Modified Regression Correlation Coefficient for Poisson Regression Model
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).
Standards for Standardized Logistic Regression Coefficients
Menard, Scott
2011-01-01
Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…
Distributed Monitoring of the R2 Statistic for Linear Regression
National Aeronautics and Space Administration — The problem of monitoring a multivariate linear regression model is relevant in studying the evolving relationship between a set of input variables (features) and...
Regression Models for Predicting Force Coefficients of Aerofoils
Directory of Open Access Journals (Sweden)
Mohammed ABDUL AKBAR
2015-09-01
Full Text Available Renewable sources of energy are attractive and advantageous in a lot of different ways. Among the renewable energy sources, wind energy is the fastest growing type. Among wind energy converters, Vertical axis wind turbines (VAWTs have received renewed interest in the past decade due to some of the advantages they possess over their horizontal axis counterparts. VAWTs have evolved into complex 3-D shapes. A key component in predicting the output of VAWTs through analytical studies is obtaining the values of lift and drag coefficients which is a function of shape of the aerofoil, ‘angle of attack’ of wind and Reynolds’s number of flow. Sandia National Laboratories have carried out extensive experiments on aerofoils for the Reynolds number in the range of those experienced by VAWTs. The volume of experimental data thus obtained is huge. The current paper discusses three Regression analysis models developed wherein lift and drag coefficients can be found out using simple formula without having to deal with the bulk of the data. Drag coefficients and Lift coefficients were being successfully estimated by regression models with R2 values as high as 0.98.
On the Occurrence of Standardized Regression Coefficients Greater than One.
Deegan, John, Jr.
1978-01-01
It is demonstrated here that standardized regression coefficients greater than one can legitimately occur. Furthermore, the relationship between the occurrence of such coefficients and the extent of multicollinearity present among the set of predictor variables in an equation is examined. Comments on the interpretation of these coefficients are…
Nakagawa, Shinichi; Johnson, Paul C D; Schielzeth, Holger
2017-09-01
The coefficient of determination R 2 quantifies the proportion of variance explained by a statistical model and is an important summary statistic of biological interest. However, estimating R 2 for generalized linear mixed models (GLMMs) remains challenging. We have previously introduced a version of R 2 that we called [Formula: see text] for Poisson and binomial GLMMs, but not for other distributional families. Similarly, we earlier discussed how to estimate intra-class correlation coefficients (ICCs) using Poisson and binomial GLMMs. In this paper, we generalize our methods to all other non-Gaussian distributions, in particular to negative binomial and gamma distributions that are commonly used for modelling biological data. While expanding our approach, we highlight two useful concepts for biologists, Jensen's inequality and the delta method, both of which help us in understanding the properties of GLMMs. Jensen's inequality has important implications for biologically meaningful interpretation of GLMMs, whereas the delta method allows a general derivation of variance associated with non-Gaussian distributions. We also discuss some special considerations for binomial GLMMs with binary or proportion data. We illustrate the implementation of our extension by worked examples from the field of ecology and evolution in the R environment. However, our method can be used across disciplines and regardless of statistical environments. © 2017 The Author(s).
Overcoming multicollinearity in multiple regression using correlation coefficient
Zainodin, H. J.; Yap, S. J.
2013-09-01
Multicollinearity happens when there are high correlations among independent variables. In this case, it would be difficult to distinguish between the contributions of these independent variables to that of the dependent variable as they may compete to explain much of the similar variance. Besides, the problem of multicollinearity also violates the assumption of multiple regression: that there is no collinearity among the possible independent variables. Thus, an alternative approach is introduced in overcoming the multicollinearity problem in achieving a well represented model eventually. This approach is accomplished by removing the multicollinearity source variables on the basis of the correlation coefficient values based on full correlation matrix. Using the full correlation matrix can facilitate the implementation of Excel function in removing the multicollinearity source variables. It is found that this procedure is easier and time-saving especially when dealing with greater number of independent variables in a model and a large number of all possible models. Hence, in this paper detailed insight of the procedure is shown, compared and implemented.
Interpreting Bivariate Regression Coefficients: Going beyond the Average
Halcoussis, Dennis; Phillips, G. Michael
2010-01-01
Statistics, econometrics, investment analysis, and data analysis classes often review the calculation of several types of averages, including the arithmetic mean, geometric mean, harmonic mean, and various weighted averages. This note shows how each of these can be computed using a basic regression framework. By recognizing when a regression model…
Li, Huaiyong; Zhang, Siyuan; Zhou, Shihong; Cao, Xueqiang
2009-09-01
Theoretical researches are performed on the alpha-R2MoO6 (R = Y, Gd, Tb Dy, Ho, Er, Tm and Yb) and pyrochlore-type R2Mo2O7 (R = Y, Nd, Sm, Gd, Tb and Dy) rare earth molybdates by using chemical bond theory of dielectric description. The chemical bonding characteristics and their relationship with thermal expansion property and compressibility are explored. The calculated values of linear thermal expansion coefficient (LTEC) and bulk modulus agree well with the available experimental values. The calculations reveal that the LTECs and the bulk moduli do have linear relationship with the ionic radii of the lanthanides: the LTEC decreases from 6.80 to 6.62 10(-6)/K and the bulk modulus increases from 141 to 154 GPa when R goes in the order Gd, Tb Dy, Ho, Er, Tm, and Yb in the alpha-R2MoO6 series; while in the R2Mo2O7 series, the LTEC ranges from 6.80 to 6.61 10(-6)/K and the bulk modulus ranges from 147 to 163 GPa when R varies in the order Nd, Sm, Gd, Tb and Dy. Copyright 2008 Wiley Periodicals, Inc.
Bias in regression coefficient estimates upon different treatments of ...
African Journals Online (AJOL)
MS and PW consistently overestimated the population parameter. EM and RI, on the other hand, tended to consistently underestimate the population parameter under non-monotonic pattern. Keywords: Missing data, bias, regression, percent missing, non-normality, missing pattern > East African Journal of Statistics Vol.
Modeling maximum daily temperature using a varying coefficient regression model
Han Li; Xinwei Deng; Dong-Yum Kim; Eric P. Smith
2014-01-01
Relationships between stream water and air temperatures are often modeled using linear or nonlinear regression methods. Despite a strong relationship between water and air temperatures and a variety of models that are effective for data summarized on a weekly basis, such models did not yield consistently good predictions for summaries such as daily maximum temperature...
Zhang, Yu-Dong; Wu, Chen-Jiang; Wang, Qing; Zhang, Jing; Wang, Xiao-Ning; Liu, Xi-Sheng; Shi, Hai-Bin
2015-08-01
The purpose of this study was to compare histogram analysis of apparent diffusion coefficient (ADC) and R2* for differentiating low-grade from high-grade clear cell renal cell carcinoma (RCC). Forty-six patients with pathologically confirmed clear cell RCC underwent preoperative BOLD and DWI MRI of the kidneys. ADCs based on the entire tumor volume were calculated with b value combinations of 0 and 800 s/mm(2). ROI-based R2* was calculated with eight TE combinations of 6.7-22.8 milliseconds. Histogram analysis of tumor ADCs and R2* values was performed to obtain mean; median; width; and fifth, 10th, 90th, and 95th percentiles and histogram inhomogeneity, kurtosis, and skewness for all lesions. Thirty-three low-grade and 13 high-grade clear cell RCCs were found at pathologic examination. The TNM classification and tumor volume of clear cell RCC significantly correlated with histogram ADC and R2* (ρ = -0.317 to 0.506; p histogram ADC and R2* indexes, 10th percentile ADC had the highest accuracy (91.3%) in discriminating low- from high-grade clear cell RCC. R2* in discriminating hemorrhage was achieved with a threshold of 68.95 Hz. At this threshold, high-grade clear cell RCC had a significantly higher prevalence of intratumor hemorrhage (high-grade, 76.9%; low-grade, 45.4%; p Histogram analysis of ADC and R2* allows differentiation of low- from high-grade clear cell RCC with high accuracy.
Using the Ridge Regression Procedures to Estimate the Multiple Linear Regression Coefficients
Gorgees, HazimMansoor; Mahdi, FatimahAssim
2018-05-01
This article concerns with comparing the performance of different types of ordinary ridge regression estimators that have been already proposed to estimate the regression parameters when the near exact linear relationships among the explanatory variables is presented. For this situations we employ the data obtained from tagi gas filling company during the period (2008-2010). The main result we reached is that the method based on the condition number performs better than other methods since it has smaller mean square error (MSE) than the other stated methods.
Estimating nonlinear selection gradients using quadratic regression coefficients: double or nothing?
Stinchcombe, John R; Agrawal, Aneil F; Hohenlohe, Paul A; Arnold, Stevan J; Blows, Mark W
2008-09-01
The use of regression analysis has been instrumental in allowing evolutionary biologists to estimate the strength and mode of natural selection. Although directional and correlational selection gradients are equal to their corresponding regression coefficients, quadratic regression coefficients must be doubled to estimate stabilizing/disruptive selection gradients. Based on a sample of 33 papers published in Evolution between 2002 and 2007, at least 78% of papers have not doubled quadratic regression coefficients, leading to an appreciable underestimate of the strength of stabilizing and disruptive selection. Proper treatment of quadratic regression coefficients is necessary for estimation of fitness surfaces and contour plots, canonical analysis of the gamma matrix, and modeling the evolution of populations on an adaptive landscape.
Yan, Jun; Aseltine, Robert H., Jr.; Harel, Ofer
2013-01-01
Comparing regression coefficients between models when one model is nested within another is of great practical interest when two explanations of a given phenomenon are specified as linear models. The statistical problem is whether the coefficients associated with a given set of covariates change significantly when other covariates are added into…
Sintering equation: determination of its coefficients by experiments - using multiple regression
International Nuclear Information System (INIS)
Windelberg, D.
1999-01-01
Sintering is a method for volume-compression (or volume-contraction) of powdered or grained material applying high temperature (less than the melting point of the material). Maekipirtti tried to find an equation which describes the process of sintering by its main parameters sintering time, sintering temperature and volume contracting. Such equation is called a sintering equation. It also contains some coefficients which characterise the behaviour of the material during the process of sintering. These coefficients have to be determined by experiments. Here we show that some linear regressions will produce wrong coefficients, but multiple regression results in an useful sintering equation. (orig.)
Yoneoka, Daisuke; Henmi, Masayuki
2017-11-30
Recently, the number of clinical prediction models sharing the same regression task has increased in the medical literature. However, evidence synthesis methodologies that use the results of these regression models have not been sufficiently studied, particularly in meta-analysis settings where only regression coefficients are available. One of the difficulties lies in the differences between the categorization schemes of continuous covariates across different studies. In general, categorization methods using cutoff values are study specific across available models, even if they focus on the same covariates of interest. Differences in the categorization of covariates could lead to serious bias in the estimated regression coefficients and thus in subsequent syntheses. To tackle this issue, we developed synthesis methods for linear regression models with different categorization schemes of covariates. A 2-step approach to aggregate the regression coefficient estimates is proposed. The first step is to estimate the joint distribution of covariates by introducing a latent sampling distribution, which uses one set of individual participant data to estimate the marginal distribution of covariates with categorization. The second step is to use a nonlinear mixed-effects model with correction terms for the bias due to categorization to estimate the overall regression coefficients. Especially in terms of precision, numerical simulations show that our approach outperforms conventional methods, which only use studies with common covariates or ignore the differences between categorization schemes. The method developed in this study is also applied to a series of WHO epidemiologic studies on white blood cell counts. Copyright © 2017 John Wiley & Sons, Ltd.
SPSS and SAS programs for comparing Pearson correlations and OLS regression coefficients.
Weaver, Bruce; Wuensch, Karl L
2013-09-01
Several procedures that use summary data to test hypotheses about Pearson correlations and ordinary least squares regression coefficients have been described in various books and articles. To our knowledge, however, no single resource describes all of the most common tests. Furthermore, many of these tests have not yet been implemented in popular statistical software packages such as SPSS and SAS. In this article, we describe all of the most common tests and provide SPSS and SAS programs to perform them. When they are applicable, our code also computes 100 × (1 - α)% confidence intervals corresponding to the tests. For testing hypotheses about independent regression coefficients, we demonstrate one method that uses summary data and another that uses raw data (i.e., Potthoff analysis). When the raw data are available, the latter method is preferred, because use of summary data entails some loss of precision due to rounding.
Yoneoka, Daisuke; Henmi, Masayuki
2017-06-01
Recently, the number of regression models has dramatically increased in several academic fields. However, within the context of meta-analysis, synthesis methods for such models have not been developed in a commensurate trend. One of the difficulties hindering the development is the disparity in sets of covariates among literature models. If the sets of covariates differ across models, interpretation of coefficients will differ, thereby making it difficult to synthesize them. Moreover, previous synthesis methods for regression models, such as multivariate meta-analysis, often have problems because covariance matrix of coefficients (i.e. within-study correlations) or individual patient data are not necessarily available. This study, therefore, proposes a brief explanation regarding a method to synthesize linear regression models under different covariate sets by using a generalized least squares method involving bias correction terms. Especially, we also propose an approach to recover (at most) threecorrelations of covariates, which is required for the calculation of the bias term without individual patient data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Juttukonda, Meher R; Mersereau, Bryant G; Chen, Yasheng; Su, Yi; Rubin, Brian G; Benzinger, Tammie L S; Lalush, David S; An, Hongyu
2015-05-15
MR-based correction for photon attenuation in PET/MRI remains challenging, particularly for neurological applications requiring quantitation of data. Existing methods are either not sufficiently accurate or are limited by the computation time required. The goal of this study was to develop an MR-based attenuation correction method that accurately separates bone tissue from air and provides continuous-valued attenuation coefficients for bone. PET/MRI and CT datasets were obtained from 98 subjects (mean age [±SD]: 66yrs [±9.8], 57 females) using an IRB-approved protocol and with informed consent. Subjects were injected with 352±29MBq of (18)F-Florbetapir tracer, and PET acquisitions were begun either immediately or 50min after injection. CT images of the head were acquired separately using a PET/CT system. Dual echo ultrashort echo-time (UTE) images and two-point Dixon images were acquired. Regions of air were segmented via a threshold of the voxel-wise multiplicative inverse of the UTE echo 1 image. Regions of bone were segmented via a threshold of the R2* image computed from the UTE echo 1 and UTE echo 2 images. Regions of fat and soft tissue were segmented using fat and water images decomposed from the Dixon images. Air, fat, and soft tissue were assigned linear attenuation coefficients (LACs) of 0, 0.092, and 0.1cm(-1), respectively. LACs for bone were derived from a regression analysis between corresponding R2* and CT values. PET images were reconstructed using the gold standard CT method and the proposed CAR-RiDR method. The RiDR segmentation method produces mean Dice coefficient±SD across subjects of 0.75±0.05 for bone and 0.60±0.08 for air. The CAR model for bone LACs greatly improves accuracy in estimating CT values (28.2%±3.0 mean error) compared to the use of a constant CT value (46.9%±5.8, punits. From our analysis, we conclude that the proposed method closely approaches (<3% error) the gold standard CT-scaled method in PET reconstruction accuracy
The performance of random coefficient regression in accounting for residual confounding.
Gustafson, Paul; Greenland, Sander
2006-09-01
Greenland (2000, Biometrics 56, 915-921) describes the use of random coefficient regression to adjust for residual confounding in a particular setting. We examine this setting further, giving theoretical and empirical results concerning the frequentist and Bayesian performance of random coefficient regression. Particularly, we compare estimators based on this adjustment for residual confounding to estimators based on the assumption of no residual confounding. This devolves to comparing an estimator from a nonidentified but more realistic model to an estimator from a less realistic but identified model. The approach described by Gustafson (2005, Statistical Science 20, 111-140) is used to quantify the performance of a Bayesian estimator arising from a nonidentified model. From both theoretical calculations and simulations we find support for the idea that superior performance can be obtained by replacing unrealistic identifying constraints with priors that allow modest departures from those constraints. In terms of point-estimator bias this superiority arises when the extent of residual confounding is substantial, but the advantage is much broader in terms of interval estimation. The benefit from modeling residual confounding is maintained when the prior distributions employed only roughly correspond to reality, for the standard identifying constraints are equivalent to priors that typically correspond much worse.
MANCOVA for one way classification with homogeneity of regression coefficient vectors
Mokesh Rayalu, G.; Ravisankar, J.; Mythili, G. Y.
2017-11-01
The MANOVA and MANCOVA are the extensions of the univariate ANOVA and ANCOVA techniques to multidimensional or vector valued observations. The assumption of a Gaussian distribution has been replaced with the Multivariate Gaussian distribution for the vectors data and residual term variables in the statistical models of these techniques. The objective of MANCOVA is to determine if there are statistically reliable mean differences that can be demonstrated between groups later modifying the newly created variable. When randomization assignment of samples or subjects to groups is not possible, multivariate analysis of covariance (MANCOVA) provides statistical matching of groups by adjusting dependent variables as if all subjects scored the same on the covariates. In this research article, an extension has been made to the MANCOVA technique with more number of covariates and homogeneity of regression coefficient vectors is also tested.
Quinino, Roberto C.; Reis, Edna A.; Bessegato, Lupercio F.
2013-01-01
This article proposes the use of the coefficient of determination as a statistic for hypothesis testing in multiple linear regression based on distributions acquired by beta sampling. (Contains 3 figures.)
Chaurasia, Ashok; Harel, Ofer
2015-02-10
Tests for regression coefficients such as global, local, and partial F-tests are common in applied research. In the framework of multiple imputation, there are several papers addressing tests for regression coefficients. However, for simultaneous hypothesis testing, the existing methods are computationally intensive because they involve calculation with vectors and (inversion of) matrices. In this paper, we propose a simple method based on the scalar entity, coefficient of determination, to perform (global, local, and partial) F-tests with multiply imputed data. The proposed method is evaluated using simulated data and applied to suicide prevention data. Copyright © 2014 John Wiley & Sons, Ltd.
Towards molecular design using 2D-molecular contour maps obtained from PLS regression coefficients
Borges, Cleber N.; Barigye, Stephen J.; Freitas, Matheus P.
2017-12-01
The multivariate image analysis descriptors used in quantitative structure-activity relationships are direct representations of chemical structures as they are simply numerical decodifications of pixels forming the 2D chemical images. These MDs have found great utility in the modeling of diverse properties of organic molecules. Given the multicollinearity and high dimensionality of the data matrices generated with the MIA-QSAR approach, modeling techniques that involve the projection of the data space onto orthogonal components e.g. Partial Least Squares (PLS) have been generally used. However, the chemical interpretation of the PLS-based MIA-QSAR models, in terms of the structural moieties affecting the modeled bioactivity has not been straightforward. This work describes the 2D-contour maps based on the PLS regression coefficients, as a means of assessing the relevance of single MIA predictors to the response variable, and thus allowing for the structural, electronic and physicochemical interpretation of the MIA-QSAR models. A sample study to demonstrate the utility of the 2D-contour maps to design novel drug-like molecules is performed using a dataset of some anti-HIV-1 2-amino-6-arylsulfonylbenzonitriles and derivatives, and the inferences obtained are consistent with other reports in the literature. In addition, the different schemes for encoding atomic properties in molecules are discussed and evaluated.
Varying coefficient subdistribution regression for left-truncated semi-competing risks data.
Li, Ruosha; Peng, Limin
2014-10-01
Semi-competing risks data frequently arise in biomedical studies when time to a disease landmark event is subject to dependent censoring by death, the observation of which however is not precluded by the occurrence of the landmark event. In observational studies, the analysis of such data can be further complicated by left truncation. In this work, we study a varying co-efficient subdistribution regression model for left-truncated semi-competing risks data. Our method appropriately accounts for the specifical truncation and censoring features of the data, and moreover has the flexibility to accommodate potentially varying covariate effects. The proposed method can be easily implemented and the resulting estimators are shown to have nice asymptotic properties. We also present inference, such as Kolmogorov-Smirnov type and Cramér Von-Mises type hypothesis testing procedures for the covariate effects. Simulation studies and an application to the Denmark diabetes registry demonstrate good finite-sample performance and practical utility of the proposed method.
Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi
2018-04-01
Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.
DEFF Research Database (Denmark)
Bini, L. M.; Diniz-Filho, J. A. F.; Rangel, T. F. L. V. B.
2009-01-01
A major focus of geographical ecology and macroecology is to understand the causes of spatially structured ecological patterns. However, achieving this understanding can be complicated when using multiple regression, because the relative importance of explanatory variables, as measured by regress...
Directory of Open Access Journals (Sweden)
METİN KAMİL ERCAN
2013-06-01
Full Text Available It is possible to determine the value of private companies by means of suggestions and assumptions derived from their financial statements. However, there comes out a serious problem in the determination of equity costs of these private companies using Capital Assets Pricing Model (CAPM as beta coefficients are unknown or unavailable. In this study, firstly, a regression model that represents the relationship between the beta coefficients and financial statements’ Variables of publicly-held companies will be developed. Then, this model will be tested and applied on private companies.
International Nuclear Information System (INIS)
Ghasemi, Jahanbakhsh; Saaidpour, Saadi
2007-01-01
A quantitative structure-property relationship (QSPR) study was performed to develop models those relate the structures of 150 drug organic compounds to their n-octanol-water partition coefficients (log P o/w ). Molecular descriptors derived solely from 3D structures of the molecular drugs. A genetic algorithm was also applied as a variable selection tool in QSPR analysis. The models were constructed using 110 molecules as training set, and predictive ability tested using 40 compounds. Modeling of log P o/w of these compounds as a function of the theoretically derived descriptors was established by multiple linear regression (MLR). Four descriptors for these compounds molecular volume (MV) (geometrical), hydrophilic-lipophilic balance (HLB) (constitutional), hydrogen bond forming ability (HB) (electronic) and polar surface area (PSA) (electrostatic) are taken as inputs for the model. The use of descriptors calculated only from molecular structure eliminates the need for experimental determination of properties for use in the correlation and allows for the estimation of log P o/w for molecules not yet synthesized. Application of the developed model to a testing set of 40 drug organic compounds demonstrates that the model is reliable with good predictive accuracy and simple formulation. The prediction results are in good agreement with the experimental value. The root mean square error of prediction (RMSEP) and square correlation coefficient (R 2 ) for MLR model were 0.22 and 0.99 for the prediction set log P o/w
International Nuclear Information System (INIS)
Elliott Campbell, J.; Moen, Jeremie C.; Ney, Richard A.; Schnoor, Jerald L.
2008-01-01
Estimates of forest soil organic carbon (SOC) have applications in carbon science, soil quality studies, carbon sequestration technologies, and carbon trading. Forest SOC has been modeled using a regression coefficient methodology that applies mean SOC densities (mass/area) to broad forest regions. A higher resolution model is based on an approach that employs a geographic information system (GIS) with soil databases and satellite-derived landcover images. Despite this advancement, the regression approach remains the basis of current state and federal level greenhouse gas inventories. Both approaches are analyzed in detail for Wisconsin forest soils from 1983 to 2001, applying rigorous error-fixing algorithms to soil databases. Resulting SOC stock estimates are 20% larger when determined using the GIS method rather than the regression approach. Average annual rates of increase in SOC stocks are 3.6 and 1.0 million metric tons of carbon per year for the GIS and regression approaches respectively. - Large differences in estimates of soil organic carbon stocks and annual changes in stocks for Wisconsin forestlands indicate a need for validation from forthcoming forest surveys
Freitas, Alex A; Limbu, Kriti; Ghafourian, Taravat
2015-01-01
Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Graphical AbstractDecision trees for the prediction of tissue partition coefficient and volume of distribution of drugs.
National Aeronautics and Space Administration — Robonaut 2, a crew assistant robotic prototype, will be integrated with IBM’s Watson. R2 will embody the artificial intelligence to enable new levels of robotic...
Directory of Open Access Journals (Sweden)
Mehmet Das
2018-01-01
Full Text Available In this study, an air heated solar collector (AHSC dryer was designed to determine the drying characteristics of the pear. Flat pear slices of 10 mm thickness were used in the experiments. The pears were dried both in the AHSC dryer and under the sun. Panel glass temperature, panel floor temperature, panel inlet temperature, panel outlet temperature, drying cabinet inlet temperature, drying cabinet outlet temperature, drying cabinet temperature, drying cabinet moisture, solar radiation, pear internal temperature, air velocity and mass loss of pear were measured at 30 min intervals. Experiments were carried out during the periods of June 2017 in Elazig, Turkey. The experiments started at 8:00 a.m. and continued till 18:00. The experiments were continued until the weight changes in the pear slices stopped. Wet basis moisture content (MCw, dry basis moisture content (MCd, adjustable moisture ratio (MR, drying rate (DR, and convective heat transfer coefficient (hc were calculated with both in the AHSC dryer and the open sun drying experiment data. It was found that the values of hc in both drying systems with a range 12.4 and 20.8 W/m2 °C. Three different kernel models were used in the support vector machine (SVM regression to construct the predictive model of the calculated hc values for both systems. The mean absolute error (MAE, root mean squared error (RMSE, relative absolute error (RAE and root relative absolute error (RRAE analysis were performed to indicate the predictive model’s accuracy. As a result, the rate of drying of the pear was examined for both systems and it was observed that the pear had dried earlier in the AHSC drying system. A predictive model was obtained using the SVM regression for the calculated hc values for the pear in the AHSC drying system. The normalized polynomial kernel was determined as the best kernel model in SVM for estimating the hc values.
Coskuntuncel, Orkun
2013-01-01
The purpose of this study is two-fold; the first aim being to show the effect of outliers on the widely used least squares regression estimator in social sciences. The second aim is to compare the classical method of least squares with the robust M-estimator using the "determination of coefficient" (R[superscript 2]). For this purpose,…
Directory of Open Access Journals (Sweden)
Sergei Vladimirovich Varaksin
2017-06-01
Full Text Available Purpose. Construction of a mathematical model of the dynamics of childbearing change in the Altai region in 2000–2016, analysis of the dynamics of changes in birth rates for multiple age categories of women of childbearing age. Methodology. A auxiliary analysis element is the construction of linear mathematical models of the dynamics of childbearing by using fuzzy linear regression method based on fuzzy numbers. Fuzzy linear regression is considered as an alternative to standard statistical linear regression for short time series and unknown distribution law. The parameters of fuzzy linear and standard statistical regressions for childbearing time series were defined with using the built in language MatLab algorithm. Method of fuzzy linear regression is not used in sociological researches yet. Results. There are made the conclusions about the socio-demographic changes in society, the high efficiency of the demographic policy of the leadership of the region and the country, and the applicability of the method of fuzzy linear regression for sociological analysis.
International Nuclear Information System (INIS)
Chilenski, M.A.; Greenwald, M.; Howard, N.T.; White, A.E.; Rice, J.E.; Walk, J.R.; Marzouk, Y.
2015-01-01
The need to fit smooth temperature and density profiles to discrete observations is ubiquitous in plasma physics, but the prevailing techniques for this have many shortcomings that cast doubt on the statistical validity of the results. This issue is amplified in the context of validation of gyrokinetic transport models (Holland et al 2009 Phys. Plasmas 16 052301), where the strong sensitivity of the code outputs to input gradients means that inadequacies in the profile fitting technique can easily lead to an incorrect assessment of the degree of agreement with experimental measurements. In order to rectify the shortcomings of standard approaches to profile fitting, we have applied Gaussian process regression (GPR), a powerful non-parametric regression technique, to analyse an Alcator C-Mod L-mode discharge used for past gyrokinetic validation work (Howard et al 2012 Nucl. Fusion 52 063002). We show that the GPR techniques can reproduce the previous results while delivering more statistically rigorous fits and uncertainty estimates for both the value and the gradient of plasma profiles with an improved level of automation. We also discuss how the use of GPR can allow for dramatic increases in the rate of convergence of uncertainty propagation for any code that takes experimental profiles as inputs. The new GPR techniques for profile fitting and uncertainty propagation are quite useful and general, and we describe the steps to implementation in detail in this paper. These techniques have the potential to substantially improve the quality of uncertainty estimates on profile fits and the rate of convergence of uncertainty propagation, making them of great interest for wider use in fusion experiments and modelling efforts. (paper)
Changes in persistence, spurious regressions and the Fisher hypothesis
DEFF Research Database (Denmark)
Kruse, Robinson; Ventosa-Santaulària, Daniel; Noriega, Antonio E.
Declining inflation persistence has been documented in numerous studies. When such series are analyzed in a regression framework in conjunction with other persistent time series, spurious regressions are likely to occur. We propose to use the coefficient of determination R2 as a test statistic to...
Nimon, Kim; Lewis, Mitzi; Kane, Richard; Haynes, R Michael
2008-05-01
Multiple regression is a widely used technique for data analysis in social and behavioral research. The complexity of interpreting such results increases when correlated predictor variables are involved. Commonality analysis provides a method of determining the variance accounted for by respective predictor variables and is especially useful in the presence of correlated predictors. However, computing commonality coefficients is laborious. To make commonality analysis accessible to more researchers, a program was developed to automate the calculation of unique and common elements in commonality analysis, using the statistical package R. The program is described, and a heuristic example using data from the Holzinger and Swineford (1939) study, readily available in the MBESS R package, is presented.
Golmohammadi, Hassan
2009-11-30
A quantitative structure-property relationship (QSPR) study was performed to develop models those relate the structure of 141 organic compounds to their octanol-water partition coefficients (log P(o/w)). A genetic algorithm was applied as a variable selection tool. Modeling of log P(o/w) of these compounds as a function of theoretically derived descriptors was established by multiple linear regression (MLR), partial least squares (PLS), and artificial neural network (ANN). The best selected descriptors that appear in the models are: atomic charge weighted partial positively charged surface area (PPSA-3), fractional atomic charge weighted partial positive surface area (FPSA-3), minimum atomic partial charge (Qmin), molecular volume (MV), total dipole moment of molecule (mu), maximum antibonding contribution of a molecule orbital in the molecule (MAC), and maximum free valency of a C atom in the molecule (MFV). The result obtained showed the ability of developed artificial neural network to prediction of partition coefficients of organic compounds. Also, the results revealed the superiority of ANN over the MLR and PLS models. Copyright 2009 Wiley Periodicals, Inc.
Garcia-Garcia, A L; Alvarez-Vera, M; Montoya-Santiyanes, L A; Dominguez-Lopez, I; Montes-Seguedo, J L; Sosa-Savedra, J C; Barceinas-Sanchez, J D O
2018-06-01
Friction is the natural response of all tribosystems. In a total knee replacement (TKR) prosthetic device, its measurement is hindered by the complex geometry of its integrating parts and that of the testing simulation rig operating under the ISO 14243-3:2014 standard. To develop prediction models of the coefficient of friction (COF) between AISI 316L steel and ultra-high molecular weight polyethylene (UHMWPE) lubricated with fetal bovine serum dilutions, the arthrokinematics and loading conditions prescribed by the ISO 142433: 2014 standard were translated to a simpler geometrical setup, via Hertz contact theory. Tribological testing proceeded by loading a stainless steel AISI 316L ball against the surface of a UHMWPE disk, with the test fluid at 37 °C. The method has been applied to study the behavior of the COF during a whole walking cycle. On the other hand, the role of protein aggregation phenomena as a lubrication mechanism has been extensively studied in hip joint replacements but little explored for the operating conditions of a TKR. Lubricant testing fluids were prepared with fetal bovine serum (FBS) dilutions having protein mass concentrations of 5, 10, 20 and 36 g/L. The results were contrasted against deionized, sterilized water. The results indicate that even at protein concentration as low as 5 g/L, protein aggregation phenomena play an important role in the lubrication of the metal-on-polymer tribopair. The regression models of the COF developed herein are available for numerical simulations of the tribological behavior of the aforementioned tribosystem. In this case, surface stress rather than film thickness should be considered. Copyright © 2018 Elsevier Ltd. All rights reserved.
R2 dark energy in the laboratory
Brax, Philippe; Valageas, Patrick; Vanhove, Pierre
2018-05-01
We analyze the role, on large cosmological scales and laboratory experiments, of the leading curvature squared contributions to the low-energy effective action of gravity. We argue for a natural relationship c0λ2≃1 at low energy between the R2 coefficients c0 of the Ricci scalar squared term in this expansion and the dark energy scale Λ =(λ MPl)4 in four-dimensional Planck mass units. We show how the compatibility between the acceleration of the expansion rate of the Universe, local tests of gravity and the quantum stability of the model all converge to select such a relationship up to a coefficient which should be determined experimentally. When embedding this low-energy theory of gravity into candidates for its ultraviolet completion, we find that the proposed relationship is guaranteed in string-inspired supergravity models with modulus stabilization and supersymmetry breaking leading to de Sitter compactifications. In this case, the scalar degree of freedom of R2 gravity is associated to a volume modulus. Once written in terms of a scalar-tensor theory, the effective theory corresponds to a massive scalar field coupled with the universal strength β =1 /√{6 } to the matter stress-energy tensor. When the relationship c0λ2≃1 is realized, we find that on astrophysical scales and in cosmology the scalar field is ultralocal and therefore no effect arises on such large scales. On the other hand, the scalar field mass is tightly constrained by the nonobservation of fifth forces in torsion pendulum experiments such as Eöt-Wash. It turns out that the observation of the dark energy scale in cosmology implies that the scalar field could be detectable by fifth-force experiments in the near future.
The number of subjects per variable required in linear regression analyses.
Austin, Peter C; Steyerberg, Ewout W
2015-06-01
To determine the number of independent variables that can be included in a linear regression model. We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression coefficients and standard errors, on the empirical coverage of estimated confidence intervals, and on the accuracy of the estimated R(2) of the fitted model. A minimum of approximately two SPV tended to result in estimation of regression coefficients with relative bias of less than 10%. Furthermore, with this minimum number of SPV, the standard errors of the regression coefficients were accurately estimated and estimated confidence intervals had approximately the advertised coverage rates. A much higher number of SPV were necessary to minimize bias in estimating the model R(2), although adjusted R(2) estimates behaved well. The bias in estimating the model R(2) statistic was inversely proportional to the magnitude of the proportion of variation explained by the population regression model. Linear regression models require only two SPV for adequate estimation of regression coefficients, standard errors, and confidence intervals. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
Guan, Ji-Jing; Feng, Yan-Qiu
2018-03-20
To evaluate the accuracy and sensitivity of quantitative susceptibility mapping (QSM) and transverse relaxation rate (R2*) mapping in the measurement of brain iron deposition. Super paramagnetic iron oxide (SPIO) phantoms and mouse models of Parkinson's disease (PD) related to iron deposition in the substantia nigra (SN) underwent 7.0 T magnetic resonance (MR) scans (Bruker, 70/16) with a multi-echo 3D gradient echo sequence, and the acquired data were processed to obtain QSM and R2*. Linear regression analysis was performed for susceptibility and R2* in the SPIO phantoms containing 5 SPIO concentrations (30, 15, 7.5, 3.75 and 1.875 µg/mL) to evaluate the accuracy of QSM and R2* in quantitative iron analysis. The sensitivities of QSM and R2* mapping in quantitative detection of brain iron deposition were assessed using mouse models of PD induced by 1-methyl-4-phenyl-1,2,3,6-tetrahy-dropyridine (MPTP) in comparison with the control mice. In SPIO phantoms, QSM provided a higher accuracy than R2* mapping and their goodness-of-fit coefficients (R 2 ) were 0.98 and 0.89, respectively. In the mouse models of PD and control mice, the susceptibility of the SN was significantly higher in the PD models (5.19∓1.58 vs 2.98∓0.88, n=5; Pbrain iron deposition than R2*, and the susceptibility derived by QSM can be a potentially useful biomarker for studying PD.
[From clinical judgment to linear regression model.
Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O
2013-01-01
When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R 2 ) indicates the importance of independent variables in the outcome.
International Nuclear Information System (INIS)
Kumar, Ajay; Ravi, P.M.; Guneshwar, S.L.; Rout, Sabyasachi; Mishra, Manish K.; Pulhani, Vandana; Tripathi, R.M.
2018-01-01
Numerous common methods (batch laboratory, the column laboratory, field-batch method, field modeling and K 0c method) are used frequently for determination of K d values. Recently, multiple regression models are considered as new best estimates for predicting the K d of radionuclides in the environment. It is also well known fact that the K d value is highly influenced by physico-chemical properties of sediment. Due to the significant variability in influencing parameters, the measured K d values can range over several orders of magnitude under different environmental conditions. The aim of this study is to develop a predictive model for K d values of 137 Cs and 60 Co based on the sediment properties using multiple linear regression analysis
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...
Energy Technology Data Exchange (ETDEWEB)
Canciam, Cesar Augusto [Universidade Tecnologica Federal do Parana (UTFPR), Campus Ponta Grossa, PR (Brazil)], e-mail: canciam@utfpr.edu.br
2012-07-01
When evaluating the consumption of bio fuels, the knowledge of the density is of great importance for rectify the effect of temperature. The thermal expansion coefficient is a thermodynamic property that provides a measure of the density variation in response to temperature variation, keeping the pressure constant. This study aimed to predict the thermal expansion coefficients of ethyl bio diesels from castor beans, soybeans, sunflower seeds and Mabea fistulifera Mart. oils and of methyl bio diesels from soybeans, sunflower seeds, souari nut, cotton, coconut, castor beans and palm oils, from beef tallow, chicken fat and hydrogenated vegetable fat residual. For this purpose, there was a linear regression analysis of the density of each bio diesel a function of temperature. These data were obtained from other works. The thermal expansion coefficients for bio diesels are between 6.3729x{sup 10-4} and 1.0410x10{sup -3} degree C-1. In all the cases, the correlation coefficients were over 0.99. (author)
Mastering Microsoft Windows Server 2008 R2
Minasi, Mark; Finn, Aidan
2010-01-01
The one book you absolutely need to get up and running with Windows Server 2008 R2. One of the world's leading Windows authorities and top-selling author Mark Minasi explores every nook and cranny of the latest version of Microsoft's flagship network operating system, Windows Server 2008 R2, giving you the most in-depth coverage in any book on the market.: Focuses on Windows Windows Server 2008 R2, the newest version of Microsoft's Windows' server line of operating system, and the ideal server for new Windows 7 clients; Author Mark Minasi is one of the world's leading Windows authorities and h
Nakamura, Kengo; Yasutaka, Tetsuo; Kuwatani, Tatsu; Komai, Takeshi
2017-11-01
In this study, we applied sparse multiple linear regression (SMLR) analysis to clarify the relationships between soil properties and adsorption characteristics for a range of soils across Japan and identify easily-obtained physical and chemical soil properties that could be used to predict K and n values of cadmium, lead and fluorine. A model was first constructed that can easily predict the K and n values from nine soil parameters (pH, cation exchange capacity, specific surface area, total carbon, soil organic matter from loss on ignition and water holding capacity, the ratio of sand, silt and clay). The K and n values of cadmium, lead and fluorine of 17 soil samples were used to verify the SMLR models by the root mean square error values obtained from 512 combinations of soil parameters. The SMLR analysis indicated that fluorine adsorption to soil may be associated with organic matter, whereas cadmium or lead adsorption to soil is more likely to be influenced by soil pH, IL. We found that an accurate K value can be predicted from more than three soil parameters for most soils. Approximately 65% of the predicted values were between 33 and 300% of their measured values for the K value; 76% of the predicted values were within ±30% of their measured values for the n value. Our findings suggest that adsorption properties of lead, cadmium and fluorine to soil can be predicted from the soil physical and chemical properties using the presented models. Copyright © 2017 Elsevier Ltd. All rights reserved.
Using R2* values to evaluate brain tumours on magnetic resonance imaging: Preliminary results
International Nuclear Information System (INIS)
Liu, Zhenghua; Liao, Haibo; Yin, Jianhua; Li, Yanfang
2014-01-01
To determine the usefulness of the R2* value in assessing the histopathological grade of glioma at magnetic resonance imaging and differentiating various brain tumours. Sixty-four patients with brain tumours underwent R2* mapping and diffusion-weighted imaging examinations. ANOVA was performed to analyse R2* values among four groups of glioma and among high-grade gliomas (grades III and IV), low-grade gliomas (grades I and II), meningiomas, and brain metastasis. Spearman's correlation coefficients were used to determine the relationships between the R2* values or apparent diffusion coefficient (ADC) and the histopathological grade of gliomas. R2* values of low- and high-grade gliomas were analysed with the receiver-operator characteristic curve. R2* values were significantly different among high-grade gliomas, low-grade gliomas, meningiomas, and brain metastasis, but not between grade I and grade II or between grade III and grade IV. The R2* value (18.73) of high-grade gliomas provided a very high sensitivity and specificity for differentiating low-grade gliomas. A strong correlation existed between the R2* value and the pathological grade of gliomas. R2* mapping is a useful sequence for determining grade of gliomas and in distinguishing benign from malignant tumours. R2* values are better than ADC for characterising gliomas. (orig.)
The Monoceros R2 Molecular Cloud
Carpenter, J. M.; Hodapp, K. W.
2008-12-01
The Monoceros R2 region was first recognized as a chain of reflection nebulae illuminated by A- and B-type stars. These nebulae are associated with a giant molecular cloud that is one of the closest massive star forming regions to the Sun. This chapter reviews the properties of the Mon R2 region, including the namesake reflection nebulae, the large scale molecula= r cloud, global star formation activity, and properties of prominent star forming regions in the cloud.
Mean centering, multicollinearity, and moderators in multiple regression: The reconciliation redux.
Iacobucci, Dawn; Schneider, Matthew J; Popovich, Deidre L; Bakamitsos, Georgios A
2017-02-01
In this article, we attempt to clarify our statements regarding the effects of mean centering. In a multiple regression with predictors A, B, and A × B (where A × B serves as an interaction term), mean centering A and B prior to computing the product term can clarify the regression coefficients (which is good) and the overall model fit R 2 will remain undisturbed (which is also good).
Granato, Gregory E.
