the dynamic buckling load of a lightly and viscously damped elastic cubic model structure modulated by a sinusoidally slowly varying dynamic load. The imperfect elastic cubic (nonlinear) structure is itself a generalization of most elastic ...

  12. Cubic Invariant Spherical Surface Harmonics in Conjunction With Diffraction Strain Pole-Figures

    NARCIS (Netherlands)

    Brakman, C.M.

    1986-01-01

    Four kinds of cubic invariant spherical surface harmonics are introduced. It has been shown previously that these harmonics occur in the equations relating measured diffraction (line-shift) elastic strain and macro-stresses generating these strains for the case of textured cubic materials. As a

  13. Defect structure of cubic solid solutions of alkaline earth and rare earth fluorides

    NARCIS (Netherlands)

    DenHartog, HW

    1996-01-01

    In this paper we will consider the disorder in some cubic solid solutions consisting of one of the alkaline earth fluorides and one of the rare earth fluorides. This is an attractive group of model materials, because these materials have a rather simple overall cubic structure. We will discuss the

  14. 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

  15. Numerical Modeling of the Stability of Face-Centered Cubic Metals with High Vacancy Concentration

    Energy Technology Data Exchange (ETDEWEB)

    Brian P. Somerday; M. I. Baskes

    1998-12-01

    The objective of this research is to assess the possibility of forming an atomically porous structure in a low-density metal, e.g., Al with vacancies up to 0.20/lattice site; and to examine the effects of hydrogen and vacancy concentration on the stability of an atomically porous structure that has been experimentally produced in nickel. The approach involves numerical modeling using the Embedded-Atom Method (EAM). High vacancy concentrations cause the Al lattice to disorder at 300K. In contrast, Ni retains the face-centered-cubic structure at 300K for vacancy concentrations up to 0.15 Vac/lattice site. Unexpectedly, the lattice with 0.15 Vac/lattice site is more stable than the lattice with 0.10 or 0.20 Vac/lattice site. The Ni systems with 0.10 and 0.15 Vac/lattice site exhibit domains consisting of uniform lattice rotations. The Ni lattice with 0.15 Vac/lattice site is more stable with an initial distribution of random vacancies compared to ordered vacancies. The equilibrium lattice structures of Ni a d Al containing vacancies and H are less ordered to structures with vacancies only at 300K.

  16. A smooth covariate rank transformation for use in regression models with a sigmoid dose–response function

    OpenAIRE

    Royston, Patrick

    2014-01-01

    We consider how to represent sigmoid-type regression relationships in a practical and parsimonious way. A pure sigmoid relationship has an asymptote at both ends of the range of a continuous covariate. Curves with a single asymptote are also important in practice. Many smoothers, such as fractional polynomials and restricted cubic regression splines, cannot accurately represent doubly asymptotic curves. Such smoothers may struggle even with singly asymptotic curves. Our approach to modeling s...

  17. A smooth covariate rank transformation for use in regression models with a sigmoid dose-response function

    OpenAIRE

    Royston, P

    2014-01-01

    We consider how to represent sigmoid-type regression relationships in a practical and parsimonious way. A pure sigmoid relationship has an asymptote at both ends of the range of a continuous covariate. Curves with a single asymptote are also important in practice. Many smoothers, such as fractional polynomials and restricted cubic regression splines, cannot accurately represent doubly asymptotic curves. Such smoothers may struggle even with singly asymptotic curves. Our approach to modeling s...

  18. Stochastic development regression using method of moments

    DEFF Research Database (Denmark)

    Kühnel, Line; Sommer, Stefan Horst

    2017-01-01

    This paper considers the estimation problem arising when inferring parameters in the stochastic development regression model for manifold valued non-linear data. Stochastic development regression captures the relation between manifold-valued response and Euclidean covariate variables using...... the stochastic development construction. It is thereby able to incorporate several covariate variables and random effects. The model is intrinsically defined using the connection of the manifold, and the use of stochastic development avoids linearizing the geometry. We propose to infer parameters using...... the Method of Moments procedure that matches known constraints on moments of the observations conditional on the latent variables. The performance of the model is investigated in a simulation example using data on finite dimensional landmark manifolds....

  19. Testing discontinuities in nonparametric regression

    KAUST Repository

    Dai, Wenlin

    2017-01-19

    In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100

  20. Logistic Regression: Concept and Application

    Science.gov (United States)

    Cokluk, Omay

    2010-01-01

    The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…

  1. Panel Smooth Transition Regression Models

    DEFF Research Database (Denmark)

    González, Andrés; Terasvirta, Timo; Dijk, Dick van

    We introduce the panel smooth transition regression model. This new model is intended for characterizing heterogeneous panels, allowing the regression coefficients to vary both across individuals and over time. Specifically, heterogeneity is allowed for by assuming that these coefficients are bou...

  2. Regression Discontinuity Design: Simulation and Application in Two Cardiovascular Trials with Continuous Outcomes

    NARCIS (Netherlands)

    van Leeuwen, Nikki; Lingsma, Hester F.; de Craen, Anton J. M.; Nieboer, Daan; Mooijaart, Simon P.; Richard, Edo; Steyerberg, Ewout W.

    2016-01-01

    In epidemiology, the regression discontinuity design has received increasing attention recently and might be an alternative to randomized controlled trials (RCTs) to evaluate treatment effects. In regression discontinuity, treatment is assigned above a certain threshold of an assignment variable for

  3. Study of nonlinear waves described by the cubic Schroedinger equation

    Energy Technology Data Exchange (ETDEWEB)

    Walstead, A.E.

    1980-03-12

    The cubic Schroedinger equation (CSE) is ubiquitous as a model equation for the long-time evolution of finite-amplitude near-monochromatic dispersive waves. It incorporates the effects of the radiation field pressure on the constitutive properties of the supporting medium in a self-consistent manner. The properties of the uniformly transiating periodic wave solutions of the one-dimensional CSE are studied here. These (so-called cnoidal) waves are characterized by the values of four parameters. Whitham's averaged variational principle is used to derive a system of quasilinear evolution equations (the modulational equations) for the values of these parameters when they are slowly varying in space and time. Explicit expressions for the characteristic velocities of the modulational equations are obtained for the full set of cnoidal waves. Riemann invariants are obtained for several limits for the stable case, and growth rates are obtained for several limits, including the solitary wave chain, for the unstable case. The results for several nontrivial limiting cases agree with those obtained by independent methods by others. The dynamics of the CSE generalized to two spatial dimensions are studied for the unstable case. A large class of similarity solutions with cylindrical symmetry are obtained systematically using infinitesimal transformation group techniques. The methods are adapted to obtain the symmetries of the action functional of the CSE and to deduce nine integral invariants. A numerical study of the self-similar solutions reveals that they are modulationally unstable and that singularities dominate the dynamics of the CSE in two dimensions. The CSE is derived using perturbation theory for a specific problem in plasma physics: the evolution of the envelope of a near-monochromatic electromagnetic wave in a cold magnetized plasma. 13 figures, 2 tables.

  4. Cubic time algorithms of amalgamating gene trees and building evolutionary scenarios

    Science.gov (United States)

    2012-01-01

    Background A long recognized problem is the inference of the supertree S that amalgamates a given set {Gj} of trees Gj, with leaves in each Gj being assigned homologous elements. We ground on an approach to find the tree S by minimizing the total cost of mappings αj of individual gene trees Gj into S. Traditionally, this cost is defined basically as a sum of duplications and gaps in each αj. The classical problem is to minimize the total cost, where S runs over the set of all trees that contain an exhaustive non-redundant set of species from all input Gj. Results We suggest a reformulation of the classical NP-hard problem of building a supertree in terms of the global minimization of the same cost functional but only over species trees S that consist of clades belonging to a fixed set P (e.g., an exhaustive set of clades in all Gj). We developed a deterministic solving algorithm with a low degree polynomial (typically cubic) time complexity with respect to the size of input data. We define an extensive set of elementary evolutionary events and suggest an original definition of mapping β of tree G into tree S. We introduce the cost functional c(G, S, f ) and define the mapping β as the global minimum of this functional with respect to the variable f, in which sense it is a generalization of classical mapping α. We suggest a reformulation of the classical NP-hard mapping (reconciliation) problem by introducing time slices into the species tree S and present a cubic time solving algorithm to compute the mapping β. We introduce two novel definitions of the evolutionary scenario based on mapping β or a random process of gene evolution along a species tree. Conclusions Developed algorithms are mathematically proved, which justifies the following statements. The supertree building algorithm finds exactly the global minimum of the total cost if only gene duplications and losses are allowed and the given sets of gene trees satisfies a certain condition. The mapping

  5. Regression analysis with categorized regression calibrated exposure: some interesting findings

    Directory of Open Access Journals (Sweden)

    Hjartåker Anette

    2006-07-01

    Full Text Available Abstract Background Regression calibration as a method for handling measurement error is becoming increasingly well-known and used in epidemiologic research. However, the standard version of the method is not appropriate for exposure analyzed on a categorical (e.g. quintile scale, an approach commonly used in epidemiologic studies. A tempting solution could then be to use the predicted continuous exposure obtained through the regression calibration method and treat it as an approximation to the true exposure, that is, include the categorized calibrated exposure in the main regression analysis. Methods We use semi-analytical calculations and simulations to evaluate the performance of the proposed approach compared to the naive approach of not correcting for measurement error, in situations where analyses are performed on quintile scale and when incorporating the original scale into the categorical variables, respectively. We also present analyses of real data, containing measures of folate intake and depression, from the Norwegian Women and Cancer study (NOWAC. Results In cases where extra information is available through replicated measurements and not validation data, regression calibration does not maintain important qualities of the true exposure distribution, thus estimates of variance and percentiles can be severely biased. We show that the outlined approach maintains much, in some cases all, of the misclassification found in the observed exposure. For that reason, regression analysis with the corrected variable included on a categorical scale is still biased. In some cases the corrected estimates are analytically equal to those obtained by the naive approach. Regression calibration is however vastly superior to the naive method when applying the medians of each category in the analysis. Conclusion Regression calibration in its most well-known form is not appropriate for measurement error correction when the exposure is analyzed on a

  6. Advanced statistics: linear regression, part II: multiple linear regression.

    Science.gov (United States)

    Marill, Keith A

    2004-01-01

    The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

  7. Logic regression and its extensions.

    Science.gov (United States)

    Schwender, Holger; Ruczinski, Ingo

    2010-01-01

    Logic regression is an adaptive classification and regression procedure, initially developed to reveal interacting single nucleotide polymorphisms (SNPs) in genetic association studies. In general, this approach can be used in any setting with binary predictors, when the interaction of these covariates is of primary interest. Logic regression searches for Boolean (logic) combinations of binary variables that best explain the variability in the outcome variable, and thus, reveals variables and interactions that are associated with the response and/or have predictive capabilities. The logic expressions are embedded in a generalized linear regression framework, and thus, logic regression can handle a variety of outcome types, such as binary responses in case-control studies, numeric responses, and time-to-event data. In this chapter, we provide an introduction to the logic regression methodology, list some applications in public health and medicine, and summarize some of the direct extensions and modifications of logic regression that have been proposed in the literature. Copyright © 2010 Elsevier Inc. All rights reserved.