2006-01-01
The Kendall-Theil Robust Line software (KTRLine-version 1.0) is a Visual Basic program that may be used with the Microsoft Windows operating system to calculate parameters for robust, nonparametric estimates of linear-regression coefficients between two continuous variables. The KTRLine software was developed by the U.S. Geological Survey, in cooperation with the Federal Highway Administration, for use in stochastic data modeling with local, regional, and national hydrologic data sets to develop planning-level estimates of potential effects of highway runoff on the quality of receiving waters. The Kendall-Theil robust line was selected because this robust nonparametric method is resistant to the effects of outliers and nonnormality in residuals that commonly characterize hydrologic data sets. The slope of the line is calculated as the median of all possible pairwise slopes between points. The intercept is calculated so that the line will run through the median of input data. A single-line model or a multisegment model may be specified. The program was developed to provide regression equations with an error component for stochastic data generation because nonparametric multisegment regression tools are not available with the software that is commonly used to develop regression models. The Kendall-Theil robust line is a median line and, therefore, may underestimate total mass, volume, or loads unless the error component or a bias correction factor is incorporated into the estimate. Regression statistics such as the median error, the median absolute deviation, the prediction error sum of squares, the root mean square error, the confidence interval for the slope, and the bias correction factor for median estimates are calculated by use of nonparametric methods. These statistics, however, may be used to formulate estimates of mass, volume, or total loads. The program is used to read a two- or three-column tab-delimited input file with variable names in the first row and
Predictive power of Brazilian equity fund performance using R2 as a measure of selectivity
Directory of Open Access Journals (Sweden)
Marcelo dos Santos Guzella
2017-03-01
Full Text Available ABSTRACT This paper aimed to investigate the impact of levels of selectivity on the performance of equity funds using a methodology applied for the first time ever (as far as we know in the Brazilian market. As an indicator of the activity level of a fund, we proposed the coefficient of determination (R2 of the regression of its returns over market returns. In total, 867 funds were analyzed in the period between November 2004 and October 2014. The hypothesis tested is that more selective funds perform better to compensate for their higher operating costs. This hypothesis was confirmed in the Brazilian market. Dynamic equally-weighted portfolios of funds were simulated, according to their past R2 and alphas, with monthly rebalancing and 12-month moving windows. The portfolio of the most selective funds had a Sharpe ratio of 0.0494, on a monthly basis, while the portfolio of the least selective funds had a Sharpe ratio of -0.0314. Performance was also higher in evaluations involving excess returns, Jensen’s alpha, and accumulated returns, as well as when compared to randomly selected portfolios. Moreover, past performance (as measured by Jensen’s alpha was also a predictor of future performance. Particularly, the portfolio composed by funds with a higher past alpha and lower past R2 presented a Sharpe ratio of 0.1483 and a Jensen’s alpha of 0.87% (significant at 1%, while the one composed of funds with a lower past alpha and lower activity level presented a Sharpe ratio of -0.0673 and an alpha of -0.32% (also significant at 1%.
Windows Server 2012 R2 administrator cookbook
Krause, Jordan
2015-01-01
This book is intended for system administrators and IT professionals with experience in Windows Server 2008 or Windows Server 2012 environments who are looking to acquire the skills and knowledge necessary to manage and maintain the core infrastructure required for a Windows Server 2012 and Windows Server 2012 R2 environment.
Studsvik's R2 reactor - Review of activities
Energy Technology Data Exchange (ETDEWEB)
Grounes, Mikael; Tomani, Hans; Graeslund, Christian; Rundquist, Hans; Skoeld, Kurt [Studsvik Nuclear AB, Nykoeping (Sweden)
1993-07-01
A general description of the R2 reactor, its associated facilities and its history is given. The facilities and range of work are described for the following types of activities: fuel testing, materials testing, neutron transmutation doping of silicon, activation analysis, radioisotope production and basic research including thermal neutron scattering, nuclear chemistry and neutron capture radiography. (author)
Mastering Windows Server 2012 R2
Minasi, Mark; Booth, Christian; Butler, Robert; McCabe, John; Panek, Robert; Rice, Michael; Roth, Stefan
2013-01-01
Check out the new Hyper-V, find new and easier ways to remotely connect back into the office, or learn all about Storage Spaces-these are just a few of the features in Windows Server 2012 R2 that are explained in this updated edition from Windows authority Mark Minasi and a team of Windows Server experts led by Kevin Greene. This book gets you up to speed on all of the new features and functions of Windows Server, and includes real-world scenarios to put them in perspective. If you're a system administrator upgrading to, migrating to, or managing Windows Server 2012 R2, find what you need to
R2 inflation in anisotropic universes
International Nuclear Information System (INIS)
Berkin, A.L.
1990-01-01
The evolution of Bianchi type-I and type-IX universes for a theory of gravity with an εR 2 term added to the usual Lagrangian is considered. As in the spatially flat Robertson-Walker case considered previously by others, inflation is found to occur. For any amount of initial anisotropy, the anisotropy decays quickly relative to the length of the inflationary epoch, and the amount of expansion is enhanced by the anisotropy. The exceptions are Bianchi type-IX universes near or at isotropy. In these cases a wide range of initial parameters causes the universe to recollapse, thus reducing the phase space in which inflation can occur. The diagonal metric is shown to be the most general form in the R 2 theory for both Bianchi type-I universes with a perfect fluid and vacuum Bianchi type-IX models
Multiple linear regression analysis
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.
Path coefficient analysis of zinc dynamics in varying soil environment
International Nuclear Information System (INIS)
Rattan, R.K.; Phung, C.V.; Singhal, S.K.; Deb, D.L.; Singh, A.K.
1994-01-01
Influence of soil properties on labile zinc, as measured by diethylene-triamine pentaacetic acid (DTPA) and zinc-65, and self-diffusion coefficients of zinc was assessed on 22 surface soil samples varying widely in their characteristics following linear regression and path coefficient analysis techniques. DTPA extractable zinc could be predicted from organic carbon status and pH of the soil with a highly significant coefficient of determination (R 2 =0.84 ** ). Ninety seven per cent variation in isotopically exchangeable zinc was explained by pH, clay content and cation exchange capacity (CEC) of soil. The self-diffusion coefficients (DaZn and DpZn) and buffer power of zinc exhibited exponential relationship with soil properties, pH being the most dominant one. Soil properties like organic matter, clay content etc. exhibited indirect effects on zinc diffusion rates via pH only. (author). 13 refs., 6 tabs
International Nuclear Information System (INIS)
Loeffler, Ralf B.; McCarville, M.B.; Song, Ruitian; Hillenbrand, Claudia M.; Wagstaff, Anne W.; Smeltzer, Matthew P.; Krafft, Axel J.; Hankins, Jane S.
2017-01-01
Liver R2* values calculated from multi-gradient echo (mGRE) magnetic resonance images (MRI) are strongly correlated with hepatic iron concentration (HIC) as shown in several independently derived biopsy calibration studies. These calibrations were established for axial single-slice breath-hold imaging at the location of the portal vein. Scanning in multi-slice mode makes the exam more efficient, since whole-liver coverage can be achieved with two breath-holds and the optimal slice can be selected afterward. Navigator echoes remove the need for breath-holds and allow use in sedated patients. To evaluate if the existing biopsy calibrations can be applied to multi-slice and navigator-controlled mGRE imaging in children with hepatic iron overload, by testing if there is a bias-free correlation between single-slice R2* and multi-slice or multi-slice navigator controlled R2*. This study included MRI data from 71 patients with transfusional iron overload, who received an MRI exam to estimate HIC using gradient echo sequences. Patient scans contained 2 or 3 of the following imaging methods used for analysis: single-slice images (n = 71), multi-slice images (n = 69) and navigator-controlled images (n = 17). Small and large blood corrected region of interests were selected on axial images of the liver to obtain R2* values for all data sets. Bland-Altman and linear regression analysis were used to compare R2* values from single-slice images to those of multi-slice images and navigator-controlled images. Bland-Altman analysis showed that all imaging method comparisons were strongly associated with each other and had high correlation coefficients (0.98 ≤ r ≤ 1.00) with P-values ≤0.0001. Linear regression yielded slopes that were close to 1. We found that navigator-gated or breath-held multi-slice R2* MRI for HIC determination measures R2* values comparable to the biopsy-validated single-slice, single breath-hold scan. We conclude that these three R2* methods can be
Energy Technology Data Exchange (ETDEWEB)
Loeffler, Ralf B.; McCarville, M.B.; Song, Ruitian; Hillenbrand, Claudia M. [St. Jude Children' s Research Hospital, Diagnostic Imaging, Memphis, TN (United States); Wagstaff, Anne W. [St. Jude Children' s Research Hospital, Diagnostic Imaging, Memphis, TN (United States); Rhodes College, Memphis, TN (United States); University of Alabama at Birmingham School of Medicine, Birmingham, AL (United States); Smeltzer, Matthew P. [St. Jude Children' s Research Hospital, Department of Biostatistics, Memphis, TN (United States); University of Memphis, Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, Memphis, TN (United States); Krafft, Axel J. [St. Jude Children' s Research Hospital, Diagnostic Imaging, Memphis, TN (United States); University Hospital Center Freiburg, Department of Radiology, Freiburg (Germany); Hankins, Jane S. [St. Jude Children' s Research Hospital, Department of Hematology, Memphis, TN (United States)
2017-01-15
Liver R2* values calculated from multi-gradient echo (mGRE) magnetic resonance images (MRI) are strongly correlated with hepatic iron concentration (HIC) as shown in several independently derived biopsy calibration studies. These calibrations were established for axial single-slice breath-hold imaging at the location of the portal vein. Scanning in multi-slice mode makes the exam more efficient, since whole-liver coverage can be achieved with two breath-holds and the optimal slice can be selected afterward. Navigator echoes remove the need for breath-holds and allow use in sedated patients. To evaluate if the existing biopsy calibrations can be applied to multi-slice and navigator-controlled mGRE imaging in children with hepatic iron overload, by testing if there is a bias-free correlation between single-slice R2* and multi-slice or multi-slice navigator controlled R2*. This study included MRI data from 71 patients with transfusional iron overload, who received an MRI exam to estimate HIC using gradient echo sequences. Patient scans contained 2 or 3 of the following imaging methods used for analysis: single-slice images (n = 71), multi-slice images (n = 69) and navigator-controlled images (n = 17). Small and large blood corrected region of interests were selected on axial images of the liver to obtain R2* values for all data sets. Bland-Altman and linear regression analysis were used to compare R2* values from single-slice images to those of multi-slice images and navigator-controlled images. Bland-Altman analysis showed that all imaging method comparisons were strongly associated with each other and had high correlation coefficients (0.98 ≤ r ≤ 1.00) with P-values ≤0.0001. Linear regression yielded slopes that were close to 1. We found that navigator-gated or breath-held multi-slice R2* MRI for HIC determination measures R2* values comparable to the biopsy-validated single-slice, single breath-hold scan. We conclude that these three R2* methods can be
Spady, Richard; Stouli, Sami
2012-01-01
We propose dual regression as an alternative to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile regression often produces in practice. Our approach introduces a mathematical programming characterization of conditional distribution f...
Recursive Algorithm For Linear Regression
Varanasi, S. V.
1988-01-01
Order of model determined easily. Linear-regression algorithhm includes recursive equations for coefficients of model of increased order. Algorithm eliminates duplicative calculations, facilitates search for minimum order of linear-regression model fitting set of data satisfactory.
Biostatistics Series Module 6: Correlation and Linear Regression.
Hazra, Avijit; Gogtay, Nithya
2016-01-01
Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.
Directory of Open Access Journals (Sweden)
Lorentz JÄNTSCHI
2006-01-01
Full Text Available Octanol-water partition coefficient of two hundred and six polychlorinated biphenyls was model by the use of an original method based on complex information obtained from compounds structure. The regression analysis shows that best results are obtained in four-varied model (r2 = 0.9168. The prediction ability of the model was studied through leave-one-out analysis (r2cv(loo = 0.9093 and in training and test sets analysis. Modeling the octanol-water partition coefficient of polychlorinated biphenyls by integration of complex structural information provide a stable and performing four-varied model, allowing us to make remarks about relationship between structure of polychlorinated biphenyls and associated octanol-water partition coefficients.
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...
Center type performance of differentiable vector fields in R2
International Nuclear Information System (INIS)
Rabanal, Roland
2007-08-01
Let X : R 2 / D → R 2 be a differentiable vector field, where D is compact. If the eigenvalues of the jacobian matrix DX z are (nonzero) purely imaginary, for all z element of R 2 / D . Then, X + v has a center type performance at infinity, for some v element of R 2 . More precisely, X + v has a periodic trajectory Γ subset of R2/ D which is surrounding D such that in the unbounded component of (R 2 / D )/ Γ all the trajectories of X + v are nontrivial cycles. In the case of global vector fields Y : R 2 → R 2 with Y (0) = 0, we prove that such eigenvalue condition implies the topological equivalency of Y with the linear vector field (x, y) → (-y, x). (author)
Zhang, Hongyang; Welch, William J.; Zamar, Ruben H.
2017-01-01
Tomal et al. (2015) introduced the notion of "phalanxes" in the context of rare-class detection in two-class classification problems. A phalanx is a subset of features that work well for classification tasks. In this paper, we propose a different class of phalanxes for application in regression settings. We define a "Regression Phalanx" - a subset of features that work well together for prediction. We propose a novel algorithm which automatically chooses Regression Phalanxes from high-dimensi...
Multicenter R2* mapping in the healthy brain
DEFF Research Database (Denmark)
Ropele, Stefan; Wattjes, Mike P; Langkammer, Christian
2014-01-01
structures. METHODS: R2* mapping was performed in 81 healthy subjects in seven centers using different 3 T systems. R2* was calculated from a dual-echo gradient echo sequence and was assessed in several deep gray matter structures. The inter-scanner and inter-subject variability of R2* was calculated...
Directory of Open Access Journals (Sweden)
Mok Tik
2014-06-01
Full Text Available This study formulates regression of vector data that will enable statistical analysis of various geodetic phenomena such as, polar motion, ocean currents, typhoon/hurricane tracking, crustal deformations, and precursory earthquake signals. The observed vector variable of an event (dependent vector variable is expressed as a function of a number of hypothesized phenomena realized also as vector variables (independent vector variables and/or scalar variables that are likely to impact the dependent vector variable. The proposed representation has the unique property of solving the coefficients of independent vector variables (explanatory variables also as vectors, hence it supersedes multivariate multiple regression models, in which the unknown coefficients are scalar quantities. For the solution, complex numbers are used to rep- resent vector information, and the method of least squares is deployed to estimate the vector model parameters after transforming the complex vector regression model into a real vector regression model through isomorphism. Various operational statistics for testing the predictive significance of the estimated vector parameter coefficients are also derived. A simple numerical example demonstrates the use of the proposed vector regression analysis in modeling typhoon paths.
Safe dismantling of the SVAFO research reactors R2 and R2-0 in Sweden
International Nuclear Information System (INIS)
ARNOLD, Hans-Uwe; BROY, Yvonne; Dirk Schneider
2017-01-01
The R2 and R2-0 reactors were part of the Swedish government's research program on nuclear power from the early 1960's. Both reactors were shut down in 2005 following a decision by former operator Studsvik Nuclear AB. The decommissioning of the R2 and R2-0 reactors is divided into three phases. The first phase - awarded to AREVA - involved dismantling of the reactors and associated systems in the reactor pool, treatment of the disassembled components as well as draining, cleaning and emptying the pool. In the second phase, the pool structure itself will be dismantled, while removal of remaining reactor systems, treatment and disposal of materials and clean-up will be carried out in the third stage. The entire work is planned to be completed before the end of this decade. The paper describes the several steps of phase 1 - starting with the team building, followed by the dismantling operations and covers challenges encountered and lessons learned as well. The reactors consist of 5.400 kg aluminum, 6.000 kg stainless steel restraint structures as well as, connection elements of the mostly flanged components (1.000 kg). The most demanding - from a radiological point of view - was the R2-0 reactor that was limited to ∼ 1 m"3 construction volumes but with an extremely heterogeneous activation profile. Based on the calculated radiological entrance data and later sampling, nuclide vectors for both reactors depending on the real placement of the single component and on the material (aluminum and stainless steel) were created. Finally, for the highest activated component from R2 reactor, 85 Sv/h were measured. The dismantling principles - adopted on a safety point of view - were the following: The always protected base area of the ponds served as a flexible buffer area for waste components and packaging. Specific protections were also installed on the walls to protect them from mechanical stress which may occur during dismantling work. A specific work platform was
Multicollinearity and Regression Analysis
Daoud, Jamal I.
2017-12-01
In regression analysis it is obvious to have a correlation between the response and predictor(s), but having correlation among predictors is something undesired. The number of predictors included in the regression model depends on many factors among which, historical data, experience, etc. At the end selection of most important predictors is something objective due to the researcher. Multicollinearity is a phenomena when two or more predictors are correlated, if this happens, the standard error of the coefficients will increase [8]. Increased standard errors means that the coefficients for some or all independent variables may be found to be significantly different from In other words, by overinflating the standard errors, multicollinearity makes some variables statistically insignificant when they should be significant. In this paper we focus on the multicollinearity, reasons and consequences on the reliability of the regression model.
Geographically weighted regression model on poverty indicator
Slamet, I.; Nugroho, N. F. T. A.; Muslich
2017-12-01
In this research, we applied geographically weighted regression (GWR) for analyzing the poverty in Central Java. We consider Gaussian Kernel as weighted function. The GWR uses the diagonal matrix resulted from calculating kernel Gaussian function as a weighted function in the regression model. The kernel weights is used to handle spatial effects on the data so that a model can be obtained for each location. The purpose of this paper is to model of poverty percentage data in Central Java province using GWR with Gaussian kernel weighted function and to determine the influencing factors in each regency/city in Central Java province. Based on the research, we obtained geographically weighted regression model with Gaussian kernel weighted function on poverty percentage data in Central Java province. We found that percentage of population working as farmers, population growth rate, percentage of households with regular sanitation, and BPJS beneficiaries are the variables that affect the percentage of poverty in Central Java province. In this research, we found the determination coefficient R2 are 68.64%. There are two categories of district which are influenced by different of significance factors.
Impact of multicollinearity on small sample hydrologic regression models
Kroll, Charles N.; Song, Peter
2013-06-01
Often hydrologic regression models are developed with ordinary least squares (OLS) procedures. The use of OLS with highly correlated explanatory variables produces multicollinearity, which creates highly sensitive parameter estimators with inflated variances and improper model selection. It is not clear how to best address multicollinearity in hydrologic regression models. Here a Monte Carlo simulation is developed to compare four techniques to address multicollinearity: OLS, OLS with variance inflation factor screening (VIF), principal component regression (PCR), and partial least squares regression (PLS). The performance of these four techniques was observed for varying sample sizes, correlation coefficients between the explanatory variables, and model error variances consistent with hydrologic regional regression models. The negative effects of multicollinearity are magnified at smaller sample sizes, higher correlations between the variables, and larger model error variances (smaller R2). The Monte Carlo simulation indicates that if the true model is known, multicollinearity is present, and the estimation and statistical testing of regression parameters are of interest, then PCR or PLS should be employed. If the model is unknown, or if the interest is solely on model predictions, is it recommended that OLS be employed since using more complicated techniques did not produce any improvement in model performance. A leave-one-out cross-validation case study was also performed using low-streamflow data sets from the eastern United States. Results indicate that OLS with stepwise selection generally produces models across study regions with varying levels of multicollinearity that are as good as biased regression techniques such as PCR and PLS.
Regression Modeling of EDM Process for AISI D2 Tool Steel with RSM
Directory of Open Access Journals (Sweden)
Shakir M. Mousa
2018-01-01
Full Text Available In this paper, Response Surface Method (RSM is utilized to carry out an investigation of the impact of input parameters: electrode type (E.T. [Gr, Cu and CuW], pulse duration of current (Ip, pulse duration on time (Ton, and pulse duration off time (Toff on the surface finish in EDM operation. To approximate and concentrate the suggested second- order regression model is generally accepted for Surface Roughness Ra, a Central Composite Design (CCD is utilized for evaluating the model constant coefficients of the input parameters on Surface Roughness (Ra. Examinations were performed on AISI D2 tool steel. The important coefficients are gotten by achieving successfully an Analysis of Variance (ANOVA at the 5 % confidence interval. The outcomes discover that Surface Roughness (Ra is much more impacted by E.T., Ton, Toff, Ip and little of their interactions action or influence. To predict the average Surface Roughness (Ra, a mathematical regression model was developed. Furthermore, for saving in time, the created model could be utilized for the choice of the high levels in the EDM procedure. The model adequacy was extremely agreeable as the constant Coefficient of Determination (R2 is observed to be 99.72% and adjusted R2-measurement (R2adj 99.60%.
Krafft, Axel J.; Loeffler, Ralf B.; Song, Ruitian; Bian, Xiao; McCarville, M. Beth; Hankins, Jane S.; Hillenbrand, Claudia M.
2015-01-01
Purpose Fat suppression (FS) via chemically selective saturation (CHESS) eliminates fat-water oscillations in multi-echo gradient echo (mGRE) R2*-MRI. However, for increasing R2* values as seen with increasing liver iron content (LIC), the water signal spectrally overlaps with the CHESS band, which may alter R2*. Here, we investigate the effect of CHESS on R2* and describe a heuristic correction for the observed CHESS-induced R2* changes. Methods Eighty patients (49/31 female/male, mean age: 18.3±11.7 years) with iron overload were scanned with a non-FS and a CHESS-FS mGRE sequence at 1.5T and 3T. Mean liver R2* values were evaluated using 3 published fitting approaches. Measured and model-corrected R2* values were compared and statistically analyzed. Results At 1.5T, CHESS led to a systematic R2* reduction (PCHESS-induced R2* bias after correction (linear regression slopes: 1.032/0.927/0.981). No CHESS-induced R2* reductions were found at 3T. Conclusion The CHESS-induced R2* bias at 1.5T needs to be considered when applying R2*-LIC biopsy calibrations for clinical LIC assessment which were established without FS at 1.5T. The proposed model corrects the R2* bias and could therefore improve clinical iron overload assessment based on linear R2*-LIC calibrations. PMID:26308155
Matson, Johnny L.; Kozlowski, Alison M.
2010-01-01
Autistic regression is one of the many mysteries in the developmental course of autism and pervasive developmental disorders not otherwise specified (PDD-NOS). Various definitions of this phenomenon have been used, further clouding the study of the topic. Despite this problem, some efforts at establishing prevalence have been made. The purpose of…
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...
Quantum Codes From Cyclic Codes Over The Ring R 2
International Nuclear Information System (INIS)
Altinel, Alev; Güzeltepe, Murat
2016-01-01
Let R 2 denotes the ring F 2 + μF 2 + υ 2 + μυ F 2 + wF 2 + μwF 2 + υwF 2 + μυwF 2 . In this study, we construct quantum codes from cyclic codes over the ring R 2 , for arbitrary length n, with the restrictions μ 2 = 0, υ 2 = 0, w 2 = 0, μυ = υμ, μw = wμ, υw = wυ and μ (υw) = (μυ) w. Also, we give a necessary and sufficient condition for cyclic codes over R 2 that contains its dual. As a final point, we obtain the parameters of quantum error-correcting codes from cyclic codes over R 2 and we give an example of quantum error-correcting codes form cyclic codes over R 2 . (paper)
The adsorption coefficient (KOC) of chlorpyrifos in clay soil
International Nuclear Information System (INIS)
Halimah Muhamad; Nashriyah Mat; Tan Yew Ai; Ismail Sahid
2005-01-01
The purpose of this study was to determine the adsorption coefficient (KOC) of chlorpyrifos in clay soil by measuring the Freundlich adsorption coefficient (Kads(f)) and desorption coefficient (1/n value) of chlorpyrifos. It was found that the Freundlich adsorption coefficient (Kads(f)) and the linear regression (r2) of the Freundlich adsorption isotherm for chlorpyrifos in the clay soil were 52.6 L/kg and 0.5244, respectively. Adsorption equilibrium time was achieved within 24 hours for clay soil. This adsorption equilibrium time was used to determine the effect of concentration on adsorption. The adsorption coefficient (KOC) of clay soil was found to be 2783 L/kg with an initial concentration solution of 1 μg/g, soil-solution ratio (1:5) at 300 C when the equilibrium between the soil matrix and solution was 24 hours. The Kdes decreased over four repetitions of the desorption process. The chlorpyrifos residues may be strongly adsorbed onto the surface of clay. (Author)
DEFF Research Database (Denmark)
Huang, Lei; Fantke, Peter; Jolliet, Olivier
2017-01-01
of chemical-material combinations. This paper develops and evaluates a quantitative property-property relationship (QPPR) to predict diffusion coefficients for a wide range of organic chemicals and materials. We first compiled a training dataset of 1103 measured diffusion coefficients for 158 chemicals in 32......Indoor releases of organic chemicals encapsulated in solid materials are major contributors to human exposures and are directly related to the internal diffusion coefficient in solid materials. Existing correlations to estimate the diffusion coefficient are only valid for a limited number...... consolidated material types. Following a detailed analysis of the temperature influence, we developed a multiple linear regression model to predict diffusion coefficients as a function of chemical molecular weight (MW), temperature, and material type (adjusted R2 of 0.93). The internal validations showed...
Some remarks on the space R2(E
Directory of Open Access Journals (Sweden)
Claes Fernström
1983-01-01
Full Text Available Let E be a compact subset of the complex plane. We denote by R(E the algebra consisting of the rational functions with poles off E. The closure of R(E in Lp(E, 1≤p1, as a necessary and sufficient condition for R2(E≠L2(E. We also construct a compact set E such that R2(E has an isolated bounded point evaluation. In section 3 we examine the smoothness properties of functions in R2(E at those points which admit bounded point evaluations.
Regression modeling methods, theory, and computation with SAS
Panik, Michael
2009-01-01
Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs.The text presents the popular ordinary least squares (OLS) approach before introducing many alternative regression methods. It covers nonparametric regression, logistic regression (including Poisson regression), Bayesian regression, robust regression, fuzzy regression, random coefficients regression,
Microsoft System Center 2012 R2 Operations Manager cookbook
Beaumont (MVP), Steve; Odika, Chiyo; Ryan, Robert
2015-01-01
If you are tasked with monitoring the IT infrastructure within your organization, this book demonstrates how System Center 2012 R2 Operations Manager offers a radical and exciting solution to modern administration.
Spectral sum rule for time delay in R2
International Nuclear Information System (INIS)
Osborn, T.A.; Sinha, K.B.; Bolle, D.; Danneels, C.
1985-01-01
A local spectral sum rule for nonrelativistic scattering in two dimensions is derived for the potential class velement ofL 4 /sup // 3 (R 2 ). The sum rule relates the integral over all scattering energies of the trace of the time-delay operator for a finite region Σis contained inR 2 to the contributions in Σ of the pure point and singularly continuous spectra
Interpretation of commonly used statistical regression models.
Kasza, Jessica; Wolfe, Rory
2014-01-01
A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.
Regression Model to Predict Global Solar Irradiance in Malaysia
Directory of Open Access Journals (Sweden)
Hairuniza Ahmed Kutty
2015-01-01
Full Text Available A novel regression model is developed to estimate the monthly global solar irradiance in Malaysia. The model is developed based on different available meteorological parameters, including temperature, cloud cover, rain precipitate, relative humidity, wind speed, pressure, and gust speed, by implementing regression analysis. This paper reports on the details of the analysis of the effect of each prediction parameter to identify the parameters that are relevant to estimating global solar irradiance. In addition, the proposed model is compared in terms of the root mean square error (RMSE, mean bias error (MBE, and the coefficient of determination (R2 with other models available from literature studies. Seven models based on single parameters (PM1 to PM7 and five multiple-parameter models (PM7 to PM12 are proposed. The new models perform well, with RMSE ranging from 0.429% to 1.774%, R2 ranging from 0.942 to 0.992, and MBE ranging from −0.1571% to 0.6025%. In general, cloud cover significantly affects the estimation of global solar irradiance. However, cloud cover in Malaysia lacks sufficient influence when included into multiple-parameter models although it performs fairly well in single-parameter prediction models.
Crystal-fields at rare-earth sites in R2Fe14B compounds
International Nuclear Information System (INIS)
Adam, S.; Adam, G.; Burzo, E.
1985-12-01
Crystal-field effects are expected to be important in R 2 Fe 14 B compounds. Within a model-independent approach, it is proved that four distinct rare-earth sites exist with respect to the crystalline electric fields, namely, R(4f; z=0), R(4f; z=0.5 c), R(4g; z=0), and R(4g; z=0.5 c), and relationships are established between the corresponding crystal-fields coefficients. Further, generalized Stevens parametrizations of the crystal field coefficients are derived at three levels of approximation for the interatomic forces inside the crystal. A crystal lattice dressing effect upon the radial electronic integrals is found to occur, the magnitude of which depends on the deviation of the interatomic forces from Coulombian. Finally, computation of crystal-field coefficients in Nd 2 Fe 14 B leads to results which raise questions about the validity of the simple Coulomb point-charge model. (author)
Linear regression in astronomy. I
Isobe, Takashi; Feigelson, Eric D.; Akritas, Michael G.; Babu, Gutti Jogesh
1990-01-01
Five methods for obtaining linear regression fits to bivariate data with unknown or insignificant measurement errors are discussed: ordinary least-squares (OLS) regression of Y on X, OLS regression of X on Y, the bisector of the two OLS lines, orthogonal regression, and 'reduced major-axis' regression. These methods have been used by various researchers in observational astronomy, most importantly in cosmic distance scale applications. Formulas for calculating the slope and intercept coefficients and their uncertainties are given for all the methods, including a new general form of the OLS variance estimates. The accuracy of the formulas was confirmed using numerical simulations. The applicability of the procedures is discussed with respect to their mathematical properties, the nature of the astronomical data under consideration, and the scientific purpose of the regression. It is found that, for problems needing symmetrical treatment of the variables, the OLS bisector performs significantly better than orthogonal or reduced major-axis regression.
International Nuclear Information System (INIS)
Gunay, Ahmet
2007-01-01
The experimental data of ammonium exchange by natural Bigadic clinoptilolite was evaluated using nonlinear regression analysis. Three two-parameters isotherm models (Langmuir, Freundlich and Temkin) and three three-parameters isotherm models (Redlich-Peterson, Sips and Khan) were used to analyse the equilibrium data. Fitting of isotherm models was determined using values of standard normalization error procedure (SNE) and coefficient of determination (R 2 ). HYBRID error function provided lowest sum of normalized error and Khan model had better performance for modeling the equilibrium data. Thermodynamic investigation indicated that ammonium removal by clinoptilolite was favorable at lower temperatures and exothermic in nature
Correlation and simple linear regression.
Zou, Kelly H; Tuncali, Kemal; Silverman, Stuart G
2003-06-01
In this tutorial article, the concepts of correlation and regression are reviewed and demonstrated. The authors review and compare two correlation coefficients, the Pearson correlation coefficient and the Spearman rho, for measuring linear and nonlinear relationships between two continuous variables. In the case of measuring the linear relationship between a predictor and an outcome variable, simple linear regression analysis is conducted. These statistical concepts are illustrated by using a data set from published literature to assess a computed tomography-guided interventional technique. These statistical methods are important for exploring the relationships between variables and can be applied to many radiologic studies.
Retro-regression--another important multivariate regression improvement.
Randić, M
2001-01-01
We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.
Oracle JDeveloper 11gR2 Cookbook
Haralabidis, Nick
2012-01-01
"Oracle JDeveloper 11gR2 Cookbook" is a practical cookbook which goes beyond the basics with immediately applicable recipes for building ADF applications at an intermediate-to-advanced level. If you are a JavaEE developer who wants to go beyond the basics of building ADF applications with Oracle JDeveloper 11gR2 and get hands on with practical recipes, this book is for you. You should be comfortable with general Java development principles, the JDeveloper IDE, and ADF basics
Decreased placental and maternal serum TRAIL-R2 levels are associated with placenta accreta.
Oztas, Efser; Ozler, Sibel; Ersoy, Ali Ozgur; Ersoy, Ebru; Caglar, Ali Turhan; Uygur, Dilek; Yucel, Aykan; Ergin, Merve; Danisman, Nuri
2016-03-01
TNF-related apoptosis-inducing ligand receptor-2 (TRAIL-R2) is produced both by decidual and trophoblast cells during pregnancy and known to participate in apoptosis. In this study, we aimed to determine and to compare maternal serum and placental TRAIL-R2 levels in patients with placenta accreta, non-adherent placenta previa and in healthy pregnancies. We also aimed to analyze the association of placenta accreta with the occurrence of previous C-sections. A total of 82 pregnant women were enrolled in this case-control study (27 placenta accreta patients, 26 non-adherent placenta previa patients and 29 age-, and BMI-matched healthy, uncomplicated pregnant controls). TRAIL-R2 levels were studied in both maternal serum and placental tissue homogenates. Determining the best predictor(s) which discriminate placenta accreta was analyzed by multiple logistic regression analyses. Adjusted odds ratios and 95% confidence intervals were also calculated. Both placental and serum TRAIL-R2 levels were significantly lower in placenta accreta group (median 34.82 pg/mg and 19.85 pg/mL, respectively) when compared with both non-adherent placenta previa (median 39.24 pg/mg and 25.99 pg/mL, respectively) and the control groups (median 41.62 pg/mg and 25.87 pg/mL, respectively) (p Placental TRAIL-R2 levels and previous cesarean section were found to be significantly associated with placenta accreta (OR: 0.934 95% CI 0.883-0.987, p = 0.016 and OR:7.725 95% CI: 2.717-21.965, p Placental and serum TRAIL-R2 levels were positively correlated. Decreased levels of placental TRAIL-R2 and previous history of cesarean section were found to be significantly associated with placenta accreta, suggesting a possible role of apoptosis in abnormal trophoblast invasion. Copyright © 2016 Elsevier Ltd. All rights reserved.
GluR2 ligand-binding core complexes
DEFF Research Database (Denmark)
Kasper, C; Lunn, M-L; Liljefors, T
2002-01-01
X-ray structures of the GluR2 ligand-binding core in complex with (S)-Des-Me-AMPA and in the presence and absence of zinc ions have been determined. (S)-Des-Me-AMPA, which is devoid of a substituent in the 5-position of the isoxazolol ring, only has limited interactions with the partly hydrophobic...
Equipment for thermal neutron flux measurements in reactor R2
Energy Technology Data Exchange (ETDEWEB)
Johansson, E; Nilsson, T; Claeson, S
1960-04-15
For most of the thermal neutron flux measurements in reactor R2 cobalt wires will be used. The loading and removal of these wires from the reactor core will be performed by means of a long aluminium tube and electromagnets. After irradiation the wires will be scanned in a semi-automatic device.
Microsoft System Center Data Protection Manager 2012 R2 cookbook
Hedblom, Robert
2015-01-01
If you are a DPM administrator, this book will help you verify your knowledge and provide you with everything you need to know about the 2012 R2 release. No prior knowledge about System Center DPM is required, however some experience of running backups will come in handy.
R2E – identifying problems, mitigating risks
Anaïs Schaeffer
2013-01-01
During LS1, the R2E project team will be working on a task as painstaking as it is crucial: to achieve a sixfold reduction in the number of electronic malfunctions caused by radiation. On their success depends the ability of the accelerator to function correctly at nominal energy. No mean challenge, considering it comes on top of the tenfold reduction already achieved since 2009. The graph plots the rate of LHC beam dumps due to single-event effects against beam luminosity. An indication of the challenge that faces the R2E project teams during LS1! The origins of the project known as R2E (Radiation to Electronics) go back to 2007, when the CNGS (CERN Neutrinos to Gran Sasso) experiment was being commissioned. "Right from the outset, some CNGS control systems were causing problems. They would regularly break down in operations with beam," recalls Markus Brugger, head of the R2E project. "Even though the beam intensity was very low, we began to suspect that radiati...
Tipirneni-Sajja, Aaryani; Krafft, Axel J; McCarville, M Beth; Loeffler, Ralf B; Song, Ruitian; Hankins, Jane S; Hillenbrand, Claudia M
2017-07-01
The objective of this study is to evaluate radial free-breathing (FB) multiecho ultrashort TE (UTE) imaging as an alternative to Cartesian FB multiecho gradient-recalled echo (GRE) imaging for quantitative assessment of hepatic iron content (HIC) in sedated patients and subjects unable to perform breath-hold (BH) maneuvers. FB multiecho GRE imaging and FB multiecho UTE imaging were conducted for 46 test group patients with iron overload who could not complete BH maneuvers (38 patients were sedated, and eight were not sedated) and 16 control patients who could complete BH maneuvers. Control patients also underwent standard BH multiecho GRE imaging. Quantitative R2* maps were calculated, and mean liver R2* values and coefficients of variation (CVs) for different acquisitions and patient groups were compared using statistical analysis. FB multiecho GRE images displayed motion artifacts and significantly lower R2* values, compared with standard BH multiecho GRE images and FB multiecho UTE images in the control cohort and FB multiecho UTE images in the test cohort. In contrast, FB multiecho UTE images produced artifact-free R2* maps, and mean R2* values were not significantly different from those measured by BH multiecho GRE imaging. Motion artifacts on FB multiecho GRE images resulted in an R2* CV that was approximately twofold higher than the R2* CV from BH multiecho GRE imaging and FB multiecho UTE imaging. The R2* CV was relatively constant over the range of R2* values for FB multiecho UTE, but it increased with increases in R2* for FB multiecho GRE imaging, reflecting that motion artifacts had a stronger impact on R2* estimation with increasing iron burden. FB multiecho UTE imaging was less motion sensitive because of radial sampling, produced excellent image quality, and yielded accurate R2* estimates within the same acquisition time used for multiaveraged FB multiecho GRE imaging. Thus, FB multiecho UTE imaging is a viable alternative for accurate HIC assessment
R 2 inflation to probe non-perturbative quantum gravity
Koshelev, Alexey S.; Sravan Kumar, K.; Starobinsky, Alexei A.
2018-03-01
It is natural to expect a consistent inflationary model of the very early Universe to be an effective theory of quantum gravity, at least at energies much less than the Planck one. For the moment, R + R 2, or shortly R 2, inflation is the most successful in accounting for the latest CMB data from the PLANCK satellite and other experiments. Moreover, recently it was shown to be ultra-violet (UV) complete via an embedding into an analytic infinite derivative (AID) non-local gravity. In this paper, we derive a most general theory of gravity that contributes to perturbed linear equations of motion around maximally symmetric space-times. We show that such a theory is quadratic in the Ricci scalar and the Weyl tensor with AID operators along with the Einstein-Hilbert term and possibly a cosmological constant. We explicitly demonstrate that introduction of the Ricci tensor squared term is redundant. Working in this quadratic AID gravity framework without a cosmological term we prove that for a specified class of space homogeneous space-times, a space of solutions to the equations of motion is identical to the space of backgrounds in a local R 2 model. We further compute the full second order perturbed action around any background belonging to that class. We proceed by extracting the key inflationary parameters of our model such as a spectral index ( n s ), a tensor-to-scalar ratio ( r) and a tensor tilt ( n t ). It appears that n s remains the same as in the local R 2 inflation in the leading slow-roll approximation, while r and n t get modified due to modification of the tensor power spectrum. This class of models allows for any value of r complete R 2 gravity a natural target for future CMB probes.
Buchner, Florian; Wasem, Jürgen; Schillo, Sonja
2017-01-01
Risk equalization formulas have been refined since their introduction about two decades ago. Because of the complexity and the abundance of possible interactions between the variables used, hardly any interactions are considered. A regression tree is used to systematically search for interactions, a methodologically new approach in risk equalization. Analyses are based on a data set of nearly 2.9 million individuals from a major German social health insurer. A two-step approach is applied: In the first step a regression tree is built on the basis of the learning data set. Terminal nodes characterized by more than one morbidity-group-split represent interaction effects of different morbidity groups. In the second step the 'traditional' weighted least squares regression equation is expanded by adding interaction terms for all interactions detected by the tree, and regression coefficients are recalculated. The resulting risk adjustment formula shows an improvement in the adjusted R 2 from 25.43% to 25.81% on the evaluation data set. Predictive ratios are calculated for subgroups affected by the interactions. The R 2 improvement detected is only marginal. According to the sample level performance measures used, not involving a considerable number of morbidity interactions forms no relevant loss in accuracy. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.
Intermediate and advanced topics in multilevel logistic regression analysis.
Austin, Peter C; Merlo, Juan
2017-09-10
Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher-level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within-cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population-average effect of covariates measured at the subject and cluster level, in contrast to the within-cluster or cluster-specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster-level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.
Shadow corrosion evaluation in the Studsvik R2 reactor
International Nuclear Information System (INIS)
Sanders, Ch.; Lysell, G.
2000-01-01
Post-irradiation examination has shown that increased corrosion occurs when zirconium alloys are in contact with or in proximity to other metallic objects. The observations indicate an influence of irradiation from the adjacent component as the enhanced corrosion occurs as a 'shadow' of the metallic object on the zirconium surface. This phenomenon could ultimately limit the lifetime of certain zirconium alloy components in the reactor. The Studsvik R2 materials test reactor has an In-Core Autoclave (INCA) test facility especially designed for water chemistry and materials research. The INCA facility has been evaluated and found suitable for shadow corrosion studies. The R2 reactor core containing the INCA facility was modeled with the Monte Carlo N-Particle (MCNP) code in order to evaluate the electron deposition in various materials and to develop a hypothesis of the shadow corrosion mechanism. (authors)
Interpreting Multiple Logistic Regression Coefficients in Prospective Observational Studies
1982-11-01
prompted close examination of the issue at a workshop on hypertriglyceridemia where some of the cautions and perspectives given in this paper were...characteristics. If this is not the interest, then to isolate and-understand the effect of a characteris- tic on CHD when it could be one of several interacting...also easily extended to the case when several independent variables are modeled in a multiple logistic equation. In this instance, if xlx 2,..., x are
System Center 2012 R2 Virtual Machine Manager cookbook
Cardoso, Edvaldo Alessandro
2014-01-01
This book is a step-by-step guide packed with recipes that cover architecture design and planning. The book is also full of deployment tips, techniques, and solutions. If you are a solutions architect, technical consultant, administrator, or any other virtualization enthusiast who needs to use Microsoft System Center Virtual Machine Manager in a real-world environment, then this is the book for you. We assume that you have previous experience with Windows 2012 R2 and Hyper-V.
A supersymmetric R2-action in six dimensions and torsion
International Nuclear Information System (INIS)
Bergshoeff, E.; Salam, A.; Sezgin, E.
1986-01-01
We give the superconformal extension of (Rsub(μνab)) 2 in six dimensions. We show that in a superconformal gauge the 3-form field Hsub(μνrho) has a natural torsion interpretation. We also give partial results on the superconformal extension of the Gauss-Bonnet combination: Rsub(μνab) 2 -4Rsub(μa) 2 +R 2 . (author)
C2R2: Training Students To Build Coastal Resilience
Ferraro, C.; Kopp, R. E.; Jordan, R.; Gong, J.; Andrews, C.; Auermuller, L. M.; Herb, J.; McDonnell, J. D.; Bond, S.
2017-12-01
In the United States, about 23 million people live within 6 meters of sea level. In many parts of the country, sea-level rise between 1960 and 2010 has already led to a 2-5-fold increase in the rate of `nuisance' flooding. On top of rising seas, intensifying hurricanes and more frequent extremes of heat, humidity and precipitation pose additional risks to coastal societies, economies and ecosystems. Addressing risks posed by changing climate conditions in coastal areas demands innovative strategies that intersect multiple disciplines including engineering, ecology, communication, climate science, and community planning. To be usable, it also requires engaging coastal stakeholders in the development of research questions, the assessment of implications of research for planning and policy, and the communication of research results. Yet traditional, disciplinary programs are poorly configured to train the workforce needed to assess coastal climate risk and to develop and deploy integrated strategies for increasing coastal climate resilience. Coastal Climate Risk & Resilience (C2R2) is an NSF Research Traineeship (NRT) working to prepare the workforce that will build coastal resilience in the face of climate risks. Through its trainee and certificate programs, C2R2 works with graduate students at Rutgers University from multiple disciplines to better integrate all the elements of coastal systems and to communicate effectively with coastal stakeholders. C2R2 students will acquire the knowledge and practical skills needed to become leading researchers and practitioners tackling the critical challenges of coastal resilience.
Advanced statistics: linear regression, part II: multiple linear regression.
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.
Differentiating regressed melanoma from regressed lichenoid keratosis.
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.
SU(2) Yang-Mills solitons in R2 gravity
Perapechka, I.; Shnir, Ya.
2018-05-01
We construct new family of spherically symmetric regular solutions of SU (2) Yang-Mills theory coupled to pure R2 gravity. The particle-like field configurations possess non-integer non-Abelian magnetic charge. A discussion of the main properties of the solutions and their differences from the usual Bartnik-McKinnon solitons in the asymptotically flat case is presented. It is shown that there is continuous family of linearly stable non-trivial solutions in which the gauge field has no nodes.
R2 effect-size measures for mediation analysis
Fairchild, Amanda J.; MacKinnon, David P.; Taborga, Marcia P.; Taylor, Aaron B.
2010-01-01
R2 effect-size measures are presented to assess variance accounted for in mediation models. The measures offer a means to evaluate both component paths and the overall mediated effect in mediation models. Statistical simulation results indicate acceptable bias across varying parameter and sample-size combinations. The measures are applied to a real-world example using data from a team-based health promotion program to improve the nutrition and exercise habits of firefighters. SAS and SPSS computer code are also provided for researchers to compute the measures in their own data. PMID:19363189
R2 effect-size measures for mediation analysis.
Fairchild, Amanda J; Mackinnon, David P; Taborga, Marcia P; Taylor, Aaron B
2009-05-01
R(2) effect-size measures are presented to assess variance accounted for in mediation models. The measures offer a means to evaluate both component paths and the overall mediated effect in mediation models. Statistical simulation results indicate acceptable bias across varying parameter and sample-size combinations. The measures are applied to a real-world example using data from a team-based health promotion program to improve the nutrition and exercise habits of firefighters. SAS and SPSS computer code are also provided for researchers to compute the measures in their own data.
Robotic Range Clearance Competition (R2C2)
2011-10-01
MON TUE MAP MAP VEG automated vegetation clearance, automated Aug 10 Aug 11 WED THU Med VEG ia and Visitor D MAP ay Aug 12 FRI SURF...competitors will not be penalized if they enter this area. For the competition we will add an additional Pan , Tilt, Zoom (PTZ) Camera that will be...Johnston’s Corner –Gas Station Restaurant: Pizza, Fired Chicken , Subs 550 W Whalen St., Guernsey, WY 82214 (307) 836-3155 R2C2 Competitor Information
R2 cosmology: Inflation without a phase transition
International Nuclear Information System (INIS)
Mijic, M.B.; Morris, M.S.; Suen, W.
1986-01-01
A pure gravity inflationary model for the Universe is examined which is based on adding an εR 2 term to the usual gravitational Lagrangian. The classical evolution is worked out, including eventual particle production and the subsequent join to radiation-dominated Friedmann behavior. We show that this model gives significant inflation essentially independent of initial conditions. The model has only one free parameter which is bounded from above by observational constraints on scalar and tensorial perturbations and from below by both the need for standard baryogenesis and the need for galaxy formation. This requires 10/sup 11/<ε/sup -1/2/<10/sup 13/ GeV
Foundations of SQL Server 2008 R2 Business Intelligence
Fouche, Guy
2011-01-01
Foundations of SQL Server 2008 R2 Business Intelligence introduces the entire exciting gamut of business intelligence tools included with SQL Server 2008. Microsoft has designed SQL Server 2008 to be more than just a database. It's a complete business intelligence (BI) platform. The database is at its core, and surrounding the core are tools for data mining, modeling, reporting, analyzing, charting, and integration with other enterprise-level software packages. SQL Server 2008 puts an incredible amount of BI functionality at your disposal. But how do you take advantage of it? That's what this
Antropov, K M; Varaksin, A N
2013-01-01
This paper provides the description of Land Use Regression (LUR) modeling and the result of its application in the study of nitrogen dioxide air pollution in Ekaterinburg. The paper describes the difficulties of the modeling for air pollution caused by motor vehicles exhaust, and the ways to address these challenges. To create LUR model of the NO2 air pollution in Ekaterinburg, concentrations of NO2 were measured, data on factors affecting air pollution were collected, a statistical analysis of the data were held. A statistical model of NO2 air pollution (coefficient of determination R2 = 0.70) and a map of pollution were created.
Distributed Monitoring of the R(sup 2) Statistic for Linear Regression
Bhaduri, Kanishka; Das, Kamalika; Giannella, Chris R.
2011-01-01
The problem of monitoring a multivariate linear regression model is relevant in studying the evolving relationship between a set of input variables (features) and one or more dependent target variables. This problem becomes challenging for large scale data in a distributed computing environment when only a subset of instances is available at individual nodes and the local data changes frequently. Data centralization and periodic model recomputation can add high overhead to tasks like anomaly detection in such dynamic settings. Therefore, the goal is to develop techniques for monitoring and updating the model over the union of all nodes data in a communication-efficient fashion. Correctness guarantees on such techniques are also often highly desirable, especially in safety-critical application scenarios. In this paper we develop DReMo a distributed algorithm with very low resource overhead, for monitoring the quality of a regression model in terms of its coefficient of determination (R2 statistic). When the nodes collectively determine that R2 has dropped below a fixed threshold, the linear regression model is recomputed via a network-wide convergecast and the updated model is broadcast back to all nodes. We show empirically, using both synthetic and real data, that our proposed method is highly communication-efficient and scalable, and also provide theoretical guarantees on correctness.
Directory of Open Access Journals (Sweden)
Sara Mortaz Hejri
2013-01-01
Full Text Available Background: One of the methods used for standard setting is the borderline regression method (BRM. This study aims to assess the reliability of BRM when the pass-fail standard in an objective structured clinical examination (OSCE was calculated by averaging the BRM standards obtained for each station separately. Materials and Methods: In nine stations of the OSCE with direct observation the examiners gave each student a checklist score and a global score. Using a linear regression model for each station, we calculated the checklist score cut-off on the regression equation for the global scale cut-off set at 2. The OSCE pass-fail standard was defined as the average of all station′s standard. To determine the reliability, the root mean square error (RMSE was calculated. The R2 coefficient and the inter-grade discrimination were calculated to assess the quality of OSCE. Results: The mean total test score was 60.78. The OSCE pass-fail standard and its RMSE were 47.37 and 0.55, respectively. The R2 coefficients ranged from 0.44 to 0.79. The inter-grade discrimination score varied greatly among stations. Conclusion: The RMSE of the standard was very small indicating that BRM is a reliable method of setting standard for OSCE, which has the advantage of providing data for quality assurance.
Pedrini, D. T.; Pedrini, Bonnie C.
Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…
Energy Technology Data Exchange (ETDEWEB)
Deng, Yangyang; Parajuli, Prem B.
2011-08-10
Evaluation of economic feasibility of a bio-gasification facility needs understanding of its unit cost under different production capacities. The objective of this study was to evaluate the unit cost of syngas production at capacities from 60 through 1800Nm 3/h using an economic model with three regression analysis techniques (simple regression, reciprocal regression, and log-log regression). The preliminary result of this study showed that reciprocal regression analysis technique had the best fit curve between per unit cost and production capacity, with sum of error squares (SES) lower than 0.001 and coefficient of determination of (R 2) 0.996. The regression analysis techniques determined the minimum unit cost of syngas production for micro-scale bio-gasification facilities of $0.052/Nm 3, under the capacity of 2,880 Nm 3/h. The results of this study suggest that to reduce cost, facilities should run at a high production capacity. In addition, the contribution of this technique could be the new categorical criterion to evaluate micro-scale bio-gasification facility from the perspective of economic analysis.
R2E strategy and activities during LS1
International Nuclear Information System (INIS)
Perrot, A.L.
2012-01-01
The level of the flux of hadrons with energy in the multi MeV range expected from the collimation system at Point 7 and from the collisions at the interaction Points 1, 5 and 8 will induce Single Event Errors (SEEs) of the standard electronics present in the equipment located around these Points. Such events would perturb LHC operation. As a consequence, within the framework of the R2E (Radiation to Electronics) Mitigation Project, the sensitive equipment will be shielded or relocated to safer areas. These mitigation activities will be performed mainly during Long Shutdown 1 (LS1). About 15 groups (including equipment owners) will be involved in these activities with work periods from a few days to several months. Some of them will have to work in parallel in several LHC points. This document presents these mitigation activities with their associated planning, organization process, and main concerns as identified today. (author)
Renormalization group procedure for potential −g/r2
Directory of Open Access Journals (Sweden)
S.M. Dawid
2018-02-01
Full Text Available Schrödinger equation with potential −g/r2 exhibits a limit cycle, described in the literature in a broad range of contexts using various regularizations of the singularity at r=0. Instead, we use the renormalization group transformation based on Gaussian elimination, from the Hamiltonian eigenvalue problem, of high momentum modes above a finite, floating cutoff scale. The procedure identifies a richer structure than the one we found in the literature. Namely, it directly yields an equation that determines the renormalized Hamiltonians as functions of the floating cutoff: solutions to this equation exhibit, in addition to the limit-cycle, also the asymptotic-freedom, triviality, and fixed-point behaviors, the latter in vicinity of infinitely many separate pairs of fixed points in different partial waves for different values of g.
6. Investigation of R2M17 compounds
International Nuclear Information System (INIS)
Elemans, J.B.A.A.; Buschow, K.H.J.
1975-01-01
A discussion is presented of the different crystallographic forms that arise in the parent RM 5 (R rare earth including yttrium or thorium; M = Fe, Co or Ni) with CaCu 5 structure in which every third R is replaced by a pair of M. This results in the stoichiometric composition R 2 M 17 . Metallographic studies of well annealed and quenched specimens of CeFesub(x), HoFesub(x) and TmFesub(x) with x varying from 8 to 9.5 showed that only those with x = 8.5 consisted of one phase. Similar experiments with ThNisub(x) and YNisub(x), x varying from 6.5 to 8.5 revealed that in these cases, single phases were obtained with x = 7.5
Octanol-air partition coefficients of polybrominated biphenyls.
Hongxia, Zhao; Jingwen, Chen; Xie, Quan; Baocheng, Qu; Xinmiao, Liang
2009-03-01
The octanol-air partition coefficients (K(OA)) for PBB15, PBB26, PBB31, PBB49, PBB103 and PBB153 were determined as a function of temperature using a gas chromatographic retention time technique with 1,1,1-trichloro-2,2-bis (4-chlorophenyl) ethane (p,p'-DDT) as a reference substance. The internal energies of phase change from octanol to air (Delta(OA)U) were calculated for the six compounds and were in the range from 74 to 116 kJ mol(-1). Simple regression equations of log K(OA) versus relative retention times (RRTs) on gas chromatography (GC), and log K(OA) versus molecular connectivity indexes (MCI) were obtained, for which the correlation coefficients (r(2)) were greater than 0.985 at 283.15K and 298.15K. Thus the K(OA) values of the remaining PBBs can be predicted by using their RRTs and MCI according to these relationships.
Regression and artificial neural network modeling for the prediction of gray leaf spot of maize.
Paul, P A; Munkvold, G P
2005-04-01
ABSTRACT Regression and artificial neural network (ANN) modeling approaches were combined to develop models to predict the severity of gray leaf spot of maize, caused by Cercospora zeae-maydis. In all, 329 cases consisting of environmental, cultural, and location-specific variables were collected for field plots in Iowa between 1998 and 2002. Disease severity on the ear leaf at the dough to dent plant growth stage was used as the response variable. Correlation and regression analyses were performed to select potentially useful predictor variables. Predictors from the best 9 of 80 regression models were used to develop ANN models. A random sample of 60% of the cases was used to train the networks, and 20% each for testing and validation. Model performance was evaluated based on coefficient of determination (R(2)) and mean square error (MSE) for the validation data set. The best models had R(2) ranging from 0.70 to 0.75 and MSE ranging from 174.7 to 202.8. The most useful predictor variables were hours of daily temperatures between 22 and 30 degrees C (85.50 to 230.50 h) and hours of nightly relative humidity >/=90% (122 to 330 h) for the period between growth stages V4 and V12, mean nightly temperature (65.26 to 76.56 degrees C) for the period between growth stages V12 and R2, longitude (90.08 to 95.14 degrees W), maize residue on the soil surface (0 to 100%), planting date (in day of the year; 112 to 182), and gray leaf spot resistance rating (2 to 7; based on a 1-to-9 scale, where 1 = most susceptible to 9 = most resistant).
Problems with change in R2 as applied to theory of reasoned action research.
Trafimow, David
2004-12-01
The paradigm of choice for theory of reasoned action research seems to depend largely on the notion of change in variance accounted for (DeltaR2) as new independent variables are added to a multiple regression equation. If adding a particular independent variable of interest increases the variance in the dependent variable that can be accounted for by the list of independent variables, then the research is deemed to be 'successful', and the researcher is considered to have made a convincing argument about the importance of the new variable. In contrast to this trend, I present arguments that suggest serious problems with the paradigm, and conclude that studies on attitude-behaviour relations would advance the field of psychology to a far greater extent if researchers abandoned it.
International Nuclear Information System (INIS)
Kumar, K. Vasanth; Porkodi, K.; Rocha, F.
2008-01-01
A comparison of linear and non-linear regression method in selecting the optimum isotherm was made to the experimental equilibrium data of methylene blue sorption by activated carbon. The r 2 was used to select the best fit linear theoretical isotherm. In the case of non-linear regression method, six error functions, namely coefficient of determination (r 2 ), hybrid fractional error function (HYBRID), Marquardt's percent standard deviation (MPSD), average relative error (ARE), sum of the errors squared (ERRSQ) and sum of the absolute errors (EABS) were used to predict the parameters involved in the two and three parameter isotherms and also to predict the optimum isotherm. For two parameter isotherm, MPSD was found to be the best error function in minimizing the error distribution between the experimental equilibrium data and predicted isotherms. In the case of three parameter isotherm, r 2 was found to be the best error function to minimize the error distribution structure between experimental equilibrium data and theoretical isotherms. The present study showed that the size of the error function alone is not a deciding factor to choose the optimum isotherm. In addition to the size of error function, the theory behind the predicted isotherm should be verified with the help of experimental data while selecting the optimum isotherm. A coefficient of non-determination, K 2 was explained and was found to be very useful in identifying the best error function while selecting the optimum isotherm
Microstructure in Zircaloy Creep Tested in the R2 Reactor
International Nuclear Information System (INIS)
Pettersson, Kjell
2004-12-01
Tubular specimens of Zircaloy-4 have been creep tested in bending in the R2 reactor in Studsvik. The creep deformation in the reactor core is accelerated in comparison with creep deformation outside the reactor core. The possible mechanisms behind this behaviour are described briefly. In order to determine which the actual mechanism is, the microstructure of the material creep tested in the R2 reactor has been examined by transmission electron microscopy. Due to the bending, material subjected to both tensile and compressive stress during creep was available. Since some of the proposed mechanisms might give microstructures which are different when the material is subjected to compressive or tensile stress it was assumed that examination of both types of material would give valuable information with regard to the operating mechanism. The result of the examination was that in the as-irradiated condition there were no obvious differences detected between materials which had been deformed in tension or compression. After a heat treatment to coarsen the irradiation induced microstructure there were still no significant differences between the two types of material. However it was now observed that in addition to dislocation loops the microstructure also contained network dislocations which presumably had been invisible in the electron microscope before heat treatment due to the high density of small dislocation loops in this state. It is therefore concluded that the most probable mechanism for irradiation creep in this case is climb and glide of the network dislocations. The role of irradiation is two-fold: It accelerates climb due to the production of point defects of which more interstitials than vacancies arrive to the network dislocations stopped at an obstacles. This leads to a net climb after which a dislocation is released from the obstacle and an amount of glide takes place. The second effect is the production of loops which serve as an increasing density of
Sparse Regression by Projection and Sparse Discriminant Analysis
Qi, Xin; Luo, Ruiyan; Carroll, Raymond J.; Zhao, Hongyu
2015-01-01
predictions. We introduce a new framework, regression by projection, and its sparse version to analyze high-dimensional data. The unique nature of this framework is that the directions of the regression coefficients are inferred first, and the lengths
Multiple regression models for energy use in air-conditioned office buildings in different climates
International Nuclear Information System (INIS)
Lam, Joseph C.; Wan, Kevin K.W.; Liu Dalong; Tsang, C.L.
2010-01-01
An attempt was made to develop multiple regression models for office buildings in the five major climates in China - severe cold, cold, hot summer and cold winter, mild, and hot summer and warm winter. A total of 12 key building design variables were identified through parametric and sensitivity analysis, and considered as inputs in the regression models. The coefficient of determination R 2 varies from 0.89 in Harbin to 0.97 in Kunming, indicating that 89-97% of the variations in annual building energy use can be explained by the changes in the 12 parameters. A pseudo-random number generator based on three simple multiplicative congruential generators was employed to generate random designs for evaluation of the regression models. The difference between regression-predicted and DOE-simulated annual building energy use are largely within 10%. It is envisaged that the regression models developed can be used to estimate the likely energy savings/penalty during the initial design stage when different building schemes and design concepts are being considered.
The R + var-epsilon R2 cosmology
International Nuclear Information System (INIS)
Morris, M.S.
1988-01-01
This thesis presents the study of a model cosmology based on the R + var-epsilon R 2 gravitational Lagrangian. It may be roughly divided into two distinct parts. First, the classical inflationary scenario is developed. Then, the formalism of quantum cosmology is employed to determined initial conditions for the classical model. In the work on the classical model, the evolution equations for an isotropic and homogeneous universe are solved to exhibit both early-time inflation and a smooth transition to subsequent radiation-dominated behavior. Then perturbations on this isotropic background are evolved through the model to provide constraints on the model parameters from the observational limits on anisotropy today. In the work on the wave function, the two boundary conditions of Vilenkin and Hartle and Hawking are compared. The wave functions obtained are restricted to the initial edge of classical Lorentzian inflationary trajectories as distributions over initial conditions for the classical inflationary model. It is found that Vilenkin's wave function prefers the universe to undergo a great deal of inflation, whereas Hartle and Hawking's wave function prefers the universe to undergo little inflation. Finally, both boundary conditions are shown to require the inhomogeneous perturbative modes start out in their ground states
Scalaron from R2-gravity as a heavy field
Pi, Shi; Zhang, Ying-li; Huang, Qing-Guo; Sasaki, Misao
2018-05-01
We study a model of inflation in which a scalar field χ is non-minimally coupled to Starobinsky's R2 gravity. After transforming it to the Einstein frame, a new scalar field, the scalaron phi, will appear and couple to χ with a nontrivial field metric, while χ acquires a positive mass via the non-minimal coupling. Initially inflation occurs along the phi direction with χ trapped near its origin by this induced mass. After phi crosses a critical value, it starts rolling down rapidly and proceeds to damped oscillations around an effective local minimum determined by the value of χ, while inflation still continues, driven by the χ field at this second stage where the effect of the non-minimal coupling becomes negligible. The presence of the damped oscillations during the transition from the first to second stage of inflation causes enhancement and oscillation features in the power spectrum of the curvature perturbation. Assuming that the oscillations may be treated perturbatively, we calculate these features by using the δ N formalism, and discuss its observational implications to large scale CMB anomalies or primordial black hole formation, depending on the scale of the features.
Directory of Open Access Journals (Sweden)
Abolfazl Nasseri
2017-03-01
software’s of SPSS and Minitab were used in statistical analysis. Results and Discussion: Roughness coefficients averaged 0.06. Results revealed that RC varied from 0.014 to 0.050 (and more than for 90 to 40% probabilities in non-vegetated canals. Also, flow velocity, hydraulic radius, cross section area, wetted perimeter and roughness coefficient were lognormal in distributions. Results also showed that flow regimes were turbulent and with increase in Reynolds numbers, roughness coefficients decrease. Sensitivity analysis of flow rate to roughness coefficient showed that with increase as 200 and 300 percent in roughness coefficients, flow rates were 0.50 and 0.33 of flow rate from average roughness coefficient. Moreover, A simple regression model was developed based on effective variables (viz. flow velocity and canal slope on roughness coefficient by omitting non-effective variables in non-vegetated canals. Developed model was as follows: (2 R2=0.99 The variables of the model were previously introduced earlier. The coefficient of determination (R2 shows that more than 99% variations in RC could be explained by flow velocity and canal slope. Conclusion: Roughness coefficient in the earth non-vegetated canals was successfully and precisely evaluated for irrigation and drainage network of Moghan (in North-west of Iran by statistical methods. Roughness coefficients averaged 0.06. The sensitivity of canal discharge to roughness coefficient was significant. It is recommended to select and apply actual values of this coefficient in engineering or computing purposes. By omitting non-effective variables in roughness coefficient in non-vegetated canals, a simple regression model with R2 of 0.99 was developed based on effective variables. In this study, the role of vegetation in channel for roughness coefficient was not evaluated. Therefore, it is recommended that the effect of different vegetation on roughness coefficient tobe evaluated with models such as hydrodynamic and zero-inertia.
AN APPLICATION OF FUNCTIONAL MULTIVARIATE REGRESSION MODEL TO MULTICLASS CLASSIFICATION
Krzyśko, Mirosław; Smaga, Łukasz
2017-01-01
In this paper, the scale response functional multivariate regression model is considered. By using the basis functions representation of functional predictors and regression coefficients, this model is rewritten as a multivariate regression model. This representation of the functional multivariate regression model is used for multiclass classification for multivariate functional data. Computational experiments performed on real labelled data sets demonstrate the effectiveness of the proposed ...
[Hyperspectral Estimation of Apple Tree Canopy LAI Based on SVM and RF Regression].
Han, Zhao-ying; Zhu, Xi-cun; Fang, Xian-yi; Wang, Zhuo-yuan; Wang, Ling; Zhao, Geng-Xing; Jiang, Yuan-mao
2016-03-01
Leaf area index (LAI) is the dynamic index of crop population size. Hyperspectral technology can be used to estimate apple canopy LAI rapidly and nondestructively. It can be provide a reference for monitoring the tree growing and yield estimation. The Red Fuji apple trees of full bearing fruit are the researching objects. Ninety apple trees canopies spectral reflectance and LAI values were measured by the ASD Fieldspec3 spectrometer and LAI-2200 in thirty orchards in constant two years in Qixia research area of Shandong Province. The optimal vegetation indices were selected by the method of correlation analysis of the original spectral reflectance and vegetation indices. The models of predicting the LAI were built with the multivariate regression analysis method of support vector machine (SVM) and random forest (RF). The new vegetation indices, GNDVI527, ND-VI676, RVI682, FD-NVI656 and GRVI517 and the previous two main vegetation indices, NDVI670 and NDVI705, are in accordance with LAI. In the RF regression model, the calibration set decision coefficient C-R2 of 0.920 and validation set decision coefficient V-R2 of 0.889 are higher than the SVM regression model by 0.045 and 0.033 respectively. The root mean square error of calibration set C-RMSE of 0.249, the root mean square error validation set V-RMSE of 0.236 are lower than that of the SVM regression model by 0.054 and 0.058 respectively. Relative analysis of calibrating error C-RPD and relative analysis of validation set V-RPD reached 3.363 and 2.520, 0.598 and 0.262, respectively, which were higher than the SVM regression model. The measured and predicted the scatterplot trend line slope of the calibration set and validation set C-S and V-S are close to 1. The estimation result of RF regression model is better than that of the SVM. RF regression model can be used to estimate the LAI of red Fuji apple trees in full fruit period.
Singh, Jagmahender; Pathak, R K; Chavali, Krishnadutt H
2011-03-20
Skeletal height estimation from regression analysis of eight sternal lengths in the subjects of Chandigarh zone of Northwest India is the topic of discussion in this study. Analysis of eight sternal lengths (length of manubrium, length of mesosternum, combined length of manubrium and mesosternum, total sternal length and first four intercostals lengths of mesosternum) measured from 252 male and 91 female sternums obtained at postmortems revealed that mean cadaver stature and sternal lengths were more in North Indians and males than the South Indians and females. Except intercostal lengths, all the sternal lengths were positively correlated with stature of the deceased in both sexes (P regression analysis of sternal lengths was found more useful than the linear regression for stature estimation. Using multivariate regression analysis, the combined length of manubrium and mesosternum in both sexes and the length of manubrium along with 2nd and 3rd intercostal lengths of mesosternum in males were selected as best estimators of stature. Nonetheless, the stature of males can be predicted with SEE of 6.66 (R(2) = 0.16, r = 0.318) from combination of MBL+BL_3+LM+BL_2, and in females from MBL only, it can be estimated with SEE of 6.65 (R(2) = 0.10, r = 0.318), whereas from the multiple regression analysis of pooled data, stature can be known with SEE of 6.97 (R(2) = 0.387, r = 575) from the combination of MBL+LM+BL_2+TSL+BL_3. The R(2) and F-ratio were found to be statistically significant for almost all the variables in both the sexes, except 4th intercostal length in males and 2nd to 4th intercostal lengths in females. The 'major' sternal lengths were more useful than the 'minor' ones for stature estimation The universal regression analysis used by Kanchan et al. [39] when applied to sternal lengths, gave satisfactory estimates of stature for males only but female stature was comparatively better estimated from simple linear regressions. But they are not proposed for the
Akbari, Somaye; Zebardast, Tannaz; Zarghi, Afshin; Hajimahdi, Zahra
2017-01-01
COX-2 inhibitory activities of some 1,4-dihydropyridine and 5-oxo-1,4,5,6,7,8-hexahydroquinoline derivatives were modeled by quantitative structure-activity relationship (QSAR) using stepwise-multiple linear regression (SW-MLR) method. The built model was robust and predictive with correlation coefficient (R 2 ) of 0.972 and 0.531 for training and test groups, respectively. The quality of the model was evaluated by leave-one-out (LOO) cross validation (LOO correlation coefficient (Q 2 ) of 0.943) and Y-randomization. We also employed a leverage approach for the defining of applicability domain of model. Based on QSAR models results, COX-2 inhibitory activity of selected data set had correlation with BEHm6 (highest eigenvalue n. 6 of Burden matrix/weighted by atomic masses), Mor03u (signal 03/unweighted) and IVDE (Mean information content on the vertex degree equality) descriptors which derived from their structures.
Determination of drying kinetics and convective heat transfer coefficients of ginger slices
Akpinar, Ebru Kavak; Toraman, Seda
2016-10-01
In the present work, the effects of some parametric values on convective heat transfer coefficients and the thin layer drying process of ginger slices were investigated. Drying was done in the laboratory by using cyclone type convective dryer. The drying air temperature was varied as 40, 50, 60 and 70 °C and the air velocity is 0.8, 1.5 and 3 m/s. All drying experiments had only falling rate period. The drying data were fitted to the twelve mathematical models and performance of these models was investigated by comparing the determination of coefficient ( R 2), reduced Chi-square ( χ 2) and root mean square error between the observed and predicted moisture ratios. The effective moisture diffusivity and activation energy were calculated using an infinite series solution of Fick's diffusion equation. The average effective moisture diffusivity values and activation energy values varied from 2.807 × 10-10 to 6.977 × 10-10 m2/s and 19.313-22.722 kJ/mol over the drying air temperature and velocity range, respectively. Experimental data was used to evaluate the values of constants in Nusselt number expression by using linear regression analysis and consequently, convective heat transfer coefficients were determined in forced convection mode. Convective heat transfer coefficient of ginger slices showed changes in ranges 0.33-2.11 W/m2 °C.
Mann-Salinas, Elizabeth A; Le, Tuan D; Shackelford, Stacy A; Bailey, Jeffrey A; Stockinger, Zsolt T; Spott, Mary Ann; Wirt, Michael D; Rickard, Rory; Lane, Ian B; Hodgetts, Timothy; Cardin, Sylvain; Remick, Kyle N; Gross, Kirby R
2016-11-01
A Role 2 registry (R2R) was developed in 2008 by the US Joint Trauma System (JTS). The purpose of this project was to undertake a preliminary review of the R2R to understand combat trauma epidemiology and related interventions at these facilities to guide training and optimal use of forward surgical capability in the future. A retrospective review of available JTS R2R records; the registry is a convenience sample entered voluntarily by members of the R2 units. Patients were classified according to basic demographics, affiliation, region where treatment was provided, mechanism of injury, type of injury, time and method of transport from point of injury (POI) to R2 facility, interventions at R2, and survival. Analysis included trauma patients aged ≥18 years or older wounded in year 2008 to 2014, and treated in Afghanistan. A total of 15,404 patients wounded and treated in R2 were included in the R2R from February 2008 to September 2014; 12,849 patients met inclusion criteria. The predominant patient affiliations included US Forces, 4,676 (36.4%); Afghan Forces, 4,549 (35.4%); and Afghan civilians, 2,178 (17.0%). Overall, battle injuries predominated (9,792 [76.2%]). Type of injury included penetrating, 7,665 (59.7%); blunt, 4,026 (31.3%); and other, 633 (4.9%). Primary mechanism of injury included explosion, 5,320 (41.4%); gunshot wounds, 3,082 (24.0%); and crash, 1,209 (9.4%). Of 12,849 patients who arrived at R2, 167 (1.3%) were dead; of 12,682 patients who were alive upon arrival, 342 (2.7%) died at R2. This evaluation of the R2R describes the patient profiles of and common injuries treated in a sample of R2 facilities in Afghanistan. Ongoing and detailed analysis of R2R information may provide evidence-based guidance to military planners and medical leaders to best prepare teams and allocate R2 resources in future operations. Given the limitations of the data set, conclusions must be interpreted in context of other available data and analyses, not in isolation
Liu, Pudong; Shi, Runhe; Wang, Hong; Bai, Kaixu; Gao, Wei
2014-10-01
Leaf pigments are key elements for plant photosynthesis and growth. Traditional manual sampling of these pigments is labor-intensive and costly, which also has the difficulty in capturing their temporal and spatial characteristics. The aim of this work is to estimate photosynthetic pigments at large scale by remote sensing. For this purpose, inverse model were proposed with the aid of stepwise multiple linear regression (SMLR) analysis. Furthermore, a leaf radiative transfer model (i.e. PROSPECT model) was employed to simulate the leaf reflectance where wavelength varies from 400 to 780 nm at 1 nm interval, and then these values were treated as the data from remote sensing observations. Meanwhile, simulated chlorophyll concentration (Cab), carotenoid concentration (Car) and their ratio (Cab/Car) were taken as target to build the regression model respectively. In this study, a total of 4000 samples were simulated via PROSPECT with different Cab, Car and leaf mesophyll structures as 70% of these samples were applied for training while the last 30% for model validation. Reflectance (r) and its mathematic transformations (1/r and log (1/r)) were all employed to build regression model respectively. Results showed fair agreements between pigments and simulated reflectance with all adjusted coefficients of determination (R2) larger than 0.8 as 6 wavebands were selected to build the SMLR model. The largest value of R2 for Cab, Car and Cab/Car are 0.8845, 0.876 and 0.8765, respectively. Meanwhile, mathematic transformations of reflectance showed little influence on regression accuracy. We concluded that it was feasible to estimate the chlorophyll and carotenoids and their ratio based on statistical model with leaf reflectance data.
Regression analysis by example
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
Keat, Sim Chong; Chun, Beh Boon; San, Lim Hwee; Jafri, Mohd Zubir Mat
2015-04-01
Climate change due to carbon dioxide (CO2) emissions is one of the most complex challenges threatening our planet. This issue considered as a great and international concern that primary attributed from different fossil fuels. In this paper, regression model is used for analyzing the causal relationship among CO2 emissions based on the energy consumption in Malaysia using time series data for the period of 1980-2010. The equations were developed using regression model based on the eight major sources that contribute to the CO2 emissions such as non energy, Liquefied Petroleum Gas (LPG), diesel, kerosene, refinery gas, Aviation Turbine Fuel (ATF) and Aviation Gasoline (AV Gas), fuel oil and motor petrol. The related data partly used for predict the regression model (1980-2000) and partly used for validate the regression model (2001-2010). The results of the prediction model with the measured data showed a high correlation coefficient (R2=0.9544), indicating the model's accuracy and efficiency. These results are accurate and can be used in early warning of the population to comply with air quality standards.
Early cost estimating for road construction projects using multiple regression techniques
Directory of Open Access Journals (Sweden)
Ibrahim Mahamid
2011-12-01
Full Text Available The objective of this study is to develop early cost estimating models for road construction projects using multiple regression techniques, based on 131 sets of data collected in the West Bank in Palestine. As the cost estimates are required at early stages of a project, considerations were given to the fact that the input data for the required regression model could be easily extracted from sketches or scope definition of the project. 11 regression models are developed to estimate the total cost of road construction project in US dollar; 5 of them include bid quantities as input variables and 6 include road length and road width. The coefficient of determination r2 for the developed models is ranging from 0.92 to 0.98 which indicate that the predicted values from a forecast models fit with the real-life data. The values of the mean absolute percentage error (MAPE of the developed regression models are ranging from 13% to 31%, the results compare favorably with past researches which have shown that the estimate accuracy in the early stages of a project is between ±25% and ±50%.
Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L
2018-02-01
A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R 2 ), using R 2 as the primary metric of assay agreement. However, the use of R 2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Belliveau, Jean-Guy; Jensen, Michael D.; Stewart, James M. P.; Solovey, Igor; Klassen, L. Martyn; Bauman, Glenn S.; Menon, Ravi S.
2018-02-01
Background and purpose. Radiation necrosis remains an irreversible long-term side-effect following radiotherapy to the brain. The ability to predict areas that could ultimately develop into necrosis could lead to prevention and management of radiation necrosis. Materials and Methods. Fischer 344 rats were irradiated using two platforms (micro-CT irradiator and x-Rad 225 IGRT) with radiation up to 30 Gy for the micro-CT and 40 Gy for the xRAD-224 to half the brain. Animals were subsequently imaged using a 9.4 T MRI scanner every 2-4 weeks for up to 28 weeks using a 7-echo gradient echo sequence. The apparent transverse relaxation constant (R2* ) was calculated and retrospectively analyzed. Results. Animals irradiated with the low-dose rate micro-CT did not exhibit any symptoms or imaging changes associated with RN. Animals irradiated with the xRAD-225 exhibited imaging changes consistent with RN at week 24. Analysis of the R2* coefficient within the lesion and hippocampus shows the potential for detection of RN up to 10 weeks prior to morphological changes. Conclusions. The ability to predict areas of RN and increases of R2* within the hippocampus provides a method for long-term monitoring and prediction of RN.
DEFF Research Database (Denmark)
Fitzenberger, Bernd; Wilke, Ralf Andreas
2015-01-01
if the mean regression model does not. We provide a short informal introduction into the principle of quantile regression which includes an illustrative application from empirical labor market research. This is followed by briefly sketching the underlying statistical model for linear quantile regression based......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...... by modeling conditional quantiles. Quantile regression can therefore detect whether the partial effect of a regressor on the conditional quantiles is the same for all quantiles or differs across quantiles. Quantile regression can provide evidence for a statistical relationship between two variables even...
Slip safety risk analysis of surface properties using the coefficients of friction of rocks.
Çoşkun, Gültekin; Sarıışık, Gencay; Sarıışık, Ali
2017-12-19
This study was conducted to determine the most appropriate surface processing techniques (SPT), environmental conditions (EC) and surface roughness (SR) to minimize the risk of slipping when pedestrians walk on a floor covering of rocks barefoot and with shoes. Coefficients of friction (COFs) and values of SR were found using five different types of rocks, four SPT and two (ramp and pendulum) tests. Results indicate that the parameters which affect the COF values of rocks include SR, EC and SPT. Simple linear regression was performed to examine the relationship between the values of the COF and the SR. The value of the COF was identified as R 2 ≥ 0.864. Statistical results, which are based on experimental measurements, show that rocks are classified according to their safe use areas depending on their COF and SR values.
Energy Technology Data Exchange (ETDEWEB)
Henninger, B., E-mail: benjamin.henninger@i-med.ac.at [Department of Radiology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck (Austria); Rauch, S. [Department of Radiology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck (Austria); Zoller, H. [Department of Internal Medicine, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck (Austria); Plaikner, M.; Jaschke, W.; Kremser, C. [Department of Radiology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck (Austria)
2017-04-15
Highlights: • MRI with R2* relaxometry is suitable to detect iron overload of the pancreas. • Pancreatic iron overload can be present in HFE associated hereditary hemochromatosis. • R2* relaxometry of the pancreas should then be performed when liver iron is present. • It can be omitted in cases with no sign of hepatic iron. - Abstract: Purpose: To evaluate pancreatic iron in patients with human hemochromatosis protein associated hereditary hemochromatosis (HHC) using R2* relaxometry. Materials and methods: 81 patients (58 male, 23 female; median age 49.5, range 10–81 years) with HHC were retrospectively studied. All underwent 1.5 T magnetic resonance imaging (MRI) of the abdomen. A fat-saturated multi-gradient echo sequence with 12 echoes (TR = 200 ms; TE-initial 0.99 ms; Delta-TE 1.41 ms; 12 echoes; flip-angle: 20°) was used for the R2* quantification of the liver and the pancreas. Parameter maps were analyzed using regions of interest (3 in the liver and 2 in the pancreas) and R2* values were correlated. Results: 59/81 patients had a liver R2* ≥ 70 1/s of which 10/59 patients had a pancreas R2* ≥ 50 1/s. No patient presented with a liver R2* < 70 1/s and pancreas R2* ≥ 50 1/s. All patients with pancreas R2* values ≥ 50 1/s had liver R2* values ≥ 70 1/s. ROC analysis resulted in a threshold of 209.4 1/s for liver R2* values to identify HFE positive patients with pancreas R2* values ≥ 50 1/s with a median specificity of 78.87% and a median sensitivity of 90%. Conclusion: In patients with HHC R2* relaxometry of the pancreas should be performed when liver iron overload is present and can be omitted in cases with no sign of hepatic iron.
International Nuclear Information System (INIS)
Henninger, B.; Rauch, S.; Zoller, H.; Plaikner, M.; Jaschke, W.; Kremser, C.
2017-01-01
Highlights: • MRI with R2* relaxometry is suitable to detect iron overload of the pancreas. • Pancreatic iron overload can be present in HFE associated hereditary hemochromatosis. • R2* relaxometry of the pancreas should then be performed when liver iron is present. • It can be omitted in cases with no sign of hepatic iron. - Abstract: Purpose: To evaluate pancreatic iron in patients with human hemochromatosis protein associated hereditary hemochromatosis (HHC) using R2* relaxometry. Materials and methods: 81 patients (58 male, 23 female; median age 49.5, range 10–81 years) with HHC were retrospectively studied. All underwent 1.5 T magnetic resonance imaging (MRI) of the abdomen. A fat-saturated multi-gradient echo sequence with 12 echoes (TR = 200 ms; TE-initial 0.99 ms; Delta-TE 1.41 ms; 12 echoes; flip-angle: 20°) was used for the R2* quantification of the liver and the pancreas. Parameter maps were analyzed using regions of interest (3 in the liver and 2 in the pancreas) and R2* values were correlated. Results: 59/81 patients had a liver R2* ≥ 70 1/s of which 10/59 patients had a pancreas R2* ≥ 50 1/s. No patient presented with a liver R2* < 70 1/s and pancreas R2* ≥ 50 1/s. All patients with pancreas R2* values ≥ 50 1/s had liver R2* values ≥ 70 1/s. ROC analysis resulted in a threshold of 209.4 1/s for liver R2* values to identify HFE positive patients with pancreas R2* values ≥ 50 1/s with a median specificity of 78.87% and a median sensitivity of 90%. Conclusion: In patients with HHC R2* relaxometry of the pancreas should be performed when liver iron overload is present and can be omitted in cases with no sign of hepatic iron.
Uca; Toriman, Ekhwan; Jaafar, Othman; Maru, Rosmini; Arfan, Amal; Saleh Ahmar, Ansari
2018-01-01
Prediction of suspended sediment discharge in a catchments area is very important because it can be used to evaluation the erosion hazard, management of its water resources, water quality, hydrology project management (dams, reservoirs, and irrigation) and to determine the extent of the damage that occurred in the catchments. Multiple Linear Regression analysis and artificial neural network can be used to predict the amount of daily suspended sediment discharge. Regression analysis using the least square method, whereas artificial neural networks using Radial Basis Function (RBF) and feedforward multilayer perceptron with three learning algorithms namely Levenberg-Marquardt (LM), Scaled Conjugate Descent (SCD) and Broyden-Fletcher-Goldfarb-Shanno Quasi-Newton (BFGS). The number neuron of hidden layer is three to sixteen, while in output layer only one neuron because only one output target. The mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R2 ) and coefficient of efficiency (CE) of the multiple linear regression (MLRg) value Model 2 (6 input variable independent) has the lowest the value of MAE and RMSE (0.0000002 and 13.6039) and highest R2 and CE (0.9971 and 0.9971). When compared between LM, SCG and RBF, the BFGS model structure 3-7-1 is the better and more accurate to prediction suspended sediment discharge in Jenderam catchment. The performance value in testing process, MAE and RMSE (13.5769 and 17.9011) is smallest, meanwhile R2 and CE (0.9999 and 0.9998) is the highest if it compared with the another BFGS Quasi-Newton model (6-3-1, 9-10-1 and 12-12-1). Based on the performance statistics value, MLRg, LM, SCG, BFGS and RBF suitable and accurately for prediction by modeling the non-linear complex behavior of suspended sediment responses to rainfall, water depth and discharge. The comparison between artificial neural network (ANN) and MLRg, the MLRg Model 2 accurately for to prediction suspended sediment discharge (kg
Understanding logistic regression analysis
Sperandei, Sandro
2014-01-01
Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using ex...
Introduction to regression graphics
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
Alternative Methods of Regression
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
Structure and Mechanism of Receptoe Sharing by the IL-10R2 Common Chain
Energy Technology Data Exchange (ETDEWEB)
Yoon, Sung-il; Jones, Brandi C.; Logsdon, Naomi J.; Harris, Bethany D.; Deshpande, Ashlesha; Radaeva, Svetlana; Halloran, Brian A.; Gao, Bin; Walter, Mark R. (NIH); (UAB)
2010-06-14
IL-10R2 is a shared cell surface receptor required for the activation of five class 2 cytokines (IL-10, IL-22, IL-26, IL-28, and IL-29) that play critical roles in host defense. To define the molecular mechanisms that regulate its promiscuous binding, we have determined the crystal structure of the IL-10R2 ectodomain at 2.14 {angstrom} resolution. IL-10R2 residues required for binding were identified by alanine scanning and used to derive computational models of IL-10/IL-10R1/IL-10R2 and IL-22/IL-22R1/IL-10R2 ternary complexes. The models reveal a conserved binding epitope that is surrounded by two clefts that accommodate the structural and chemical diversity of the cytokines. These results provide a structural framework for interpreting IL-10R2 single nucleotide polymorphisms associated with human disease.
Structure and Mechanism of Receptor Sharing by the IL-10R2 Common Chain
Energy Technology Data Exchange (ETDEWEB)
Yoon, Sung-il; Jones, Brandi C.; Logsdon, Naomi J.; Harris, Bethany D.; Deshpande, Ashlesha; Radaeva, Svetlana; Halloran, Brian A.; Gao, Bin; Walter, Mark R. (NIH); (UAB)
2010-07-19
IL-10R2 is a shared cell surface receptor required for the activation of five class 2 cytokines (IL-10, IL-22, IL-26, IL-28, and IL-29) that play critical roles in host defense. To define the molecular mechanisms that regulate its promiscuous binding, we have determined the crystal structure of the IL-10R2 ectodomain at 2.14 {angstrom} resolution. IL-10R2 residues required for binding were identified by alanine scanning and used to derive computational models of IL-10/IL-10R1/IL-10R2 and IL-22/IL-22R1/IL-10R2 ternary complexes. The models reveal a conserved binding epitope that is surrounded by two clefts that accommodate the structural and chemical diversity of the cytokines. These results provide a structural framework for interpreting IL-10R2 single nucleotide polymorphisms associated with human disease.