  8. Application of random regression models to the genetic evaluation ...

    African Journals Online (AJOL)

    Estimates of genetic correlations were greater than 0.82 among measures of weight at all ages. The resulting covariance functions were used to estimate breeding values of each animal along the age trajectory. Genetic trends for CW over the years showed only a slightly increasing pattern, suggesting that CW did not ...

  9. Covariance Functions and Random Regression Models in the ...

    African Journals Online (AJOL)

    ARC-IRENE

    Since its inception the application of genetic principles to selective breeding of farm animals has led ... animal increases in size or weight continuously over time until reaching a plateau at maturity. Such a process .... where A and I are the numerator relationship matrix and an identity matrix, respectively; KG and KC are the.

  10. Covariance Functions and Random Regression Models in the ...

    African Journals Online (AJOL)

    ARC-IRENE

    many, highly correlated measures (Meyer, 1998a). Several approaches have been proposed to deal with such data, from simplest repeatability models (SRM) to complex multivariate models (MTM). The SRM considers different measurements at different stages (ages) as a realization of the same genetic trait with constant.

  11. Evaluation of Development Programs: Randomized Controlled Trials or Regressions?

    NARCIS (Netherlands)

    Elbers, C.T.M.; Gunning, J.W.

    2014-01-01

    Can project evaluation methods be used to evaluate programs: complex interventions involving multiple activities? A program evaluation cannot be based simply on separate evaluations of its components if interactions between the activities are important. In this paper a measure is proposed, the total

  12. Practical Session: Simple Linear Regression

    Science.gov (United States)

    Clausel, M.; Grégoire, G.

    2014-12-01

    Two exercises are proposed to illustrate the simple linear regression. The first one is based on the famous Galton's data set on heredity. We use the lm R command and get coefficients estimates, standard error of the error, R2, residuals …In the second example, devoted to data related to the vapor tension of mercury, we fit a simple linear regression, predict values, and anticipate on multiple linear regression. This pratical session is an excerpt from practical exercises proposed by A. Dalalyan at EPNC (see Exercises 1 and 2 of http://certis.enpc.fr/~dalalyan/Download/TP_ENPC_4.pdf).

  13. NC-TODIM-Based MAGDM under a Neutrosophic Cubic Set Environment

    Directory of Open Access Journals (Sweden)

    Surapati Pramanik

    2017-11-01

    Full Text Available A neutrosophic cubic set is the hybridization of the concept of a neutrosophic set and an interval neutrosophic set. A neutrosophic cubic set has the capacity to express the hybrid information of both the interval neutrosophic set and the single valued neutrosophic set simultaneously. As newly defined, little research on the operations and applications of neutrosophic cubic sets has been reported in the current literature. In the present paper, we propose the score and accuracy functions for neutrosophic cubic sets and prove their basic properties. We also develop a strategy for ranking of neutrosophic cubic numbers based on the score and accuracy functions. We firstly develop a TODIM (Tomada de decisao interativa e multicritévio in the neutrosophic cubic set (NC environment, which we call the NC-TODIM. We establish a new NC-TODIM strategy for solving multi attribute group decision making (MAGDM in neutrosophic cubic set environment. We illustrate the proposed NC-TODIM strategy for solving a multi attribute group decision making problem to show the applicability and effectiveness of the developed strategy. We also conduct sensitivity analysis to show the impact of ranking order of the alternatives for different values of the attenuation factor of losses for multi-attribute group decision making strategies.

  14. Fractional random walk lattice dynamics

    Science.gov (United States)

    Michelitsch, T. M.; Collet, B. A.; Riascos, A. P.; Nowakowski, A. F.; Nicolleau, F. C. G. A.

    2017-02-01

    We analyze time-discrete and time-continuous ‘fractional’ random walks on undirected regular networks with special focus on cubic periodic lattices in n  =  1, 2, 3,.. dimensions. The fractional random walk dynamics is governed by a master equation involving fractional powers of Laplacian matrices {{L}\\fracα{2}}} where α =2 recovers the normal walk. First we demonstrate that the interval 0<α ≤slant 2 is admissible for the fractional random walk. We derive analytical expressions for the transition matrix of the fractional random walk and closely related the average return probabilities. We further obtain the fundamental matrix {{Z}(α )} , and the mean relaxation time (Kemeny constant) for the fractional random walk. The representation for the fundamental matrix {{Z}(α )} relates fractional random walks with normal random walks. We show that the matrix elements of the transition matrix of the fractional random walk exihibit for large cubic n-dimensional lattices a power law decay of an n-dimensional infinite space Riesz fractional derivative type indicating emergence of Lévy flights. As a further footprint of Lévy flights in the n-dimensional space, the transition matrix and return probabilities of the fractional random walk are dominated for large times t by slowly relaxing long-wave modes leading to a characteristic {{t}-\\frac{n{α}} -decay. It can be concluded that, due to long range moves of fractional random walk, a small world property is emerging increasing the efficiency to explore the lattice when instead of a normal random walk a fractional random walk is chosen.

  15. Multiple Regression and Its Discontents

    Science.gov (United States)

    Snell, Joel C.; Marsh, Mitchell

    2012-01-01

    Multiple regression is part of a larger statistical strategy originated by Gauss. The authors raise questions about the theory and suggest some changes that would make room for Mandelbrot and Serendipity.

  16. A generalized cubic Volterra lattice hierarchy and its integrable couplings system

    Energy Technology Data Exchange (ETDEWEB)

    Xia Tiecheng [Department of Mathematics, Shanghai University, Shanghai 200444 (China); Department of Mathematics, Bohai University, Jinzhou of Liaoning Province 121000 (China); Department of Mathematics, Tianjin University, Tianjin 300072 (China); E-mail: xiatc@yahoo.com.cn; You Fucai [Department of Mathematics, Bohai University, Jinzhou of Liaoning Province 121000 (China); Chen Dengyuan [Department of Mathematics, Shanghai University, Shanghai 200444 (China)

    2006-01-01

    In terms of properties of the known loop algebra A{approx}{sub 1} and difference operators, a new algebraic system {chi} is constructed. By using the algebraic system {chi}, a discrete matrix spectral problem is introduced and a hierarchy of nonlinear lattice equations is derived. From the hierarchy the celebrated cubic Volterra lattice equation is engendered. We call the hierarchy a generalized cubic Volterra hierarchy. Then an extended algebraic system {chi}-bar of {chi} is presented, from which the integrable couplings system of the generalized cubic Volterra lattice are obtained.

  17. Chiral Surface Twists and Skyrmion Stability in Nanolayers of Cubic Helimagnets.

    Science.gov (United States)

    Leonov, A O; Togawa, Y; Monchesky, T L; Bogdanov, A N; Kishine, J; Kousaka, Y; Miyagawa, M; Koyama, T; Akimitsu, J; Koyama, Ts; Harada, K; Mori, S; McGrouther, D; Lamb, R; Krajnak, M; McVitie, S; Stamps, R L; Inoue, K

    2016-08-19

    Theoretical analysis and Lorentz transmission electron microscopy (LTEM) investigations in an FeGe wedge demonstrate that chiral twists arising near the surfaces of noncentrosymmetric ferromagnets [Meynell et al., Phys. Rev. B 90, 014406 (2014)] provide a stabilization mechanism for magnetic Skyrmion lattices and helicoids in cubic helimagnet nanolayers. The magnetic phase diagram obtained for freestanding cubic helimagnet nanolayers shows that magnetization processes differ fundamentally from those in bulk cubic helimagnets and are characterized by the first-order transitions between modulated phases. LTEM investigations exhibit a series of hysteretic transformation processes among the modulated phases, which results in the formation of the multidomain patterns.

  18. Regression methods for medical research

    CERN Document Server

    Tai, Bee Choo

    2013-01-01

    Regression Methods for Medical Research provides medical researchers with the skills they need to critically read and interpret research using more advanced statistical methods. The statistical requirements of interpreting and publishing in medical journals, together with rapid changes in science and technology, increasingly demands an understanding of more complex and sophisticated analytic procedures.The text explains the application of statistical models to a wide variety of practical medical investigative studies and clinical trials. Regression methods are used to appropriately answer the

  19. Forecasting with Dynamic Regression Models

    CERN Document Server

    Pankratz, Alan

    2012-01-01

    One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.

  20. Linear and logistic regression analysis

    NARCIS (Netherlands)

    Tripepi, G.; Jager, K. J.; Dekker, F. W.; Zoccali, C.