Sabour, Mohammad Reza; Moftakhari Anasori Movahed, Saman
2017-02-01
The soil sorption partition coefficient logK oc is an indispensable parameter that can be used in assessing the environmental risk of organic chemicals. In order to predict soil sorption partition coefficient for different and even unknown compounds in a fast and accurate manner, a radial basis function neural network (RBFNN) model was developed. Eight topological descriptors of 800 organic compounds were used as inputs of the model. These 800 organic compounds were chosen from a large and very diverse data set. Generalized Regression Neural Network (GRNN) was utilized as the function in this neural network model due to its capability to adapt very quickly. Hence, it can be used to predict logK oc for new chemicals, as well. Out of total data set, 560 organic compounds were used for training and 240 to test efficiency of the model. The obtained results indicate that the model performance is very well. The correlation coefficients (R2) for training and test sets were 0.995 and 0.933, respectively. The root-mean square errors (RMSE) were 0.2321 for training set and 0.413 for test set. As the results for both training and test set are extremely satisfactory, the proposed neural network model can be employed not only to predict logK oc of known compounds, but also to be adaptive for prediction of this value precisely for new products that enter the market each year. Copyright © 2016 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Eugenia E Montiel
Full Text Available R2 non-LTR retrotransposons exclusively insert into the 28S rRNA genes of their host, and are expressed by co-transcription with the rDNA unit. The grasshopper Eyprepocnemis plorans contains transcribed rDNA clusters on most of its A chromosomes, as well as non-transcribed rDNA clusters on the parasitic B chromosomes found in many populations. Here the structure of the E. plorans R2 element, its abundance relative to the number of rDNA units and its retrotransposition activity were determined. Animals screened from five populations contained on average over 12,000 rDNA units on their A chromosomes, but surprisingly only about 100 R2 elements. Monitoring the patterns of R2 insertions in individuals from these populations revealed only low levels of retrotransposition. The low rates of R2 insertion observed in E. plorans differ from the high levels of R2 insertion previously observed in insect species that have many fewer rDNA units. It is proposed that high levels of R2 are strongly selected against in E. plorans, because the rDNA transcription machinery in this species is unable to differentiate between R2-inserted and uninserted units. The B chromosomes of E. plorans contain an additional 7,000 to 15,000 rDNA units, but in contrast to the A chromosomes, from 150 to over 1,500 R2 elements. The higher concentration of R2 in the inactive B chromosomes rDNA clusters suggests these chromosomes can act as a sink for R2 insertions thus further reducing the level of insertions on the A chromosomes. These studies suggest an interesting evolutionary relationship between the parasitic B chromosomes and R2 elements.
The Implementation of C-ID, R2D2 Model on Learning Reading Comprehension
Rayanto, Yudi Hari; Rusmawan, Putu Ngurah
2016-01-01
The purposes of this research are to find out, (1) whether C-ID, R2D2 model is effective to be implemented on learning Reading comprehension, (2) college students' activity during the implementation of C-ID, R2D2 model on learning Reading comprehension, and 3) college students' learning achievement during the implementation of C-ID, R2D2 model on…
Henninger, B; Rauch, S; Zoller, H; Plaikner, M; Jaschke, W; Kremser, C
2017-04-01
To evaluate pancreatic iron in patients with human hemochromatosis protein associated hereditary hemochromatosis (HHC) using R2* relaxometry. 81 patients (58 male, 23 female; median age 49.5, range 10-81 years) with HHC were retrospectively studied. All underwent 1.5T magnetic resonance imaging (MRI) of the abdomen. A fat-saturated multi-gradient echo sequence with 12 echoes (TR=200ms; TE-initial 0.99ms; Delta-TE 1.41ms; 12 echoes; flip-angle: 20°) was used for the R2* quantification of the liver and the pancreas. Parameter maps were analyzed using regions of interest (3 in the liver and 2 in the pancreas) and R2* values were correlated. 59/81 patients had a liver R2*≥70 1/s of which 10/59 patients had a pancreas R2*≥50 1/s. No patient presented with a liver R2*pancreas R2*≥50 1/s. All patients with pancreas R2* values≥50 1/s had liver R2* values≥70 1/s. ROC analysis resulted in a threshold of 209.4 1/s for liver R2* values to identify HFE positive patients with pancreas R2* values≥50 1/s with a median specificity of 78.87% and a median sensitivity of 90%. In patients with HHC R2* relaxometry of the pancreas should be performed when liver iron overload is present and can be omitted in cases with no sign of hepatic iron. Copyright © 2017 Elsevier B.V. All rights reserved.
MCSA Windows Server 2012 R2 installation and configuration study guide exam 70-410
Panek, William
2015-01-01
Master Windows Server installation and configuration withhands-on practice and interactive study aids for the MCSA: WindowsServer 2012 R2 exam 70-410 MCSA: Windows Server 2012 R2 Installation and ConfigurationStudy Guide: Exam 70-410 provides complete preparationfor exam 70-410: Installing and Configuring Windows Server 2012 R2.With comprehensive coverage of all exam topics and plenty ofhands-on practice, this self-paced guide is the ideal resource forthose preparing for the MCSA on Windows Server 2012 R2. Real-worldscenarios demonstrate how the lessons are applied in everydaysettings. Reader
R2P in the UN Security Council: Darfur, Libya and beyond
Gifkins, J
2016-01-01
It has been argued that consensus on the responsibility to protect (R2P) was lost in the UN Security Council as a result of the NATO-led intervention in Libya in 2011. This argument assumes that there was more agreement on R2P before the Libyan intervention than there was afterwards. Yet a close examination of the Security Council’s use of language on R2P shows the opposite: R2P was highly contentious within the Security Council prior to the Libyan intervention, and less so afterwards. Not on...
Describing Growth Pattern of Bali Cows Using Non-linear Regression Models
Directory of Open Access Journals (Sweden)
Mohd. Hafiz A.W
2016-12-01
Full Text Available The objective of this study was to evaluate the best fit non-linear regression model to describe the growth pattern of Bali cows. Estimates of asymptotic mature weight, rate of maturing and constant of integration were derived from Brody, von Bertalanffy, Gompertz and Logistic models which were fitted to cross-sectional data of body weight taken from 74 Bali cows raised in MARDI Research Station Muadzam Shah Pahang. Coefficient of determination (R2 and residual mean squares (MSE were used to determine the best fit model in describing the growth pattern of Bali cows. Von Bertalanffy model was the best model among the four growth functions evaluated to determine the mature weight of Bali cattle as shown by the highest R2 and lowest MSE values (0.973 and 601.9, respectively, followed by Gompertz (0.972 and 621.2, respectively, Logistic (0.971 and 648.4, respectively and Brody (0.932 and 660.5, respectively models. The correlation between rate of maturing and mature weight was found to be negative in the range of -0.170 to -0.929 for all models, indicating that animals of heavier mature weight had lower rate of maturing. The use of non-linear model could summarize the weight-age relationship into several biologically interpreted parameters compared to the entire lifespan weight-age data points that are difficult and time consuming to interpret.
Mansouri, Edris; Feizi, Faranak; Jafari Rad, Alireza; Arian, Mehran
2018-03-01
This paper uses multivariate regression to create a mathematical model for iron skarn exploration in the Sarvian area, central Iran, using multivariate regression for mineral prospectivity mapping (MPM). The main target of this paper is to apply multivariate regression analysis (as an MPM method) to map iron outcrops in the northeastern part of the study area in order to discover new iron deposits in other parts of the study area. Two types of multivariate regression models using two linear equations were employed to discover new mineral deposits. This method is one of the reliable methods for processing satellite images. ASTER satellite images (14 bands) were used as unique independent variables (UIVs), and iron outcrops were mapped as dependent variables for MPM. According to the results of the probability value (p value), coefficient of determination value (R2) and adjusted determination coefficient (Radj2), the second regression model (which consistent of multiple UIVs) fitted better than other models. The accuracy of the model was confirmed by iron outcrops map and geological observation. Based on field observation, iron mineralization occurs at the contact of limestone and intrusive rocks (skarn type).
Determination of corneal elasticity coefficient using the ORA database.
Avetisov, Sergei E; Novikov, Ivan A; Bubnova, Irina A; Antonov, Alexei A; Siplivyi, Vladimir I
2010-07-01
To propose a new approach for the study of corneal biomechanics using the Reichert Ocular Response Analyzer (ORA) database, which is based on changes in velocity retardation in the central cornea at the peak of flattening. The ORA applanation curve was analyzed using a mathematical technique, which allowed calculation of the elasticity coefficient (Ke), which is primarily characteristic of the elastic properties of the cornea. Elasticity coefficient values were obtained in patients with presumably different biomechanical properties of the cornea: "normal" cornea (71 eyes, normal group), keratoconus (34 eyes, keratoconus group), LASIK (36 eyes, LASIK group), and glaucoma with elevated and compensated intraocular pressure (lOP) (38 eyes, glaucoma group). The mean Ke value in the normal group was 11.05 +/- 1.6, and the corneal thickness correlation coefficient r2 was 0.48. In the keratoconus group, the mean Ke value was 4.91 +/- 1.87 and the corneal thickness correlation coefficient r2 was 0.47. In the LASIK group, Ke and r2 were 5.99 +/- 1.18 and 0.39, respectively. In the glaucoma group, the same eyes that experienced a two-fold reduction in lOP developed a statistically significant reduction in the Ke (1.06 times lower), whereas their corneal hysteresis value increased 1.25 times. The elasticity coefficient calculated using the ORA applanation curve can be used in the evaluation of corneal biomechanical properties.
Transport Coefficients of Fluids
Eu, Byung Chan
2006-01-01
Until recently the formal statistical mechanical approach offered no practicable method for computing the transport coefficients of liquids, and so most practitioners had to resort to empirical fitting formulas. This has now changed, as demonstrated in this innovative monograph. The author presents and applies new methods based on statistical mechanics for calculating the transport coefficients of simple and complex liquids over wide ranges of density and temperature. These molecular theories enable the transport coefficients to be calculated in terms of equilibrium thermodynamic properties, and the results are shown to account satisfactorily for experimental observations, including even the non-Newtonian behavior of fluids far from equilibrium.
Ghadiriyan Arani, M.; Pahlavani, P.; Effati, M.; Noori Alamooti, F.
2017-09-01
Today, one of the social problems influencing on the lives of many people is the road traffic crashes especially the highway ones. In this regard, this paper focuses on highway of capital and the most populous city in the U.S. state of Georgia and the ninth largest metropolitan area in the United States namely Atlanta. Geographically weighted regression and general centrality criteria are the aspects of traffic used for this article. In the first step, in order to estimate of crash intensity, it is needed to extract the dual graph from the status of streets and highways to use general centrality criteria. With the help of the graph produced, the criteria are: Degree, Pageranks, Random walk, Eccentricity, Closeness, Betweenness, Clustering coefficient, Eigenvector, and Straightness. The intensity of crash point is counted for every highway by dividing the number of crashes in that highway to the total number of crashes. Intensity of crash point is calculated for each highway. Then, criteria and crash point were normalized and the correlation between them was calculated to determine the criteria that are not dependent on each other. The proposed hybrid approach is a good way to regression issues because these effective measures result to a more desirable output. R2 values for geographically weighted regression using the Gaussian kernel was 0.539 and also 0.684 was obtained using a triple-core cube. The results showed that the triple-core cube kernel is better for modeling the crash intensity.
Directory of Open Access Journals (Sweden)
M. Ghadiriyan Arani
2017-09-01
Full Text Available Today, one of the social problems influencing on the lives of many people is the road traffic crashes especially the highway ones. In this regard, this paper focuses on highway of capital and the most populous city in the U.S. state of Georgia and the ninth largest metropolitan area in the United States namely Atlanta. Geographically weighted regression and general centrality criteria are the aspects of traffic used for this article. In the first step, in order to estimate of crash intensity, it is needed to extract the dual graph from the status of streets and highways to use general centrality criteria. With the help of the graph produced, the criteria are: Degree, Pageranks, Random walk, Eccentricity, Closeness, Betweenness, Clustering coefficient, Eigenvector, and Straightness. The intensity of crash point is counted for every highway by dividing the number of crashes in that highway to the total number of crashes. Intensity of crash point is calculated for each highway. Then, criteria and crash point were normalized and the correlation between them was calculated to determine the criteria that are not dependent on each other. The proposed hybrid approach is a good way to regression issues because these effective measures result to a more desirable output. R2 values for geographically weighted regression using the Gaussian kernel was 0.539 and also 0.684 was obtained using a triple-core cube. The results showed that the triple-core cube kernel is better for modeling the crash intensity.
Application of Soft Computing Techniques and Multiple Regression Models for CBR prediction of Soils
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Fatimah Khaleel Ibrahim
2017-08-01
Full Text Available The techniques of soft computing technique such as Artificial Neutral Network (ANN have improved the predicting capability and have actually discovered application in Geotechnical engineering. The aim of this research is to utilize the soft computing technique and Multiple Regression Models (MLR for forecasting the California bearing ratio CBR( of soil from its index properties. The indicator of CBR for soil could be predicted from various soils characterizing parameters with the assist of MLR and ANN methods. The data base that collected from the laboratory by conducting tests on 86 soil samples that gathered from different projects in Basrah districts. Data gained from the experimental result were used in the regression models and soft computing techniques by using artificial neural network. The liquid limit, plastic index , modified compaction test and the CBR test have been determined. In this work, different ANN and MLR models were formulated with the different collection of inputs to be able to recognize their significance in the prediction of CBR. The strengths of the models that were developed been examined in terms of regression coefficient (R2, relative error (RE% and mean square error (MSE values. From the results of this paper, it absolutely was noticed that all the proposed ANN models perform better than that of MLR model. In a specific ANN model with all input parameters reveals better outcomes than other ANN models.
Soil moisture estimation using multi linear regression with terraSAR-X data
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G. García
2016-06-01
Full Text Available The first five centimeters of soil form an interface where the main heat fluxes exchanges between the land surface and the atmosphere occur. Besides ground measurements, remote sensing has proven to be an excellent tool for the monitoring of spatial and temporal distributed data of the most relevant Earth surface parameters including soil’s parameters. Indeed, active microwave sensors (Synthetic Aperture Radar - SAR offer the opportunity to monitor soil moisture (HS at global, regional and local scales by monitoring involved processes. Several inversion algorithms, that derive geophysical information as HS from SAR data, were developed. Many of them use electromagnetic models for simulating the backscattering coefficient and are based on statistical techniques, such as neural networks, inversion methods and regression models. Recent studies have shown that simple multiple regression techniques yield satisfactory results. The involved geophysical variables in these methodologies are descriptive of the soil structure, microwave characteristics and land use. Therefore, in this paper we aim at developing a multiple linear regression model to estimate HS on flat agricultural regions using TerraSAR-X satellite data and data from a ground weather station. The results show that the backscatter, the precipitation and the relative humidity are the explanatory variables of HS. The results obtained presented a RMSE of 5.4 and a R2 of about 0.6
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Matthias Schmid
Full Text Available Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on the interval (0,1. Consequently, beta regression is a convenient tool for analyzing percentage responses. The classical approach to fit a beta regression model is to use maximum likelihood estimation with subsequent AIC-based variable selection. As an alternative to this established - yet unstable - approach, we propose a new estimation technique called boosted beta regression. With boosted beta regression estimation and variable selection can be carried out simultaneously in a highly efficient way. Additionally, both the mean and the variance of a percentage response can be modeled using flexible nonlinear covariate effects. As a consequence, the new method accounts for common problems such as overdispersion and non-binomial variance structures.
Tracking time-varying coefficient-functions
DEFF Research Database (Denmark)
Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Joensen, Alfred K.
2000-01-01
is a combination of recursive least squares with exponential forgetting and local polynomial regression. It is argued, that it is appropriate to let the forgetting factor vary with the value of the external signal which is the argument of the coefficient functions. Some of the key properties of the modified method...... are studied by simulation...
Understanding logistic regression analysis.
Sperandei, Sandro
2014-01-01
Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using examples to make it as simple as possible. After definition of the technique, the basic interpretation of the results is highlighted and then some special issues are discussed.
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
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-
γ-Aminobutyric Acid Type B (GABAB) Receptor Internalization Is Regulated by the R2 Subunit*
Hannan, Saad; Wilkins, Megan E.; Dehghani-Tafti, Ebrahim; Thomas, Philip; Baddeley, Stuart M.; Smart, Trevor G.
2011-01-01
γ-Aminobutyric acid type B (GABAB) receptors are important for slow synaptic inhibition in the CNS. The efficacy of inhibition is directly related to the stability of cell surface receptors. For GABAB receptors, heterodimerization between R1 and R2 subunits is critical for cell surface expression and signaling, but how this determines the rate and extent of receptor internalization is unknown. Here, we insert a high affinity α-bungarotoxin binding site into the N terminus of the R2 subunit and reveal its dominant role in regulating the internalization of GABAB receptors in live cells. To simultaneously study R1a and R2 trafficking, a new α-bungarotoxin binding site-labeling technique was used, allowing α-bungarotoxin conjugated to different fluorophores to selectively label R1a and R2 subunits. This approach demonstrated that R1a and R2 are internalized as dimers. In heterologous expression systems and neurons, the rates and extents of internalization for R1aR2 heteromers and R2 homomers are similar, suggesting a regulatory role for R2 in determining cell surface receptor stability. The fast internalization rate of R1a, which has been engineered to exit the endoplasmic reticulum, was slowed to that of R2 by truncating the R1a C-terminal tail or by removing a dileucine motif in its coiled-coil domain. Slowing the rate of internalization by co-assembly with R2 represents a novel role for GPCR heterodimerization whereby R2 subunits, via their C terminus coiled-coil domain, mask a dileucine motif on R1a subunits to determine the surface stability of the GABAB receptor. PMID:21724853
Building a SuAVE browse interface to R2R's Linked Data
Clark, D.; Stocks, K. I.; Arko, R. A.; Zaslavsky, I.; Whitenack, T.
2017-12-01
The Rolling Deck to Repository program (R2R) is creating and evaluating a new browse portal based on the SuAVE platform and the R2R linked data graph. R2R manages the underway sensor data collected by the fleet of US academic research vessels, and provides a discovery and access point to those data at its website, www.rvdata.us. R2R has a database-driven search interface, but seeks a more capable and extensible browse interface that could be built off of the substantial R2R linked data resources. R2R's Linked Data graph organizes its data holdings around key concepts (e.g. cruise, vessel, device type, operator, award, organization, publication), anchored by persistent identifiers where feasible. The "Survey Analysis via Visual Exploration" or SuAVE platform (suave.sdsc.edu) is a system for online publication, sharing, and analysis of images and metadata. It has been implemented as an interface to diverse data collections, but has not been driven off of linked data in the past. SuAVE supports several features of interest to R2R, including faceted searching, collaborative annotations, efficient subsetting, Google maps-like navigation over an image gallery, and several types of data analysis. Our initial SuAVE-based implementation was through a CSV export from the R2R PostGIS-enabled PostgreSQL database. This served to demonstrate the utility of SuAVE but was static and required reloading as R2R data holdings grew. We are now working to implement a SPARQL-based ("RDF Query Language") service that directly leverages the R2R Linked Data graph and offers the ability to subset and/or customize output.We will show examples of SuAVE faceted searches on R2R linked data concepts, and discuss our experience to date with this work in progress.
Significance testing in ridge regression for genetic data
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De Iorio Maria
2011-09-01
Full Text Available Abstract Background Technological developments have increased the feasibility of large scale genetic association studies. Densely typed genetic markers are obtained using SNP arrays, next-generation sequencing technologies and imputation. However, SNPs typed using these methods can be highly correlated due to linkage disequilibrium among them, and standard multiple regression techniques fail with these data sets due to their high dimensionality and correlation structure. There has been increasing interest in using penalised regression in the analysis of high dimensional data. Ridge regression is one such penalised regression technique which does not perform variable selection, instead estimating a regression coefficient for each predictor variable. It is therefore desirable to obtain an estimate of the significance of each ridge regression coefficient. Results We develop and evaluate a test of significance for ridge regression coefficients. Using simulation studies, we demonstrate that the performance of the test is comparable to that of a permutation test, with the advantage of a much-reduced computational cost. We introduce the p-value trace, a plot of the negative logarithm of the p-values of ridge regression coefficients with increasing shrinkage parameter, which enables the visualisation of the change in p-value of the regression coefficients with increasing penalisation. We apply the proposed method to a lung cancer case-control data set from EPIC, the European Prospective Investigation into Cancer and Nutrition. Conclusions The proposed test is a useful alternative to a permutation test for the estimation of the significance of ridge regression coefficients, at a much-reduced computational cost. The p-value trace is an informative graphical tool for evaluating the results of a test of significance of ridge regression coefficients as the shrinkage parameter increases, and the proposed test makes its production computationally feasible.
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...... shrinks the coefficient of each observation in the estimated functions; thus, it is widely used for minimizing influence of outliers. We propose to additionally add weights to the slack variables in the constraints (CF‐weights) and call the combination of weights the doubly weighted SVR. We illustrate...... the differences and similarities of the two types of weights by demonstrating the connection between the Least Absolute Shrinkage and Selection Operator (LASSO) and the SVR. We show that an SVR problem can be transformed to a LASSO problem plus a linear constraint and a box constraint. We demonstrate...
Understanding poisson regression.
Hayat, Matthew J; Higgins, Melinda
2014-04-01
Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes. Copyright 2014, SLACK Incorporated.
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Vukić Vladimir Đ.
2012-01-01
Full Text Available Following a deep discharge of AGM SVT 300 valve-regulated lead-acid batteries using the ten-hour discharge current, the batteries were charged using variable current. In accordance with the obtained results, exponential and polynomial functions for the approximation of the specified processes were analyzed. The main evaluation instrument for the quality of the implemented approximations was the adjusted coefficient of determination R-2. It was perceived that the battery discharge process might be successfully approximated with both an exponential and the second order polynomial function. On all the occasions analyzed, values of the adjusted coefficient of determination were greater than 0.995. The charging process of the deeply discharged batteries was successfully approximated with the exponential function; the measured values of the adjusted coefficient of determination being nearly 0.95. Apart from the high measured values of the adjusted coefficient of determination, polynomial approximations of the second and third order did not provide satisfactory results regarding the interpolation of the battery charging characteristics. A possibility for a practical implementation of the procured regression functions in uninterruptible power supply systems was described.
Wisnieff, Cynthia; Liu, Tian; Wang, Yi; Spincemaille, Pascal
2016-06-01
In this work, we demonstrate that in the presence of ordered sub-voxel structure such as tubular organization, biomaterials with molecular isotropy exhibits only apparent R2* anisotropy, while biomaterials with molecular anisotropy exhibit both apparent R2* and susceptibility anisotropy by means of susceptibility tensor imaging (STI). To this end, R2* and STI from gradient echo magnitude and phase data were examined in phantoms made from carbon fiber and Gadolinium (Gd) solutions with and without intrinsic molecular order and sub-voxel structure as well as in the in vivo brain. Confidence in the tensor reconstructions was evaluated with a wild bootstrap analysis. Carbon fiber showed both apparent anisotropy in R2* and anisotropy in STI, while the Gd filled capillary tubes only showed apparent anisotropy on R2*. Similarly, white matter showed anisotropic R2* and magnetic susceptibility with higher confidence, while the cerebral veins displayed only strong apparent R2* tensor anisotropy. Ordered sub-voxel tissue microstructure leads to apparent R2* anisotropy, which can be found in both white matter tracts and cerebral veins. However, additional molecular anisotropy is required for magnetic susceptibility anisotropy, which can be found in white matter tracts but not in cerebral veins. Copyright © 2016 Elsevier Inc. All rights reserved.
High nigral iron deposition in LRRK2 and Parkin mutation carriers using R2* relaxometry
DEFF Research Database (Denmark)
Pyatigorskaya, Nadya; Sharman, Michael; Corvol, Jean-Christophe
2015-01-01
symptomatic and two asymptomatic Parkin subjects, nine symptomatic and five asymptomatic LRRK2 subjects) were compared with 20 patients with idiopathic PD (IPD) and 20 healthy subjects. Images were obtained at 3 teslas, using multi-echo T2 and T2* sequences. R2 and R2* values were calculated in the substantia...
R2U2: Monitoring and Diagnosis of Security Threats for Unmanned Aerial Systems
Schumann, Johann; Moosbruger, Patrick; Rozier, Kristin Y.
2015-01-01
We present R2U2, a novel framework for runtime monitoring of security properties and diagnosing of security threats on-board Unmanned Aerial Systems (UAS). R2U2, implemented in FPGA hardware, is a real-time, REALIZABLE, RESPONSIVE, UNOBTRUSIVE Unit for security threat detection. R2U2 is designed to continuously monitor inputs from the GPS and the ground control station, sensor readings, actuator outputs, and flight software status. By simultaneously monitoring and performing statistical reasoning, attack patterns and post-attack discrepancies in the UAS behavior can be detected. R2U2 uses runtime observer pairs for linear and metric temporal logics for property monitoring and Bayesian networks for diagnosis of security threats. We discuss the design and implementation that now enables R2U2 to handle security threats and present simulation results of several attack scenarios on the NASA DragonEye UAS.
Discharge Coefficient of Rectangular Short-Crested Weir with Varying Slope Coefficients
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Yuejun Chen
2018-02-01
Full Text Available Rectangular short-crested weirs are widely used for simple structure and high discharge capacity. As one of the most important and influential factors of discharge capacity, side slope can improve the hydraulic characteristics of weirs at special conditions. In order to systemically study the effects of upstream and downstream slope coefficients S1 and S2 on overflow discharge coefficient in a rectangular short-crested weir the Volume of Fluid (VOF method and the Renormalization Group (RNG κ-ε turbulence model are used. In this study, the slope coefficient ranges from V to 3H:1V and each model corresponds to five total energy heads of H0 ranging from 8.0 to 24.0 cm. Comparisons of discharge coefficients and free surface profiles between simulated and laboratory results display a good agreement. The simulated results show that the difference of discharge coefficients will decrease with upstream slopes and increase with downstream slopes as H0 increases. For a given H0, the discharge coefficient has a convex parabolic relation with S1 and a piecewise linearity relation with S2. The maximum discharge coefficient is always obtained at S2 = 0.8. There exists a difference between upstream and downstream slope coefficients in the influence range of free surface curvatures. Furthermore, a proposed discharge coefficient equation by nonlinear regression is a function of upstream and downstream slope coefficients.
Kolasa-Wiecek, Alicja
2015-04-01
The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO2 emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH4 emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (-0.64) as the most important variables. The adjusted coefficient is suitable and equals R2=0.90. For N2O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N2O emission is the peat and wood fuel consumption. Copyright © 2015. Published by Elsevier B.V.
Energy Technology Data Exchange (ETDEWEB)
Serai, Suraj D.; Fleck, Robert J. [Cincinnati Children' s Hospital Medical Center, Department of Radiology, MLC 5031, Cincinnati, OH (United States); Quinn, Charles T. [Cincinnati Children' s Hospital Medical Center, Division of Hematology, Cincinnati, OH (United States); Zhang, Bin [Cincinnati Children' s Hospital Medical Center, Division of Biostatistics and Epidemiology, Cincinnati, OH (United States); Podberesky, Daniel J. [Nemours Children' s Health System Nemours Children' s Hospital, Department of Radiology, Orlando, FL (United States)
2015-10-15
Serial surveillance of liver iron concentration (LIC) provides guidance for chelation therapy in patients with iron overload. The diagnosis of iron overload traditionally relies on core liver biopsy, which is limited by invasiveness, sampling error, cost and general poor acceptance by pediatric patients and parents. Thus noninvasive diagnostic methods such as MRI are highly attractive for quantification of liver iron concentration. To compare two MRI-based methods for liver iron quantification in children. 64 studies on 48 children and young adults (age range 4-21 years) were examined by gradient recalled echo (GRE) R2* and spin-echo R2 MRI at 1.5T to evaluate liver iron concentration. Scatter plots and Bland-Altman difference plots were generated to display and assess the relationship between the methods. With the protocols used in this investigation, Bland-Altman agreement between the methods is best when LIC is <20 mg/g dry tissue. Scatter plots show that all values with LIC <20 mg/g dry tissue fall within the 95% prediction limits. Liver iron concentration as determined by the R2* and R2 MR methods is statistically comparable, with no statistical difference between these methods for LIC <20 mg/g. (orig.)
Neutrosophic Correlation and Simple Linear Regression
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A. A. Salama
2014-09-01
Full Text Available Since the world is full of indeterminacy, the neutrosophics found their place into contemporary research. The fundamental concepts of neutrosophic set, introduced by Smarandache. Recently, Salama et al., introduced the concept of correlation coefficient of neutrosophic data. In this paper, we introduce and study the concepts of correlation and correlation coefficient of neutrosophic data in probability spaces and study some of their properties. Also, we introduce and study the neutrosophic simple linear regression model. Possible applications to data processing are touched upon.
DEFF Research Database (Denmark)
Bache, Stefan Holst
A new and alternative quantile regression estimator is developed and it is shown that the estimator is root n-consistent and asymptotically normal. The estimator is based on a minimax ‘deviance function’ and has asymptotically equivalent properties to the usual quantile regression estimator. It is......, however, a different and therefore new estimator. It allows for both linear- and nonlinear model specifications. A simple algorithm for computing the estimates is proposed. It seems to work quite well in practice but whether it has theoretical justification is still an open question....
DEFF Research Database (Denmark)
Ozenne, Brice; Sørensen, Anne Lyngholm; Scheike, Thomas
2017-01-01
In the presence of competing risks a prediction of the time-dynamic absolute risk of an event can be based on cause-specific Cox regression models for the event and the competing risks (Benichou and Gail, 1990). We present computationally fast and memory optimized C++ functions with an R interface...... for predicting the covariate specific absolute risks, their confidence intervals, and their confidence bands based on right censored time to event data. We provide explicit formulas for our implementation of the estimator of the (stratified) baseline hazard function in the presence of tied event times. As a by...... functionals. The software presented here is implemented in the riskRegression package....
ChR2 transgenic animals in peripheral sensory system: Sensing light as various sensations.
Ji, Zhi-Gang; Wang, Hongxia
2016-04-01
Since the introduction of Channelrhodopsin-2 (ChR2) to neuroscience, optogenetics technology was developed, making it possible to activate specific neurons or circuits with spatial and temporal precision. Various ChR2 transgenic animal models have been generated and are playing important roles in revealing the mechanisms of neural activities, mapping neural circuits, controlling the behaviors of animals as well as exploring new strategy for treating the neurological diseases in both central and peripheral nervous system. An animal including humans senses environments through Aristotle's five senses (sight, hearing, smell, taste and touch). Usually, each sense is associated with a kind of sensory organ (eyes, ears, nose, tongue and skin). Is it possible that one could hear light, smell light, taste light and touch light? When ChR2 is targeted to different peripheral sensory neurons by viral vectors or generating ChR2 transgenic animals, the animals can sense the light as various sensations such as hearing, touch, pain, smell and taste. In this review, we focus on ChR2 transgenic animals in the peripheral nervous system. Firstly the working principle of ChR2 as an optogenetic actuator is simply described. Then the current transgenic animal lines where ChR2 was expressed in peripheral sensory neurons are presented and the findings obtained by these animal models are reviewed. Copyright © 2016 Elsevier Inc. All rights reserved.
NEAR-INFRARED CIRCULAR AND LINEAR POLARIMETRY OF MONOCEROS R2
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Kwon, Jungmi; Tamura, Motohide [Department of Astronomy, Graduate School of Science, The University of Tokyo, 113-0033 (Japan); Hough, James H. [University of Hertfordshire, Hatfield, Herts AL10 9AB (United Kingdom); Nagata, Tetsuya [Kyoto University, Sakyo-ku, Kyoto 606-8502 (Japan); Kusakabe, Nobuhiko [National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo 181-8588 (Japan)
2016-09-01
We have conducted simultaneous JHK{sub s}-band imaging circular and linear polarimetry of the Monoceros R2 (Mon R2) cluster. We present results from deep and wide near-infrared linear polarimetry of the Mon R2 region. Prominent and extended polarized nebulosities over the Mon R2 field are revisited, and an infrared reflection nebula associated with the Mon R2 cluster and two local reflection nebulae, vdB 67 and vdB 69, is detected. We also present results from deep imaging circular polarimetry in the same region. For the first time, the observations show relatively high degrees of circular polarization (CP) in Mon R2, with as much as approximately 10% in the K{sub s} band. The maximum CP extent of a ring-like nebula around the Mon R2 cluster is approximately 0.60 pc, while that of a western nebula, around vdB 67, is approximately 0.24 pc. The extended size of the CP is larger than those seen in the Orion region around IRc2, while the maximum degree of CP of ∼10% is smaller than those of ∼17% seen in the Orion region. Nonetheless, both the CP size and degree of this region are among the largest in our infrared CP survey of star-forming regions. We have also investigated the time variability of the degree of the polarization of several infrared sources and found possible variations in three sources.
An R2 statistic for fixed effects in the linear mixed model.
Edwards, Lloyd J; Muller, Keith E; Wolfinger, Russell D; Qaqish, Bahjat F; Schabenberger, Oliver
2008-12-20
Statisticians most often use the linear mixed model to analyze Gaussian longitudinal data. The value and familiarity of the R(2) statistic in the linear univariate model naturally creates great interest in extending it to the linear mixed model. We define and describe how to compute a model R(2) statistic for the linear mixed model by using only a single model. The proposed R(2) statistic measures multivariate association between the repeated outcomes and the fixed effects in the linear mixed model. The R(2) statistic arises as a 1-1 function of an appropriate F statistic for testing all fixed effects (except typically the intercept) in a full model. The statistic compares the full model with a null model with all fixed effects deleted (except typically the intercept) while retaining exactly the same covariance structure. Furthermore, the R(2) statistic leads immediately to a natural definition of a partial R(2) statistic. A mixed model in which ethnicity gives a very small p-value as a longitudinal predictor of blood pressure (BP) compellingly illustrates the value of the statistic. In sharp contrast to the extreme p-value, a very small R(2) , a measure of statistical and scientific importance, indicates that ethnicity has an almost negligible association with the repeated BP outcomes for the study.
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.
2010-04-01
... nonqualified deferred compensation plans. 31.3306(r)(2)-1 Section 31.3306(r)(2)-1 Internal Revenue INTERNAL..., Internal Revenue Code of 1954) § 31.3306(r)(2)-1 Treatment of amounts deferred under certain nonqualified deferred compensation plans. (a) In general. Section 3306(r)(2) provides a special timing rule for the tax...
Nazeer, Majid; Bilal, Muhammad
2018-04-01
Landsat-5 Thematic Mapper (TM) dataset have been used to estimate salinity in the coastal area of Hong Kong. Four adjacent Landsat TM images were used in this study, which was atmospherically corrected using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative transfer code. The atmospherically corrected images were further used to develop models for salinity using Ordinary Least Square (OLS) regression and Geographically Weighted Regression (GWR) based on in situ data of October 2009. Results show that the coefficient of determination ( R 2) of 0.42 between the OLS estimated and in situ measured salinity is much lower than that of the GWR model, which is two times higher ( R 2 = 0.86). It indicates that the GWR model has more ability than the OLS regression model to predict salinity and show its spatial heterogeneity better. It was observed that the salinity was high in Deep Bay (north-western part of Hong Kong) which might be due to the industrial waste disposal, whereas the salinity was estimated to be constant (32 practical salinity units) towards the open sea.
MCSA Windows Server 2012 R2 administration study guide exam 70-411
Panek, William
2015-01-01
Complete exam coverage, hands-on practice, and interactive studytools for the MCSA: Administering Windows Server 2012 R2 exam70-411 MCSA: Windows Server 2012 R2 Administration Study Guide: Exam70-411 provides comprehensive preparation for exam 70-411:Administering Windows Server 2012 R2. With full coverage of allexam domains, this guide contains everything you need to know to befully prepared on test day. Real-world scenarios illustrate thepractical applications of the lessons, and hands-on exercises allowyou to test yourself against everyday tasks. You get access to aninteractive practice te
An ODIP effort to map R2R ocean data terms to international vocabularies
Ferreira, Renata; Stocks, Karen; Arko, Robert
2014-05-01
The heterogeneity of terminology used in describing data creates a barrier to the efficient discovery and re-use of data, particularly across institutional, programmatic, and disciplinary boundaries. Here we explore the outcomes of a student project to crosswalk terms between the Rolling Deck to Repository (R2R) program and other international systems, as part of the Ocean Data Interoperability Platform (ODIP). R2R is a US program developing and implementing an information management system to preserve and provide access to routine underway data collected by U.S academic research vessels. R2R participates in ODIP, an international forum for improving the interoperability and effective sharing of marine data resources through technical workshops and joint prototypes. The vocabulary mapping effort lays a foundation for future ocean data portals through which users search and access international ocean data using familiar terms. R2R describes its data with a suite of controlled vocabularies (http://www.rvdata.us/voc) some of which were developed locally or are specific to the US. The goal of this student project is to crosswalk local/national vocabularies to authoritative international vocabularies, where they exist, or to vocabularies widely used by ODIP partners. Specifically, R2R developed the following crosswalks: R2R science party names to ORCID person identifiers, UNOLS ports to SeaDataNet Ports Gazetteer, R2R Device Models to NVS SeaVoX Device Catalog, and R2R Organizations to the European Directory of Marine Organizations (EDMO). Mappings were done in simple spreadsheets using synonymy relationships only, and will be published as part of the R2R Linked Data resources. The level of success in crosswalking was variable. The majority of ports were successfully mapped. Differences in the character sets (i.e. whether diacritic marks were used) caused automated matching to fail occasionally, but the number of ports was small enough that these could be manually
Directory of Open Access Journals (Sweden)
Jichul Ryu
2016-04-01
Full Text Available In this study, 52 asymptotic Curve Number (CN regression equations were developed for combinations of representative land covers and hydrologic soil groups. In addition, to overcome the limitations of the original Long-term Hydrologic Impact Assessment (L-THIA model when it is applied to larger watersheds, a watershed-scale L-THIA Asymptotic CN (ACN regression equation model (watershed-scale L-THIA ACN model was developed by integrating the asymptotic CN regressions and various modules for direct runoff/baseflow/channel routing. The watershed-scale L-THIA ACN model was applied to four watersheds in South Korea to evaluate the accuracy of its streamflow prediction. The coefficient of determination (R2 and Nash–Sutcliffe Efficiency (NSE values for observed versus simulated streamflows over intervals of eight days were greater than 0.6 for all four of the watersheds. The watershed-scale L-THIA ACN model, including the asymptotic CN regression equation method, can simulate long-term streamflow sufficiently well with the ten parameters that have been added for the characterization of streamflow.
Bayesian logistic regression analysis
Van Erp, H.R.N.; Van Gelder, P.H.A.J.M.
2012-01-01
In this paper we present a Bayesian logistic regression analysis. It is found that if one wishes to derive the posterior distribution of the probability of some event, then, together with the traditional Bayes Theorem and the integrating out of nuissance parameters, the Jacobian transformation is an
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.
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.
Bayesian ARTMAP for regression.
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.
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...... with the proposed explicit noise-model extension....
and Multinomial Logistic Regression
African Journals Online (AJOL)
This work presented the results of an experimental comparison of two models: Multinomial Logistic Regression (MLR) and Artificial Neural Network (ANN) for classifying students based on their academic performance. The predictive accuracy for each model was measured by their average Classification Correct Rate (CCR).
Mechanisms of neuroblastoma regression
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
r2VIM: A new variable selection method for random forests in genome-wide association studies.
Szymczak, Silke; Holzinger, Emily; Dasgupta, Abhijit; Malley, James D; Molloy, Anne M; Mills, James L; Brody, Lawrence C; Stambolian, Dwight; Bailey-Wilson, Joan E
2016-01-01
Machine learning methods and in particular random forests (RFs) are a promising alternative to standard single SNP analyses in genome-wide association studies (GWAS). RFs provide variable importance measures (VIMs) to rank SNPs according to their predictive power. However, in contrast to the established genome-wide significance threshold, no clear criteria exist to determine how many SNPs should be selected for downstream analyses. We propose a new variable selection approach, recurrent relative variable importance measure (r2VIM). Importance values are calculated relative to an observed minimal importance score for several runs of RF and only SNPs with large relative VIMs in all of the runs are selected as important. Evaluations on simulated GWAS data show that the new method controls the number of false-positives under the null hypothesis. Under a simple alternative hypothesis with several independent main effects it is only slightly less powerful than logistic regression. In an experimental GWAS data set, the same strong signal is identified while the approach selects none of the SNPs in an underpowered GWAS. The novel variable selection method r2VIM is a promising extension to standard RF for objectively selecting relevant SNPs in GWAS while controlling the number of false-positive results.
Unobtrusive Software and System Health Management with R2U2 on a Parallel MIMD Coprocessor
Schumann, Johann; Moosbrugger, Patrick
2017-01-01
Dynamic monitoring of software and system health of a complex cyber-physical system requires observers that continuously monitor variables of the embedded software in order to detect anomalies and reason about root causes. There exists a variety of techniques for code instrumentation, but instrumentation might change runtime behavior and could require costly software re-certification. In this paper, we present R2U2E, a novel realization of our real-time, Realizable, Responsive, and Unobtrusive Unit (R2U2). The R2U2E observers are executed in parallel on a dedicated 16-core EPIPHANY co-processor, thereby avoiding additional computational overhead to the system under observation. A DMA-based shared memory access architecture allows R2U2E to operate without any code instrumentation or program interference.
Calculations of the magnetic properties of R2M14B intermetallic compounds (R=rare earth, M=Fe, Co)
International Nuclear Information System (INIS)
Ito, Masaaki; Yano, Masao; Dempsey, Nora M.; Givord, Dominique
2016-01-01
The hard magnetic properties of “R–M–B” (R=rare earth, M=mainly Fe) magnets derive from the specific intrinsic magnetic properties encountered in Fe-rich R 2 M 14 B compounds. Exchange interactions are dominated by the 3d elements, Fe and Co, and may be modeled at the macroscopic scale with good accuracy. Based on classical formulae that relate the anisotropy coefficients to the crystalline electric field parameters and exchange interactions, a simple numerical approach is used to derive the temperature dependence of anisotropy in various R 2 Fe 14 B compounds (R=Pr, Nd, Dy). Remarkably, a unique set of crystal field parameters give fair agreement with the experimentally measured properties of all compounds. This implies reciprocally that the properties of compounds that incorporate a mixture of different rare-earth elements may be predicted accurately. This is of special interest for material optimization that often involves the partial replacement of Nd with another R element and also the substitution of Co for Fe. - Highlights: • Anisotropy constants derived from CEF parameters of R 2 M 14 B compounds (M=Fe, Co). • Anisotropy constants of all R 2 Fe 14 B compounds using unique set of CEF parameters. • Moment non-collinearity in magnetization processes under B app along hard axis.