    2008-01-01

    In previous articles of this series, we focused on relative risks and odds ratios as measures of effect to assess the relationship between exposure to risk factors and clinical outcomes and on control for confounding. In randomized clinical trials, the random allocation of patients is hoped to

  1. Dislocation Velocities and Dislocation Structure in Cubic Zirconia and Sapphire

    Science.gov (United States)

    Farber, Boris Yarovlevick

    The dislocation structure around elevated temperature indentations in 9.4 and 21 mol% rm Y_2O _3 fully-stabilized cubic ZrO_2 (c-ZrO_2) was investigated using selective etching and transmission electron microscopy (TEM). Cracking arising from interaction between slip bands was observed in the 21 mol% rm Y_2O _3 material, and direct evidence of the formation of Lomer type dislocation pile-ups leading to crack nucleation was obtained by TEM. Stress and temperature dependencies of the edge and screw dislocation velocities in c-ZrO_2 were measured. The activation energy for motion of the edge dislocations (5.0 +/- 0.4 eV) is slightly lower than that for screw dislocations (5.6 +/- 0.6 eV). The stress exponent (m) is close to 1 at low temperatures (stress relaxation in the vicinity of room temperature Knoop indents in c-ZrO_2 was investigated using photoelasticity method. A rapid low temperature stress relaxation was observed, and a mechanism was proposed. The temperature dependence of the Vickers hardness was measured on the basal (0001} and pyramidal {11|23} planes of single crystal alpha -Al_2O_3 (sapphire) from room temperature to 1273 K. The plastic zone surrounding the indents was investigated using selective etching and TEM. Indentation was accompanied by three competitive damage processes: fracture, twinning and dislocation plasticity. At room temperature, cracking predominated. At intermediate temperatures, extensive rhombohedral twinning was observed, while at higher temperatures, prismatic slip bands on {11|20} dominated the microstructure. The dislocation substructure at the vicinity of the indents consists of fairly straight dislocations lying on basal and/or prism planes and aligned along crystallographic directions. The details of the glide dissociation of perfect screw dislocations into three collinear partials, the mechanism of the microplasticity of sapphire single crystals, and details of the Peierls potential are discussed. An anomalously high low

  2. Use of the Primitive Unit Cell in Understanding Subtle Features of the Cubic Closest-Packed Structure

    Science.gov (United States)

    Hawkins, John A.; Rittenhouse, Jeffrey L.; Soper, Linda M.; Rittenhouse, Robert C.

    2008-01-01

    One of the most important crystal structures adopted by metals is characterized by the "abcabc"...stacking of close-packed layers. This structure is commonly referred to in textbooks as the cubic close-packed (ccp) or face-centered cubic (fcc) structure, since the entire lattice can be generated by replication of a face-centered cubic unit cell…

  3. Exact diagonalization of cubic lattice models in commensurate Abelian magnetic fluxes and translational invariant non-Abelian potentials

    Science.gov (United States)

    Burrello, M.; Fulga, I. C.; Lepori, L.; Trombettoni, A.

    2017-11-01

    We present a general analytical formalism to determine the energy spectrum of a quantum particle in a cubic lattice subject to translationally invariant commensurate magnetic fluxes and in the presence of a general space-independent non-Abelian gauge potential. We first review and analyze the case of purely Abelian potentials, showing also that the so-called Hasegawa gauge yields a decomposition of the Hamiltonian into sub-matrices having minimal dimension. Explicit expressions for such matrices are derived, also for general anisotropic fluxes. Later on, we show that the introduction of a translational invariant non-Abelian coupling for multi-component spinors does not affect the dimension of the minimal Hamiltonian blocks, nor the dimension of the magnetic Brillouin zone. General formulas are presented for the U(2) case and explicit examples are investigated involving π and 2π/3 magnetic fluxes. Finally, we numerically study the effect of random flux perturbations.

  4. Epitaxial growth and properties of cubic group III-nitride layers

    Science.gov (United States)

    Schikora, D.; Schoettger, B.; As, Donat J.; Lischka, K.

    1997-06-01

    Single-phase cubic GaN and InN layers are grown by plasma assisted MBE. The temperature-dependence of the surface reconstruction is elaborated. The structural stability of the cubic growth in dependence of the growth stoichiometry is studied by RHEED measurements and numerical simulations of the experimental RHEED patterns. Growth oscillations on cubic GaN and during the growth of GaN-InN single quantum wells are recorded at nearly stoichiometric adatom coverage. Photoluminescence reveals the dominant optical transitions of cubic GaN and InN. Using in-situ RHEED to control the surface stoichiometry it is possible to grow N-stabilized layers resulting in intrinsic p-type GaN epilayers with hole concentrations of about p equals 1 X 1013 cm-3 and mobilities of about (mu) p equals 320 cm2/Vs, respectively.

  5. CHARACTERIZATION OF PRECIPITATES IN CUBIC SILICON CARBIDE IMPLANTED WITH 25Mg+ IONS

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Weilin; Spurgeon, Steven R.; Liu, Jia; Edwards, Danny J.; Schreiber, Daniel K.; Henager, Charles H.; Kurtz, Richard J.; Wang, Yongqiang

    2016-09-26

    The aim of this study is to characterize precipitates in Mg+ ion implanted and high-temperature annealed cubic silicon carbide using scanning transmission electron microscopy, electron energy loss spectroscopy and atom probe tomography.

  6. Unified treatment of coupled optical and acoustic phonons in piezoelectric cubic materials

    DEFF Research Database (Denmark)

    Willatzen, Morten; Wang, Zhong Lin

    2015-01-01

    A unified treatment of coupled optical and acoustic phonons in piezoelectric cubic materials is presented whereby the lattice displacement vector and the internal ionic displacement vector are found simultaneously. It is shown that phonon couplings exist in pairs only; either between the electric...... potential and the lattice displacement coordinate perpendicular to the phonon wave vector or between the two other lattice displacement components. The former leads to coupled acousto-optical phonons by virtue of the piezoelectric effect. We then establish three new conjectures that entirely stem from...... piezoelectricity in a cubic structured material slab. First, it is shown that isolated optical phonon modes generally cannot exist in piezoelectric cubic slabs. Second, we prove that confined acousto-optical phonon modes only exist for a discrete set of in-plane wave numbers in piezoelectric cubic slabs. Third...

  7. Three-dimensional unsteady natural convection and entropy generation in an inclined cubical trapezoidal cavity with

    National Research Council Canada - National Science Library

    Ahmed Kadhim Hussein; Kolsi Lioua; Ramesh Chand; S. Sivasankaran; Rasoul Nikbakhti; Dong Li; Borjini Mohamed Naceur; Ben Aïssia Habib

    2016-01-01

    Numerical computation of unsteady laminar three-dimensional natural convection and entropy generation in an inclined cubical trapezoidal air-filled cavity is performed for the first time in this work...

  8. Cubic membranes: a legend beyond the Flatland* of cell membrane organization.

    Science.gov (United States)

    Almsherqi, Zakaria A; Kohlwein, Sepp D; Deng, Yuru

    2006-06-19

    Cubic membranes represent highly curved, three-dimensional nanoperiodic structures that correspond to mathematically well defined triply periodic minimal surfaces. Although they have been observed in numerous cell types and under different conditions, particularly in stressed, diseased, or virally infected cells, knowledge about the formation and function of nonlamellar, cubic structures in biological systems is scarce, and research so far is restricted to the descriptive level. We show that the "organized smooth endoplasmic reticulum" (OSER; Snapp, E.L., R.S. Hegde, M. Francolini, F. Lombardo, S. Colombo, E. Pedrazzini, N. Borgese, and J. Lippincott-Schwartz. 2003. J. Cell Biol. 163:257-269), which is formed in response to elevated levels of specific membrane-resident proteins, is actually the two-dimensional representation of two subtypes of cubic membrane morphology. Controlled OSER induction may thus provide, for the first time, a valuable tool to study cubic membrane formation and function at the molecular level.

  9. Numerical treatment of Hunter Saxton equation using cubic trigonometric B-spline collocation method

    Science.gov (United States)

    Hashmi, M. S.; Awais, Muhammad; Waheed, Ammarah; Ali, Qutab

    2017-09-01

    In this article, authors proposed a computational model based on cubic trigonometric B-spline collocation method to solve Hunter Saxton equation. The nonlinear second order partial differential equation arises in modeling of nematic liquid crystals and describes some aspects of orientation wave. The problem is decomposed into system of linear equations using cubic trigonometric B-spline collocation method with quasilinearization. To show the efficiency of the proposed method, two numerical examples have been tested for different values of t. The results are described using error tables and graphs and compared with the results existed in literature. It is evident that results are in good agreement with analytical solution and better than Arbabi, Nazari, and Davishi, Optik 127, 5255-5258 (2016). In current problem, it is also observed that the cubic trigonometric B-spline gives better results as compared to cubic B-spline.

  10. Hypothesis Testing of Parameters for Ordinary Linear Circular Regression

    Directory of Open Access Journals (Sweden)

    Abdul Ghapor Hussin

    2006-07-01

    Full Text Available This paper presents the hypothesis testing of parameters for ordinary linear circular regression model assuming the circular random error distributed as von Misses distribution. The main interests are in testing of the intercept and slope parameter of the regression line. As an illustration, this hypothesis testing will be used in analyzing the wind and wave direction data recorded by two different techniques which are HF radar system and anchored wave buoy.

  11. Quantitative determination of hexagonal minority phase in cubic GaN using Raman spectroscopy

    Science.gov (United States)

    Siegle, H.; Eckey, L.; Hoffmann, A.; Thomsen, C.; Meyer, B. K.; Schikora, D.; Hankeln, M.; Lischka, K.

    1995-12-01

    We show that Raman scattering is a very sensitive and straightforward tool for the quantitative determination of a structural minority phase in GaN. In- and on-plane excitations, as well as polarization dependent measurements on predominantly cubic and hexagonal GaN samples, were performed and forward scattering effects were found. We were able to verify as an example the phase purity of a cubic GaN sample down to the 1% level.

  12. Cubic and quartic planar differential systems with exact algebraic limit cycles

    Directory of Open Access Journals (Sweden)

    Ahmed Bendjeddou

    2011-01-01

    Full Text Available We construct cubic and quartic polynomial planar differential systems with exact limit cycles that are ovals of algebraic real curves of degree four. The result obtained for the cubic case generalizes a proposition of [9]. For the quartic case, we deduce for the first time a class of systems with four algebraic limit cycles and another for which nested configurations of limit cycles occur.

  13. Inferential Models for Linear Regression

    Directory of Open Access Journals (Sweden)

    Zuoyi Zhang

    2011-09-01

    Full Text Available Linear regression is arguably one of the most widely used statistical methods in applications.  However, important problems, especially variable selection, remain a challenge for classical modes of inference.  This paper develops a recently proposed framework of inferential models (IMs in the linear regression context.  In general, an IM is able to produce meaningful probabilistic summaries of the statistical evidence for and against assertions about the unknown parameter of interest and, moreover, these summaries are shown to be properly calibrated in a frequentist sense.  Here we demonstrate, using simple examples, that the IM framework is promising for linear regression analysis --- including model checking, variable selection, and prediction --- and for uncertain inference in general.

  14. Selective Chemical Vapor Deposition Growth of Cubic FeGe Nanowires That Support Stabilized Magnetic Skyrmions.

    Science.gov (United States)

    Stolt, Matthew J; Li, Zi-An; Phillips, Brandon; Song, Dongsheng; Mathur, Nitish; Dunin-Borkowski, Rafal E; Jin, Song

    2017-01-11

    Magnetic skyrmions are topologically stable vortex-like spin structures that are promising for next generation information storage applications. Materials that host magnetic skyrmions, such as MnSi and FeGe with the noncentrosymmetric cubic B20 crystal structure, have been shown to stabilize skyrmions upon nanostructuring. Here, we report a chemical vapor deposition method to selectively grow nanowires (NWs) of cubic FeGe out of three possible FeGe polymorphs for the first time using finely ground particles of cubic FeGe as seeds. X-ray diffraction and transmission electron microscopy (TEM) confirm that these micron-length NWs with ∼100 nm to 1 μm diameters have the cubic B20 crystal structure. Although Fe 13 Ge 8 NWs are also formed, the two types of NWs can be readily differentiated by their faceting. Lorentz TEM imaging of the cubic FeGe NWs reveals a skyrmion lattice phase under small applied magnetic fields (∼0.1 T) at 233 K, a skyrmion chain state at lower temperatures (95 K) and under high magnetic fields (∼0.4 T), and a larger skyrmion stability window than bulk FeGe. This synthetic approach to cubic FeGe NWs that support stabilized skyrmions opens a route toward the exploration of new skyrmion physics and devices based on similar nanostructures.

  15. A Matlab program for stepwise regression

    Directory of Open Access Journals (Sweden)

    Yanhong Qi

    2016-03-01

    Full Text Available The stepwise linear regression is a multi-variable regression for identifying statistically significant variables in the linear regression equation. In present study, we presented the Matlab program of stepwise regression.

  16. Logistic regression for circular data

    Science.gov (United States)

    Al-Daffaie, Kadhem; Khan, Shahjahan

    2017-05-01

    This paper considers the relationship between a binary response and a circular predictor. It develops the logistic regression model by employing the linear-circular regression approach. The maximum likelihood method is used to estimate the parameters. The Newton-Raphson numerical method is used to find the estimated values of the parameters. A data set from weather records of Toowoomba city is analysed by the proposed methods. Moreover, a simulation study is considered. The R software is used for all computations and simulations.

  17. Quasi-least squares regression

    CERN Document Server

    Shults, Justine

    2014-01-01

    Drawing on the authors' substantial expertise in modeling longitudinal and clustered data, Quasi-Least Squares Regression provides a thorough treatment of quasi-least squares (QLS) regression-a computational approach for the estimation of correlation parameters within the framework of generalized estimating equations (GEEs). The authors present a detailed evaluation of QLS methodology, demonstrating the advantages of QLS in comparison with alternative methods. They describe how QLS can be used to extend the application of the traditional GEE approach to the analysis of unequally spaced longitu

  18. Biplots in Reduced-Rank Regression

    NARCIS (Netherlands)

    Braak, ter C.J.F.; Looman, C.W.N.

    1994-01-01

    Regression problems with a number of related response variables are typically analyzed by separate multiple regressions. This paper shows how these regressions can be visualized jointly in a biplot based on reduced-rank regression. Reduced-rank regression combines multiple regression and principal

  19. Growth Regression and Economic Theory

    NARCIS (Netherlands)

    Elbers, Chris; Gunning, Jan Willem

    2002-01-01

    In this note we show that the standard, loglinear growth regression specificationis consistent with one and only one model in the class of stochastic Ramsey models. Thismodel is highly restrictive: it requires a Cobb-Douglas technology and a 100% depreciationrate and it implies that risk does not

  20. Regression of lumbar disk herniation

    Directory of Open Access Journals (Sweden)

    G. Yu Evzikov

    2015-01-01

    Full Text Available Compression of the spinal nerve root, giving rise to pain and sensory and motor disorders in the area of its innervation is the most vivid manifestation of herniated intervertebral disk. Different treatment modalities, including neurosurgery, for evolving these conditions are discussed. There has been recent evidence that spontaneous regression of disk herniation can regress. The paper describes a female patient with large lateralized disc extrusion that has caused compression of the nerve root S1, leading to obvious myotonic and radicular syndrome. Magnetic resonance imaging has shown that the clinical manifestations of discogenic radiculopathy, as well myotonic syndrome and morphological changes completely regressed 8 months later. The likely mechanism is inflammation-induced resorption of a large herniated disk fragment, which agrees with the data available in the literature. A decision to perform neurosurgery for which the patient had indications was made during her first consultation. After regression of discogenic radiculopathy, there was only moderate pain caused by musculoskeletal diseases (facet syndrome, piriformis syndrome that were successfully eliminated by minimally invasive techniques. 

  1. Claim reserving with fuzzy regression

    OpenAIRE

    Bahrami, Tahereh; BAHRAMI, Masuod

    2015-01-01

    Abstract. Claims reserving plays a key role for the insurance. Therefore, various statistical methods are used to provide for an adequate amount of claim reserves. Since claim reserves are always variable, fuzzy set theory is used to handle this variability. In this paper, non-symmetric fuzzy regression is integrated in the Taylor’s method to develop a new method for claim reserving.

  2. Multimodality in GARCH regression models

    NARCIS (Netherlands)

    Ooms, M.; Doornik, J.A.

    2008-01-01

    It is shown empirically that mixed autoregressive moving average regression models with generalized autoregressive conditional heteroskedasticity (Reg-ARMA-GARCH models) can have multimodality in the likelihood that is caused by a dummy variable in the conditional mean. Maximum likelihood estimates

  3. Fungible Weights in Multiple Regression

    Science.gov (United States)

    Waller, Niels G.

    2008-01-01

    Every set of alternate weights (i.e., nonleast squares weights) in a multiple regression analysis with three or more predictors is associated with an infinite class of weights. All members of a given class can be deemed "fungible" because they yield identical "SSE" (sum of squared errors) and R[superscript 2] values. Equations for generating…

  4. On Weighted Support Vector Regression

    DEFF Research Database (Denmark)

    Han, Xixuan; Clemmensen, Line Katrine Harder

    2014-01-01

    We propose a new type of weighted support vector regression (SVR), motivated by modeling local dependencies in time and space in prediction of house prices. The classic weights of the weighted SVR are added to the slack variables in the objective function (OF‐weights). This procedure directly...

  5. PROBIT REGRESSION IN PREDICTION ANALYSIS

    African Journals Online (AJOL)

    Admin

    2008-12-12

    Dec 12, 2008 ... GLOBAL JOURNAL OF MATHEMATICAL SCIENCES VOL. ... INTRODUCTION. For some dichotomous variables, the response y is actually a proxy for a variable that is continuous (Newsom, 2005). A regression ... M. E. Nja, Dept. of Mathematics / Statistics Cross River University of Technology, Calabar ...

  6. Ridge Regression for Interactive Models.

    Science.gov (United States)

    Tate, Richard L.

    1988-01-01

    An exploratory study of the value of ridge regression for interactive models is reported. Assuming that the linear terms in a simple interactive model are centered to eliminate non-essential multicollinearity, a variety of common models, representing both ordinal and disordinal interactions, are shown to have "orientations" that are…

  7. Logistic regression: a brief primer.

    Science.gov (United States)

    Stoltzfus, Jill C

    2011-10-01

    Regression techniques are versatile in their application to medical research because they can measure associations, predict outcomes, and control for confounding variable effects. As one such technique, logistic regression is an efficient and powerful way to analyze the effect of a group of independent variables on a binary outcome by quantifying each independent variable's unique contribution. Using components of linear regression reflected in the logit scale, logistic regression iteratively identifies the strongest linear combination of variables with the greatest probability of detecting the observed outcome. Important considerations when conducting logistic regression include selecting independent variables, ensuring that relevant assumptions are met, and choosing an appropriate model building strategy. For independent variable selection, one should be guided by such factors as accepted theory, previous empirical investigations, clinical considerations, and univariate statistical analyses, with acknowledgement of potential confounding variables that should be accounted for. Basic assumptions that must be met for logistic regression include independence of errors, linearity in the logit for continuous variables, absence of multicollinearity, and lack of strongly influential outliers. Additionally, there should be an adequate number of events per independent variable to avoid an overfit model, with commonly recommended minimum "rules of thumb" ranging from 10 to 20 events per covariate. Regarding model building strategies, the three general types are direct/standard, sequential/hierarchical, and stepwise/statistical, with each having a different emphasis and purpose. Before reaching definitive conclusions from the results of any of these methods, one should formally quantify the model's internal validity (i.e., replicability within the same data set) and external validity (i.e., generalizability beyond the current sample). The resulting logistic regression model

  8. Hierarchical Adaptive Regression Kernels for Regression with Functional Predictors.

    Science.gov (United States)

    Woodard, Dawn B; Crainiceanu, Ciprian; Ruppert, David

    2013-01-01

    We propose a new method for regression using a parsimonious and scientifically interpretable representation of functional predictors. Our approach is designed for data that exhibit features such as spikes, dips, and plateaus whose frequency, location, size, and shape varies stochastically across subjects. We propose Bayesian inference of the joint functional and exposure models, and give a method for efficient computation. We contrast our approach with existing state-of-the-art methods for regression with functional predictors, and show that our method is more effective and efficient for data that include features occurring at varying locations. We apply our methodology to a large and complex dataset from the Sleep Heart Health Study, to quantify the association between sleep characteristics and health outcomes. Software and technical appendices are provided in online supplemental materials.