R2R - software to speed the depiction of aesthetic consensus RNA secondary structures
2011-01-01
Background With continuing identification of novel structured noncoding RNAs, there is an increasing need to create schematic diagrams showing the consensus features of these molecules. RNA structural diagrams are typically made either with general-purpose drawing programs like Adobe Illustrator, or with automated or interactive programs specific to RNA. Unfortunately, the use of applications like Illustrator is extremely time consuming, while existing RNA-specific programs produce figures that are useful, but usually not of the same aesthetic quality as those produced at great cost in Illustrator. Additionally, most existing RNA-specific applications are designed for drawing single RNA molecules, not consensus diagrams. Results We created R2R, a computer program that facilitates the generation of aesthetic and readable drawings of RNA consensus diagrams in a fraction of the time required with general-purpose drawing programs. Since the inference of a consensus RNA structure typically requires a multiple-sequence alignment, the R2R user annotates the alignment with commands directing the layout and annotation of the RNA. R2R creates SVG or PDF output that can be imported into Adobe Illustrator, Inkscape or CorelDRAW. R2R can be used to create consensus sequence and secondary structure models for novel RNA structures or to revise models when new representatives for known RNA classes become available. Although R2R does not currently have a graphical user interface, it has proven useful in our efforts to create 100 schematic models of distinct noncoding RNA classes. Conclusions R2R makes it possible to obtain high-quality drawings of the consensus sequence and structural models of many diverse RNA structures with a more practical amount of effort. R2R software is available at http://breaker.research.yale.edu/R2R and as an Additional file. PMID:21205310
R2R--software to speed the depiction of aesthetic consensus RNA secondary structures.
Weinberg, Zasha; Breaker, Ronald R
2011-01-04
With continuing identification of novel structured noncoding RNAs, there is an increasing need to create schematic diagrams showing the consensus features of these molecules. RNA structural diagrams are typically made either with general-purpose drawing programs like Adobe Illustrator, or with automated or interactive programs specific to RNA. Unfortunately, the use of applications like Illustrator is extremely time consuming, while existing RNA-specific programs produce figures that are useful, but usually not of the same aesthetic quality as those produced at great cost in Illustrator. Additionally, most existing RNA-specific applications are designed for drawing single RNA molecules, not consensus diagrams. We created R2R, a computer program that facilitates the generation of aesthetic and readable drawings of RNA consensus diagrams in a fraction of the time required with general-purpose drawing programs. Since the inference of a consensus RNA structure typically requires a multiple-sequence alignment, the R2R user annotates the alignment with commands directing the layout and annotation of the RNA. R2R creates SVG or PDF output that can be imported into Adobe Illustrator, Inkscape or CorelDRAW. R2R can be used to create consensus sequence and secondary structure models for novel RNA structures or to revise models when new representatives for known RNA classes become available. Although R2R does not currently have a graphical user interface, it has proven useful in our efforts to create 100 schematic models of distinct noncoding RNA classes. R2R makes it possible to obtain high-quality drawings of the consensus sequence and structural models of many diverse RNA structures with a more practical amount of effort. R2R software is available at http://breaker.research.yale.edu/R2R and as an Additional file.
Improved liver R2* mapping by pixel-wise curve fitting with adaptive neighborhood regularization.
Wang, Changqing; Zhang, Xinyuan; Liu, Xiaoyun; He, Taigang; Chen, Wufan; Feng, Qianjin; Feng, Yanqiu
2018-08-01
To improve liver R2* mapping by incorporating adaptive neighborhood regularization into pixel-wise curve fitting. Magnetic resonance imaging R2* mapping remains challenging because of the serial images with low signal-to-noise ratio. In this study, we proposed to exploit the neighboring pixels as regularization terms and adaptively determine the regularization parameters according to the interpixel signal similarity. The proposed algorithm, called the pixel-wise curve fitting with adaptive neighborhood regularization (PCANR), was compared with the conventional nonlinear least squares (NLS) and nonlocal means filter-based NLS algorithms on simulated, phantom, and in vivo data. Visually, the PCANR algorithm generates R2* maps with significantly reduced noise and well-preserved tiny structures. Quantitatively, the PCANR algorithm produces R2* maps with lower root mean square errors at varying R2* values and signal-to-noise-ratio levels compared with the NLS and nonlocal means filter-based NLS algorithms. For the high R2* values under low signal-to-noise-ratio levels, the PCANR algorithm outperforms the NLS and nonlocal means filter-based NLS algorithms in the accuracy and precision, in terms of mean and standard deviation of R2* measurements in selected region of interests, respectively. The PCANR algorithm can reduce the effect of noise on liver R2* mapping, and the improved measurement precision will benefit the assessment of hepatic iron in clinical practice. Magn Reson Med 80:792-801, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.
R2R - software to speed the depiction of aesthetic consensus RNA secondary structures
Directory of Open Access Journals (Sweden)
Weinberg Zasha
2011-01-01
Full Text Available Abstract Background With continuing identification of novel structured noncoding RNAs, there is an increasing need to create schematic diagrams showing the consensus features of these molecules. RNA structural diagrams are typically made either with general-purpose drawing programs like Adobe Illustrator, or with automated or interactive programs specific to RNA. Unfortunately, the use of applications like Illustrator is extremely time consuming, while existing RNA-specific programs produce figures that are useful, but usually not of the same aesthetic quality as those produced at great cost in Illustrator. Additionally, most existing RNA-specific applications are designed for drawing single RNA molecules, not consensus diagrams. Results We created R2R, a computer program that facilitates the generation of aesthetic and readable drawings of RNA consensus diagrams in a fraction of the time required with general-purpose drawing programs. Since the inference of a consensus RNA structure typically requires a multiple-sequence alignment, the R2R user annotates the alignment with commands directing the layout and annotation of the RNA. R2R creates SVG or PDF output that can be imported into Adobe Illustrator, Inkscape or CorelDRAW. R2R can be used to create consensus sequence and secondary structure models for novel RNA structures or to revise models when new representatives for known RNA classes become available. Although R2R does not currently have a graphical user interface, it has proven useful in our efforts to create 100 schematic models of distinct noncoding RNA classes. Conclusions R2R makes it possible to obtain high-quality drawings of the consensus sequence and structural models of many diverse RNA structures with a more practical amount of effort. R2R software is available at http://breaker.research.yale.edu/R2R and as an Additional file.
Ridge Regression Signal Processing
Kuhl, Mark R.
1990-01-01
The introduction of the Global Positioning System (GPS) into the National Airspace System (NAS) necessitates the development of Receiver Autonomous Integrity Monitoring (RAIM) techniques. In order to guarantee a certain level of integrity, a thorough understanding of modern estimation techniques applied to navigational problems is required. The extended Kalman filter (EKF) is derived and analyzed under poor geometry conditions. It was found that the performance of the EKF is difficult to predict, since the EKF is designed for a Gaussian environment. A novel approach is implemented which incorporates ridge regression to explain the behavior of an EKF in the presence of dynamics under poor geometry conditions. The basic principles of ridge regression theory are presented, followed by the derivation of a linearized recursive ridge estimator. Computer simulations are performed to confirm the underlying theory and to provide a comparative analysis of the EKF and the recursive ridge estimator.
Subset selection in regression
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...
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.
Regression in organizational leadership.
Kernberg, O F
1979-02-01
The choice of good leaders is a major task for all organizations. Inforamtion regarding the prospective administrator's personality should complement questions regarding his previous experience, his general conceptual skills, his technical knowledge, and the specific skills in the area for which he is being selected. The growing psychoanalytic knowledge about the crucial importance of internal, in contrast to external, object relations, and about the mutual relationships of regression in individuals and in groups, constitutes an important practical tool for the selection of leaders.
Classification and regression trees
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.
Engineering Assessment and Certification of Integrity of the 177-R2 tank system
International Nuclear Information System (INIS)
Graser, D.A.; Schwartz, W.W.
1993-10-01
This Engineering Assessment and Certification of Integrity of retention tanks 177-R2U1, 177-R2Al, and 177-R2A2 has been prepared in response to 40 CFR 265.192(a) and 22 CCR 66265.192(a) for new tank systems that store hazardous waste and have secondary containment. The regulations require that this assessment be completed and certified by an independent, qualified, California-registered professional engineer before the tank system is placed in use as a hazardous waste storage tank system. The technical assessments for the 177-R2Ul, 177-R2A1, and 177-R2A2 tank systems have been reviewed by an independent, qualified, California-registered professional engineer, who has certified that the tank systems have sufficient structural integrity, are acceptable for transferring and storing hazardous waste, are compatible with the stored waste, and the tanks and containment system are suitably designed to achieve the requirements of the applicable regulations so they will not collapse, rupture, or fail. This document will be kept on file by the Lawrence Livermore National Laboratory (LLNL) Environment Protection Department
R2R-printed inverted OPV modules - towards arbitrary patterned designs
Välimäki, M.; Apilo, P.; Po, R.; Jansson, E.; Bernardi, A.; Ylikunnari, M.; Vilkman, M.; Corso, G.; Puustinen, J.; Tuominen, J.; Hast, J.
2015-05-01
We describe the fabrication of roll-to-roll (R2R) printed organic photovoltaic (OPV) modules using gravure printing and rotary screen-printing processes. These two-dimensional printing techniques are differentiating factors from coated OPVs enabling the direct patterning of arbitrarily shaped and sized features into visual shapes and, increasing the freedom to connect the cells in modules. The inverted OPV structures comprise five layers that are either printed or patterned in an R2R printing process. We examined the rheological properties of the inks used and their relationship with the printability, the compatibility between the processed inks, and the morphology of the R2R-printed layers. We also evaluate the dimensional accuracy of the printed pattern, which is an important consideration in designing arbitrarily-shaped OPV structures. The photoactive layer and top electrode exhibited excellent cross-dimensional accuracy corresponding to the designed width. The transparent electron transport layer extended 300 µm beyond the designed values, whereas the hole transport layer shrank 100 µm. We also examined the repeatability of the R2R fabrication process when the active area of the module varied from 32.2 cm2 to 96.5 cm2. A thorough layer-by-layer optimization of the R2R printing processes resulted in realization of R2R-printed 96.5 cm2 sized modules with a maximum power conversion efficiency of 2.1% (mean 1.8%) processed with high functionality.
Ishida, Keishi; Aoki, Kaori; Takishita, Tomoko; Miyara, Masatsugu; Sakamoto, Shuichiro; Sanoh, Seigo; Kimura, Tomoki; Kanda, Yasunari; Ohta, Shigeru; Kotake, Yaichiro
2017-08-11
Tributyltin (TBT), which has been widely used as an antifouling agent in paints, is a common environmental pollutant. Although the toxicity of high-dose TBT has been extensively reported, the effects of low concentrations of TBT are relatively less well studied. We have previously reported that low-concentration TBT decreases α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA)-type glutamate receptor subunit 2 ( GluR2 ) expression in cortical neurons and enhances neuronal vulnerability to glutamate. However, the mechanism of this TBT-induced GluR2 decrease remains unknown. Therefore, we examined the effects of TBT on the activity of transcription factors that control GluR2 expression. Exposure of primary cortical neurons to 20 nM TBT for 3 h to 9 days resulted in a decrease in GluR2 mRNA expression. Moreover, TBT inhibited the DNA binding activity of nuclear respiratory factor-1 (NRF-1), a transcription factor that positively regulates the GluR2 . This result indicates that TBT inhibits the activity of NRF-1 and subsequently decreases GluR2 expression. In addition, 20 nM TBT decreased the expression of genes such as cytochrome c, cytochrome c oxidase (COX) 4, and COX 6c, which are downstream of NRF-1. Our results suggest that NRF-1 inhibition is an important molecular action of the neurotoxicity induced by low-concentration TBT.
Low-Concentration Tributyltin Decreases GluR2 Expression via Nuclear Respiratory Factor-1 Inhibition
Ishida, Keishi; Aoki, Kaori; Takishita, Tomoko; Miyara, Masatsugu; Sakamoto, Shuichiro; Sanoh, Seigo; Kimura, Tomoki; Kanda, Yasunari; Ohta, Shigeru; Kotake, Yaichiro
2017-01-01
Tributyltin (TBT), which has been widely used as an antifouling agent in paints, is a common environmental pollutant. Although the toxicity of high-dose TBT has been extensively reported, the effects of low concentrations of TBT are relatively less well studied. We have previously reported that low-concentration TBT decreases α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA)-type glutamate receptor subunit 2 (GluR2) expression in cortical neurons and enhances neuronal vulnerability to glutamate. However, the mechanism of this TBT-induced GluR2 decrease remains unknown. Therefore, we examined the effects of TBT on the activity of transcription factors that control GluR2 expression. Exposure of primary cortical neurons to 20 nM TBT for 3 h to 9 days resulted in a decrease in GluR2 mRNA expression. Moreover, TBT inhibited the DNA binding activity of nuclear respiratory factor-1 (NRF-1), a transcription factor that positively regulates the GluR2. This result indicates that TBT inhibits the activity of NRF-1 and subsequently decreases GluR2 expression. In addition, 20 nM TBT decreased the expression of genes such as cytochrome c, cytochrome c oxidase (COX) 4, and COX 6c, which are downstream of NRF-1. Our results suggest that NRF-1 inhibition is an important molecular action of the neurotoxicity induced by low-concentration TBT. PMID:28800112
Attenuation coefficients of soils
International Nuclear Information System (INIS)
Martini, E.; Naziry, M.J.
1989-01-01
As a prerequisite to the interpretation of gamma-spectrometric in situ measurements of activity concentrations of soil radionuclides the attenuation of 60 to 1332 keV gamma radiation by soil samples varying in water content and density has been investigated. A useful empirical equation could be set up to describe the dependence of the mass attenuation coefficient upon photon energy for soil with a mean water content of 10%, with the results comparing well with data in the literature. The mean density of soil in the GDR was estimated at 1.6 g/cm 3 . This value was used to derive the linear attenuation coefficients, their range of variation being 10%. 7 figs., 5 tabs. (author)
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...
Parisi Kern, Andrea; Ferreira Dias, Michele; Piva Kulakowski, Marlova; Paulo Gomes, Luciana
2015-05-01
Reducing construction waste is becoming a key environmental issue in the construction industry. The quantification of waste generation rates in the construction sector is an invaluable management tool in supporting mitigation actions. However, the quantification of waste can be a difficult process because of the specific characteristics and the wide range of materials used in different construction projects. Large variations are observed in the methods used to predict the amount of waste generated because of the range of variables involved in construction processes and the different contexts in which these methods are employed. This paper proposes a statistical model to determine the amount of waste generated in the construction of high-rise buildings by assessing the influence of design process and production system, often mentioned as the major culprits behind the generation of waste in construction. Multiple regression was used to conduct a case study based on multiple sources of data of eighteen residential buildings. The resulting statistical model produced dependent (i.e. amount of waste generated) and independent variables associated with the design and the production system used. The best regression model obtained from the sample data resulted in an adjusted R(2) value of 0.694, which means that it predicts approximately 69% of the factors involved in the generation of waste in similar constructions. Most independent variables showed a low determination coefficient when assessed in isolation, which emphasizes the importance of assessing their joint influence on the response (dependent) variable. Copyright © 2015 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Garzelli, M.V.
2011-01-01
The analytical package written in FORM presented in this paper allows the computation of the complete set of Feynman Rules producing the Rational terms of kind R 2 contributing to the virtual part of NLO corrections in the Standard Model of the Electroweak interactions. Building block topologies filled by means of generic scalars, vectors and fermions, allowing to build these Feynman Rules in terms of specific elementary particles, are explicitly given in the R ξ gauge class, together with the automatic dressing procedure to obtain the Feynman Rules from them. The results in more specific gauges, like the 't Hooft Feynman one, follow as particular cases, in both the HV and the FDH dimensional regularization schemes. As a check on our formulas, the gauge independence of the total Rational contribution (R 1 +R 2 ) to renormalized S-matrix elements is verified by considering the specific example of the H →γγ decay process at 1-loop. This package can be of interest for people aiming at a better understanding of the nature of the Rational terms. It is organized in a modular way, allowing a further use of some its files even in different contexts. Furthermore, it can be considered as a first seed in the effort towards a complete automation of the process of the analytical calculation of the R 2 effective vertices, given the Lagrangian of a generic gauge theory of particle interactions. (orig.)
Testing the equality of nonparametric regression curves based on ...
African Journals Online (AJOL)
Abstract. In this work we propose a new methodology for the comparison of two regression functions f1 and f2 in the case of homoscedastic error structure and a fixed design. Our approach is based on the empirical Fourier coefficients of the regression functions f1 and f2 respectively. As our main results we obtain the ...
Implicit collinearity effect in linear regression: Application to basal ...
African Journals Online (AJOL)
Collinearity of predictor variables is a severe problem in the least square regression analysis. It contributes to the instability of regression coefficients and leads to a wrong prediction accuracy. Despite these problems, studies are conducted with a large number of observed and derived variables linked with a response ...
Shafaei, S M; Kamgar, S
2017-07-01
This paper deals with studying and modeling static friction coefficient (SFC) and dynamic friction coefficient (DFC) of wheat grain as affected by several treatments. Significance of single effect (SE) and dual interaction effect (DIE) of treatments (moisture content and contact surface) on SFC and, SE, DIE, and triple interaction effect (TIE) of treatments (moisture content, contact surface and sliding velocity) on DFC were determined using statistical analysis methods. Multiple linear regression (MLR) modeling was employed to predict SFC and DFC on different contact surfaces. Predictive ability of developed MLR models was evaluated using some statistical parameters (coefficient of determination ( R 2 ), root mean square error (RMSE), and mean relative deviation modulus (MRDM)). Results indicated that significant increasing DIE of treatments on SFC was 3.2 and 3 times greater than significant increasing SE of moisture content and contact surface, respectively. In case of DFC, the significant increasing TIE of treatments was 8.8, 3.7, and 8.9 times greater than SE of moisture content, contact surface, and sliding velocity, respectively. It was also found that the SE of contact surface on SFC was 1.1 times greater than that of moisture content and the SE of contact surface on DFC was 2.4 times greater than that of moisture content or sliding velocity. According to the reasonable average of statistical parameters ( R 2 = 0.955, RMSE = 0.01788 and MRDM = 3.152%), the SFC and DFC could be successfully predicted by suggested MLR models. Practically, it is recommended to apply the models for direct prediction of SFC and DFC, respective to each contact surface, based on moisture content and sliding velocity.
[Value of R2(*) in evaluating the biological behavior of primary hepatocellular carcinoma].
Tian, S F; Liu, A L; Liu, J H; Li, Y; Liu, X D; Huang, K; Song, Q W; Xu, M Z; Guo, W Y
2016-04-19
To investigate the correlation between R2(*) value of enhanced T2 star-weighted angiography (ESWAN) sequence and primary hepatocellular carcinoma infiltration and tumor thrombus, and investigate the biological behavior of HCC. A total of 221 cases of patients' imaging data with MRI examination(including ESWAN sequence) diagnosed as primary HCC were retrospectively analyzed.All the patients were collected from January 2014 to September 2015 in the First Affiliated Hospital of Dalian Medical University.The differences of R2(*) values in different MR types of HCC were analyzed.All patients were divided into infiltration group and non-infiltration group, tumor thrombus group and non-tumor thrombus group, the R2(*) values of the paired groups were compared.The diagnostic efficiency of R2(*) in HCC infiltration and tumor thrombus were evaluated by ROC curve, and to find out the threshold values. The MR types of 221 patients included 90 cases of nodular type, 62 cases of massive type, 69 cases of diffuse type.70 patients had tumor thrombus.The R2(*) values of different MR types were (21.82±8.52), (24.17±8.84)and (34.45±11.73) Hz, respectively.There was no statistically significant difference between the nodular and the massive types (P=0.144), while the difference between the nodular and diffuse type, the massive and diffuse types were statistically significant(P=0.000). The R2(*) values of infiltration group and non-infiltration group were (34.45±11.73) and (22.78±8.70) Hz , the R2(*) values of tumor thrombus group and non-tumor thrombus group were (31.20±12.17) and (24.21±9.90) Hz, the difference also had statistically significant(t=7.397 and 4.534, P=0.000 and 0.000). The AUC of R2(*) values for infiltration and tumor thrombus were 0.804, 0.681. R2(*) ≥24.68 Hz was the threshold value to diagnose the infiltration and tumor thrombus. R2(*) value can be used as a MR non-enhancement quantitative index to evaluate the biological behavior of HCC.
In Vivo Quantification of Cerebral R2FNx01-Response to Graded Hyperoxia at 3 Tesla
Directory of Open Access Journals (Sweden)
Grigorios Gotzamanis
2015-01-01
Full Text Available Objectives: This study aims to quantify the response of the transverse relaxation rate of the magnetic resonance (MR signal of the cerebral tissue in healthy volunteers to the administration of air with step-wise increasing percentage of oxygen. Materials and Methods: The transverse relaxation rate (R2FNx01 of the MR signal was quantified in seven volunteers under respiratory intake of normobaric gas mixtures containing 21, 50, 75, and 100% oxygen, respectively. End-tidal breath composition, arterial blood saturation (SaO 2 , and heart pulse rate were monitored during the challenge. R2FNx01 maps were computed from multi-echo, gradient-echo magnetic resonance imaging (MRI data, acquired at 3.0T. The average values in the segmented white matter (WM and gray matter (GM were tested by the analysis of variance (ANOVA, with Bonferroni post-hoc correction. The GM R2FNx01-reactivity to hyperoxia was modeled using the Hill′s equation. Results: Graded hyperoxia resulted in a progressive and significant (P < 0.05 decrease of the R2FNx01 in GM. Under normoxia the GM-R2FNx01 was 17.2 ± 1.1 s -1 . At 75% O 2 supply, the R2FNx01 had reached a saturation level, with 16.4 ± 0.7 s -1 (P = 0.02, without a significant further decrease for 100% O 2 . The R2FNx01-response of GM correlated positively with CO 2 partial pressure (R = 0.69 ± 0.19 and negatively with SaO 2 (R = -0.74 ± 0.17. The WM showed a similar progressive, but non-significant, decrease in the relaxation rates, with an increase in oxygen intake (P = 0.055. The Hill′s model predicted a maximum R2FNx01 response of the GM, of 3.5%, with half the maximum at 68% oxygen concentration. Conclusions: The GM-R2FNx01 responds to hyperoxia in a concentration-dependent manner, suggesting that monitoring and modeling of the R2FNx01-response may provide new oxygenation biomarkers for tumor therapy or assessment of cerebrovascular reactivity in patients.
Toropov, A A; Toropova, A P; Raska, I
2008-04-01
Simplified molecular input line entry system (SMILES) has been utilized in constructing quantitative structure-property relationships (QSPR) for octanol/water partition coefficient of vitamins and organic compounds of different classes by optimal descriptors. Statistical characteristics of the best model (vitamins) are the following: n=17, R(2)=0.9841, s=0.634, F=931 (training set); n=7, R(2)=0.9928, s=0.773, F=690 (test set). Using this approach for modeling octanol/water partition coefficient for a set of organic compounds gives a model that is statistically characterized by n=69, R(2)=0.9872, s=0.156, F=5184 (training set) and n=70, R(2)=0.9841, s=0.179, F=4195 (test set).
Delwiche, Stephen R; Reeves, James B
2010-01-01
In multivariate regression analysis of spectroscopy data, spectral preprocessing is often performed to reduce unwanted background information (offsets, sloped baselines) or accentuate absorption features in intrinsically overlapping bands. These procedures, also known as pretreatments, are commonly smoothing operations or derivatives. While such operations are often useful in reducing the number of latent variables of the actual decomposition and lowering residual error, they also run the risk of misleading the practitioner into accepting calibration equations that are poorly adapted to samples outside of the calibration. The current study developed a graphical method to examine this effect on partial least squares (PLS) regression calibrations of near-infrared (NIR) reflection spectra of ground wheat meal with two analytes, protein content and sodium dodecyl sulfate sedimentation (SDS) volume (an indicator of the quantity of the gluten proteins that contribute to strong doughs). These two properties were chosen because of their differing abilities to be modeled by NIR spectroscopy: excellent for protein content, fair for SDS sedimentation volume. To further demonstrate the potential pitfalls of preprocessing, an artificial component, a randomly generated value, was included in PLS regression trials. Savitzky-Golay (digital filter) smoothing, first-derivative, and second-derivative preprocess functions (5 to 25 centrally symmetric convolution points, derived from quadratic polynomials) were applied to PLS calibrations of 1 to 15 factors. The results demonstrated the danger of an over reliance on preprocessing when (1) the number of samples used in a multivariate calibration is low (<50), (2) the spectral response of the analyte is weak, and (3) the goodness of the calibration is based on the coefficient of determination (R(2)) rather than a term based on residual error. The graphical method has application to the evaluation of other preprocess functions and various
Ennouri, Karim; Ben Ayed, Rayda; Triki, Mohamed Ali; Ottaviani, Ennio; Mazzarello, Maura; Hertelli, Fathi; Zouari, Nabil
2017-07-01
The aim of the present work was to develop a model that supplies accurate predictions of the yields of delta-endotoxins and proteases produced by B. thuringiensis var. kurstaki HD-1. Using available medium ingredients as variables, a mathematical method, based on Plackett-Burman design (PB), was employed to analyze and compare data generated by the Bootstrap method and processed by multiple linear regressions (MLR) and artificial neural networks (ANN) including multilayer perceptron (MLP) and radial basis function (RBF) models. The predictive ability of these models was evaluated by comparison of output data through the determination of coefficient (R 2 ) and mean square error (MSE) values. The results demonstrate that the prediction of the yields of delta-endotoxin and protease was more accurate by ANN technique (87 and 89% for delta-endotoxin and protease determination coefficients, respectively) when compared with MLR method (73.1 and 77.2% for delta-endotoxin and protease determination coefficients, respectively), suggesting that the proposed ANNs, especially MLP, is a suitable new approach for determining yields of bacterial products that allow us to make more appropriate predictions in a shorter time and with less engineering effort.
Joshi, Shuchi N; Srinivas, Nuggehally R; Parmar, Deven V
2018-03-01
Our aim was to develop and validate the extrapolative performance of a regression model using a limited sampling strategy for accurate estimation of the area under the plasma concentration versus time curve for saroglitazar. Healthy subject pharmacokinetic data from a well-powered food-effect study (fasted vs fed treatments; n = 50) was used in this work. The first 25 subjects' serial plasma concentration data up to 72 hours and corresponding AUC 0-t (ie, 72 hours) from the fasting group comprised a training dataset to develop the limited sampling model. The internal datasets for prediction included the remaining 25 subjects from the fasting group and all 50 subjects from the fed condition of the same study. The external datasets included pharmacokinetic data for saroglitazar from previous single-dose clinical studies. Limited sampling models were composed of 1-, 2-, and 3-concentration-time points' correlation with AUC 0-t of saroglitazar. Only models with regression coefficients (R 2 ) >0.90 were screened for further evaluation. The best R 2 model was validated for its utility based on mean prediction error, mean absolute prediction error, and root mean square error. Both correlations between predicted and observed AUC 0-t of saroglitazar and verification of precision and bias using Bland-Altman plot were carried out. None of the evaluated 1- and 2-concentration-time points models achieved R 2 > 0.90. Among the various 3-concentration-time points models, only 4 equations passed the predefined criterion of R 2 > 0.90. Limited sampling models with time points 0.5, 2, and 8 hours (R 2 = 0.9323) and 0.75, 2, and 8 hours (R 2 = 0.9375) were validated. Mean prediction error, mean absolute prediction error, and root mean square error were prediction of saroglitazar. The same models, when applied to the AUC 0-t prediction of saroglitazar sulfoxide, showed mean prediction error, mean absolute prediction error, and root mean square error model predicts the exposure of
Steganalysis using logistic regression
Lubenko, Ivans; Ker, Andrew D.
2011-02-01
We advocate Logistic Regression (LR) as an alternative to the Support Vector Machine (SVM) classifiers commonly used in steganalysis. LR offers more information than traditional SVM methods - it estimates class probabilities as well as providing a simple classification - and can be adapted more easily and efficiently for multiclass problems. Like SVM, LR can be kernelised for nonlinear classification, and it shows comparable classification accuracy to SVM methods. This work is a case study, comparing accuracy and speed of SVM and LR classifiers in detection of LSB Matching and other related spatial-domain image steganography, through the state-of-art 686-dimensional SPAM feature set, in three image sets.
SEPARATION PHENOMENA LOGISTIC REGRESSION
Directory of Open Access Journals (Sweden)
Ikaro Daniel de Carvalho Barreto
2014-03-01
Full Text Available This paper proposes an application of concepts about the maximum likelihood estimation of the binomial logistic regression model to the separation phenomena. It generates bias in the estimation and provides different interpretations of the estimates on the different statistical tests (Wald, Likelihood Ratio and Score and provides different estimates on the different iterative methods (Newton-Raphson and Fisher Score. It also presents an example that demonstrates the direct implications for the validation of the model and validation of variables, the implications for estimates of odds ratios and confidence intervals, generated from the Wald statistics. Furthermore, we present, briefly, the Firth correction to circumvent the phenomena of separation.
DEFF Research Database (Denmark)
Ozenne, Brice; Sørensen, Anne Lyngholm; Scheike, Thomas
2017-01-01
In the presence of competing risks a prediction of the time-dynamic absolute risk of an event can be based on cause-specific Cox regression models for the event and the competing risks (Benichou and Gail, 1990). We present computationally fast and memory optimized C++ functions with an R interface......-product we obtain fast access to the baseline hazards (compared to survival::basehaz()) and predictions of survival probabilities, their confidence intervals and confidence bands. Confidence intervals and confidence bands are based on point-wise asymptotic expansions of the corresponding statistical...
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...
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...
The Truth About Ballistic Coefficients
Courtney, Michael; Courtney, Amy
2007-01-01
The ballistic coefficient of a bullet describes how it slows in flight due to air resistance. This article presents experimental determinations of ballistic coefficients showing that the majority of bullets tested have their previously published ballistic coefficients exaggerated from 5-25% by the bullet manufacturers. These exaggerated ballistic coefficients lead to inaccurate predictions of long range bullet drop, retained energy and wind drift.
On Solving Lq-Penalized Regressions
Directory of Open Access Journals (Sweden)
Tracy Zhou Wu
2007-01-01
Full Text Available Lq-penalized regression arises in multidimensional statistical modelling where all or part of the regression coefficients are penalized to achieve both accuracy and parsimony of statistical models. There is often substantial computational difficulty except for the quadratic penalty case. The difficulty is partly due to the nonsmoothness of the objective function inherited from the use of the absolute value. We propose a new solution method for the general Lq-penalized regression problem based on space transformation and thus efficient optimization algorithms. The new method has immediate applications in statistics, notably in penalized spline smoothing problems. In particular, the LASSO problem is shown to be polynomial time solvable. Numerical studies show promise of our approach.
Influence diagnostics in meta-regression model.
Shi, Lei; Zuo, ShanShan; Yu, Dalei; Zhou, Xiaohua
2017-09-01
This paper studies the influence diagnostics in meta-regression model including case deletion diagnostic and local influence analysis. We derive the subset deletion formulae for the estimation of regression coefficient and heterogeneity variance and obtain the corresponding influence measures. The DerSimonian and Laird estimation and maximum likelihood estimation methods in meta-regression are considered, respectively, to derive the results. Internal and external residual and leverage measure are defined. The local influence analysis based on case-weights perturbation scheme, responses perturbation scheme, covariate perturbation scheme, and within-variance perturbation scheme are explored. We introduce a method by simultaneous perturbing responses, covariate, and within-variance to obtain the local influence measure, which has an advantage of capable to compare the influence magnitude of influential studies from different perturbations. An example is used to illustrate the proposed methodology. Copyright © 2017 John Wiley & Sons, Ltd.
Chen, Qiang; Mei, Kun; Dahlgren, Randy A; Wang, Ting; Gong, Jian; Zhang, Minghua
2016-12-01
As an important regulator of pollutants in overland flow and interflow, land use has become an essential research component for determining the relationships between surface water quality and pollution sources. This study investigated the use of ordinary least squares (OLS) and geographically weighted regression (GWR) models to identify the impact of land use and population density on surface water quality in the Wen-Rui Tang River watershed of eastern China. A manual variable excluding-selecting method was explored to resolve multicollinearity issues. Standard regression coefficient analysis coupled with cluster analysis was introduced to determine which variable had the greatest influence on water quality. Results showed that: (1) Impact of land use on water quality varied with spatial and seasonal scales. Both positive and negative effects for certain land-use indicators were found in different subcatchments. (2) Urban land was the dominant factor influencing N, P and chemical oxygen demand (COD) in highly urbanized regions, but the relationship was weak as the pollutants were mainly from point sources. Agricultural land was the primary factor influencing N and P in suburban and rural areas; the relationship was strong as the pollutants were mainly from agricultural surface runoff. Subcatchments located in suburban areas were identified with urban land as the primary influencing factor during the wet season while agricultural land was identified as a more prevalent influencing factor during the dry season. (3) Adjusted R 2 values in OLS models using the manual variable excluding-selecting method averaged 14.3% higher than using stepwise multiple linear regressions. However, the corresponding GWR models had adjusted R 2 ~59.2% higher than the optimal OLS models, confirming that GWR models demonstrated better prediction accuracy. Based on our findings, water resource protection policies should consider site-specific land-use conditions within each watershed to
The correlation between R2' and bone mineral measurements in human vertebrae: an in vitro study
International Nuclear Information System (INIS)
Brismar, T.B.; Karlsson, M.; Li, T.Q.; Ringertz, H.
1999-01-01
The aim of this study was to investigate whether MR imaging of trabecular bone structure using magnetic inhomogeneity measurements is related to the amount of bone mineral in human vertebrae. Weight, bone mineral content (BMC DXA ), bone mineral per area (BMA DXA ) and bone mineral density (BMD CT ) were determined in 12 defatted human lumbar vertebrae (L2-L4) by weighing, dual X-ray absorptiometry (DXA) and CT. Inhomogeneity caused by susceptibility differences between trabecular bone and surrounding water was studied with MR imaging at 1.5 T using the GESFIDE sequence. The pulse sequence determines the transverse relaxation rate R2 * and its two components, the non-reversible transverse relaxation rate (R2) and the reversible transverse relaxation rate (R2'; i. e. relaxation rate due to magnetic susceptibility) in a single scan. Voxel size was 0.9 x 1.9 x 5.0 mm. Positive significant correlations between R2' and weight, BMC DXA , BMA DXA and BMD CT were observed (r > 0.61 and p DXA and BMD CT (r > 0.66 and p DXA . Thus, R2' measurements are related to the amount of bone mineral, but they also provide information which is not obtainable from bone mineral measurements. (orig.) (orig.)
Prenatal Exposure to Tributyltin Decreases GluR2 Expression in the Mouse Brain.
Ishida, Keishi; Saiki, Takashi; Umeda, Kanae; Miyara, Masatsugu; Sanoh, Seigo; Ohta, Shigeru; Kotake, Yaichiro
2017-01-01
Tributyltin (TBT), a common environmental contaminant, is widely used as an antifouling agent in paint. We previously reported that exposure of primary cortical neurons to TBT in vitro decreased the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor subunit glutamate receptor 2 (GluR2) expression and subsequently increased neuronal vulnerability to glutamate. Therefore, to identify whether GluR2 expression also decreases after TBT exposure in vivo, we evaluated the changes in GluR2 expression in the mouse brain after prenatal or postnatal exposure to 10 and 25 ppm TBT through pellet diets. Although the mean feed intake and body weight did not decrease in TBT-exposed mice compared with that in control mice, GluR2 expression in the cerebral cortex and hippocampus decreased after TBT exposure during the prenatal period. These results indicate that a decrease in neuronal GluR2 may be involved in TBT-induced neurotoxicity, especially during the fetal period.
Effects of microwave exposure on motor learning and GluR2 phosphorylation in rabbit cerebellum
International Nuclear Information System (INIS)
Liu Yong; Wang Denggao; Zhang Guangbin; Zhou Wen; Yang Xuesen
2007-01-01
Objective: To investigate the effects of microwave exposure on motor learning and Glutamate receptor 2(GluR2) phosphorylation in rat cerebellum. Methods: The rabbits were trained for seven days to form eye-blink conditioning, and then divided randomly into control and microwave exposure group (at hours 0,3,24 and 72 subgroups after exposure, respectively). The rabbits were accepted 90 mW/cm 2 microwave exposure for 30 minutes, and the rectal temperature were detected immediately after exposure and specific absorption rate (SAR) value were calculated. Eye-blink conditioning were detected immediately after exposure, and cerebellar GluR2 protein and GluR2 phosphorylation were detected with Western blotting. Results: Rectal temperature of rabbits were increased by 3.02 degree C after exposure, and SAR value was 8.74 W/kg. The eye-blink conditioning decreased significantly after exposure, and cerebellar GluR2 protein expression had no significant alteration but phosphorylation reduced significantly after exposure. Conclusions: 90 mW/cm 2 microwave exposure has injurious effects on cerebellar GluR2 phosphorylation and motor learning. (authors)
Kuiper, Gerhardus J A J M; Houben, Rik; Wetzels, Rick J H; Verhezen, Paul W M; Oerle, Rene van; Ten Cate, Hugo; Henskens, Yvonne M C; Lancé, Marcus D
2017-11-01
Low platelet counts and hematocrit levels hinder whole blood point-of-care testing of platelet function. Thus far, no reference ranges for MEA (multiple electrode aggregometry) and PFA-100 (platelet function analyzer 100) devices exist for low ranges. Through dilution methods of volunteer whole blood, platelet function at low ranges of platelet count and hematocrit levels was assessed on MEA for four agonists and for PFA-100 in two cartridges. Using (multiple) regression analysis, 95% reference intervals were computed for these low ranges. Low platelet counts affected MEA in a positive correlation (all agonists showed r 2 ≥ 0.75) and PFA-100 in an inverse correlation (closure times were prolonged with lower platelet counts). Lowered hematocrit did not affect MEA testing, except for arachidonic acid activation (ASPI), which showed a weak positive correlation (r 2 = 0.14). Closure time on PFA-100 testing was inversely correlated with hematocrit for both cartridges. Regression analysis revealed different 95% reference intervals in comparison with originally established intervals for both MEA and PFA-100 in low platelet or hematocrit conditions. Multiple regression analysis of ASPI and both tests on the PFA-100 for combined low platelet and hematocrit conditions revealed that only PFA-100 testing should be adjusted for both thrombocytopenia and anemia. 95% reference intervals were calculated using multiple regression analysis. However, coefficients of determination of PFA-100 were poor, and some variance remained unexplained. Thus, in this pilot study using (multiple) regression analysis, we could establish reference intervals of platelet function in anemia and thrombocytopenia conditions on PFA-100 and in thrombocytopenia conditions on MEA.
DEFF Research Database (Denmark)
Hansen, Henrik; Tarp, Finn
2001-01-01
This paper examines the relationship between foreign aid and growth in real GDP per capita as it emerges from simple augmentations of popular cross country growth specifications. It is shown that aid in all likelihood increases the growth rate, and this result is not conditional on ‘good’ policy....... investment. We conclude by stressing the need for more theoretical work before this kind of cross-country regressions are used for policy purposes.......This paper examines the relationship between foreign aid and growth in real GDP per capita as it emerges from simple augmentations of popular cross country growth specifications. It is shown that aid in all likelihood increases the growth rate, and this result is not conditional on ‘good’ policy...
Statistical mechanics of the $N$-point vortex system with random intensities on $R^2$
Directory of Open Access Journals (Sweden)
Cassio Neri
2005-01-01
Full Text Available The system of N -point vortices on $mathbb{R}^2$ is considered under the hypothesis that vortex intensities are independent and identically distributed random variables with respect to a law $P$ supported on $(0,1]$. It is shown that, in the limit as $N$ approaches $infty$, the 1-vortex distribution is a minimizer of the free energy functional and is associated to (some solutions of the following non-linear Poisson Equation:$$ -Delta u(x = C^{-1}int_{(0,1]} rhbox{e}^{-eta ru(x- gamma r|x|^2}P(hbox{d}r, quadforall xin mathbb{R}^2, $$where $displaystyle C = int_{(0,1]}int_{mathbb{R}^2}hbox{e}^{-eta ru(y - gamma r|y|^2}hbox{d} yP(hbox{d}r$
Some thermoelectric properties of the light rare earth sesquiselenides (R2Se/sub 3-x/)
International Nuclear Information System (INIS)
Takeshita, T.; Beaudry, B.J.; Gschneidner, K.A. Jr.
1981-01-01
Rare earth sesquiselenides of the Th 3 P 4 structure show variable electric properties over their homogeneity range, i.e., ranging from metallic (R 3 Se 4 ) to semimetallic (R 2 Se/sub 3-x/, where 0.14 > x > 0) to semiconducting (R 2 Se 3 ). The composition change is due to the formation of metal vacancies in the Th 3 P 4 structure with no vacancies at R 3 Se 4 and 4.75 at. % vacancies at R 2 Se 3 . The rare earth sesquiselenides are also refractory materials and therefore are of interest for high temperature thermoelectric applications. Preliminary results of thermoelectric power and electrical resistivity measurements on the light lanthanide sesquiselenides (La through Sm) are presented
Data Retrieved by ARCADE-R2 Experiment On Board the BEXUS-17 Balloon
Barbetta, M.; Branz, F.; Carron, A.; Olivieri, L.; Prendin, J.; Sansone, F.; Savioli, L.; Spinello, F.; Francesconi, A.
2015-09-01
The Autonomous Rendezvous, Control And Docking Experiment — Reflight 2 (ARCADE-R2) is a technology demonstrator aiming to prove automatic attitude determination and control, rendezvous and docking capabilities for small scale spacecraft and aircraft. The development of such capabilities could be fundamental to create, in the near future, fleets of cooperative, autonomous unmanned aerial vehicles for mapping, surveillance, inspection and remote observation of hazardous environments; small-class satellites could also benefit from the employment of docking systems to extend and reconfigure their mission profiles. ARCADE-R2 is designed to test these technologies on a stratospheric flight on board the BEXUS-17 balloon, allowing to demonstrate them in a harsh environment subjected to gusty winds and high pressure and temperature variations. In this paper, ARCADE-R2 architecture is introduced and the main results obtained from a stratospheric balloon flight are presented.
Zhang, Yanyan; Ma, Haile; Wang, Bei; Qu, Wenjuan; Wali, Asif; Zhou, Cunshan
2016-08-01
Ultrasound pretreatment of wheat gluten (WG) before enzymolysis can improve the angiotensin converting enzyme (ACE) inhibitory activity of the hydrolysates by alerting the structure of substrate proteins. Establishment of a relationship between the structure of WG and ACE inhibitory activity of the hydrolysates to judge the end point of the ultrasonic pretreatment is vital. The results of stepwise multiple linear regression (MLR) showed that the contents of free sulfhydryl, α-helix, disulfide bond, surface hydrophobicity and random coil were significantly correlated to ACE Inhibitory activity of the hydrolysate, with the standard partial regression coefficients were 3.729, -0.676, -0.252, 0.022 and 0.156, respectively. The R(2) of this model was 0.970. External validation showed that the stepwise MLR model could well predict the ACE inhibitory activity of hydrolysate based on the content of free sulfhydryl, α-helix, disulfide bond, surface hydrophobicity and random coil of WG before hydrolysis. A stepwise multiple linear regression model describing the quantitative relationships between the structure of WG and the ACE Inhibitory activity of the hydrolysates was established. This model can be used to predict the endpoint of the ultrasonic pretreatment. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.
Bowen, Stephen R; Chappell, Richard J; Bentzen, Søren M; Deveau, Michael A; Forrest, Lisa J; Jeraj, Robert
2012-01-01
Purpose To quantify associations between pre-radiotherapy and post-radiotherapy PET parameters via spatially resolved regression. Materials and methods Ten canine sinonasal cancer patients underwent PET/CT scans of [18F]FDG (FDGpre), [18F]FLT (FLTpre), and [61Cu]Cu-ATSM (Cu-ATSMpre). Following radiotherapy regimens of 50 Gy in 10 fractions, veterinary patients underwent FDG PET/CT scans at three months (FDGpost). Regression of standardized uptake values in baseline FDGpre, FLTpre and Cu-ATSMpre tumour voxels to those in FDGpost images was performed for linear, log-linear, generalized-linear and mixed-fit linear models. Goodness-of-fit in regression coefficients was assessed by R2. Hypothesis testing of coefficients over the patient population was performed. Results Multivariate linear model fits of FDGpre to FDGpost were significantly positive over the population (FDGpost~0.17 FDGpre, p=0.03), and classified slopes of RECIST non-responders and responders to be different (0.37 vs. 0.07, p=0.01). Generalized-linear model fits related FDGpre to FDGpost by a linear power law (FDGpost~FDGpre0.93, pregression analysis indicates that pre-treatment FDG PET uptake is most strongly associated with three-month post-treatment FDG PET uptake in this patient population, though associations are histopathology-dependent. PMID:22682748
R2d2 Drives Selfish Sweeps in the House Mouse.
Didion, John P; Morgan, Andrew P; Yadgary, Liran; Bell, Timothy A; McMullan, Rachel C; Ortiz de Solorzano, Lydia; Britton-Davidian, Janice; Bult, Carol J; Campbell, Karl J; Castiglia, Riccardo; Ching, Yung-Hao; Chunco, Amanda J; Crowley, James J; Chesler, Elissa J; Förster, Daniel W; French, John E; Gabriel, Sofia I; Gatti, Daniel M; Garland, Theodore; Giagia-Athanasopoulou, Eva B; Giménez, Mabel D; Grize, Sofia A; Gündüz, İslam; Holmes, Andrew; Hauffe, Heidi C; Herman, Jeremy S; Holt, James M; Hua, Kunjie; Jolley, Wesley J; Lindholm, Anna K; López-Fuster, María J; Mitsainas, George; da Luz Mathias, Maria; McMillan, Leonard; Ramalhinho, Maria da Graça Morgado; Rehermann, Barbara; Rosshart, Stephan P; Searle, Jeremy B; Shiao, Meng-Shin; Solano, Emanuela; Svenson, Karen L; Thomas-Laemont, Patricia; Threadgill, David W; Ventura, Jacint; Weinstock, George M; Pomp, Daniel; Churchill, Gary A; Pardo-Manuel de Villena, Fernando
2016-06-01
A selective sweep is the result of strong positive selection driving newly occurring or standing genetic variants to fixation, and can dramatically alter the pattern and distribution of allelic diversity in a population. Population-level sequencing data have enabled discoveries of selective sweeps associated with genes involved in recent adaptations in many species. In contrast, much debate but little evidence addresses whether "selfish" genes are capable of fixation-thereby leaving signatures identical to classical selective sweeps-despite being neutral or deleterious to organismal fitness. We previously described R2d2, a large copy-number variant that causes nonrandom segregation of mouse Chromosome 2 in females due to meiotic drive. Here we show population-genetic data consistent with a selfish sweep driven by alleles of R2d2 with high copy number (R2d2(HC)) in natural populations. We replicate this finding in multiple closed breeding populations from six outbred backgrounds segregating for R2d2 alleles. We find that R2d2(HC) rapidly increases in frequency, and in most cases becomes fixed in significantly fewer generations than can be explained by genetic drift. R2d2(HC) is also associated with significantly reduced litter sizes in heterozygous mothers, making it a true selfish allele. Our data provide direct evidence of populations actively undergoing selfish sweeps, and demonstrate that meiotic drive can rapidly alter the genomic landscape in favor of mutations with neutral or even negative effects on overall Darwinian fitness. Further study will reveal the incidence of selfish sweeps, and will elucidate the relative contributions of selfish genes, adaptation and genetic drift to evolution. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
Simplified prediction of postoperative cardiac surgery outcomes with a novel score: R2CHADS2.
Peguero, Julio G; Lo Presti, Saberio; Issa, Omar; Podesta, Carlos; Parise, Helen; Layka, Ayman; Brenes, Juan C; Lamelas, Joseph; Lamas, Gervasio A
2016-07-01
To compare the accuracy of R2CHADS2, CHADS2, and CHA2DS2-VASc scores vs the Society of Thoracic Surgeons (STS) score as predictors of morbidity and mortality after cardiovascular surgery. All patients who underwent cardiothoracic surgery at our institution from January 2008 to July 2013 were analyzed. Only those patients who fulfilled the criteria for STS score calculation were included. The R2CHADS2 score was computed as follows: 2 points for GFR < 60 mL/min/1.73 m(2) (R2), prior stroke or TIA (S2); 1 point for history of congestive heart failure (C), hypertension (H), age ≥75 years (A), or diabetes (D). Area under the curve (AUC) analysis was used to estimate the accuracy of the different scores. The end point variables included operative mortality, permanent stroke, and renal failure as defined by the STS database system. Of the 3,492 patients screened, 2,263 met the inclusion criteria. These included 1,160 (51%) isolated valve surgery, 859 (38%) coronary artery bypass graft surgery, and 245 (11%) combined procedures. There were 147 postoperative events: 75 (3%) patients had postoperative renal failure, 48 (2%) had operative mortality, and 24 (1%) had permanent stroke. AUC analysis revealed that STS, R2CHADS2, CHADS2, and CHA2DS2-VASc reliably estimated all postoperative outcomes. STS and R2CHADS2 scores had the best accuracy overall, with no significant difference in AUC values between them. The R2CHADS2 score estimates postoperative events with acceptable accuracy and if further validated may be used as a simple preoperative risk tool calculator. Copyright © 2016 Elsevier Inc. All rights reserved.
MiR-2 family regulates insect metamorphosis by controlling the juvenile hormone signaling pathway.
Lozano, Jesus; Montañez, Raúl; Belles, Xavier
2015-03-24
In 2009 we reported that depletion of Dicer-1, the enzyme that catalyzes the final step of miRNA biosynthesis, prevents metamorphosis in Blattella germanica. However, the precise regulatory roles of miRNAs in the process have remained elusive. In the present work, we have observed that Dicer-1 depletion results in an increase of mRNA levels of Krüppel homolog 1 (Kr-h1), a juvenile hormone-dependent transcription factor that represses metamorphosis, and that depletion of Kr-h1 expression in Dicer-1 knockdown individuals rescues metamorphosis. We have also found that the 3'UTR of Kr-h1 mRNA contains a functional binding site for miR-2 family miRNAs (for miR-2, miR-13a, and miR-13b). These data suggest that metamorphosis impairment caused by Dicer-1 and miRNA depletion is due to a deregulation of Kr-h1 expression and that this deregulation is derived from a deficiency of miR-2 miRNAs. We corroborated this by treating the last nymphal instar of B. germanica with an miR-2 inhibitor, which impaired metamorphosis, and by treating Dicer-1-depleted individuals with an miR-2 mimic to allow nymphal-to-adult metamorphosis to proceed. Taken together, the data indicate that miR-2 miRNAs scavenge Kr-h1 transcripts when the transition from nymph to adult should be taking place, thus crucially contributing to the correct culmination of metamorphosis.
Rolling Deck to Repository (R2R): Standards and Semantics for Open Access to Research Data
Arko, Robert; Carbotte, Suzanne; Chandler, Cynthia; Smith, Shawn; Stocks, Karen
2015-04-01
In recent years, a growing number of funding agencies and professional societies have issued policies calling for open access to research data. The Rolling Deck to Repository (R2R) program is working to ensure open access to the environmental sensor data routinely acquired by the U.S. academic research fleet. Currently 25 vessels deliver 7 terabytes of data to R2R each year, acquired from a suite of geophysical, oceanographic, meteorological, and navigational sensors on over 400 cruises worldwide. R2R is working to ensure these data are preserved in trusted repositories, discoverable via standard protocols, and adequately documented for reuse. R2R maintains a master catalog of cruises for the U.S. academic research fleet, currently holding essential documentation for over 3,800 expeditions including vessel and cruise identifiers, start/end dates and ports, project titles and funding awards, science parties, dataset inventories with instrument types and file formats, data quality assessments, and links to related content at other repositories. A Digital Object Identifier (DOI) is published for 1) each cruise, 2) each original field sensor dataset, 3) each post-field data product such as quality-controlled shiptrack navigation produced by the R2R program, and 4) each document such as a cruise report submitted by the science party. Scientists are linked to personal identifiers, such as the Open Researcher and Contributor ID (ORCID), where known. Using standard global identifiers such as DOIs and ORCIDs facilitates linking with journal publications and generation of citation metrics. Since its inception, the R2R program has worked in close collaboration with other data repositories in the development of shared semantics for oceanographic research. The R2R cruise catalog uses community-standard terms and definitions hosted by the NERC Vocabulary Server, and publishes ISO metadata records for each cruise that use community-standard profiles developed with the NOAA Data
Pro EDI in BizTalk Server 2006 R2 electronic document interchange solutions
Beckner, Mark
2008-01-01
As business becomes more dependent on working with partners, suppliers, and other organizations in a streamlined way, Electronic Data Interchange (EDI) is one of the next big waves in connected systems. Microsoft BizTalk Server 2006 R2 offers an efficient, integrated way to deploy EDI solutions, and with the help of this book, readers will see how EDI can be used in their business and how best to get it set up with BizTalk. This book offers insights into the brand-new Biztalk 2006 R2--based EDI functionality, including the far greater flexibility in handling interchange. It gives advice coveri
MCSA Windows Server 2012 R2 configuring advanced services study guide exam 70-412
Panek, William
2015-01-01
The bestselling MCSA study guide, with expert instruction andhands-on practice MCSA Windows Server 2012 R2 Configuring Advanced ServicesStudy Guide provides focused preparation for exam 70-412 and isfully updated to align with the latest Windows Server 2012 R2objectives. This comprehensive guide covers 100 percent of all examobjective domains, and includes hundreds of practice questions andanswers. You get access to video demonstrations, electronicflashcards, and practice exams, and hands-on exercises based onreal-world scenarios allow you to apply your skills to everydaytasks. Organized by o
Curved fronts in the Belousov-Zhabotinskii reaction-diffusion systems in R2
Niu, Hong-Tao; Wang, Zhi-Cheng; Bu, Zhen-Hui
2018-05-01
In this paper we consider a diffusion system with the Belousov-Zhabotinskii (BZ for short) chemical reaction. Following Brazhnik and Tyson [4] and Pérez-Muñuzuri et al. [45], who predicted V-shaped fronts theoretically and discovered V-shaped fronts by experiments respectively, we give a rigorous mathematical proof of their results. We establish the existence of V-shaped traveling fronts in R2 by constructing a proper supersolution and a subsolution. Furthermore, we establish the stability of the V-shaped front in R2.
Microsoft® Office Communications Server 2007 R2 Resource Kit
Maximo, Rui; Ramanathan, Rajesh; Kamdar, Nirav
2009-01-01
In-depth, comprehensive, and fully revised for R2-this RESOURCE KIT delivers the information you need to deploy, manage, and troubleshoot Microsoft Office Communications Server 2007 R2. Get technical insights, scenarios, and best practices from those who know the technology best-the engineers who designed and developed it-along with 90+ Windows PowerShell™ scripts, bonus references, and other essential resources on CD. Get expert advice on how to: Plan server roles, infrastructure, topology, and securityDesign and manage enterprise instant messaging (IM), presence, and conferencing solutio
Oracle Data Guard 11gR2 administration beginner's guide
Baransel, Emre
2013-01-01
Using real-world examples and hands-on tasks, Oracle Data Guard 11gR2 Administration Beginner's Guide will give you a solid foundation in Oracle Data Guard. It has been designed to teach you everything you need to know to successfully create and operate Data Guard environments with maximum flexibility, compatibility, and effectiveness.If you are an Oracle database administrator who wants to configure and administer Data Guard configurations, then ""Oracle Data Guard 11gR2 Administration Beginner's Guide"" is for you. With a basic understanding of Oracle database administration, you'll be able
Thermal expansion and spontaneous magnetostriction of R2Co7 intermetallic compounds
International Nuclear Information System (INIS)
Andreev, A.V.; Bartashevich, M.I.; Deryagin, A.V.; Zadvorkin, S.M.; Tarasov, E.N.
1988-01-01
Thermal expansion of R 2 Co 7 (R=Y, Nd, Gd, Tb) single crystals was invesigated by the method of X-ray dilatometry. Anomalous of thermal expansion, taking place during magnetic ordering and spin reorientation were used to determine linear and volumetric magnetistriction deformations. Constants of anisotropic magnetostriction of all R 2 Co 7 compounds with nonzero orbital moment of rare earth ion were calculated on the basis of single-ion model according to deformation values and with account of temperature dependences of the magnitude and direction of magnetic moment
The microcomputer scientific software series 2: general linear model--regression.
Harold M. Rauscher
1983-01-01
The general linear model regression (GLMR) program provides the microcomputer user with a sophisticated regression analysis capability. The output provides a regression ANOVA table, estimators of the regression model coefficients, their confidence intervals, confidence intervals around the predicted Y-values, residuals for plotting, a check for multicollinearity, a...
Quantum Non-Markovian Langevin Equations and Transport Coefficients
International Nuclear Information System (INIS)
Sargsyan, V.V.; Antonenko, N.V.; Kanokov, Z.; Adamian, G.G.
2005-01-01
Quantum diffusion equations featuring explicitly time-dependent transport coefficients are derived from generalized non-Markovian Langevin equations. Generalized fluctuation-dissipation relations and analytic expressions for calculating the friction and diffusion coefficients in nuclear processes are obtained. The asymptotic behavior of the transport coefficients and correlation functions for a damped harmonic oscillator that is linearly coupled in momentum to a heat bath is studied. The coupling to a heat bath in momentum is responsible for the appearance of the diffusion coefficient in coordinate. The problem of regression of correlations in quantum dissipative systems is analyzed
A better coefficient of determination for genetic profile analysis.
Lee, Sang Hong; Goddard, Michael E; Wray, Naomi R; Visscher, Peter M
2012-04-01
Genome-wide association studies have facilitated the construction of risk predictors for disease from multiple Single Nucleotide Polymorphism markers. The ability of such "genetic profiles" to predict outcome is usually quantified in an independent data set. Coefficients of determination (R(2) ) have been a useful measure to quantify the goodness-of-fit of the genetic profile. Various pseudo-R(2) measures for binary responses have been proposed. However, there is no standard or consensus measure because the concept of residual variance is not easily defined on the observed probability scale. Unlike other nongenetic predictors such as environmental exposure, there is prior information on genetic predictors because for most traits there are estimates of the proportion of variation in risk in the population due to all genetic factors, the heritability. It is this useful ability to benchmark that makes the choice of a measure of goodness-of-fit in genetic profiling different from that of nongenetic predictors. In this study, we use a liability threshold model to establish the relationship between the observed probability scale and underlying liability scale in measuring R(2) for binary responses. We show that currently used R(2) measures are difficult to interpret, biased by ascertainment, and not comparable to heritability. We suggest a novel and globally standard measure of R(2) that is interpretable on the liability scale. Furthermore, even when using ascertained case-control studies that are typical in human disease studies, we can obtain an R(2) measure on the liability scale that can be compared directly to heritability. © 2012 Wiley Periodicals, Inc.
Luo, Chongliang; Liu, Jin; Dey, Dipak K; Chen, Kun
2016-07-01
In many fields, multi-view datasets, measuring multiple distinct but interrelated sets of characteristics on the same set of subjects, together with data on certain outcomes or phenotypes, are routinely collected. The objective in such a problem is often two-fold: both to explore the association structures of multiple sets of measurements and to develop a parsimonious model for predicting the future outcomes. We study a unified canonical variate regression framework to tackle the two problems simultaneously. The proposed criterion integrates multiple canonical correlation analysis with predictive modeling, balancing between the association strength of the canonical variates and their joint predictive power on the outcomes. Moreover, the proposed criterion seeks multiple sets of canonical variates simultaneously to enable the examination of their joint effects on the outcomes, and is able to handle multivariate and non-Gaussian outcomes. An efficient algorithm based on variable splitting and Lagrangian multipliers is proposed. Simulation studies show the superior performance of the proposed approach. We demonstrate the effectiveness of the proposed approach in an [Formula: see text] intercross mice study and an alcohol dependence study. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Genetic inhibition of PKA phosphorylation of RyR2 prevents dystrophic cardiomyopathy
Sarma, Satyam; Li, Na; van Oort, Ralph J.; Reynolds, Corey; Skapura, Darlene G.; Wehrens, Xander H. T.
2010-01-01
Aberrant intracellular Ca(2+) regulation is believed to contribute to the development of cardiomyopathy in Duchenne muscular dystrophy. Here, we tested whether inhibition of protein kinase A (PKA) phosphorylation of ryanodine receptor type 2 (RyR2) prevents dystrophic cardiomyopathy by reducing SR
Genome-wide identification and characterization of R2R3MYB family in Rosaceae.
González, Máximo; Carrasco, Basilio; Salazar, Erika
2016-09-01
Transcription factors R2R3MYB family have been associated with the control of secondary metabolites, development of structures, cold tolerance and response to biotic and abiotic stress, among others. In recent years, genomes of Rosaceae botanical family are available. Although this information has been used to study the karyotype evolution of these species from an ancestral genome, there are no studies that treat the evolution and diversity of gene families present in these species or in the botanical family. Here we present the first comparative study of the R2R3MYB subfamily of transcription factors in three species of Rosaceae family (Malus domestica, Prunus persica and Fragaria vesca). We described 186, 98 and 86 non-redundant gene models for apple, peach and strawberry, respectively. In this research, we analyzed the intron-exon structure and genomic distribution of R2R3MYB families mentioned above. The phylogenetic comparisons revealed putative functions of some R2R3MYB transcription factors. This analysis found 44 functional subgroups, seven of which were unique for Rosaceae. In addition, our results showed a highly collinearity among some genes revealing the existence of conserved gene models between the three species studied. Although some gene models in these species have been validated under several approaches, more research in the Rosaceae family is necessary to determine gene expression patterns in specific tissues and development stages to facilitate understanding of the regulatory and biochemical mechanism in this botanical family.
Convex Bodies With Minimal Volume Product in R^2 --- A New Proof
Lin, Youjiang
2010-01-01
In this paper, a new proof of the following result is given: The product of the volumes of an origin symmetric convex bodies $K$ in R^2 and of its polar body is minimal if and only if $K$ is a parallelogram.
R2/R0-WTR decommissioning cost. Comparison and benchmarking analysis
International Nuclear Information System (INIS)
Varley, Geoff; Rusch, Chris
2001-10-01
SKI charged NAC International with the task of determining whether or not the decommissioning cost estimates of R2/R0 (hereafter simply referred to as R2) and Aagesta research reactors are reasonable. The associated work was performed in two phases. The objective in Phase I was to make global comparisons of the R2 and Aagesta decommissioning estimates with the estimates/actual costs for the decommissioning of similar research reactors in other countries. This report presents the results of the Phase II investigations. Phase II focused on selected discrete work packages within the decommissioning program of the WTR reactor. To the extent possible a comparison of those tasks with estimates for the R2 reactor has been made, as a basis for providing an opinion on the reasonableness of the R2 estimate. The specific WTR packages include: reactor vessel and internals dismantling; biological shield dismantling; primary coolant piping dismantling; electrical equipment removal; waste packaging; transportation and disposal of radioactive concrete and reactor components; project management, licensing and engineering; and removal of ancillary facilities. The specific tasks were characterised and analysed in terms of fundamental parameters including: task definition; labour hours expended; labour cost; labour productivity; length of work week; working efficiency; working environment and impact on job execution; external costs (contract labour, materials and equipment); total cost; waste volumes; and waste packaging and transport costs. Based on such detailed raw data, normalised unit resources have been derived for selected parts of the decommissioning program, as a first step towards developing benchmarking data for D and D activities at research reactors. Several general conclusions emerged from the WTR decommissioning project. Site characterisation can confirm or negate major assumptions, quantify waste volumes, delineate obstacles to completing work, provide an understanding
Substrate recognition and function of the R2TP complex in response to cellular stress
Czech Academy of Sciences Publication Activity Database
von Morgen, Patrick; Hořejší, Zuzana; Macůrek, Libor
2015-01-01
Roč. 6, February 2015 (2015) ISSN 1664-8021 R&D Projects: GA ČR(CZ) GA14-34264S; GA MŠk LO1220 Institutional support: RVO:68378050 Keywords : R2TPcomplex * proteinfolding * DNAdamageresponse Subject RIV: EB - Genetics ; Molecular Biology
Chiral recognition in electron scattering by S- and R-2-butanol
DEFF Research Database (Denmark)
Jones, Nykola C.; Hoffmann, Søren Vrønning; Field, David
2015-01-01
Experiments are described involving the low energy scattering of electrons from the two optical enantiomers S- and R- 2-butanol. Using a synchrotron radiation photoionization source on the ASTRID storage ring, scattering spectra are reported between a few meV and 140 meV at an electron energy...
(2S,4R-2-[(1R-1-(4-Bromophenyl-2-nitroethyl]-4-ethylcyclohexanone
Directory of Open Access Journals (Sweden)
Chi-Xiao Zhang
2013-02-01
Full Text Available The crystal structure of the title compound, C16H20BrNO3, contains three chiral centers in the configuration 1R,2S,6R. The cyclohexane ring is in a chair conformation. In the crystal, molecules are linked by weak C—H...O interactions, forming chains along the a-axis direction.
Mapping HL7 CDA R2 Formatted Mass Screening Data to OpenEHR Archetypes.
Kobayashi, Shinji; Kume, Naoto; Yoshihara, Hiroyuki
2017-01-01
Mass screening of adults was performed to manage employee healthcare. The screening service defined the data collection format as HL7 Clinical Document Architecture (CDA) R2. To capture mass screening data for nationwide electronic health records (her), we programmed a model within the CDA format and mapped the data items to the ISO13606/openEHR archetype for semantic interoperabiilty.
Herschel/HIFI observations of CO, H2O and NH3 in Monoceros R2
Pilleri, P.; Fuente, A.; Cernicharo, J.; Ossenkopf, V.; Berne, O.; Gerin, M.; Pety, J.; Goicoechea, J. R.; Rizzo, J. R.; Montillaud, J.; Gonzalez-Garcia, M.; Joblin, C.; Le Bourlot, J.; Le Petit, F.; Kramer, C.
Context. Mon R2, at a distance of 830 pc, is the only ultracompact H II region (UCH II) where the associated photon-dominated region (PDR) can be resolved with Herschel. Owing to its brightness and proximity, it is one of the best-suited sources for investigating the chemistry and physics of highly
2016-04-01
Nanotechnologies -- Terminology and definitions for nano-objects -- Nanoparticle, nanofibre and nanoplate Definitions Abrasion - wearing away...ER D C SR -1 6- 2 Environmental Consequences of Nanotechnologies Abrasion Testing of Products Containing Nanomaterials, SOP-R-2...ERDC online library at http://acwc.sdp.sirsi.net/client/default. Environmental Consequences of Nanotechnologies ERDC SR-16-2 April 2016
Synthesis and steriostructure of 5-(5-R-2- furfur lidene)- barbituric acid
International Nuclear Information System (INIS)
Abdel-Wahab, A.
2012-01-01
Heterocyclic compounds 5-(5-R-2-furfur lidene)- barbituric acid were obtained and their physical and chemical properties were studied. Their structures were identified by spectroscopic methods. This study proved by 1 H-NMR Spectroscopy data that these compounds exist in S-cis form. (author)
The nature of hydrogen bonding in R-2(2)(8) crystal motifs - a computational exploration
Czech Academy of Sciences Publication Activity Database
Deepa, Palanisamy; Solomon, R. V.; Vedha, S. A.; Kolandaivel, P.; Venuvanalingam, P.
2014-01-01
Roč. 112, č. 24 (2014), s. 3195-3205 ISSN 0026-8976 Institutional support: RVO:61388963 Keywords : NCI plot * hydrogen bonds * R-2(2)(8) motif * organic crystals * NBO * QTAIM analysis Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 1.720, year: 2014
Instant migration from Windows Server 2008 and 2008 R2 to 2012 how-to
Sivarajan, Santhosh
2013-01-01
Presented in a hands-on reference manual style, with real-world scenarios to lead you through each process. This book is intended for Windows server administrators who are performing migrations from their existing Windows Server 2008 / 2008 R2 environment to Windows Server 2012. The reader must be familiar with Windows Server 2008.
Aide, Nicolas; Louis, Marie-Hélène; Dutoit, Soizic; Labiche, Alexandre; Lemoisson, Edwige; Briand, Mélanie; Nataf, Valérie; Poulain, Laurent; Gauduchon, Pascal; Talbot, Jean-Noël; Montravers, Françoise
2007-10-01
To evaluate the accuracy of semi-quantitative small-animal PET data, uncorrected for attenuation, and then of the same semi-quantitative data corrected by means of recovery coefficients (RCs) based on phantom studies. A phantom containing six fillable spheres (diameter range: 4.4-14 mm) was filled with an 18F-FDG solution (spheres/background activity=10.1, 5.1 and 2.5). RCs, defined as measured activity/expected activity, were calculated. Nude rats harbouring tumours (n=50) were imaged after injection of 18F-FDG and sacrificed. The standardized uptake value (SUV) in tumours was determined with small-animal PET and compared to ex-vivo counting (ex-vivo SUV). Small-animal PET SUVs were corrected with RCs based on the greatest tumour diameter. Tumour proliferation was assessed with cyclin A immunostaining and correlated to the SUV. RCs ranged from 0.33 for the smallest sphere to 0.72 for the largest. A sigmoidal correlation was found between RCs and sphere diameters (r(2)=0.99). Small-animal PET SUVs were well correlated with ex-vivo SUVs (y=0.48x-0.2; r(2)=0.71) and the use of RCs based on the greatest tumour diameter significantly improved regression (y=0.84x-0.81; r(2)=0.77), except for tumours with important necrosis. Similar results were obtained without sacrificing animals, by using PET images to estimate tumour dimensions. RC-based corrections improved correlation between small-animal PET SUVs and tumour proliferation (uncorrected data: Rho=0.79; corrected data: Rho=0.83). Recovery correction significantly improves both accuracy of small-animal PET semi-quantitative data in rat studies and their correlation with tumour proliferation, except for largely necrotic tumours.
On the Kendall Correlation Coefficient
Stepanov, Alexei
2015-01-01
In the present paper, we first discuss the Kendall rank correlation coefficient. In continuous case, we define the Kendall rank correlation coefficient in terms of the concomitants of order statistics, find the expected value of the Kendall rank correlation coefficient and show that the later is free of n. We also prove that in continuous case the Kendall correlation coefficient converges in probability to its expected value. We then propose to consider the expected value of the Kendall rank ...
R2R Eventlogger: Community-wide Recording of Oceanographic Cruise Science Events
Maffei, A. R.; Chandler, C. L.; Stolp, L.; Lerner, S.; Avery, J.; Thiel, T.
2012-12-01
Methods used by researchers to track science events during a science research cruise - and to note when and where these occur - varies widely. Handwritten notebooks, printed forms, watch-keeper logbooks, data-logging software, and customized software have all been employed. The quality of scientific results is affected by the consistency and care with which such events are recorded and integration of multi-cruise results is hampered because recording methods vary widely from cruise to cruise. The Rolling Deck to Repository (R2R) program has developed an Eventlogger system that will eventually be deployed on most vessels in the academic research fleet. It is based on the open software package called ELOG (http://midas.psi.ch/elog/) originally authored by Stefan Ritt and enhanced by our team. Lessons have been learned in its development and use on several research cruises. We have worked hard to find approaches that encourage cruise participants to use tools like the eventlogger. We examine these lessons and several eventlogger datasets from past cruises. We further describe how the R2R Science Eventlogger works in concert with the other R2R program elements to help coordinate research vessels into a coordinated mobile observing fleet. Making use of data collected on different research cruises is enabled by adopting common ways of describing science events, the science instruments employed, the data collected, etc. The use of controlled vocabularies and the practice of mapping these local vocabularies to accepted oceanographic community vocabularies helps to bind shipboard research events from different cruises into a more cohesive set of fleet-wide events that can be queried and examined in a cross-cruise manner. Examples of the use of the eventlogger during multi-cruise oceanographic research programs along with examples of resultant eventlogger data will be presented. Additionally we will highlight the importance of vocabulary use strategies to the success of the
Lee, Hyunyeol; Englund, Erin K; Wehrli, Felix W
2018-03-23
Quantitative BOLD (qBOLD), a non-invasive MRI method for assessment of hemodynamic and metabolic properties of the brain in the baseline state, provides spatial maps of deoxygenated blood volume fraction (DBV) and hemoglobin oxygen saturation (HbO 2 ) by means of an analytical model for the temporal evolution of free-induction-decay signals in the extravascular compartment. However, mutual coupling between DBV and HbO 2 in the signal model results in considerable estimation uncertainty precluding achievement of a unique set of solutions. To address this problem, we developed an interleaved qBOLD method (iqBOLD) that combines extravascular R 2 ' and intravascular R 2 mapping techniques so as to obtain prior knowledge for the two unknown parameters. To achieve these goals, asymmetric spin echo and velocity-selective spin-labeling (VSSL) modules were interleaved in a single pulse sequence. Prior to VSSL, arterial blood and CSF signals were suppressed to produce reliable estimates for cerebral venous blood volume fraction (CBV v ) as well as venous blood R 2 (to yield HbO 2 ). Parameter maps derived from the VSSL module were employed to initialize DBV and HbO 2 in the qBOLD processing. Numerical simulations and in vivo experiments at 3 T were performed to evaluate the performance of iqBOLD in comparison to the parent qBOLD method. Data obtained in eight healthy subjects yielded plausible values averaging 60.1 ± 3.3% for HbO 2 and 3.1 ± 0.5 and 2.0 ± 0.4% for DBV in gray and white matter, respectively. Furthermore, the results show that prior estimates of CBV v and HbO 2 from the VSSL component enhance the solution stability in the qBOLD processing, and thus suggest the feasibility of iqBOLD as a promising alternative to the conventional technique for quantifying neurometabolic parameters. Copyright © 2018. Published by Elsevier Inc.
International Nuclear Information System (INIS)
Jafri, Y.Z.; Kamal, L.
2007-01-01
Various statistical techniques was used on five-year data from 1998-2002 of average humidity, rainfall, maximum and minimum temperatures, respectively. The relationships to regression analysis time series (RATS) were developed for determining the overall trend of these climate parameters on the basis of which forecast models can be corrected and modified. We computed the coefficient of determination as a measure of goodness of fit, to our polynomial regression analysis time series (PRATS). The correlation to multiple linear regression (MLR) and multiple linear regression analysis time series (MLRATS) were also developed for deciphering the interdependence of weather parameters. Spearman's rand correlation and Goldfeld-Quandt test were used to check the uniformity or non-uniformity of variances in our fit to polynomial regression (PR). The Breusch-Pagan test was applied to MLR and MLRATS, respectively which yielded homoscedasticity. We also employed Bartlett's test for homogeneity of variances on a five-year data of rainfall and humidity, respectively which showed that the variances in rainfall data were not homogenous while in case of humidity, were homogenous. Our results on regression and regression analysis time series show the best fit to prediction modeling on climatic data of Quetta, Pakistan. (author)
Voltage-dependent modulation of cardiac ryanodine receptors (RyR2 by protamine.
Directory of Open Access Journals (Sweden)
Paula L Diaz-Sylvester
Full Text Available It has been reported that protamine (>10 microg/ml blocks single skeletal RyR1 channels and inhibits RyR1-mediated Ca2+ release from sarcoplasmic reticulum microsomes. We extended these studies to cardiac RyR2 reconstituted into planar lipid bilayers. We found that protamine (0.02-20 microg/ml added to the cytosolic surface of fully activated RyR2 affected channel activity in a voltage-dependent manner. At membrane voltage (V(m; SR lumen-cytosol = 0 mV, protamine induced conductance transitions to several intermediate states (substates as well as full block of RyR2. At V(m>10 mV, the substate with the highest level of conductance was predominant. Increasing V(m from 0 to +80 mV, decreased the number of transitions and residence of the channel in this substate. The drop in current amplitude (full opening to substate had the same magnitude at 0 and +80 mV despite the approximately 3-fold increase in amplitude of the full opening. This is more similar to rectification of channel conductance induced by other polycations than to the action of selective conductance modifiers (ryanoids, imperatoxin. A distinctive effect of protamine (which might be shared with polylysines and histones but not with non-peptidic polycations is the activation of RyR2 in the presence of nanomolar cytosolic Ca2+ and millimolar Mg2+ levels. Our results suggest that RyRs would be subject to dual modulation (activation and block by polycationic domains of neighboring proteins via electrostatic interactions. Understanding these interactions could be important as such anomalies may be associated with the increased RyR2-mediated Ca2+ leak observed in cardiac diseases.
A NEW RADIO RECOMBINATION LINE MASER OBJECT TOWARD THE MonR2 H II REGION
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Jimenez-Serra, I.; Zhang, Q.; Dierickx, M.; Patel, N. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Baez-Rubio, A.; Rivilla, V. M.; Martin-Pintado, J., E-mail: ijimenez-serra@cfa.harvard.edu, E-mail: qzhang@cfa.harvard.edu, E-mail: mdierickx@cfa.harvard.edu, E-mail: npatel@cfa.harvard.edu, E-mail: ryvendel@gmail.com, E-mail: jmartin@cab.inta-csic.es, E-mail: baezra@cab.inta-csic.es [Centro de Astrobiologia (CSIC/INTA), Ctra. de Torrejon a Ajalvir km 4, E-28850 Torrejon de Ardoz, Madrid (Spain)
2013-02-10
We report the detection of a new radio recombination line (RRL) maser object toward the IRS2 source in the MonR2 ultracompact H II region. The continuum emission at 1.3 mm and 0.85 mm and the H30{alpha} and H26{alpha} lines were observed with the Submillimeter Array (SMA) at angular resolutions of {approx}0.''5-3''. The SMA observations show that the MonR2-IRS2 source is very compact and remains unresolved at spatial scales {<=}400 AU. Its continuum power spectrum at millimeter wavelengths is almost flat ({alpha} = -0.16, with S{sub {nu}}{proportional_to}{nu}{sup {alpha}}), indicating that this source is dominated by optically thin free-free emission. The H30{alpha} and H26{alpha} RRL emission is also compact and peaks toward the position of the MonR2-IRS2 source. The measured RRL profiles are double peaked with the H26{alpha} line showing a clear asymmetry in its spectrum. Since the derived line-to-continuum flux ratios ({approx}80 and 180 km s{sup -1} for H30{alpha} and H26{alpha}, respectively) exceed the LTE predictions, the RRLs toward MonR2-IRS2 are affected by maser amplification. The amplification factors are, however, smaller than those found toward the emission-line star MWC349A, indicating that MonR2-IRS2 is a weakly amplified maser. Radiative transfer modeling of the RRL emission toward this source shows that the RRL masers arise from a dense and collimated jet embedded in a cylindrical ionized wind, oriented nearly along the direction of the line of sight. High-angular resolution observations at submillimeter wavelengths are needed to unveil weakly amplified RRL masers in very young massive stars.
Vindhyal, Mohinder; Vindhyal, Shravani R; Haneke, Travis; Ndunda, Paul M; Eid, Freidy; Kallail, K James
2017-12-11
Introduction Atrial fibrillation (AF), the most common cardiac arrhythmia, affects approximately 2.3 million patients in the United States, costing around $26 billion. Atrial fibrillation is associated with a two- to seven-fold increased risk of stroke, one of the most serious complications. Chronic kidney disease affects approximately 13% of the US population and has been associated with higher rates of AF than the general population. In patients with chronic kidney disease (CKD), the risk of stroke increases as the glomerular filtration rate (GFR) decreases, especially in CKD stages three and four. Several risks stratification scores such as CHADS2 (congestive heart failure, hypertension, age, diabetes mellitus, stroke), CHA2DS2VASc (congestive heart failure, hypertension, age, diabetes mellitus, stroke, vascular disease, age, sex), and R2CHADS2 (renal failure, congestive heart failure, age, diabetes, stroke) scores are used for stroke risk assessment in patients with non-valvular atrial fibrillation (NVAF). This study investigates the association between renal functions and risk stratification scoring systems in patients with non-valvular AF presenting with stroke. Methods Using the convenience sampling method, 171 subjects were selected from the eligible population (n = 386). A Pearson product-moment correlation coefficient was calculated to determine the association between the GFR and each of the CHA2DS2VASc and R2CHADS2 scores. In addition, a Pearson product-moment correlation coefficient was calculated to determine the association between the CHA2DS2VASc and R2CHADS2 scores. Results The selected population represented 44.3% of the eligible subjects. Of these, 88% were Caucasian, 60% were female, and the mean age was 78 years. The mean CHA2DS2VASc score was six (range 2-9). The mean eGFR was 69.77 (range 6-108). Both the mode and the median CHA2DS2VASc score was four (range 2-8). A weak, but significant, negative correlation was found between renal
International Nuclear Information System (INIS)
2009-01-01
This document describes the plans for decommissioning of the nuclear research and material test reactors R2 and R2-0, situated at the Studsvik site close to the city of Nykoeping, Sweden. The purpose of the document is to serve as information for the European Commission, and to fulfil the requirements of Article 37 of the Euratom Treaty. Studsvik is situated on the Baltic coast, about 20 km east of Nykoeping and 80 km southwest of Stockholm. The site comprises the reactors R2 and R2-0 and several facilities for material investigation and radioactive waste treatment and storage. The reactors were used for a number of different purposes from 1960 until June 2005, when they were shut down following a decision by the operator. Decommissioning of the reactor facility is planned to be completed in 2016 after dismantling and conditioning of radioactive parts and demolition of the facility. Solid and liquid radioactive wastes from the dismantling activities will be treated and stored on-site awaiting final disposal. The waste treatment facilities, which are situated in other buildings at the Studsvik site, are planned to continue operation during and after the decommissioning of the reactor facility. All nuclear fuel has been transferred to a separate storage facility and is being shipped to the US according to existing agreements. The objective of the planned dismantling activities is to achieve clearance of the facility to make it possible to either demolish the buildings or use them for other purposes. The operator has divided the planning for dismantling and demolition of the facility into three phases [1]: Dismantling 1, including primary system decontamination, dismantling of the reactors with systems in the reactor pool, draining, cleaning and temporary covering of the reactor pool. This phase has begun and is due to last till approximately December 2009. Dismantling 2, including dismantling of systems in the reactor facility, removal of equipment, radiological
Hajiebrahimi, Ali; Owji, Hajar; Hemmati, Shiva
2017-10-01
R2R3-MYB transcription factors (TFs) have been shown to play important roles in plants, including in development and in various stress conditions. Phylogenetic analysis showed the presence of 249 R2R3-MYB TFs in Brassica napus, called BnaR2R3-MYB TFs, clustered into 38 clades. BnaR2R3-MYB TFs were distributed on 19 chromosomes of B. napus. Sixteen gene clusters were identified. BnaR2R3-MYB TFs were characterized by motif prediction, gene structure analysis, and gene ontology. Evolutionary analysis revealed that BnaR2R3-MYB TFs are mainly formed as a result of whole-genome duplication. Orthologs and paralogs of BnaR2R3-MYB TFs were identified in B. napus, B. rapa, B. oleracea, and Arabidopsis thaliana using synteny-based methods. Purifying selection was pervasive within R2R3-MYB TFs. K n /K s values lower than 0.3 indicated that BnaR2R3-MYB TFs are being functionally converged. The role of gene conversion in the formation of BnaR2R3-MYB TFs was significant. Cis-regulatory elements in the upstream regions of BnaR2R3-MYB genes, miRNA targeting BnaR2R3MYB TFs, and post translational modifications were identified. Digital expression data revealed that BnaR2R3-MYB genes were highly expressed in the roots and under high salinity treatment after 24 h. BnaMYB21, BnaMYB141, and BnaMYB148 have been suggested for improving salt-tolerant B. napus. BnaR2R3-MYB genes were mostly up regulated on the 14th day post inoculation with Leptosphaeria biglobosa and L. maculan. BnaMYB150 is a candidate for increased tolerance to Leptospheria in B. napus.
SDE based regression for random PDEs
Bayer, Christian
2016-01-01
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.
Fixed kernel regression for voltammogram feature extraction
International Nuclear Information System (INIS)
Acevedo Rodriguez, F J; López-Sastre, R J; Gil-Jiménez, P; Maldonado Bascón, S; Ruiz-Reyes, N
2009-01-01
Cyclic voltammetry is an electroanalytical technique for obtaining information about substances under analysis without the need for complex flow systems. However, classifying the information in voltammograms obtained using this technique is difficult. In this paper, we propose the use of fixed kernel regression as a method for extracting features from these voltammograms, reducing the information to a few coefficients. The proposed approach has been applied to a wine classification problem with accuracy rates of over 98%. Although the method is described here for extracting voltammogram information, it can be used for other types of signals
SDE based regression for random PDEs
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.
Ghaedi, M; Rahimi, Mahmoud Reza; Ghaedi, A M; Tyagi, Inderjeet; Agarwal, Shilpi; Gupta, Vinod Kumar
2016-01-01
Two novel and eco friendly adsorbents namely tin oxide nanoparticles loaded on activated carbon (SnO2-NP-AC) and activated carbon prepared from wood tree Pistacia atlantica (AC-PAW) were used for the rapid removal and fast adsorption of methyl orange (MO) from the aqueous phase. The dependency of MO removal with various adsorption influential parameters was well modeled and optimized using multiple linear regressions (MLR) and least squares support vector regression (LSSVR). The optimal parameters for the LSSVR model were found based on γ value of 0.76 and σ(2) of 0.15. For testing the data set, the mean square error (MSE) values of 0.0010 and the coefficient of determination (R(2)) values of 0.976 were obtained for LSSVR model, and the MSE value of 0.0037 and the R(2) value of 0.897 were obtained for the MLR model. The adsorption equilibrium and kinetic data was found to be well fitted and in good agreement with Langmuir isotherm model and second-order equation and intra-particle diffusion models respectively. The small amount of the proposed SnO2-NP-AC and AC-PAW (0.015 g and 0.08 g) is applicable for successful rapid removal of methyl orange (>95%). The maximum adsorption capacity for SnO2-NP-AC and AC-PAW was 250 mg g(-1) and 125 mg g(-1) respectively. Copyright © 2015 Elsevier Inc. All rights reserved.