  9. Investigating the Accuracy of Three Estimation Methods for Regression Discontinuity Design

    Science.gov (United States)

    Sun, Shuyan; Pan, Wei

    2013-01-01

    Regression discontinuity design is an alternative to randomized experiments to make causal inference when random assignment is not possible. This article first presents the formal identification and estimation of regression discontinuity treatment effects in the framework of Rubin's causal model, followed by a thorough literature review of…

  10. Least-squares regression of adsorption equilibrium data: comparing the options.

    Science.gov (United States)

    El-Khaiary, Mohammad I

    2008-10-01

    Experimental and simulated adsorption equilibrium data were analyzed by different methods of least-squares regression. The methods used were linear regression, nonlinear regression, and orthogonal distance regression. The results of the regression analysis of the experimental data showed that the different regression methods produced different estimates of the adsorption isotherm parameters, and consequently, different conclusions about the surface properties of the adsorbent and the mechanism of adsorption. A Langmuir-type simulated data set was calculated and several levels of random error were added to the data set. The results of regression analysis of the simulated data set showed that orthogonal distance regression gives the most accurate and efficient estimates of the isotherm parameters. Nonlinear regression and one form of the linearized Langmuir isotherm also gave accurate estimates, but only at low levels of random error.

  11. Hierarchical Adaptive Regression Kernels for Regression with Functional Predictors

    OpenAIRE

    Woodard, Dawn B.; Crainiceanu, Ciprian; Ruppert, David

    2013-01-01

    We propose a new method for regression using a parsimonious and scientifically interpretable representation of functional predictors. Our approach is designed for data that exhibit features such as spikes, dips, and plateaus whose frequency, location, size, and shape varies stochastically across subjects. We propose Bayesian inference of the joint functional and exposure models, and give a method for efficient computation. We contrast our approach with existing state-of-the-art methods for re...

  12. A Monte Carlo simulation study comparing linear regression, beta regression, variable-dispersion beta regression and fractional logit regression at recovering average difference measures in a two sample design.

    Science.gov (United States)

    Meaney, Christopher; Moineddin, Rahim

    2014-01-24

    In biomedical research, response variables are often encountered which have bounded support on the open unit interval--(0,1). Traditionally, researchers have attempted to estimate covariate effects on these types of response data using linear regression. Alternative modelling strategies may include: beta regression, variable-dispersion beta regression, and fractional logit regression models. This study employs a Monte Carlo simulation design to compare the statistical properties of the linear regression model to that of the more novel beta regression, variable-dispersion beta regression, and fractional logit regression models. In the Monte Carlo experiment we assume a simple two sample design. We assume observations are realizations of independent draws from their respective probability models. The randomly simulated draws from the various probability models are chosen to emulate average proportion/percentage/rate differences of pre-specified magnitudes. Following simulation of the experimental data we estimate average proportion/percentage/rate differences. We compare the estimators in terms of bias, variance, type-1 error and power. Estimates of Monte Carlo error associated with these quantities are provided. If response data are beta distributed with constant dispersion parameters across the two samples, then all models are unbiased and have reasonable type-1 error rates and power profiles. If the response data in the two samples have different dispersion parameters, then the simple beta regression model is biased. When the sample size is small (N0 = N1 = 25) linear regression has superior type-1 error rates compared to the other models. Small sample type-1 error rates can be improved in beta regression models using bias correction/reduction methods. In the power experiments, variable-dispersion beta regression and fractional logit regression models have slightly elevated power compared to linear regression models. Similar results were observed if the

  13. Statistical learning from a regression perspective

    CERN Document Server

    Berk, Richard A

    2016-01-01

    This textbook considers statistical learning applications when interest centers on the conditional distribution of the response variable, given a set of predictors, and when it is important to characterize how the predictors are related to the response. As a first approximation, this can be seen as an extension of nonparametric regression. This fully revised new edition includes important developments over the past 8 years. Consistent with modern data analytics, it emphasizes that a proper statistical learning data analysis derives from sound data collection, intelligent data management, appropriate statistical procedures, and an accessible interpretation of results. A continued emphasis on the implications for practice runs through the text. Among the statistical learning procedures examined are bagging, random forests, boosting, support vector machines and neural networks. Response variables may be quantitative or categorical. As in the first edition, a unifying theme is supervised learning that can be trea...

  14. Active set support vector regression.

    Science.gov (United States)

    Musicant, David R; Feinberg, Alexander

    2004-03-01

    This paper presents active set support vector regression (ASVR), a new active set strategy to solve a straightforward reformulation of the standard support vector regression problem. This new algorithm is based on the successful ASVM algorithm for classification problems, and consists of solving a finite number of linear equations with a typically large dimensionality equal to the number of points to be approximated. However, by making use of the Sherman-Morrison-Woodbury formula, a much smaller matrix of the order of the original input space is inverted at each step. The algorithm requires no specialized quadratic or linear programming code, but merely a linear equation solver which is publicly available. ASVR is extremely fast, produces comparable generalization error to other popular algorithms, and is available on the web for download.

  15. AUTISTIC EPILEPTIFORM REGRESSION (A REVIEW

    Directory of Open Access Journals (Sweden)

    L. Yu. Glukhova

    2012-01-01

    Full Text Available The author represents the review of current scientific literature devoted to autistic epileptiform regression — the special form of autistic disorder, characterized by development of severe communicative disorders in children as a result of continuous prolonged epileptiform activity on EEG. This condition has been described by R.F. Tuchman and I. Rapin in 1997. The author describes the aspects of pathogenesis, clinical pictures and diagnostics of this disorder, including the peculiar anomalies on EEG (benign epileptiform patterns of childhood, with a high index of epileptiform activity, especially in the sleep. The especial attention is given to approaches to the treatment of autistic epileptiform regression. Efficacy of valproates, corticosteroid hormones and antiepileptic drugs of other groups is considered.

  16. Binary data regression: Weibull distribution

    Science.gov (United States)

    Caron, Renault; Polpo, Adriano

    2009-12-01

    The problem of estimation in binary response data has receivied a great number of alternative statistical solutions. Generalized linear models allow for a wide range of statistical models for regression data. The most used model is the logistic regression, see Hosmer et al. [6]. However, as Chen et al. [5] mentions, when the probability of a given binary response approaches 0 at a different rate than it approaches 1, symmetric linkages are inappropriate. A class of models based on Weibull distribution indexed by three parameters is introduced here. Maximum likelihood methods are employed to estimate the parameters. The objective of the present paper is to show a solution for the estimation problem under the Weibull model. An example showing the quality of the model is illustrated by comparing it with the alternative probit and logit models.

  17. Spontaneous regression of colon cancer.

    Science.gov (United States)

    Kihara, Kyoichi; Fujita, Shin; Ohshiro, Taihei; Yamamoto, Seiichiro; Sekine, Shigeki

    2015-01-01

    A case of spontaneous regression of transverse colon cancer is reported. A 64-year-old man was diagnosed as having cancer of the transverse colon at a local hospital. Initial and second colonoscopy examinations revealed a typical cancer of the transverse colon, which was diagnosed as moderately differentiated adenocarcinoma. The patient underwent right hemicolectomy 6 weeks after the initial colonoscopy. The resected specimen showed only a scar at the tumor site, and no cancerous tissue was proven histologically. The patient is alive with no evidence of recurrence 1 year after surgery. Although an antitumor immune response is the most likely explanation, the exact nature of the phenomenon was unclear. We describe this rare case and review the literature pertaining to spontaneous regression of colorectal cancer. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  18. Polynomial Regressions and Nonsense Inference

    Directory of Open Access Journals (Sweden)

    Daniel Ventosa-Santaulària

    2013-11-01

    Full Text Available Polynomial specifications are widely used, not only in applied economics, but also in epidemiology, physics, political analysis and psychology, just to mention a few examples. In many cases, the data employed to estimate such specifications are time series that may exhibit stochastic nonstationary behavior. We extend Phillips’ results (Phillips, P. Understanding spurious regressions in econometrics. J. Econom. 1986, 33, 311–340. by proving that an inference drawn from polynomial specifications, under stochastic nonstationarity, is misleading unless the variables cointegrate. We use a generalized polynomial specification as a vehicle to study its asymptotic and finite-sample properties. Our results, therefore, lead to a call to be cautious whenever practitioners estimate polynomial regressions.