Kim, T. W.; Park, G. H.
2014-12-01
Seasonal variation of aragonite saturation state (Ωarag) in the North Pacific Ocean (NPO) was investigated, using multiple linear regression (MLR) models produced from the PACIFICA (Pacific Ocean interior carbon) dataset. Data within depth ranges of 50-1200m were used to derive MLR models, and three parameters (potential temperature, nitrate, and apparent oxygen utilization (AOU)) were chosen as predictor variables because these parameters are associated with vertical mixing, DIC (dissolved inorganic carbon) removal and release which all affect Ωarag in water column directly or indirectly. The PACIFICA dataset was divided into 5° × 5° grids, and a MLR model was produced in each grid, giving total 145 independent MLR models over the NPO. Mean RMSE (root mean square error) and r2 (coefficient of determination) of all derived MLR models were approximately 0.09 and 0.96, respectively. Then the obtained MLR coefficients for each of predictor variables and an intercept were interpolated over the study area, thereby making possible to allocate MLR coefficients to data-sparse ocean regions. Predictability from the interpolated coefficients was evaluated using Hawaiian time-series data, and as a result mean residual between measured and predicted Ωarag values was approximately 0.08, which is less than the mean RMSE of our MLR models. The interpolated MLR coefficients were combined with seasonal climatology of World Ocean Atlas 2013 (1° × 1°) to produce seasonal Ωarag distributions over various depths. Large seasonal variability in Ωarag was manifested in the mid-latitude Western NPO (24-40°N, 130-180°E) and low-latitude Eastern NPO (0-12°N, 115-150°W). In the Western NPO, seasonal fluctuations of water column stratification appeared to be responsible for the seasonal variation in Ωarag (~ 0.5 at 50 m) because it closely followed temperature variations in a layer of 0-75 m. In contrast, remineralization of organic matter was the main cause for the seasonal
Polynomial regression analysis and significance test of the regression function
International Nuclear Information System (INIS)
Gao Zhengming; Zhao Juan; He Shengping
2012-01-01
In order to analyze the decay heating power of a certain radioactive isotope per kilogram with polynomial regression method, the paper firstly demonstrated the broad usage of polynomial function and deduced its parameters with ordinary least squares estimate. Then significance test method of polynomial regression function is derived considering the similarity between the polynomial regression model and the multivariable linear regression model. Finally, polynomial regression analysis and significance test of the polynomial function are done to the decay heating power of the iso tope per kilogram in accord with the authors' real work. (authors)
International Nuclear Information System (INIS)
Yan, Jidong; Xu, Jing; Fei, Yao; Jiang, Congshan; Zhu, Wenhua; Han, Yan; Lu, Shemin
2016-01-01
Thioredoxin reductase 2 (TrxR2) is a selenium (Se) containing protein. Se deficiency is associated with an endemic osteoarthropathy characterized by impaired cartilage formation. It is unclear whether TrxR2 have roles in cartilage function. We examined the effects of TrxR2 on chondrogenic ATDC5 cells through shRNA-mediated gene silencing of TrxR2. We demonstrated TrxR2 deficiencies could enhance chondrogenic differentiation and apoptosis of ATDC5 cells. TrxR2 deficiencies increased accumulation of cartilage glycosaminoglycans (GAGs) and mineralization. TrxR2 deficiencies also stimulated expression of extracellular (ECM) gene including Collagen II and Aggrecan. The enhanced chondrogenic properties were further confirmed by activation of Akt signaling which are required for chondrogenesis. In addition, TrxR2 deficiencies promoted chondrocyte proliferation through acceleration of cell cycle progression by increase in both S and G2/M phase cell distribution accompanied with induction of parathyroid hormone-related protein (PTHrP). Moreover, TrxR2 deficiencies induced chondrocyte death via apoptosis and increased cell sensitivity to exogenous oxidative stress. Furthermore, TrxR2 deficiencies induced emission of mitochondrial reactive oxygen species (ROS) without alteration of mitochondrial membrane potential and intracellular ATP content. Finally, treatment of TrxR2 deficiency cells with N-acetylcysteine (NAC) inhibited mitochondrial ROS production and chondrocyte apoptosis. NAC also prevented chondrogenic differentiation of TrxR2 deficiency cells by suppression of ECM gene expression, GAGs accumulation and mineralization, as well as attenuation of Akt signaling. Thus, TrxR2-mediated mitochondrial integrity is indispensable for chondrogenic differentiation of ATDC5 cells. TrxR2 deficiency-induced impaired proliferation and death of chondrocytes may be the pathological mechanism of the osteoarthropathy due to Se deficiency. Notably, this study also uncover the roles of
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Yan, Jidong [Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an, Shaanxi 710061 (China); Xu, Jing [Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an, Shaanxi 710061 (China); Fei, Yao [College of Life Sciences, Northwest University, Xi’an, Shaanxi Province 710069 (China); Jiang, Congshan; Zhu, Wenhua; Han, Yan [Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an, Shaanxi 710061 (China); Lu, Shemin, E-mail: lushemin@xjtu.edu.cn [Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an, Shaanxi 710061 (China); Key Laboratory of Environment and Genes Related to Diseases, Xi’an Jiaotong University, Ministry of Education of China (China)
2016-05-15
Thioredoxin reductase 2 (TrxR2) is a selenium (Se) containing protein. Se deficiency is associated with an endemic osteoarthropathy characterized by impaired cartilage formation. It is unclear whether TrxR2 have roles in cartilage function. We examined the effects of TrxR2 on chondrogenic ATDC5 cells through shRNA-mediated gene silencing of TrxR2. We demonstrated TrxR2 deficiencies could enhance chondrogenic differentiation and apoptosis of ATDC5 cells. TrxR2 deficiencies increased accumulation of cartilage glycosaminoglycans (GAGs) and mineralization. TrxR2 deficiencies also stimulated expression of extracellular (ECM) gene including Collagen II and Aggrecan. The enhanced chondrogenic properties were further confirmed by activation of Akt signaling which are required for chondrogenesis. In addition, TrxR2 deficiencies promoted chondrocyte proliferation through acceleration of cell cycle progression by increase in both S and G2/M phase cell distribution accompanied with induction of parathyroid hormone-related protein (PTHrP). Moreover, TrxR2 deficiencies induced chondrocyte death via apoptosis and increased cell sensitivity to exogenous oxidative stress. Furthermore, TrxR2 deficiencies induced emission of mitochondrial reactive oxygen species (ROS) without alteration of mitochondrial membrane potential and intracellular ATP content. Finally, treatment of TrxR2 deficiency cells with N-acetylcysteine (NAC) inhibited mitochondrial ROS production and chondrocyte apoptosis. NAC also prevented chondrogenic differentiation of TrxR2 deficiency cells by suppression of ECM gene expression, GAGs accumulation and mineralization, as well as attenuation of Akt signaling. Thus, TrxR2-mediated mitochondrial integrity is indispensable for chondrogenic differentiation of ATDC5 cells. TrxR2 deficiency-induced impaired proliferation and death of chondrocytes may be the pathological mechanism of the osteoarthropathy due to Se deficiency. Notably, this study also uncover the roles of
Assessing risk factors for periodontitis using regression
Lobo Pereira, J. A.; Ferreira, Maria Cristina; Oliveira, Teresa
2013-10-01
Multivariate statistical analysis is indispensable to assess the associations and interactions between different factors and the risk of periodontitis. Among others, regression analysis is a statistical technique widely used in healthcare to investigate and model the relationship between variables. In our work we study the impact of socio-demographic, medical and behavioral factors on periodontal health. Using regression, linear and logistic models, we can assess the relevance, as risk factors for periodontitis disease, of the following independent variables (IVs): Age, Gender, Diabetic Status, Education, Smoking status and Plaque Index. The multiple linear regression analysis model was built to evaluate the influence of IVs on mean Attachment Loss (AL). Thus, the regression coefficients along with respective p-values will be obtained as well as the respective p-values from the significance tests. The classification of a case (individual) adopted in the logistic model was the extent of the destruction of periodontal tissues defined by an Attachment Loss greater than or equal to 4 mm in 25% (AL≥4mm/≥25%) of sites surveyed. The association measures include the Odds Ratios together with the correspondent 95% confidence intervals.
4-bit digital to analog converter using R-2R ladder and binary weighted resistors
Diosanto, J.; Batac, M. L.; Pereda, K. J.; Caldo, R.
2017-06-01
The use of a 4-bit digital-to-analog converter using two methods; Binary Weighted Resistors and R-2R Ladder is designed and presented in this paper. The main components that were used in constructing both circuits were different resistor values, operational amplifier (LM741) and single pole double throw switches. Both circuits were designed using MULTISIM software to be able to test the circuit for its ideal application and FRITZING software for the layout designing and fabrication to the printed circuit board. The implementation of both systems in an actual circuit benefits in determining and comparing the advantages and disadvantages of each. It was realized that the binary weighted circuit is more efficient DAC, having lower percentage error of 0.267% compared to R-2R ladder circuit which has a minimum of percentage error of 4.16%.
International Nuclear Information System (INIS)
Wang Dongsheng; Wang Jinglan
2003-01-01
The good linear relationship with significance level α = 0.01 exists between isotope in precipitation and surface air temperature with multi-year average in 32 stations of China, and the yearly δD-temperature coefficient = 3.1‰/1℃ and the yearly δ 18 O-temperature coefficient = 0.36‰/1℃, and its determination coefficient R 2 = 0.67 and 0.64 respectively. So the isotope-temperature coefficient with yearly average can serve as the temperature yearly measure. But the monthly average isotope-temperature coefficient in each station is variable according to both of space and time, and its repeatability is determined by the meteorological regimes. According to the monthly isotope-temperature coefficient (B) and the coefficient of determination (R 2 ) and its α, all of China can be zoned the following three belts: (1) In the North Belt, B>O, R 2 ≈ 0.3-0.65, α = 0.01, the relation between monthly isotope in precipitation and surface air temperature (RMIT) belongs to a direct correlation and is closer in 99% probability; (2) In the South Belt, B
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.
Regression in autistic spectrum disorders.
Stefanatos, Gerry A
2008-12-01
A significant proportion of children diagnosed with Autistic Spectrum Disorder experience a developmental regression characterized by a loss of previously-acquired skills. This may involve a loss of speech or social responsitivity, but often entails both. This paper critically reviews the phenomena of regression in autistic spectrum disorders, highlighting the characteristics of regression, age of onset, temporal course, and long-term outcome. Important considerations for diagnosis are discussed and multiple etiological factors currently hypothesized to underlie the phenomenon are reviewed. It is argued that regressive autistic spectrum disorders can be conceptualized on a spectrum with other regressive disorders that may share common pathophysiological features. The implications of this viewpoint are discussed.
JESS-D-16-00284 R2.pdf | forthcoming | jess | Volumes | public ...
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Indian Academy of Sciences (India)
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Indian Academy of Sciences (India)
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Indian Academy of Sciences (India)
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Indian Academy of Sciences (India)
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JESS-D-16-00005R2.pdf | forthcoming | jess | Volumes | public ...
Indian Academy of Sciences (India)
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Low-Concentration Tributyltin Decreases GluR2 Expression via Nuclear Respiratory Factor-1 Inhibition
Ishida, Keishi; Aoki, Kaori; Takishita, Tomoko; Miyara, Masatsugu; Sakamoto, Shuichiro; Sanoh, Seigo; Kimura, Tomoki; Kanda, Yasunari; Ohta, Shigeru; Kotake, Yaichiro
2017-01-01
Tributyltin (TBT), which has been widely used as an antifouling agent in paints, is a common environmental pollutant. Although the toxicity of high-dose TBT has been extensively reported, the effects of low concentrations of TBT are relatively less well studied. We have previously reported that low-concentration TBT decreases ?-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA)-type glutamate receptor subunit 2 (GluR2) expression in cortical neurons and enhances neuronal vulnerability ...
JESS-D-16-00578 R2.pdf | forthcoming | jess | Volumes | public ...
Indian Academy of Sciences (India)
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JESS-D-16-00482 R2.pdf | forthcoming | jess | Volumes | public ...
Indian Academy of Sciences (India)
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Indian Academy of Sciences (India)
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JESS-D-16-00542 R2.pdf | forthcoming | jess | Volumes | public ...
Indian Academy of Sciences (India)
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Indian Academy of Sciences (India)
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JESS-D-16-00589 R2.pdf | forthcoming | jess | Volumes | public ...
Indian Academy of Sciences (India)
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JESS-D-16-00197 R2.pdf | forthcoming | jess | Volumes | public ...
Indian Academy of Sciences (India)
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Indian Academy of Sciences (India)
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Indian Academy of Sciences (India)
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Indian Academy of Sciences (India)
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Indian Academy of Sciences (India)
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Indian Academy of Sciences (India)
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Indian Academy of Sciences (India)
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Indian Academy of Sciences (India)
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Indian Academy of Sciences (India)
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JESS-D-15-00464R2.pdf | forthcoming | jess | Volumes | public ...
Indian Academy of Sciences (India)
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Indian Academy of Sciences (India)
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Arko, Robert; Chandler, Cynthia; Stocks, Karen; Smith, Shawn; Clark, Paul; Shepherd, Adam; Moore, Carla; Beaulieu, Stace
2013-04-01
The Rolling Deck to Repository (R2R) program is developing infrastructure to ensure the underway sensor data from U.S. academic oceanographic research vessels are routinely and consistently documented, preserved in long-term archives, and disseminated to the science community. The entire R2R Catalog is published online as a Linked Data collection, making it easily accessible to encourage discovery and integration with data at other repositories. We are developing the R2R Linked Data collection with specific goals in mind: 1.) We facilitate data access and reuse by publishing the richest possible collection of resources to describe vessels, cruises, instruments, and datasets from the U.S. academic fleet, including data quality assessment results and clean trackline navigation; 2.) We facilitate data citation through the entire lifecycle from field acquisition to shoreside archiving to journal articles and global syntheses, by publishing Digital Object Identifiers (DOIs) for datasets and encoding them directly into our Linked Data resources; and 3.) We facilitate federation with other repositories such as the Biological and Chemical Oceanography Data Management Office (BCO-DMO), InterRidge Vents Database, and Index to Marine and Lacustrine Geological Samples (IMLGS), by reciprocal linking between RDF resources and supporting the RDF Query Language. R2R participates in the Ocean Data Interoperability Platform (ODIP), a joint European-U.S.-Australian partnership to facilitate the sharing of data and documentation across international borders. We publish our controlled vocabularies as a Simple Knowledge Organization System (SKOS) concept collection, and are working toward alignment with SeaDataNet and other community-standard terms using the NERC Vocabulary Server (NVS). http://rvdata.us/
Support vector regression methodology for estimating global solar radiation in Algeria
Guermoui, Mawloud; Rabehi, Abdelaziz; Gairaa, Kacem; Benkaciali, Said
2018-01-01
Accurate estimation of Daily Global Solar Radiation (DGSR) has been a major goal for solar energy applications. In this paper we show the possibility of developing a simple model based on the Support Vector Regression (SVM-R), which could be used to estimate DGSR on the horizontal surface in Algeria based only on sunshine ratio as input. The SVM model has been developed and tested using a data set recorded over three years (2005-2007). The data was collected at the Applied Research Unit for Renewable Energies (URAER) in Ghardaïa city. The data collected between 2005-2006 are used to train the model while the 2007 data are used to test the performance of the selected model. The measured and the estimated values of DGSR were compared during the testing phase statistically using the Root Mean Square Error (RMSE), Relative Square Error (rRMSE), and correlation coefficient (r2), which amount to 1.59(MJ/m2), 8.46 and 97,4%, respectively. The obtained results show that the SVM-R is highly qualified for DGSR estimation using only sunshine ratio.
Directory of Open Access Journals (Sweden)
Marjan Čeh
2018-05-01
Full Text Available The goal of this study is to analyse the predictive performance of the random forest machine learning technique in comparison to commonly used hedonic models based on multiple regression for the prediction of apartment prices. A data set that includes 7407 records of apartment transactions referring to real estate sales from 2008–2013 in the city of Ljubljana, the capital of Slovenia, was used in order to test and compare the predictive performances of both models. Apparent challenges faced during modelling included (1 the non-linear nature of the prediction assignment task; (2 input data being based on transactions occurring over a period of great price changes in Ljubljana whereby a 28% decline was noted in six consecutive testing years; and (3 the complex urban form of the case study area. Available explanatory variables, organised as a Geographic Information Systems (GIS ready dataset, including the structural and age characteristics of the apartments as well as environmental and neighbourhood information were considered in the modelling procedure. All performance measures (R2 values, sales ratios, mean average percentage error (MAPE, coefficient of dispersion (COD revealed significantly better results for predictions obtained by the random forest method, which confirms the prospective of this machine learning technique on apartment price prediction.
Directory of Open Access Journals (Sweden)
Mustakim Mustakim
2016-02-01
Full Text Available The largest region that produces oil palm in Indonesia has an important role in improving the welfare of society and economy. Oil palm has increased significantly in Riau Province in every period, to determine the production development for the next few years with the functions and benefits of oil palm carried prediction production results that were seen from time series data last 8 years (2005-2013. In its prediction implementation, it was done by comparing the performance of Support Vector Regression (SVR method and Artificial Neural Network (ANN. From the experiment, SVR produced the best model compared with ANN. It is indicated by the correlation coefficient of 95% and 6% for MSE in the kernel Radial Basis Function (RBF, whereas ANN produced only 74% for R2 and 9% for MSE on the 8th experiment with hiden neuron 20 and learning rate 0,1. SVR model generates predictions for next 3 years which increased between 3% - 6% from actual data and RBF model predictions.
FED-R2: concept and magnet design of a low-cost FED
International Nuclear Information System (INIS)
Williams, J.E.C.; Becker, H.; Blackfield, D.; Bobrov, E.; Bromberg, L.; Cohn, D.R.; Diatchenko, N.; LeClaire, R.
1982-12-01
High performance resistive magnet technology was used to develop a design for a compact, low cost version of the fusion engineering device FED. We refer to this design as FED-R2, for FED-resistive magnet design 2 to distinguish it from the larger resistive magnet design for FED which uses demountable coils (FED-R1). The main objectives of FED-R2 are: (1) to demonstrate reliable, quasi-steady state (long pulse, high duty factor) operation with Q/sub p/ approx. 5; (2) to demonstrate Q/sub p/ > 5 operation for a limited number of pulses; (3) to provide high neutron flux for irradiation of nuclear test modules with a total area greater tha 20m 2 ; (4) to utilize steady-state RF current drive if this option appears promising. Based upon the costing codes at the Fusion Engineering Design Center and upon TFTR costs, the estimated direct costs of FED-R2 would be on the range 380 to 460M, a factor of about 2 below that of the baseline FED design
High-pressure synthesis and characterizations of the R2Pt2O7 pyrochlores.
Cai, Yunqi; Cui, Qi; Cheng, Jinguang; Dun, Zhiling; Zhou, Haidong; Ma, Jie; Cruz, C. Dela; Yan, Jiaqiang; Li, Xiang; Zhou, Jianshi
Pyrochlore R2B2O7 where R3 + stands for rear-earth ion and B4 + for a nonmagnetic cation such as Sn4 +or Ti4 +consist of an important family of geometrically frustrated magnets, which have been the focus of extensive investigations over last decades. To further enlarge the R2B2O7, we have chosen to stabilize the Pt-based cubic pyrochlores under HPHT conditions for two reasons: (1) Pt4 + is in a low-spin state which ionic radius is located in between Ti4 + (0.605\\x85) and Sn4 + (0.69\\x85), and (2) Pt4 + has a spatially much more extended 5d orbitals and thus enhanced Pt 5d-O 2p hybridizations that might modify the local anisotropic exchange interactions. Such an effect has never been taken into account in the previous studies. In this work, we will present the detailed characterizations on the pyrochlores R2Pt2O7 obtained under HPHT conditions. This work is supported by the National Science Foundation of China (Grant Nos.11304371, 11574377), part of the work was supported by the CEM, and NSF MRSEC, under Grant DMR-1420451, and Grant No. NSF-DMR-1350002.
Antifungal potential of Bacillus vallismortis R2 against different phytopathogenic fungi
Energy Technology Data Exchange (ETDEWEB)
Kaur, P.K.; Kaur, J.; Saini, H.S.
2015-07-01
The cash crops grown in an agro-climatic region are prone to infection by various fungal pathogens. The use of chemical fungicides over the years has resulted in emergence of resistant fungal strains, thereby necessitating the development of effective and environmental friendly alternatives. The natural antagonistic interactions among different microbial populations have been exploited as an eco-friendly approach for controlling fungal pathogens resistant to synthetic chemicals. Morphologically distinct bacterial cultures (150), isolated from rhizospheric soils of wheat, rice, onion and tomato plants were screened for their antifungal potential against seven phytopathogenic fungi prevalent in the State of Punjab (India). The bacterial isolate R2, identified as Bacillus vallismortis, supported more than 50% inhibition of different phytopathogenic fungi (Alternaria alternata, Rhizoctonia oryzae, Fusarium oxysporum, Fusarium moniliforme, Colletotrichum sp, Helminthosporium sp and Magnaporthe grisea) in dual culture plate assay. The thin layer chromatography based bio-autography of acid-precipitated biomolecules (APB) indicated the presence of more than one type of antifungal molecule, as evidenced from zones of inhibition against the respective fungal pathogen. The initial analytical studies indicated the presence of surfactin, iturin A and fengycin-like compounds in APB. The antifungal activity of whole cells and APB of isolate R2 was evaluated by light and scanning electron microscopy. The wheat grains treated with APB and exposed to spores of A. alternata showed resistance to the development of black point disease, thereby indicating the potential application of R2 and its biomolecules at field scale level. (Author)
R2* mapping for brain iron: associations with cognition in normal aging.
Ghadery, Christine; Pirpamer, Lukas; Hofer, Edith; Langkammer, Christian; Petrovic, Katja; Loitfelder, Marisa; Schwingenschuh, Petra; Seiler, Stephan; Duering, Marco; Jouvent, Eric; Schmidt, Helena; Fazekas, Franz; Mangin, Jean-Francois; Chabriat, Hugues; Dichgans, Martin; Ropele, Stefan; Schmidt, Reinhold
2015-02-01
Brain iron accumulates during aging and has been associated with neurodegenerative disorders including Alzheimer's disease. Magnetic resonance (MR)-based R2* mapping enables the in vivo detection of iron content in brain tissue. We investigated if during normal brain aging iron load relates to cognitive impairment in region-specific patterns in a community-dwelling cohort of 336 healthy, middle aged, and older adults from the Austrian Stroke Prevention Family Study. MR imaging and R2* mapping in the basal ganglia and neocortex were done at 3T. Comprehensive neuropsychological testing assessed memory, executive function, and psychomotor speed. We found the highest iron concentration in the globus pallidus, and pallidal and putaminal iron was significantly and inversely associated with cognitive performance in all cognitive domains, except memory. These associations were iron load dependent. Vascular brain lesions and brain volume did not mediate the relationship between iron and cognitive performance. We conclude that higher R2*-determined iron in the basal ganglia correlates with cognitive impairment during brain aging independent of concomitant brain abnormalities. The prognostic significance of this finding needs to be determined. Copyright © 2015 Elsevier Inc. All rights reserved.
Magnetic phase transitions in R2Fe17 compounds under pressure
International Nuclear Information System (INIS)
Arnold, Z.; Kamarad, J.
1994-01-01
The effect of the pressure up to 1.4 GPa on the Curie temperature T c in the R 2 Fe 17 intermetallics with R = Nd, Er and Y was measured using a low field susceptibility technique. The identical character of the temperature dependence of susceptibility χ(T) of the R 2 Fe 17 intermetallics observed at ambient pressure (sharp step-like drop at T c ) is preserved at high pressures only in the case of Nd 2 Fe 17 . Pronounced broadening and splitting of the sharp drop of χ(T) was observed in Er 2 Fe 17 and Y 2 Fe 17 respectively. The initial pressure slopes of dTc/dp are large and negative for all studied compounds, having nearly the same values (dTc/dp = -36K/GPa for Nd 2 Fe 17 compound). The results are discussed from the point of view of the sensitivity of T c on the crystal structure, the number of nearest neighbors of Fe atoms and the possible effect of disordered structures in the R 2 Fe 17 intermetallics
2016-10-01
Cisplatin (2uM, 30 hrs) PN (5uM, 55hrs) + Cisplatin (2uM, 30 hrs) • Thorough studies are needed to examine the unknown mechanism of IFNgR2 and Bax as well as...mouse xenograft model. Task3: To determine the mechanism of increased IFNγR2 expression in PCa. We found that NFkB inhibitor suppressed IFNγR2 expression...suggesting that hyper-activation of NFkB may be one of the mechanisms of IFNγR2 overexpression in PCa. These results support our hypothesis that
Advanced statistics: linear regression, part I: simple linear regression.
Marill, Keith A
2004-01-01
Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.
Analysis of quantile regression as alternative to ordinary least squares
Ibrahim Abdullahi; Abubakar Yahaya
2015-01-01
In this article, an alternative to ordinary least squares (OLS) regression based on analytical solution in the Statgraphics software is considered, and this alternative is no other than quantile regression (QR) model. We also present goodness of fit statistic as well as approximate distributions of the associated test statistics for the parameters. Furthermore, we suggest a goodness of fit statistic called the least absolute deviation (LAD) coefficient of determination. The procedure is well ...
Quadrature formulas for Fourier coefficients
Bojanov, Borislav
2009-09-01
We consider quadrature formulas of high degree of precision for the computation of the Fourier coefficients in expansions of functions with respect to a system of orthogonal polynomials. In particular, we show the uniqueness of a multiple node formula for the Fourier-Tchebycheff coefficients given by Micchelli and Sharma and construct new Gaussian formulas for the Fourier coefficients of a function, based on the values of the function and its derivatives. © 2009 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Wenjun Huang
Full Text Available Herba epimedii (Epimedium, a traditional Chinese medicine, has been widely used as a kidney tonic and antirheumatic medicine for thousands of years. The bioactive components in herba epimedii are mainly prenylated flavonol glycosides, end-products of the flavonoid pathway. Epimedium species are also used as garden plants due to the colorful flowers and leaves. Many R2R3-MYB transcription factors (TFs have been identified to regulate the flavonoid and anthocyanin biosynthetic pathways. However, little is known about the R2R3-MYB TFs involved in regulation of the flavonoid pathway in Epimedium. Here, we reported the isolation and functional characterization of the first R2R3-MYB TF (EsMYBA1 from Epimedium sagittatum (Sieb. Et Zucc. Maxim. Conserved domains and phylogenetic analysis showed that EsMYBA1 belonged to the subgroup 6 clade (anthocyanin-related MYB clade of R2R3-MYB family, which includes Arabidopsis AtPAP1, apple MdMYB10 and legume MtLAP1. EsMYBA1 was preferentially expressed in leaves, especially in red leaves that contain higher content of anthocyanin. Alternative splicing of EsMYBA1 resulted in three transcripts and two of them encoded a MYB-related protein. Yeast two-hybrid and transient luciferase expression assay showed that EsMYBA1 can interact with several bHLH regulators of the flavonoid pathway and activate the promoters of dihydroflavonol 4-reductase (DFR and anthocyanidin synthase (ANS. In both transgenic tobacco and Arabidopsis, overexpression of EsMYBA1 induced strong anthocyanin accumulation in reproductive and/or vegetative tissues via up-regulation of the main flavonoid-related genes. Furthermore, transient expression of EsMYBA1 in E. sagittatum leaves by Agrobacterium infiltration also induced anthocyanin accumulation in the wounded area. This first functional characterization of R2R3-MYB TFs in Epimedium species will promote further studies of the flavonoid biosynthesis and regulation in medicinal plants.
Huang, Wenjun; Sun, Wei; Lv, Haiyan; Luo, Ming; Zeng, Shaohua; Pattanaik, Sitakanta; Yuan, Ling; Wang, Ying
2013-01-01
Herba epimedii (Epimedium), a traditional Chinese medicine, has been widely used as a kidney tonic and antirheumatic medicine for thousands of years. The bioactive components in herba epimedii are mainly prenylated flavonol glycosides, end-products of the flavonoid pathway. Epimedium species are also used as garden plants due to the colorful flowers and leaves. Many R2R3-MYB transcription factors (TFs) have been identified to regulate the flavonoid and anthocyanin biosynthetic pathways. However, little is known about the R2R3-MYB TFs involved in regulation of the flavonoid pathway in Epimedium. Here, we reported the isolation and functional characterization of the first R2R3-MYB TF (EsMYBA1) from Epimedium sagittatum (Sieb. Et Zucc.) Maxim. Conserved domains and phylogenetic analysis showed that EsMYBA1 belonged to the subgroup 6 clade (anthocyanin-related MYB clade) of R2R3-MYB family, which includes Arabidopsis AtPAP1, apple MdMYB10 and legume MtLAP1. EsMYBA1 was preferentially expressed in leaves, especially in red leaves that contain higher content of anthocyanin. Alternative splicing of EsMYBA1 resulted in three transcripts and two of them encoded a MYB-related protein. Yeast two-hybrid and transient luciferase expression assay showed that EsMYBA1 can interact with several bHLH regulators of the flavonoid pathway and activate the promoters of dihydroflavonol 4-reductase (DFR) and anthocyanidin synthase (ANS). In both transgenic tobacco and Arabidopsis, overexpression of EsMYBA1 induced strong anthocyanin accumulation in reproductive and/or vegetative tissues via up-regulation of the main flavonoid-related genes. Furthermore, transient expression of EsMYBA1 in E. sagittatum leaves by Agrobacterium infiltration also induced anthocyanin accumulation in the wounded area. This first functional characterization of R2R3-MYB TFs in Epimedium species will promote further studies of the flavonoid biosynthesis and regulation in medicinal plants.
Rolling Deck to Repository (R2R): Technical Design - Experiences and Lessons (Invited)
Arko, R. A.; Carbotte, S. M.; Miller, S. P.; Chandler, C. L.; Ferrini, V.; Stocks, K.; Maffei, A. R.; Smith, S. R.; Bourassa, M. A.; McLean, S. J.; Alberts, J. C.
2009-12-01
The NSF-funded Rolling Deck to Repository (R2R) project envisions the academic research fleet as an integrated global observing system, with routine “underway” sensor data flowing directly from research vessels to a central shore-side repository. It is a complex endeavor involving many stakeholders - technicians at sea, data managers on shore, ship schedulers, clearance officers, funding agencies, National Data Centers, data synthesis projects, the science community, and the public - working toward a common goal of acquiring, documenting, archiving, evaluating, and disseminating high-quality scientific data. The technical design for R2R is guided by several key principles: 1) The data pipeline is modular, so that initial stages (e.g. inventory and review of data shipments, posting of catalog records and track maps) may proceed routinely for every cruise, while later stages (e.g. quality assessment and production of file-level metadata) may proceed at different rates for different data types; 2) Cruise documentation (e.g. sailing orders, review/release of data inventories, vessel profiles) is gathered primarily via an authenticated Web portal, linked with the UNOLS scheduling database to synchronize vocabularies and eliminate redundancies; and 3) Every data set will be documented and delivered to the appropriate National Data Center for long-term archiving and dissemination after proprietary holds are cleared, while R2R maintains a master cruise catalog that links all the data sets together. This design accommodates the diversity of instrument types, data volumes, and shipment schedules among fleet operators. During its pilot development period, R2R has solicited feedback at community workshops, UNOLS meetings, and conference presentations, including fleet-wide surveys of current practices and instrument inventories. Several vessel operators began submitting cruise data and documentation during the pilot, providing a test bed for database development and Web
Coefficient Alpha: A Reliability Coefficient for the 21st Century?
Yang, Yanyun; Green, Samuel B.
2011-01-01
Coefficient alpha is almost universally applied to assess reliability of scales in psychology. We argue that researchers should consider alternatives to coefficient alpha. Our preference is for structural equation modeling (SEM) estimates of reliability because they are informative and allow for an empirical evaluation of the assumptions…
Coefficient estimates of negative powers and inverse coefficients for ...
Indian Academy of Sciences (India)
and the inequality is sharp for the inverse of the Koebe function k(z) = z/(1 − z)2. An alternative approach to the inverse coefficient problem for functions in the class S has been investigated by Schaeffer and Spencer [27] and FitzGerald [6]. Although, the inverse coefficient problem for the class S has been completely solved ...
Measuring of heat transfer coefficient
DEFF Research Database (Denmark)
Henningsen, Poul; Lindegren, Maria
Subtask 3.4 Measuring of heat transfer coefficient Subtask 3.4.1 Design and setting up of tests to measure heat transfer coefficient Objective: Complementary testing methods together with the relevant experimental equipment are to be designed by the two partners involved in order to measure...... the heat transfer coefficient for a wide range of interface conditions in hot and warm forging processes. Subtask 3.4.2 Measurement of heat transfer coefficient The objective of subtask 3.4.2 is to determine heat transfer values for different interface conditions reflecting those typically operating in hot...
Estimation of octanol/water partition coefficients using LSER parameters
Luehrs, Dean C.; Hickey, James P.; Godbole, Kalpana A.; Rogers, Tony N.
1998-01-01
The logarithms of octanol/water partition coefficients, logKow, were regressed against the linear solvation energy relationship (LSER) parameters for a training set of 981 diverse organic chemicals. The standard deviation for logKow was 0.49. The regression equation was then used to estimate logKow for a test of 146 chemicals which included pesticides and other diverse polyfunctional compounds. Thus the octanol/water partition coefficient may be estimated by LSER parameters without elaborate software but only moderate accuracy should be expected.
Energy Technology Data Exchange (ETDEWEB)
2009-01-15
This document describes the plans for decommissioning of the nuclear research and material test reactors R2 and R2-0, situated at the Studsvik site close to the city of Nykoeping, Sweden. The purpose of the document is to serve as information for the European Commission, and to fulfil the requirements of Article 37 of the Euratom Treaty. Studsvik is situated on the Baltic coast, about 20 km east of Nykoeping and 80 km southwest of Stockholm. The site comprises the reactors R2 and R2-0 and several facilities for material investigation and radioactive waste treatment and storage. The reactors were used for a number of different purposes from 1960 until June 2005, when they were shut down following a decision by the operator. Decommissioning of the reactor facility is planned to be completed in 2016 after dismantling and conditioning of radioactive parts and demolition of the facility. Solid and liquid radioactive wastes from the dismantling activities will be treated and stored on-site awaiting final disposal. The waste treatment facilities, which are situated in other buildings at the Studsvik site, are planned to continue operation during and after the decommissioning of the reactor facility. All nuclear fuel has been transferred to a separate storage facility and is being shipped to the US according to existing agreements. The objective of the planned dismantling activities is to achieve clearance of the facility to make it possible to either demolish the buildings or use them for other purposes. The operator has divided the planning for dismantling and demolition of the facility into three phases [1]: Dismantling 1, including primary system decontamination, dismantling of the reactors with systems in the reactor pool, draining, cleaning and temporary covering of the reactor pool. This phase has begun and is due to last till approximately December 2009. Dismantling 2, including dismantling of systems in the reactor facility, removal of equipment, radiological
Mass transfer coefficient of slug flow for organic solvent-aqueous system in a microreactor
International Nuclear Information System (INIS)
Tuek, Ana Jurinjak; Anic, Iva; Kurtanjek, Zelimir; Zelic, Bruno
2015-01-01
Application of microreactor systems could be the next break-through in the intensification of chemical and biochemical processes. The common flow regime for organic solvent-aqueous phase two-phase systems is a segmented flow. Internal circulations in segments cause high mass transfer and conversion. We analyzed slug flow in seven systems of organic solvents and aqueous phase. To analyze how slug lengths in tested systems depend on linear velocity and physical and chemical properties of used organic solvents, regression models were proposed. It was shown that models based on linearization of approximation by potentials give low correlation for slug length prediction; however, application of an essential nonlinear model of multiple layer perception (MLP) neural network gives high correlation with R 2 =0.9. General sensitivity analysis was applied for the MLP neural network model, which showed that 80% of variance in slug length for the both phases is accounted for the viscosity and density of the organic phases; 10% is accounted by surface tension of the organic phase, while molecular masses and flow rates each account for 5%. For defined geometry of microreactor, mass transfer has been determined by carrying out the neutralization experiment with NaOH where acetic acid diffuses from organic phase (hexane) into aqueous phase. Estimated mass transfer coefficients were in the range k L a=4,652-1,9807 h -1
Moderation analysis using a two-level regression model.
Yuan, Ke-Hai; Cheng, Ying; Maxwell, Scott
2014-10-01
Moderation analysis is widely used in social and behavioral research. The most commonly used model for moderation analysis is moderated multiple regression (MMR) in which the explanatory variables of the regression model include product terms, and the model is typically estimated by least squares (LS). This paper argues for a two-level regression model in which the regression coefficients of a criterion variable on predictors are further regressed on moderator variables. An algorithm for estimating the parameters of the two-level model by normal-distribution-based maximum likelihood (NML) is developed. Formulas for the standard errors (SEs) of the parameter estimates are provided and studied. Results indicate that, when heteroscedasticity exists, NML with the two-level model gives more efficient and more accurate parameter estimates than the LS analysis of the MMR model. When error variances are homoscedastic, NML with the two-level model leads to essentially the same results as LS with the MMR model. Most importantly, the two-level regression model permits estimating the percentage of variance of each regression coefficient that is due to moderator variables. When applied to data from General Social Surveys 1991, NML with the two-level model identified a significant moderation effect of race on the regression of job prestige on years of education while LS with the MMR model did not. An R package is also developed and documented to facilitate the application of the two-level model.
Directory of Open Access Journals (Sweden)
Chihiro Sugiyama
2015-01-01
Full Text Available In vitro estimating strategies for potential neurotoxicity are required to screen multiple substances. In a previous study, we showed that exposure to low-concentrations of some chemicals, such as organotin, decreased the expression of GluR2 protein, which is a subunit of alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA-type glutamate receptors, and led to neuronal vulnerability. This result suggested that GluR2 decreases as an index of neuronal cell sensitivity and vulnerability to various toxic insults. Accordingly, we developed a versatile method that is a large scale determination of GluR2 protein expression in the presence of environmental chemicals by means of AlphaLISA technology. Various analytical conditions were optimized, and then GluR2 protein amount was measured by the method using AlphaLISA. The GluR2 amounts were strongly correlated with that of measured by western blotting, which is currently used to determine GluR2 expression. An ideal standard curve could be written with the authentic GluR2 protein from 0 ng to 100 ng. Subsequently, twenty environmental chemicals were screened and nitenpyram was identified as a chemical which lead to decrease in GluR2 protein expression. This assay may provide a tool for detecting neurotoxic chemicals according to decreases in GluR2 protein expression.
R-2HG Exhibits Anti-tumor Activity by Targeting FTO/m6A/MYC/CEBPA Signaling.
Su, Rui; Dong, Lei; Li, Chenying; Nachtergaele, Sigrid; Wunderlich, Mark; Qing, Ying; Deng, Xiaolan; Wang, Yungui; Weng, Xiaocheng; Hu, Chao; Yu, Mengxia; Skibbe, Jennifer; Dai, Qing; Zou, Dongling; Wu, Tong; Yu, Kangkang; Weng, Hengyou; Huang, Huilin; Ferchen, Kyle; Qin, Xi; Zhang, Bin; Qi, Jun; Sasaki, Atsuo T; Plas, David R; Bradner, James E; Wei, Minjie; Marcucci, Guido; Jiang, Xi; Mulloy, James C; Jin, Jie; He, Chuan; Chen, Jianjun
2018-01-11
R-2-hydroxyglutarate (R-2HG), produced at high levels by mutant isocitrate dehydrogenase 1/2 (IDH1/2) enzymes, was reported as an oncometabolite. We show here that R-2HG also exerts a broad anti-leukemic activity in vitro and in vivo by inhibiting leukemia cell proliferation/viability and by promoting cell-cycle arrest and apoptosis. Mechanistically, R-2HG inhibits fat mass and obesity-associated protein (FTO) activity, thereby increasing global N 6 -methyladenosine (m 6 A) RNA modification in R-2HG-sensitive leukemia cells, which in turn decreases the stability of MYC/CEBPA transcripts, leading to the suppression of relevant pathways. Ectopically expressed mutant IDH1 and S-2HG recapitulate the effects of R-2HG. High levels of FTO sensitize leukemic cells to R-2HG, whereas hyperactivation of MYC signaling confers resistance that can be reversed by the inhibition of MYC signaling. R-2HG also displays anti-tumor activity in glioma. Collectively, while R-2HG accumulated in IDH1/2 mutant cancers contributes to cancer initiation, our work demonstrates anti-tumor effects of 2HG in inhibiting proliferation/survival of FTO-high cancer cells via targeting FTO/m 6 A/MYC/CEBPA signaling. Copyright © 2017 Elsevier Inc. All rights reserved.
Linear regression in astronomy. II
Feigelson, Eric D.; Babu, Gutti J.
1992-01-01
A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.
Time-adaptive quantile regression
DEFF Research Database (Denmark)
Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg; Madsen, Henrik
2008-01-01
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......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...... 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....
Singh, Preet Mohinder; Borle, Anuradha; Shah, Dipal; Sinha, Ashish; Makkar, Jeetinder Kaur; Trikha, Anjan; Goudra, Basavana Gouda
2016-04-01
Prophylactic continuous positive airway pressure (CPAP) can prevent pulmonary adverse events following upper abdominal surgeries. The present meta-regression evaluates and quantifies the effect of degree/duration of (CPAP) on the incidence of postoperative pulmonary events. Medical databases were searched for randomized controlled trials involving adult patients, comparing the outcome in those receiving prophylactic postoperative CPAP versus no CPAP, undergoing high-risk abdominal surgeries. Our meta-analysis evaluated the relationship between the postoperative pulmonary complications and the use of CPAP. Furthermore, meta-regression was used to quantify the effect of cumulative duration and degree of CPAP on the measured outcomes. Seventy-three potentially relevant studies were identified, of which 11 had appropriate data, allowing us to compare a total of 362 and 363 patients in CPAP and control groups, respectively. Qualitatively, Odds ratio for CPAP showed protective effect for pneumonia [0.39 (0.19-0.78)], atelectasis [0.51 (0.32-0.80)] and pulmonary complications [0.37 (0.24-0.56)] with zero heterogeneity. For prevention of pulmonary complications, odds ratio was better for continuous than intermittent CPAP. Meta-regression demonstrated a positive correlation between the degree of CPAP and the incidence of pneumonia with a regression coefficient of +0.61 (95 % CI 0.02-1.21, P = 0.048, τ (2) = 0.078, r (2) = 7.87 %). Overall, adverse effects were similar with or without the use of CPAP. Prophylactic postoperative use of continuous CPAP significantly reduces the incidence of postoperative pneumonia, atelectasis and pulmonary complications in patients undergoing high-risk abdominal surgeries. Quantitatively, increasing the CPAP levels does not necessarily enhance the protective effect against pneumonia. Instead, protective effect diminishes with increasing degree of CPAP.