  19. Quantile Regression With Measurement Error

    KAUST Repository

    Wei, Ying

    2009-08-27

    Regression quantiles can be substantially biased when the covariates are measured with error. In this paper we propose a new method that produces consistent linear quantile estimation in the presence of covariate measurement error. The method corrects the measurement error induced bias by constructing joint estimating equations that simultaneously hold for all the quantile levels. An iterative EM-type estimation algorithm to obtain the solutions to such joint estimation equations is provided. The finite sample performance of the proposed method is investigated in a simulation study, and compared to the standard regression calibration approach. Finally, we apply our methodology to part of the National Collaborative Perinatal Project growth data, a longitudinal study with an unusual measurement error structure. © 2009 American Statistical Association.

  20. 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 Impact factor: 0.379, year: 2016 http:// library .utia.cas.cz/separaty/2017/SI/bocek-0476587.pdf

  1. QUANTILE CALCULUS AND CENSORED REGRESSION.

    Science.gov (United States)

    Huang, Yijian

    2010-06-01

    Quantile regression has been advocated in survival analysis to assess evolving covariate effects. However, challenges arise when the censoring time is not always observed and may be covariate-dependent, particularly in the presence of continuously-distributed covariates. In spite of several recent advances, existing methods either involve algorithmic complications or impose a probability grid. The former leads to difficulties in the implementation and asymptotics, whereas the latter introduces undesirable grid dependence. To resolve these issues, we develop fundamental and general quantile calculus on cumulative probability scale in this article, upon recognizing that probability and time scales do not always have a one-to-one mapping given a survival distribution. These results give rise to a novel estimation procedure for censored quantile regression, based on estimating integral equations. A numerically reliable and efficient Progressive Localized Minimization (PLMIN) algorithm is proposed for the computation. This procedure reduces exactly to the Kaplan-Meier method in the k-sample problem, and to standard uncensored quantile regression in the absence of censoring. Under regularity conditions, the proposed quantile coefficient estimator is uniformly consistent and converges weakly to a Gaussian process. Simulations show good statistical and algorithmic performance. The proposal is illustrated in the application to a clinical study.

  2. Gaussian Process Regression Model in Spatial Logistic Regression

    Science.gov (United States)

    Sofro, A.; Oktaviarina, A.

    2018-01-01

    Spatial analysis has developed very quickly in the last decade. One of the favorite approaches is based on the neighbourhood of the region. Unfortunately, there are some limitations such as difficulty in prediction. Therefore, we offer Gaussian process regression (GPR) to accommodate the issue. In this paper, we will focus on spatial modeling with GPR for binomial data with logit link function. The performance of the model will be investigated. We will discuss the inference of how to estimate the parameters and hyper-parameters and to predict as well. Furthermore, simulation studies will be explained in the last section.

  3. Zone-Center Raman Active Modes In Cubic And Hexagonal Diamond

    Science.gov (United States)

    Mehl, Michael J.; Pickard, Warren E.

    1989-07-01

    The recent interest in the growth of thin diamond films has led us to consider the differences between the hexagonal (lonsdaleite) and cubic structures. Both phases have very similar properties, and empirical and theoretical considerations indicate that their structural energies are nearly identical. When thin films are grown the hexagonal phase may compete with the cubic phase, making characterization of the film difficult. Cubic diamond has one Raman active mode, while hexagonal diamond has three. The opportunity thus exists for Raman spectroscopy to differentiate between the two tetrahedrally bonded phases (as well as "amorphous" or graphitic phases). Electronic structure calculations can be used to obtain theoretical Q=0 frequencies of the Raman active modes in both structures. We have used the first principles Linearized Augmented Plane Wave method within the local density approximation to calculate the zone center phonon frequencies. The calculated frequency of the cubic diamond Raman mode is 1336 cm-1, very close to the experimental value of 1333 cm-1. Our calculations indicate that the hexagonal structure A t has a zone-center frequency of 1269 cm-1, the Elg mode is at 1215 cm-1, and the E1g mode is at 430 cm-1. Anharmonic corrections are rather large (2-3%) in the cubic diamond Raman mode and in the hexagonal Al mode, but are not important in the E2g and Elg modes. We will compare our results with the available experimental information.

  4. Two-dimensional matter-wave solitons and vortices in competing cubic-quintic nonlinear lattices

    Science.gov (United States)

    Gao, Xuzhen; Zeng, Jianhua

    2018-02-01

    The nonlinear lattice — a new and nonlinear class of periodic potentials — was recently introduced to generate various nonlinear localized modes. Several attempts failed to stabilize two-dimensional (2D) solitons against their intrinsic critical collapse in Kerr media. Here, we provide a possibility for supporting 2D matter-wave solitons and vortices in an extended setting — the cubic and quintic model — by introducing another nonlinear lattice whose period is controllable and can be different from its cubic counterpart, to its quintic nonlinearity, therefore making a fully "nonlinear quasi-crystal". A variational approximation based on Gaussian ansatz is developed for the fundamental solitons and in particular, their stability exactly follows the inverted Vakhitov-Kolokolov stability criterion, whereas the vortex solitons are only studied by means of numerical methods. Stability regions for two types of localized mode — the fundamental and vortex solitons — are provided. A noteworthy feature of the localized solutions is that the vortex solitons are stable only when the period of the quintic nonlinear lattice is the same as the cubic one or when the quintic nonlinearity is constant, while the stable fundamental solitons can be created under looser conditions. Our physical setting (cubic-quintic model) is in the framework of the Gross-Pitaevskii equation or nonlinear Schrödinger equation, the predicted localized modes thus may be implemented in Bose-Einstein condensates and nonlinear optical media with tunable cubic and quintic nonlinearities.

  5. Randomized Binomial Tree and Pricing of American-Style Options

    OpenAIRE

    Hu Xiaoping; Cao Jie

    2014-01-01

    Randomized binomial tree and methods for pricing American options were studied. Firstly, both the completeness and the no-arbitrage conditions in the randomized binomial tree market were proved. Secondly, the description of the node was given, and the cubic polynomial relationship between the number of nodes and the time steps was also obtained. Then, the characteristics of paths and storage structure of the randomized binomial tree were depicted. Then, the procedure and method for pricing Am...

  6. Producing The New Regressive Left

    DEFF Research Database (Denmark)

    Crone, Christine

    to be a committed artist, and how that translates into supporting al-Assad’s rule in Syria; the Ramadan programme Harrir Aqlak’s attempt to relaunch an intellectual renaissance and to promote religious pluralism; and finally, al-Mayadeen’s cooperation with the pan-Latin American TV station TeleSur and its ambitions...... becomes clear from the analytical chapters is the emergence of the new cross-ideological alliance of The New Regressive Left. This emerging coalition between Shia Muslims, religious minorities, parts of the Arab Left, secular cultural producers, and the remnants of the political,strategic resistance...

  7. An Evaluation of Ridge Regression.

    Science.gov (United States)

    1981-12-01

    of the parameter estimates, is a decreasing function of k. The idea of ridge regression, as suggested by Hoerl and Kennard (Ref 12:58-63), is to pick...CROSS? 0 CR0553 f.812 CR0554 0 CR0555 4.39? CROSS6 0 ALSO 4.922 KSO 0 NVARSO 4. A5059 .622 CONTFNTS OF CASE NUlIPER 209 SEQHUI 209. SUOILE PEGANAL CASWGT...KSQ .000 NVARSO 9. RSOSO .846 CONTENTS OF CASE NUMBER 55 SEONUN 55. SUfTFILE PEGANAL CASWGI 2.0000 459 .970 RI 76600 K .025 NVA? 3. MSE .177 NS[IS

  8. Linguistic Neutrosophic Cubic Numbers and Their Multiple Attribute Decision-Making Method

    Directory of Open Access Journals (Sweden)

    Jun Ye

    2017-09-01

    Full Text Available To describe both certain linguistic neutrosophic information and uncertain linguistic neutrosophic information simultaneously in the real world, this paper originally proposes the concept of a linguistic neutrosophic cubic number (LNCN, including an internal LNCN and external LNCN. In LNCN, its uncertain linguistic neutrosophic number consists of the truth, indeterminacy, and falsity uncertain linguistic variables, and its linguistic neutrosophic number consists of the truth, indeterminacy, and falsity linguistic variables to express their hybrid information. Then, we present the operational laws of LNCNs and the score, accuracy, and certain functions of LNCN for comparing/ranking LNCNs. Next, we propose a LNCN weighted arithmetic averaging (LNCNWAA operator and a LNCN weighted geometric averaging (LNCNWGA operator to aggregate linguistic neutrosophic cubic information and discuss their properties. Further, a multiple attribute decision-making method based on the LNCNWAA or LNCNWGA operator is developed under a linguistic neutrosophic cubic environment. Finally, an illustrative example is provided to indicate the application of the developed method.

  9. Cubic Copper Hexacyanoferrates Nanoparticles: Facile Template-Free Deposition and Electrocatalytic Sensing Towards Hydrazine

    Directory of Open Access Journals (Sweden)

    Xingxing Wang

    2011-01-01

    Full Text Available Cubic copper hexacyanoferrate (CuHCF nanoparticles prepared via electrolytic deposition are presented with their morphology and crystalline structure characterized with SEM and XRD. The advantage of this methodology is that it allows the fabrication of uniform cubic nanoparticles with permeable structures onto the desired underlying electrode substrate. It was observed that the CuHCF film acts as a permeable membrane for cations such as K+, Na+, Li+, and NH4+ with a selection order of K+> Li+>NH4+> Na+. Furthermore, the analytical utility of these cubic-like CuHCF morphologies supported on a glassy carbon electrode was evaluated towards the electrochemical oxidation of hydrazine which was found to exhibit a linear response over the range 66 M to 17 mM with a detection limit corresponding to 16.5 M.

  10. Varying-coefficient functional linear regression

    OpenAIRE

    Wu, Yichao; Fan, Jianqing; Müller, Hans-Georg

    2010-01-01

    Functional linear regression analysis aims to model regression relations which include a functional predictor. The analog of the regression parameter vector or matrix in conventional multivariate or multiple-response linear regression models is a regression parameter function in one or two arguments. If, in addition, one has scalar predictors, as is often the case in applications to longitudinal studies, the question arises how to incorporate these into a functional regression model. We study...

  11. Age estimation based on pelvic ossification using regression models from conventional radiography.

    Science.gov (United States)

    Zhang, Kui; Dong, Xiao-Ai; Fan, Fei; Deng, Zhen-Hua

    2016-07-01

    To establish regression models for age estimation from the combination of the ossification of iliac crest and ischial tuberosity. One thousand three hundred and seventy-nine conventional pelvic radiographs at the West China Hospital of Sichuan University between January 2010 and June 2012 were evaluated retrospectively. The receiver operating characteristic analysis was performed to measure the value of estimation of 18 years of age with the classification scheme for the iliac crest and ischial tuberosity. Regression analysis was performed, and formulas for calculating approximate chronological age according to the combination developmental status of the ossification for the iliac crest and ischial tuberosity were developed. The areas under the receiver operating characteristic (ROC) curves were above 0.9 (p ossification and the ischial tuberosity may be used for age estimation. And the present established cubic regression model according to the combination developmental status of the ossification for the iliac crest and ischial tuberosity can be used for age estimation.

  12. On the scenario of reconnection in non-twist cubic maps

    Energy Technology Data Exchange (ETDEWEB)

    Tigan, Gheorghe [Department of Mathematics, ' Politehnica' University of Timisoara, Pta Victoriei, No. 2, 300006 Timisoara, Timis (Romania)]. E-mail: gtigan73@yahoo.com

    2006-12-15

    In this paper, we study the reconnection process in the dynamics of cubic non-twist maps, introduced in [Howard JE, Humpherys J. Nonmonotonic twist maps. Physica D 1995; 256-76]. In order to describe the route to reconnection of the involved Poincare-Birkhoff chains we investigate an approximate interpolating Hamiltonian of the map under study. Our study reveals that the scenario of reconnection of cubic non-twist maps is different from that occurring in the dynamics of quadratic non-twist maps.

  13. Analysis of moderately thin-walled beam cross-sections by cubic isoparametric elements

    DEFF Research Database (Denmark)

    Høgsberg, Jan Becker; Krenk, Steen

    2014-01-01

    In technical beam theory the six equilibrium states associated with homogeneous tension, bending, shear and torsion are treated as individual load cases. This enables the formulation of weak form equations governing the warping from shear and torsion. These weak form equations are solved...... numerically by introducing a cubic-linear two-dimensional isoparametric element. The cubic interpolation of this element accurately represents quadratic shear stress variations along cross-section walls, and thus moderately thin-walled cross-sections are effectively discretized by these elements. The ability...

  14. Cubic systems with invariant affine straight lines of total parallel multiplicity seven

    Directory of Open Access Journals (Sweden)

    Alexandru Suba

    2013-12-01

    Full Text Available In this article, we study the planar cubic differential systems with invariant affine straight lines of total parallel multiplicity seven. We classify these system according to their geometric properties encoded in the configurations of invariant straight lines. We show that there are only 17 different topological phase portraits in the Poincar\\'e disc associated to this family of cubic systems up to a reversal of the sense of their orbits, and we provide representatives of every class modulo an affine change of variables and rescaling of the time variable.

  15. Preconditioning cubic spline collocation method by FEM and FDM for elliptic equations

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sang Dong [KyungPook National Univ., Taegu (Korea, Republic of)

    1996-12-31

    In this talk we discuss the finite element and finite difference technique for the cubic spline collocation method. For this purpose, we consider the uniformly elliptic operator A defined by Au := -{Delta}u + a{sub 1}u{sub x} + a{sub 2}u{sub y} + a{sub 0}u in {Omega} (the unit square) with Dirichlet or Neumann boundary conditions and its discretization based on Hermite cubic spline spaces and collocation at the Gauss points. Using an interpolatory basis with support on the Gauss points one obtains the matrix A{sub N} (h = 1/N).

  16. GA Based Rational cubic B-Spline Representation for Still Image Interpolation

    Directory of Open Access Journals (Sweden)

    Samreen Abbas

    2016-12-01

    Full Text Available In this paper, an image interpolation scheme is designed for 2D natural images. A local support rational cubic spline with control parameters, as interpolatory function, is being optimized using Genetic Algorithm (GA. GA is applied to determine the appropriate values of control parameter used in the description of rational cubic spline. Three state-of-the-art Image Quality Assessment (IQA models with traditional one are hired for comparison with existing image interpolation schemes and perceptual quality check of resulting images. The results show that the proposed scheme is better than the existing ones in comparison.

  17. Drag force in bimodal cubic-quintic nonlinear Schr\\"odinger equation

    CERN Document Server

    Feijoo, David; Paredes, Ángel; Michinel, Humberto

    2016-01-01

    We consider a system of two cubic-quintic non-linear Schr\\"odinger equations in two dimensions, coupled by repulsive cubic terms. We analyse situations in which a probe lump of one of the modes is surrounded by a fluid of the other one and analyse their interaction. We find a realization of D'Alembert's paradox for small velocities and non-trivial drag forces for larger ones. We present numerical analysis including the search of static and traveling form-preserving solutions along with simulations of the dynamical evolution in some representative examples.

  18. Effect of shear on cubic phases in gels of a diblock copolymer

    DEFF Research Database (Denmark)

    Hamley, I.W.; Pople, J.A.; Fairclough, J.P.A.

    1998-01-01

    The effect of shear on the orientation of cubic micellar phases formed by a poly(oxyethylene)poly(oxybutylene) diblock copolymer in aqueous solution has been investigated using small-angle x-ray scattering (SAXS) and small-angle neutron scattering (SANS). SAXS was performed on samples oriented...... in a Couette cell using steady shear, and SANS was performed on samples subject to oscillatory shear in situ in a rheometer with a shear sandwich configuration. A body-centered-cubic (bcc) phase observed for gels with concentrations greater than 30 wt % copolymer was found to orient into a polydomain structure...

  19. Secure optical generalized filter bank multi-carrier system based on cubic constellation masked method.

    Science.gov (United States)

    Zhang, Lijia; Liu, Bo; Xin, Xiangjun

    2015-06-15

    A secure optical generalized filter bank multi-carrier (GFBMC) system with carrier-less amplitude-phase (CAP) modulation is proposed in this Letter. The security is realized through cubic constellation-masked method. Large key space and more flexibility masking can be obtained by cubic constellation masking aligning with the filter bank. An experiment of 18 Gb/s encrypted GFBMC/CAP system with 25-km single-mode fiber transmission is performed to demonstrate the feasibility of the proposed method.

  20. A note on the prolongation structure of the cubically nonlinear integrable Camassa-Holm type equation

    Energy Technology Data Exchange (ETDEWEB)

    Stalin, S. [Centre for Nonlinear Dynamics, School of Physics, Bharathidasan University, Tiruchirappalli 620024, Tamil Nadu (India); Senthilvelan, M., E-mail: velan@cnld.bdu.ac.in [Centre for Nonlinear Dynamics, School of Physics, Bharathidasan University, Tiruchirappalli 620024, Tamil Nadu (India)

    2011-10-17

    In this Letter, we formulate an exterior differential system for the newly discovered cubically nonlinear integrable Camassa-Holm type equation. From the exterior differential system we establish the integrability of this equation. We then study Cartan prolongation structure of this equation. We also discuss the method of identifying conservation laws and Baecklund transformation for this equation from the identified exterior differential system. -- Highlights: → An exterior differential system for a cubic nonlinear integrable equation is given. → The conservation laws from the exterior differential system is derived. → The Baecklund transformation from the Cartan-Ehresmann connection is obtained.

  1. Comments on the random Thirring model

    Science.gov (United States)

    Berkooz, Micha; Narayan, Prithvi; Rozali, Moshe; Simón, Joan

    2017-09-01

    The Thirring model with random couplings is a translationally invariant generalisation of the SYK model to 1+1 dimensions, which is tractable in the large N limit. We compute its two point function, at large distances, for any strength of the random coupling. For a given realisation, the couplings contain both irrelevant and relevant marginal operators, but statistically, in the large N limit, the random couplings are overall always marginally irrelevant, in sharp distinction to the usual Thirring model. We show the leading term to the β function in conformal perturbation theory, which is quadratic in the couplings, vanishes, while its usually subleading cubic term matches our RG flow.

  2. Nonparametric Regression with Common Shocks

    Directory of Open Access Journals (Sweden)

    Eduardo A. Souza-Rodrigues

    2016-09-01

    Full Text Available This paper considers a nonparametric regression model for cross-sectional data in the presence of common shocks. Common shocks are allowed to be very general in nature; they do not need to be finite dimensional with a known (small number of factors. I investigate the properties of the Nadaraya-Watson kernel estimator and determine how general the common shocks can be while still obtaining meaningful kernel estimates. Restrictions on the common shocks are necessary because kernel estimators typically manipulate conditional densities, and conditional densities do not necessarily exist in the present case. By appealing to disintegration theory, I provide sufficient conditions for the existence of such conditional densities and show that the estimator converges in probability to the Kolmogorov conditional expectation given the sigma-field generated by the common shocks. I also establish the rate of convergence and the asymptotic distribution of the kernel estimator.

  3. Practical Session: Multiple Linear Regression

    Science.gov (United States)

    Clausel, M.; Grégoire, G.

    2014-12-01

    Three exercises are proposed to illustrate the simple linear regression. In the first one investigates the influence of several factors on atmospheric pollution. It has been proposed by D. Chessel and A.B. Dufour in Lyon 1 (see Sect. 6 of http://pbil.univ-lyon1.fr/R/pdf/tdr33.pdf) and is based on data coming from 20 cities of U.S. Exercise 2 is an introduction to model selection whereas Exercise 3 provides a first example of analysis of variance. Exercises 2 and 3 have been proposed by A. Dalalyan at ENPC (see Exercises 2 and 3 of http://certis.enpc.fr/~dalalyan/Download/TP_ENPC_5.pdf).

  4. Kernel Multitask Regression for Toxicogenetics.

    Science.gov (United States)

    Bernard, Elsa; Jiao, Yunlong; Scornet, Erwan; Stoven, Veronique; Walter, Thomas; Vert, Jean-Philippe

    2017-10-01

    The development of high-throughput in vitro assays to study quantitatively the toxicity of chemical compounds on genetically characterized human-derived cell lines paves the way to predictive toxicogenetics, where one would be able to predict the toxicity of any particular compound on any particular individual. In this paper we present a machine learning-based approach for that purpose, kernel multitask regression (KMR), which combines chemical characterizations of molecular compounds with genetic and transcriptomic characterizations of cell lines to predict the toxicity of a given compound on a given cell line. We demonstrate the relevance of the method on the recent DREAM8 Toxicogenetics challenge, where it ranked among the best state-of-the-art models, and discuss the importance of choosing good descriptors for cell lines and chemicals. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Lumbar herniated disc: spontaneous regression.

    Science.gov (United States)

    Altun, Idiris; Yüksel, Kasım Zafer

    2017-01-01

    Low back pain is a frequent condition that results in substantial disability and causes admission of patients to neurosurgery clinics. To evaluate and present the therapeutic outcomes in lumbar disc hernia (LDH) patients treated by means of a conservative approach, consisting of bed rest and medical therapy. This retrospective cohort was carried out in the neurosurgery departments of hospitals in Kahramanmaraş city and 23 patients diagnosed with LDH at the levels of L3-L4, L4-L5 or L5-S1 were enrolled. The average age was 38.4 ± 8.0 and the chief complaint was low back pain and sciatica radiating to one or both lower extremities. Conservative treatment was administered. Neurological examination findings, durations of treatment and intervals until symptomatic recovery were recorded. Laségue tests and neurosensory examination revealed that mild neurological deficits existed in 16 of our patients. Previously, 5 patients had received physiotherapy and 7 patients had been on medical treatment. The number of patients with LDH at the level of L3-L4, L4-L5, and L5-S1 were 1, 13, and 9, respectively. All patients reported that they had benefit from medical treatment and bed rest, and radiologic improvement was observed simultaneously on MRI scans. The average duration until symptomatic recovery and/or regression of LDH symptoms was 13.6 ± 5.4 months (range: 5-22). It should be kept in mind that lumbar disc hernias could regress with medical treatment and rest without surgery, and there should be an awareness that these patients could recover radiologically. This condition must be taken into account during decision making for surgical intervention in LDH patients devoid of indications for emergent surgery.

  6. Representations of the rotation reflection symmetry group of the four-dimensional cubic lattice

    Science.gov (United States)

    Mandula, Jeffrey E.; Zweig, George; Govaerts, Jan

    1983-11-01

    The structure and representations of the rotation reflection symmetry group of the four-dimensional cubic lattice are described. Their connections with the representations of the three-dimensional lattice rotation reflection group, and with the representations of the continuous O(3) and O(4) groups are given.

  7. Representations of the rotation reflection symmetry group of the four-dimensional cubic lattice

    Energy Technology Data Exchange (ETDEWEB)

    Mandula, J.E. (Washington Univ., St. Louis, MO (USA). Dept. of Physics); Zweig, G. (Los Alamos National Lab., NM (USA)); Govaerts, J. (Louvain Univ. (Belgium). Inst. for Theoretical Physics)

    1983-11-15

    The structure and representations of the rotation reflection symmetry group of the four-dimensional cubic lattice are described. Their connections with the representations of the three-dimensional lattice rotation reflection group, and with the representations of the continuous O(3) and O(4) groups are given.

  8. Electron correlation in a three dimensional cluster of the cubic lattice ...

    African Journals Online (AJOL)

    We study the one-band Hubbard model in a three dimensional simple cubic lattice, with periodic boundary conditions, by means of a variational analytic approach. Ground state energies and pairing correlations depend implicitly on the interaction strength (U/41). It is shown that for two electrons, the interaction is always ...

  9. Motion of a Rigid Rod Rocking Back and Forth Cubic-Quintic Duffing Oscillators

    DEFF Research Database (Denmark)

    Ganji, S. S.; Barari, Amin; Karimpour, S.

    2012-01-01

    In this work, we implemented the first-order approximation of the Iteration Perturbation Method (IPM) for approximating the behavior of a rigid rod rocking back and forth on a circular surface without slipping as well as Cubic-Quintic Duffing Oscillators. Comparing the results with the exact...

  10. Surface relaxation and surface energy of face –centered Cubic ...

    African Journals Online (AJOL)

    DR. MIKE HORSFALL

    Surface relaxation and surface energy of face –centered Cubic metals. 1AGHEMENLO H E; *2IYAYI, S E; 3AVWIRI ,G O. 1, 3 Department of Physics, Ambrose Alli University, Ekpoma, Nigeria. 2 Department of Physics, University of Benin, Benin City, Nigeria. 3 Department of Physics, University of Port Harcourt, PH, Nigeria.

  11. Effects of quadratic and cubic nonlinearities on a perfectly tuned parametric amplifier

    DEFF Research Database (Denmark)

    Neumeyer, Stefan; Sorokin, Vladislav; Thomsen, Jon Juel

    2016-01-01

    We consider the performance of a parametric amplifier with perfect tuning (two-to-one ratio between the parametric and direct excitation frequencies) and quadratic and cubic nonlinearities. A forced Duffing–Mathieu equation with appended quadratic nonlinearity is considered as the model system...

  12. Semisymmetric cubic graphs of order 16p2 16p2 16p2

    Indian Academy of Sciences (India)

    An undirected graph without isolated vertices is said to be semisymmetric if its full automorphism group acts transitively on its edge set but not on its vertex set. In this paper, we inquire the existence of connected semisymmetric cubic graphs of order 162. It is shown that for every odd prime , there exists a semisymmetric ...

  13. The influence of a cubic building on a roof mounted wind turbine

    NARCIS (Netherlands)

    Micallef, D.; Sant, Tonio; Simao Ferreira, C.

    2016-01-01

    The performance of a wind turbine located above a cubic building is not well understood. This issue is of fundamental importance for the design of small scale wind turbines. One variable which is of particular importance in this respect is the turbine height above roof level. In this work, the

  14. Estimating cubic volume of small diameter tree-length logs from ponderosa and lodgepole pine.

    Science.gov (United States)

    Marlin E. Plank; James M. Cahill

    1984-01-01

    A sample of 351 ponderosa pine (Pinus ponderosa Dougl. ex Laws.) and 509 lodgepole pine (Pinus contorta Dougl. ex Loud.) logs were used to evaluate the performance of three commonly used formulas for estimating cubic volume. Smalian's formula, Bruce's formula, and Huber's formula were tested to determine which...

  15. Lactoferrin-derived antimicrobial peptide induces a micellar cubic phase in a model membrane system

    NARCIS (Netherlands)

    Bastos, M.; Silva, T.; Teixeira, V.; Nazmi, K.; Bolscher, J.G.M.; Funari, S.S.; Uhríková, D.

    2011-01-01

    The observation of a micellar cubic phase is reported for a mixture of an antimicrobial peptide from the Lactoferrin family, LFampin 265-284, and a model membrane system of dimyristoylphosphatidylcholine/dimyristoylphosphatidylglycerol (3:1), as derived from small-angle x-ray diffraction (SAXD)

  16. Estimating load weights with Huber's Cubic Volume formula: a field trial.

    Science.gov (United States)

    Dale R. Waddell

    1989-01-01

    Log weights were estimated from the product of Huber's cubic volume formula and green density. Tags showing estimated log weights were attached to logs in the field, and the weights were tallied into a single load weight as logs were assembled for aerial yarding. Accuracy of the estimated load weights was evaluated by comparing the predicted with the actual load...

  17. Towards high-resolution 3D flow field measurements at cubic meter scales

    NARCIS (Netherlands)

    Schanz, Daniel; Huhn, Florian; Gesemann, Sebastian; Dierksheide, Uwe; van de Meerendonk, R.; Manovski, P.; Schröder, A.

    We present results from two large-volume volumetric flow experiments. The first of these, investigating a thermal plume at low velocities (up to 0.35 m/s) demonstrates the abilities and requirements to reach volume sizes up to and probably beyond one cubic meter. It is shown that the use of Helium

  18. Localized Pd Overgrowth on Cubic Pt Nanocrystals for Enhanced Electrocatalytic Oxidation of Formic Acid

    Energy Technology Data Exchange (ETDEWEB)

    Lee, H.; Habas, S.E.; Somorjai, G.A.; Yang, P.

    2008-03-20

    Binary Pt/Pd nanoparticles were synthesized by localized overgrowth of Pd on cubic Pt seeds for the investigation of electrocatalytic formic acid oxidation. The binary particles exhibited much less self-poisoning and a lower activation energy relative to Pt nanocubes, consistent with the single crystal study.

  19. Maximal independent set graph partitions for representations of body-centered cubic lattices

    DEFF Research Database (Denmark)

    Erleben, Kenny

    2009-01-01

    A maximal independent set graph data structure for a body-centered cubic lattice is presented. Refinement and coarsening operations are defined in terms of set-operations resulting in robust and easy implementation compared to a quad-tree-based implementation. The graph only stores information...

  20. On the dynamic Stability of a quadratic-cubic elastic model structure ...

    African Journals Online (AJOL)

    The main substance of this investigation is the determination of the dynamic buckling load of an imperfect quadratic-cubic elastic model structure , which ,in itself, is a Mathematical generalization of some of the many physical structures normally encountered in engineering practice and allied fields. The load function in ...