Quantile regression theory and applications
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
Predicting Fuel Ignition Quality Using 1H NMR Spectroscopy and Multiple Linear Regression
Abdul Jameel, Abdul Gani
2016-09-14
An improved model for the prediction of ignition quality of hydrocarbon fuels has been developed using 1H nuclear magnetic resonance (NMR) spectroscopy and multiple linear regression (MLR) modeling. Cetane number (CN) and derived cetane number (DCN) of 71 pure hydrocarbons and 54 hydrocarbon blends were utilized as a data set to study the relationship between ignition quality and molecular structure. CN and DCN are functional equivalents and collectively referred to as D/CN, herein. The effect of molecular weight and weight percent of structural parameters such as paraffinic CH3 groups, paraffinic CH2 groups, paraffinic CH groups, olefinic CH–CH2 groups, naphthenic CH–CH2 groups, and aromatic C–CH groups on D/CN was studied. A particular emphasis on the effect of branching (i.e., methyl substitution) on the D/CN was studied, and a new parameter denoted as the branching index (BI) was introduced to quantify this effect. A new formula was developed to calculate the BI of hydrocarbon fuels using 1H NMR spectroscopy. Multiple linear regression (MLR) modeling was used to develop an empirical relationship between D/CN and the eight structural parameters. This was then used to predict the DCN of many hydrocarbon fuels. The developed model has a high correlation coefficient (R2 = 0.97) and was validated with experimentally measured DCN of twenty-two real fuel mixtures (e.g., gasolines and diesels) and fifty-nine blends of known composition, and the predicted values matched well with the experimental data.
The onion (Allium cepa L. R2R3-MYB gene MYB1 regulates anthocyanin biosynthesis
Directory of Open Access Journals (Sweden)
Kathy Schwinn
2016-12-01
Full Text Available Bulb colour is an important consumer trait for onion (Allium cepa L., Allioideae, Asparagales. The bulbs accumulate a range of flavonoid compounds, including anthocyanins (red, flavonols (pale yellow and chalcones (bright yellow. Flavonoid regulation is poorly characterised in onion and in other plants belonging to the Asparagales, despite being a major plant order containing many important crop and ornamental species. R2R3-MYB transcription factors associated with the regulation of distinct branches of the flavonoid pathway were isolated from onion. These belonged to sub-groups (SGs that commonly activate anthocyanin (SG6, MYB1 or flavonol (SG7, MYB29 production, or repress phenylpropanoid/flavonoid synthesis (SG4, MYB4, MYB5. MYB1 was demonstrated to be a positive regulator of anthocyanin biosynthesis by the induction of anthocyanin production in onion tissue when transiently overexpressd and by reduction of pigmentation when transiently repressed via RNAi. Furthermore, ectopic red pigmentation was observed in garlic (A. sativum L. plants stably transformed with a construct for co-overexpression of MYB1 and a bHLH partner. MYB1 also was able to complement the acyanic petal phenotype of a defined R2R3-MYB anthocyanin mutant in Antirrhinum majus of the asterid clade of eudicots. The availability of sequence information for flavonoid-related MYBs from onion enabled phylogenetic groupings to be determined across monocotyledonous and dicotyledonous species, including the identification of characteristic amino acid motifs. This analysis suggests that divergent evolution of the R2R3-MYB family has occurred between Poaceae/Orchidaceae and Allioideae species. The DNA sequences identified will be valuable for future analysis of classical flavonoid genetic loci in Allium crops and will assist the breeding of these important crop species.
The Onion (Allium cepa L.) R2R3-MYB Gene MYB1 Regulates Anthocyanin Biosynthesis
Schwinn, Kathy E.; Ngo, Hanh; Kenel, Fernand; Brummell, David A.; Albert, Nick W.; McCallum, John A.; Pither-Joyce, Meeghan; Crowhurst, Ross N.; Eady, Colin; Davies, Kevin M.
2016-01-01
Bulb color is an important consumer trait for onion (Allium cepa L., Allioideae, Asparagales). The bulbs accumulate a range of flavonoid compounds, including anthocyanins (red), flavonols (pale yellow), and chalcones (bright yellow). Flavonoid regulation is poorly characterized in onion and in other plants belonging to the Asparagales, despite being a major plant order containing many important crop and ornamental species. R2R3-MYB transcription factors associated with the regulation of distinct branches of the flavonoid pathway were isolated from onion. These belonged to sub-groups (SGs) that commonly activate anthocyanin (SG6, MYB1) or flavonol (SG7, MYB29) production, or repress phenylpropanoid/flavonoid synthesis (SG4, MYB4, MYB5). MYB1 was demonstrated to be a positive regulator of anthocyanin biosynthesis by the induction of anthocyanin production in onion tissue when transiently overexpressed and by reduction of pigmentation when transiently repressed via RNAi. Furthermore, ectopic red pigmentation was observed in garlic (Allium sativum L.) plants stably transformed with a construct for co-overexpression of MYB1 and a bHLH partner. MYB1 also was able to complement the acyanic petal phenotype of a defined R2R3-MYB anthocyanin mutant in Antirrhinum majus of the asterid clade of eudicots. The availability of sequence information for flavonoid-related MYBs from onion enabled phylogenetic groupings to be determined across monocotyledonous and dicotyledonous species, including the identification of characteristic amino acid motifs. This analysis suggests that divergent evolution of the R2R3-MYB family has occurred between Poaceae/Orchidaceae and Allioideae species. The DNA sequences identified will be valuable for future analysis of classical flavonoid genetic loci in Allium crops and will assist the breeding of these important crop species. PMID:28018399
Kinematic Study of Ionized and Molecular Gases in Ultracompact HII Region in Monoceros R2
Kim, Hwihyun; Lacy, John H.; Jaffe, Daniel Thomas
2017-06-01
Monoceros R2 (Mon R2) is an UltraCompact HII region (UCHII) surrounded by several PhotoDissociation Regions (PDRs). It is an excellent example to investigate the chemistry and physics of early stage of massive star formation due to its proximity (830pc) and brightness. Previous studies suggest that the wind from the star holds the ionized gas up against the dense molecular core and the higher pressure at the head drives the ionized gas along the shell. In order for the model to work, there should be evidence for dense molecular gas along the shell walls, irradiated by the UCHII region and perhaps entrained into the flow along the walls.We obtained the Immersion Grating INfrared Spectrograph (IGRINS) spectra of Mon R2 to study the kinematic patterns in the areas where ionized and molecular gases interact. The position-velocity maps from the high resolution (R~45,000) H- and K-band (1.4-2.5μm) IGRINS spectra demonstrate that the ionized gases (Brackett and Pfund series, He and Fe emission lines; Δv ≈ 40km/s) flow along the walls of the surrounding clouds. This is consistent with the model by Zhu et al. (2008). In the PV maps of the H2 emission lines there is no obvious motion (Δv ≈ 10km/s) of the molecular hydrogen right at the ionization boundary. This implies that the molecular gas is not taking part in the flow as the ionized gas is moving along the cavity walls.This work used the Immersion Grating Infrared Spectrograph (IGRINS) that was developed under a collaboration between the University of Texas at Austin and the Korea Astronomy and Space Science Institute (KASI) with the financial support of the US National Science Foundation (NSF; grant AST-1229522), of the University of Texas at Austin, and of the Korean GMTProject of KASI.
The Onion (Allium cepa L.) R2R3-MYB Gene MYB1 Regulates Anthocyanin Biosynthesis.
Schwinn, Kathy E; Ngo, Hanh; Kenel, Fernand; Brummell, David A; Albert, Nick W; McCallum, John A; Pither-Joyce, Meeghan; Crowhurst, Ross N; Eady, Colin; Davies, Kevin M
2016-01-01
Bulb color is an important consumer trait for onion ( Allium cepa L., Allioideae, Asparagales). The bulbs accumulate a range of flavonoid compounds, including anthocyanins (red), flavonols (pale yellow), and chalcones (bright yellow). Flavonoid regulation is poorly characterized in onion and in other plants belonging to the Asparagales, despite being a major plant order containing many important crop and ornamental species. R2R3-MYB transcription factors associated with the regulation of distinct branches of the flavonoid pathway were isolated from onion. These belonged to sub-groups (SGs) that commonly activate anthocyanin (SG6, MYB1) or flavonol (SG7, MYB29) production, or repress phenylpropanoid/flavonoid synthesis (SG4, MYB4, MYB5). MYB1 was demonstrated to be a positive regulator of anthocyanin biosynthesis by the induction of anthocyanin production in onion tissue when transiently overexpressed and by reduction of pigmentation when transiently repressed via RNAi. Furthermore, ectopic red pigmentation was observed in garlic ( Allium sativum L.) plants stably transformed with a construct for co-overexpression of MYB1 and a bHLH partner. MYB1 also was able to complement the acyanic petal phenotype of a defined R2R3-MYB anthocyanin mutant in Antirrhinum maju s of the asterid clade of eudicots. The availability of sequence information for flavonoid-related MYBs from onion enabled phylogenetic groupings to be determined across monocotyledonous and dicotyledonous species, including the identification of characteristic amino acid motifs. This analysis suggests that divergent evolution of the R2R3-MYB family has occurred between Poaceae/Orchidaceae and Allioideae species. The DNA sequences identified will be valuable for future analysis of classical flavonoid genetic loci in Allium crops and will assist the breeding of these important crop species.
Neutron scattering study on R2PdSi3 (R=Ho,Er,Tm) compounds
International Nuclear Information System (INIS)
Tang, Fei
2010-01-01
Previous studies on the family of inter-metallic rare-earth compounds R 2 PdSi 3 revealed multifaceted magnetic properties, for instance, spin-glass like behavior. Experimental observations include: Signs of a crystallographic superstructure, complicated magnetic structures both in zero field and in applied magnetic fields as well as a generic phase in applied fields for compounds in the series with the heavy rare-earths R=Gd, Tb, Dy, Ho, Er and Tm. This thesis expands the studies on the magnetic properties of R 2 PdSi 3 employing mainly neutron scattering on single crystals with the focus on the compounds with R=Ho, Er and Tm. A detailed analysis of the crystallographic superstructure using modulation wave approach and group theory is presented. The resulting structure implies the existence of two different rare-earth sites with reduced symmetry and an arrangement of the different sites according to sequences as determined by the superstructure. It is shown that the reduced symmetry of the rare-earth sites is explicitly observed in the energy spectra of inelastic neutron scattering. The results on the magnetic structures and excitations are shown and discussed in the framework of the superstructure model. Specifically the generic phase in applied fields is interpreted as a direct consequence of the crystallographic superstructure. It is rather unusual that a crystallographic superstructure is playing such a decisive, and through the field dependence also tunable role in determining the magnetic properties as observed in R 2 PdSi 3 . The mediating interactions between the crystallographic part and the magnetic part of the system are discussed. (orig.)
Linear regression and the normality assumption.
Schmidt, Amand F; Finan, Chris
2017-12-16
Researchers often perform arbitrary outcome transformations to fulfill the normality assumption of a linear regression model. This commentary explains and illustrates that in large data settings, such transformations are often unnecessary, and worse may bias model estimates. Linear regression assumptions are illustrated using simulated data and an empirical example on the relation between time since type 2 diabetes diagnosis and glycated hemoglobin levels. Simulation results were evaluated on coverage; i.e., the number of times the 95% confidence interval included the true slope coefficient. Although outcome transformations bias point estimates, violations of the normality assumption in linear regression analyses do not. The normality assumption is necessary to unbiasedly estimate standard errors, and hence confidence intervals and P-values. However, in large sample sizes (e.g., where the number of observations per variable is >10) violations of this normality assumption often do not noticeably impact results. Contrary to this, assumptions on, the parametric model, absence of extreme observations, homoscedasticity, and independency of the errors, remain influential even in large sample size settings. Given that modern healthcare research typically includes thousands of subjects focusing on the normality assumption is often unnecessary, does not guarantee valid results, and worse may bias estimates due to the practice of outcome transformations. Copyright © 2017 Elsevier Inc. All rights reserved.
Bayesian Inference of a Multivariate Regression Model
Directory of Open Access Journals (Sweden)
Marick S. Sinay
2014-01-01
Full Text Available We explore Bayesian inference of a multivariate linear regression model with use of a flexible prior for the covariance structure. The commonly adopted Bayesian setup involves the conjugate prior, multivariate normal distribution for the regression coefficients and inverse Wishart specification for the covariance matrix. Here we depart from this approach and propose a novel Bayesian estimator for the covariance. A multivariate normal prior for the unique elements of the matrix logarithm of the covariance matrix is considered. Such structure allows for a richer class of prior distributions for the covariance, with respect to strength of beliefs in prior location hyperparameters, as well as the added ability, to model potential correlation amongst the covariance structure. The posterior moments of all relevant parameters of interest are calculated based upon numerical results via a Markov chain Monte Carlo procedure. The Metropolis-Hastings-within-Gibbs algorithm is invoked to account for the construction of a proposal density that closely matches the shape of the target posterior distribution. As an application of the proposed technique, we investigate a multiple regression based upon the 1980 High School and Beyond Survey.
General regression and representation model for classification.
Directory of Open Access Journals (Sweden)
Jianjun Qian
Full Text Available Recently, the regularized coding-based classification methods (e.g. SRC and CRC show a great potential for pattern classification. However, most existing coding methods assume that the representation residuals are uncorrelated. In real-world applications, this assumption does not hold. In this paper, we take account of the correlations of the representation residuals and develop a general regression and representation model (GRR for classification. GRR not only has advantages of CRC, but also takes full use of the prior information (e.g. the correlations between representation residuals and representation coefficients and the specific information (weight matrix of image pixels to enhance the classification performance. GRR uses the generalized Tikhonov regularization and K Nearest Neighbors to learn the prior information from the training data. Meanwhile, the specific information is obtained by using an iterative algorithm to update the feature (or image pixel weights of the test sample. With the proposed model as a platform, we design two classifiers: basic general regression and representation classifier (B-GRR and robust general regression and representation classifier (R-GRR. The experimental results demonstrate the performance advantages of proposed methods over state-of-the-art algorithms.
Varying coefficients model with measurement error.
Li, Liang; Greene, Tom
2008-06-01
We propose a semiparametric partially varying coefficient model to study the relationship between serum creatinine concentration and the glomerular filtration rate (GFR) among kidney donors and patients with chronic kidney disease. A regression model is used to relate serum creatinine to GFR and demographic factors in which coefficient of GFR is expressed as a function of age to allow its effect to be age dependent. GFR measurements obtained from the clearance of a radioactively labeled isotope are assumed to be a surrogate for the true GFR, with the relationship between measured and true GFR expressed using an additive error model. We use locally corrected score equations to estimate parameters and coefficient functions, and propose an expected generalized cross-validation (EGCV) method to select the kernel bandwidth. The performance of the proposed methods, which avoid distributional assumptions on the true GFR and residuals, is investigated by simulation. Accounting for measurement error using the proposed model reduced apparent inconsistencies in the relationship between serum creatinine and GFR among different clinical data sets derived from kidney donor and chronic kidney disease source populations.
R2WinBUGS: A Package for Running WinBUGS from R
Directory of Open Access Journals (Sweden)
Sibylle Sturtz
2005-01-01
Full Text Available The R2WinBUGS package provides convenient functions to call WinBUGS from R. It automatically writes the data and scripts in a format readable by WinBUGS for processing in batch mode, which is possible since version 1.4. After the WinBUGS process has finished, it is possible either to read the resulting data into R by the package itself--which gives a compact graphical summary of inference and convergence diagnostics--or to use the facilities of the coda package for further analyses of the output. Examples are given to demonstrate the usage of this package.
Power measurement in the boiling capsules in R2 using delayed neutron detector
International Nuclear Information System (INIS)
Roennberg, G.
1979-03-01
LWR fuel testing is performed in the R2 reactor by irradiation in both loops and so-called boiling capsules. The loops have forced cooling, and the power can be measured calorimetrically by conventional instrumentation. The boiling capsules have convection cooling, and it has therefore been necessary to develop a special technique for power measurement, the delayed neutron detector (DND). The DND is a pneumatic rabbit system, which activates small uranium samples in the boiling capsules and counts the delayed neutrons for determination of the fission rate. This report describes the equipment used, the procedure of measurement, and the method of evaluation. (atuhor)
Recursion Formulae for Obtaining Surfaces with Constant Mean Curvature in R2,1
International Nuclear Information System (INIS)
Tian Yongbo; Nan Zhijie; Tian Chou
2007-01-01
Though the Baecklund transformation on time-like surfaces with constant mean curvature surfaces in R 2,1 has been obtained, it is not easy to obtain corresponding surfaces because the procedure of solving the related integrable system cannot be avoided when the Baecklund transformation is used. For sake of this, in this article, some special work is done to reform the Baecklund transformation to a recursion formula, by which we can construct time-like surfaces with constant mean curvature form known ones just by quadrature procedure.
Site-specific magnetic anisotropies in R2Fe14B systems
Yoshioka, T.; Tsuchiura, H.
2018-04-01
The local magnetic anisotropy of R ions in R2Fe14B (R = Dy, Ho) systems is studied based on a microscopic effective spin model constructed from the information obtained by using first-principles calculations. By taking into account up to 6-th order crystal electric field parameters, the model satisfactory describes the observed magnetization curves and the temperature dependence of anisotropy constants. We found that at low temperatures, the noncollinear structure appears in the Ho2Fe14B system reflecting the local magnetic anisotropy.
DEFF Research Database (Denmark)
Broendberg, Anders Krogh; Nielsen, Jens Cosedis; Bjerre, Jesper
2017-01-01
probands, 18 symptomatic and 10 asymptomatic relatives with a RyR2 mutation. Twenty (87%) probands and 10 (36%) relatives had severe presenting symptoms (sudden cardiac death (SCD), aborted SCD (ASCD) or syncope).As compared with symptomatic relatives, probands had lower age at onset of symptoms (16 years...... (IQR, 10-33) vs 43 years (IQR, 25-54), pnear-fatal events (ASCD, SCD) (16vs5, p... events in the majority of probands and also occurred in 36% of relatives identified through family screening. Probands were younger at disease onset and more prone to fatal or near-fatal events than relatives....
Degradation and stability of R2R manufactured polymer solar cells
DEFF Research Database (Denmark)
Norrman, Kion; Krebs, Frederik C
2009-01-01
Polymer solar cells have many advantages such as light weight, flexibility, environmental friendliness, low thermal budget, low cost and most notably very fast modes of production by printing techniques. Production experiments have shown that it is highly feasible with existing technology to mass...... produce polymer solar cells at a very low cost. We have employed state-of-the-art analytical techniques to address the challenging issues of degradation and stability of R2R manufactured devices. We have specifically studied the relative effect of oxygen and water on the operational devices in regard...
Rolling Deck to Repository (R2R): Linking and Integrating Data for Oceanographic Research
Arko, R. A.; Chandler, C. L.; Clark, P. D.; Shepherd, A.; Moore, C.
2012-12-01
The Rolling Deck to Repository (R2R) program is developing infrastructure to ensure the underway sensor data from NSF-supported oceanographic research vessels are routinely and consistently documented, preserved in long-term archives, and disseminated to the science community. We have published the entire R2R Catalog as a Linked Data collection, making it easily accessible to encourage linking and integration with data at other repositories. We are developing the R2R Linked Data collection with specific goals in mind: 1.) We facilitate data access and reuse by providing the richest possible collection of resources to describe vessels, cruises, instruments, and datasets from the U.S. academic fleet, including data quality assessment results and clean trackline navigation. We are leveraging or adopting existing community-standard concepts and vocabularies, particularly concepts from the Biological and Chemical Oceanography Data Management Office (BCO-DMO) ontology and terms from the pan-European SeaDataNet vocabularies, and continually re-publish resources as new concepts and terms are mapped. 2.) We facilitate data citation through the entire data lifecycle from field acquisition to shoreside archiving to (ultimately) global syntheses and journal articles. We are implementing globally unique and persistent identifiers at the collection, dataset, and granule levels, and encoding these citable identifiers directly into the Linked Data resources. 3.) We facilitate linking and integration with other repositories that publish Linked Data collections for the U.S. academic fleet, such as BCO-DMO and the Index to Marine and Lacustrine Geological Samples (IMLGS). We are initially mapping datasets at the resource level, and plan to eventually implement rule-based mapping at the concept level. We work collaboratively with partner repositories to develop best practices for URI patterns and consensus on shared vocabularies. The R2R Linked Data collection is implemented as a
Rolling Deck to Repository (R2R): Big Data and Standard Services for the Fleet Community
Arko, R. A.; Carbotte, S. M.; Chandler, C. L.; Smith, S. R.; Stocks, K. I.
2014-12-01
The Rolling Deck to Repository (R2R; http://rvdata.us/) program curates underway environmental sensor data from the U.S. academic oceanographic research fleet, ensuring data sets are routinely and consistently documented, preserved in long-term archives, and disseminated to the science community. Currently 25 in-service vessels contribute 7 terabytes of data to R2R each year, acquired from a full suite of geophysical, oceanographic, meteorological, and navigational sensors on over 400 cruises worldwide. To accommodate this large volume and variety of data, R2R has developed highly efficient stewardship procedures. These include scripted "break out" of cruise data packages from each vessel based on standard filename and directory patterns; automated harvest of cruise metadata from the UNOLS Office via Web Services and from OpenXML-based forms submitted by vessel operators; scripted quality assessment routines that calculate statistical summaries and standard ratings for selected data types; adoption of community-standard controlled vocabularies for vessel codes, instrument types, etc, provided by the NERC Vocabulary Server, in lieu of maintaining custom local term lists; and a standard package structure based on the IETF BagIt format for delivering data to long-term archives. Documentation and standard post-field products, including quality-controlled shiptrack navigation data for every cruise, are published in multiple services and formats to satisfy a diverse range of clients. These include Catalog Service for Web (CSW), GeoRSS, and OAI-PMH discovery services via a GeoNetwork portal; OGC Web Map and Feature Services for GIS clients; a citable Digital Object Identifier (DOI) for each dataset; ISO 19115-2 standard geospatial metadata records suitable for submission to long-term archives as well as the POGO global catalog; and Linked Open Data resources with a SPARQL query endpoint for Semantic Web clients. R2R participates in initiatives such as the Ocean Data
Application of random regression models to the genetic evaluation ...
African Journals Online (AJOL)
The model included fixed regression on AM (range from 30 to 138 mo) and the effect of herd-measurement date concatenation. Random parts of the model were RRM coefficients for additive and permanent environmental effects, while residual effects were modelled to account for heterogeneity of variance by AY. Estimates ...
Testing discontinuities in nonparametric regression
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
Testing discontinuities in nonparametric regression
Dai, Wenlin; Zhou, Yuejin; Tong, Tiejun
2017-01-01
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
Logistic Regression: Concept and Application
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…
Sabine absorption coefficients to random incidence absorption coefficients
DEFF Research Database (Denmark)
Jeong, Cheol-Ho
2014-01-01
into random incidence absorption coefficients for porous absorbers are investigated. Two optimization-based conversion methods are suggested: the surface impedance estimation for locally reacting absorbers and the flow resistivity estimation for extendedly reacting absorbers. The suggested conversion methods...
Background stratified Poisson regression analysis of cohort data.
Richardson, David B; Langholz, Bryan
2012-03-01
Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models.
Background stratified Poisson regression analysis of cohort data
International Nuclear Information System (INIS)
Richardson, David B.; Langholz, Bryan
2012-01-01
Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models. (orig.)
Fungible weights in logistic regression.
Jones, Jeff A; Waller, Niels G
2016-06-01
In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
International Nuclear Information System (INIS)
Leng Ling; Zhang Tianyi; Kleinman, Lawrence; Zhu Wei
2007-01-01
Regression analysis, especially the ordinary least squares method which assumes that errors are confined to the dependent variable, has seen a fair share of its applications in aerosol science. The ordinary least squares approach, however, could be problematic due to the fact that atmospheric data often does not lend itself to calling one variable independent and the other dependent. Errors often exist for both measurements. In this work, we examine two regression approaches available to accommodate this situation. They are orthogonal regression and geometric mean regression. Comparisons are made theoretically as well as numerically through an aerosol study examining whether the ratio of organic aerosol to CO would change with age
2010-01-21
...] International Conference on Harmonisation; Guidance on M3(R2) Nonclinical Safety Studies for the Conduct of... the availability of a guidance entitled ``M3(R2) Nonclinical Safety Studies for the Conduct of Human... auspices of the International Conference on Harmonisation of Technical Requirements for Registration of...
Tumor regression patterns in retinoblastoma
International Nuclear Information System (INIS)
Zafar, S.N.; Siddique, S.N.; Zaheer, N.
2016-01-01
To observe the types of tumor regression after treatment, and identify the common pattern of regression in our patients. Study Design: Descriptive study. Place and Duration of Study: Department of Pediatric Ophthalmology and Strabismus, Al-Shifa Trust Eye Hospital, Rawalpindi, Pakistan, from October 2011 to October 2014. Methodology: Children with unilateral and bilateral retinoblastoma were included in the study. Patients were referred to Pakistan Institute of Medical Sciences, Islamabad, for chemotherapy. After every cycle of chemotherapy, dilated funds examination under anesthesia was performed to record response of the treatment. Regression patterns were recorded on RetCam II. Results: Seventy-four tumors were included in the study. Out of 74 tumors, 3 were ICRB group A tumors, 43 were ICRB group B tumors, 14 tumors belonged to ICRB group C, and remaining 14 were ICRB group D tumors. Type IV regression was seen in 39.1% (n=29) tumors, type II in 29.7% (n=22), type III in 25.6% (n=19), and type I in 5.4% (n=4). All group A tumors (100%) showed type IV regression. Seventeen (39.5%) group B tumors showed type IV regression. In group C, 5 tumors (35.7%) showed type II regression and 5 tumors (35.7%) showed type IV regression. In group D, 6 tumors (42.9%) regressed to type II non-calcified remnants. Conclusion: The response and success of the focal and systemic treatment, as judged by the appearance of different patterns of tumor regression, varies with the ICRB grouping of the tumor. (author)
Directory of Open Access Journals (Sweden)
Hossein Riahi Modvar
2008-09-01
Full Text Available Longitudinal dispersion coefficient in rivers and natural streams is usually estimated by simple inaccurate empirical relations because of the complexity of the phenomenon. In this study, the adaptive neuro-fuzzy inference system (ANFIS is used to develop a new flexible tool for predicting the longitudinal dispersion coefficient. The system has the ability to understand and realize the phenomenon without the need for mathematical governing equations.. The training and testing of this new model are accomplished using a set of available published filed data. Several statistical and graphical criteria are used to check the accuracy of the model. The dispersion coefficient values predicted by the ANFIS model compares satisfactorily with the measured data. The predicted values are also compared with those predicted by existing empirical equations reported in the literature to find that the ANFIS model with R2=0.99 and RMSE=15.18 in training stage and R2=0.91 and RMSE=187.8 in testing stage is superior in predicting the dispersion coefficient to the most accurate empirical equation with R2=0.48 and RMSE=295.7. The proposed methodology is a new approach to estimating dispersion coefficient in streams and can be combined with mathematical models of pollutant transfer or real-time updating of these models.
Nishidate, Izumi; Wiswadarma, Aditya; Hase, Yota; Tanaka, Noriyuki; Maeda, Takaaki; Niizeki, Kyuichi; Aizu, Yoshihisa
2011-08-01
In order to visualize melanin and blood concentrations and oxygen saturation in human skin tissue, a simple imaging technique based on multispectral diffuse reflectance images acquired at six wavelengths (500, 520, 540, 560, 580 and 600nm) was developed. The technique utilizes multiple regression analysis aided by Monte Carlo simulation for diffuse reflectance spectra. Using the absorbance spectrum as a response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as predictor variables, multiple regression analysis provides regression coefficients. Concentrations of melanin and total blood are then determined from the regression coefficients using conversion vectors that are deduced numerically in advance, while oxygen saturation is obtained directly from the regression coefficients. Experiments with a tissue-like agar gel phantom validated the method. In vivo experiments with human skin of the human hand during upper limb occlusion and of the inner forearm exposed to UV irradiation demonstrated the ability of the method to evaluate physiological reactions of human skin tissue.
Probabilistic optimization of safety coefficients
International Nuclear Information System (INIS)
Marques, M.; Devictor, N.; Magistris, F. de
1999-01-01
This article describes a reliability-based method for the optimization of safety coefficients defined and used in design codes. The purpose of the optimization is to determine the partial safety coefficients which minimize an objective function for sets of components and loading situations covered by a design rule. This objective function is a sum of distances between the reliability of the components designed using the safety coefficients and a target reliability. The advantage of this method is shown on the examples of the reactor vessel, a vapour pipe and the safety injection circuit. (authors)
Design Concepts of Emergency Response Robot Platform K-R2D2
Energy Technology Data Exchange (ETDEWEB)
Noh, Sun Young; Jeong, Kyungmin [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2016-10-15
From the analysis for various mobile robots competed in DARPA Robotics Challenge, there are some drawbacks in using two or four legs because bipedal locomotion is not yet suitable for maintaining stability and quadrupedal locomotion is difficult to go through narrow aisles. Motivated by the above observations, we propose a K-R2D2 robot platform with three legs arranged in the form of a triangle like as R2-D2 robot which is a fictional robot character in the Star Wars movies. This robot has 3 legs with tracks in each sole of the leg. It is statically stable since there are three contact points to ground. In addition, three legs are also possible to design a structure walking stairs that can expand and contract in the vertical direction. This paper has presented the conceptual design, it is developed on the purpose of quick response instead of emergent workers to the extreme conditions disasters. This robot is emergency response robot platform KR2D2 with three legs, which is statically stable to walk or wheel depending on the terrains and move quickly as possible as on uneven terrain or stairs.
Shadow corrosion testing in the INCA facility in the Studsvik R2 reactor
International Nuclear Information System (INIS)
Nystrand, A.C.; Lassing, A.
1999-01-01
Shadow corrosion is a phenomenon which occurs when zirconium alloys are in contact with or in proximity to other metallic objects in a boiling water reactor environment (BWR, RBMK, SGHWR etc.). An enhanced corrosion occurs on the zirconium alloy with the appearance of a 'shadow' of the metallic object. The magnitude of the shadow corrosion can be significant, and is potentially limiting for the lifetime of certain zirconium alloy components in BWRs and other reactors with a similar water chemistry. In order to evaluate the suitability of the In-Core Autoclave (INCA) in the Studsvik R2 materials testing reactor as an experimental facility for studying shadow corrosion, a demonstration test has been performed. A number of test specimens consisting of Zircaloy-2 tubing in contact with Inconel were exposed in an oxidising water chemistry. Some of the specimens were placed within the reactor core and some above the core. The conclusion of this experiment after post irradiation examination is that it is possible to use the INCA facility in the Studsvik R2 reactor to develop a significant level of shadow corrosion after only 800 hours of irradiation. (author)
Design Concepts of Emergency Response Robot Platform K-R2D2
International Nuclear Information System (INIS)
Noh, Sun Young; Jeong, Kyungmin
2016-01-01
From the analysis for various mobile robots competed in DARPA Robotics Challenge, there are some drawbacks in using two or four legs because bipedal locomotion is not yet suitable for maintaining stability and quadrupedal locomotion is difficult to go through narrow aisles. Motivated by the above observations, we propose a K-R2D2 robot platform with three legs arranged in the form of a triangle like as R2-D2 robot which is a fictional robot character in the Star Wars movies. This robot has 3 legs with tracks in each sole of the leg. It is statically stable since there are three contact points to ground. In addition, three legs are also possible to design a structure walking stairs that can expand and contract in the vertical direction. This paper has presented the conceptual design, it is developed on the purpose of quick response instead of emergent workers to the extreme conditions disasters. This robot is emergency response robot platform KR2D2 with three legs, which is statically stable to walk or wheel depending on the terrains and move quickly as possible as on uneven terrain or stairs
Minimal $R+R^2$ Supergravity Models of Inflation Coupled to Matter
Ferrara, S
2014-01-01
The supersymmetric extension of "Starobinsky" $R+\\alpha R^2$ models of inflation is particularly simple in the "new minimal" formalism of supergravity, where the inflaton has no scalar superpartners. This paper is devoted to matter couplings in such supergravity models. We show how in the new minimal formalism matter coupling presents certain features absent in other formalisms. In particular, for the large class of matter couplings considered in this paper, matter must possess an R-symmetry, which is gauged by the vector field which becomes dynamical in the "new minimal" completion of the $R+\\alpha R^2$ theory. Thus, in the dual formulation of the theory, where the gauge vector is part of a massive vector multiplet, the inflaton is the superpartner of the massive vector of a nonlinearly realized R-symmetry. The F-term potential of this theory is of no-scale type, while the inflaton potential is given by the D-term of the gauged R-symmetry. The absolute minimum of the potential is always exactly supersymmetri...
Borodachev, S. M.
2016-06-01
The simple derivation of recursive least squares (RLS) method equations is given as special case of Kalman filter estimation of a constant system state under changing observation conditions. A numerical example illustrates application of RLS to multicollinearity problem.
Deriving proper uniform priors for regression coefficients, Parts I, II, and III
van Erp, H.R.N.; Linger, R.O.; van Gelder, P.H.A.J.M.
2017-01-01
It is a relatively well-known fact that in problems of Bayesian model selection, improper priors should, in general, be avoided. In this paper we will derive and discuss a collection of four proper uniform priors which lie on an ascending scale of informativeness. It will turn out that these
Regression to Causality : Regression-style presentation influences causal attribution
DEFF Research Database (Denmark)
Bordacconi, Mats Joe; Larsen, Martin Vinæs
2014-01-01
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...... 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...... more likely. Our experiment drew on a sample of 235 university students from three different social science degree programs (political science, sociology and economics), all of whom had received substantial training in statistics. The subjects were asked to compare and evaluate the validity...
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
Photon mass attenuation coefficients, effective atomic numbers and ...
Indian Academy of Sciences (India)
of atomic number Z was performed using the logarithmic regression analysis of the data measured by the authors and reported earlier. The best-fit coefficients so obtained in the photon ..... This photon build-up is a function of thickness and atomic number of the sample and also the incident photon energy, which combine to ...
On the misinterpretation of the correlation coefficient in pharmaceutical sciences
DEFF Research Database (Denmark)
Sonnergaard, Jørn
2006-01-01
The correlation coefficient is often used and more often misused as a universal parameter expressing the quality in linear regression analysis. The popularity of this dimensionless quantity is evident as it is easy to communicate and considered to be unproblematic to comprehend. However, illustra...
Distinct human and mouse membrane trafficking systems for sweet taste receptors T1r2 and T1r3.
Shimizu, Madoka; Goto, Masao; Kawai, Takayuki; Yamashita, Atsuko; Kusakabe, Yuko
2014-01-01
The sweet taste receptors T1r2 and T1r3 are included in the T1r taste receptor family that belongs to class C of the G protein-coupled receptors. Heterodimerization of T1r2 and T1r3 is required for the perception of sweet substances, but little is known about the mechanisms underlying this heterodimerization, including membrane trafficking. We developed tagged mouse T1r2 and T1r3, and human T1R2 and T1R3 and evaluated membrane trafficking in human embryonic kidney 293 (HEK293) cells. We found that human T1R3 surface expression was only observed when human T1R3 was coexpressed with human T1R2, whereas mouse T1r3 was expressed without mouse T1r2 expression. A domain-swapped chimera and truncated human T1R3 mutant showed that the Venus flytrap module and cysteine-rich domain (CRD) of human T1R3 contain a region related to the inhibition of human T1R3 membrane trafficking and coordinated regulation of human T1R3 membrane trafficking. We also found that the Venus flytrap module of both human T1R2 and T1R3 are needed for membrane trafficking, suggesting that the coexpression of human T1R2 and T1R3 is required for this event. These results suggest that the Venus flytrap module and CRD receive taste substances and play roles in membrane trafficking of human T1R2 and T1R3. These features are different from those of mouse receptors, indicating that human T1R2 and T1R3 are likely to have a novel membrane trafficking system.
Logic regression and its extensions.
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.
Quadrature formulas for Fourier coefficients
Bojanov, Borislav; Petrova, Guergana
2009-01-01
We consider quadrature formulas of high degree of precision for the computation of the Fourier coefficients in expansions of functions with respect to a system of orthogonal polynomials. In particular, we show the uniqueness of a multiple node
Diffusion coefficient for anomalous transport
International Nuclear Information System (INIS)
1986-01-01
A report on the progress towards the goal of estimating the diffusion coefficient for anomalous transport is given. The gyrokinetic theory is used to identify different time and length scale inherent to the characteristics of plasmas which exhibit anomalous transport
Global Land Use Regression Model for Nitrogen Dioxide Air Pollution.
Larkin, Andrew; Geddes, Jeffrey A; Martin, Randall V; Xiao, Qingyang; Liu, Yang; Marshall, Julian D; Brauer, Michael; Hystad, Perry
2017-06-20
Nitrogen dioxide is a common air pollutant with growing evidence of health impacts independent of other common pollutants such as ozone and particulate matter. However, the worldwide distribution of NO 2 exposure and associated impacts on health is still largely uncertain. To advance global exposure estimates we created a global nitrogen dioxide (NO 2 ) land use regression model for 2011 using annual measurements from 5,220 air monitors in 58 countries. The model captured 54% of global NO 2 variation, with a mean absolute error of 3.7 ppb. Regional performance varied from R 2 = 0.42 (Africa) to 0.67 (South America). Repeated 10% cross-validation using bootstrap sampling (n = 10,000) demonstrated a robust performance with respect to air monitor sampling in North America, Europe, and Asia (adjusted R 2 within 2%) but not for Africa and Oceania (adjusted R 2 within 11%) where NO 2 monitoring data are sparse. The final model included 10 variables that captured both between and within-city spatial gradients in NO 2 concentrations. Variable contributions differed between continental regions, but major roads within 100 m and satellite-derived NO 2 were consistently the strongest predictors. The resulting model can be used for global risk assessments and health studies, particularly in countries without existing NO 2 monitoring data or models.
Fuel Temperature Coefficient of Reactivity
Energy Technology Data Exchange (ETDEWEB)
Loewe, W.E.
2001-07-31
A method for measuring the fuel temperature coefficient of reactivity in a heterogeneous nuclear reactor is presented. The method, which is used during normal operation, requires that calibrated control rods be oscillated in a special way at a high reactor power level. The value of the fuel temperature coefficient of reactivity is found from the measured flux responses to these oscillations. Application of the method in a Savannah River reactor charged with natural uranium is discussed.
Properties of Traffic Risk Coefficient
Tang, Tie-Qiao; Huang, Hai-Jun; Shang, Hua-Yan; Xue, Yu
2009-10-01
We use the model with the consideration of the traffic interruption probability (Physica A 387(2008)6845) to study the relationship between the traffic risk coefficient and the traffic interruption probability. The analytical and numerical results show that the traffic interruption probability will reduce the traffic risk coefficient and that the reduction is related to the density, which shows that this model can improve traffic security.
Energy Technology Data Exchange (ETDEWEB)
Henninger, B.; Rauch, S.; Schocke, M.; Jaschke, W.; Kremser, C. [Medical University of Innsbruck, Department of Radiology, Innsbruck (Austria); Zoller, H. [Medical University of Innsbruck, Department of Internal Medicine, Innsbruck (Austria); Kannengiesser, S. [Siemens AG, Healthcare Sector, MR Applications Development, Erlangen (Germany); Zhong, X. [Siemens Healthcare, MR R and D Collaborations, Atlanta, GA (United States); Reiter, G. [Siemens AG, Healthcare Sector, MR R and D Collaborations, Graz (Austria)
2015-05-01
To evaluate the automated two-point Dixon screening sequence for the detection and estimated quantification of hepatic iron and fat compared with standard sequences as a reference. One hundred and two patients with suspected diffuse liver disease were included in this prospective study. The following MRI protocol was used: 3D-T1-weighted opposed- and in-phase gradient echo with two-point Dixon reconstruction and dual-ratio signal discrimination algorithm (''screening'' sequence); fat-saturated, multi-gradient-echo sequence with 12 echoes; gradient-echo T1 FLASH opposed- and in-phase. Bland-Altman plots were generated and correlation coefficients were calculated to compare the sequences. The screening sequence diagnosed fat in 33, iron in 35 and a combination of both in 4 patients. Correlation between R2* values of the screening sequence and the standard relaxometry was excellent (r = 0.988). A slightly lower correlation (r = 0.978) was found between the fat fraction of the screening sequence and the standard sequence. Bland-Altman revealed systematically lower R2* values obtained from the screening sequence and higher fat fraction values obtained with the standard sequence with a rather high variability in agreement. The screening sequence is a promising method with fast diagnosis of the predominant liver disease. It is capable of estimating the amount of hepatic fat and iron comparable to standard methods. (orig.)
International Nuclear Information System (INIS)
Henninger, B.; Rauch, S.; Schocke, M.; Jaschke, W.; Kremser, C.; Zoller, H.; Kannengiesser, S.; Zhong, X.; Reiter, G.
2015-01-01
To evaluate the automated two-point Dixon screening sequence for the detection and estimated quantification of hepatic iron and fat compared with standard sequences as a reference. One hundred and two patients with suspected diffuse liver disease were included in this prospective study. The following MRI protocol was used: 3D-T1-weighted opposed- and in-phase gradient echo with two-point Dixon reconstruction and dual-ratio signal discrimination algorithm (''screening'' sequence); fat-saturated, multi-gradient-echo sequence with 12 echoes; gradient-echo T1 FLASH opposed- and in-phase. Bland-Altman plots were generated and correlation coefficients were calculated to compare the sequences. The screening sequence diagnosed fat in 33, iron in 35 and a combination of both in 4 patients. Correlation between R2* values of the screening sequence and the standard relaxometry was excellent (r = 0.988). A slightly lower correlation (r = 0.978) was found between the fat fraction of the screening sequence and the standard sequence. Bland-Altman revealed systematically lower R2* values obtained from the screening sequence and higher fat fraction values obtained with the standard sequence with a rather high variability in agreement. The screening sequence is a promising method with fast diagnosis of the predominant liver disease. It is capable of estimating the amount of hepatic fat and iron comparable to standard methods. (orig.)
Wu, Chih-Da; Chen, Yu-Cheng; Pan, Wen-Chi; Zeng, Yu-Ting; Chen, Mu-Jean; Guo, Yue Leon; Lung, Shih-Chun Candice
2017-05-01
This study utilized a long-term satellite-based vegetation index, and considered culture-specific emission sources (temples and Chinese restaurants) with Land-use Regression (LUR) modelling to estimate the spatial-temporal variability of PM 2.5 using data from Taipei metropolis, which exhibits typical Asian city characteristics. Annual average PM 2.5 concentrations from 2006 to 2012 of 17 air quality monitoring stations established by Environmental Protection Administration of Taiwan were used for model development. PM 2.5 measurements from 2013 were used for external data verification. Monthly Normalized Difference Vegetation Index (NDVI) images coupled with buffer analysis were used to assess the spatial-temporal variations of greenness surrounding the monitoring sites. The distribution of temples and Chinese restaurants were included to represent the emission contributions from incense and joss money burning, and gas cooking, respectively. Spearman correlation coefficient and stepwise regression were used for LUR model development, and 10-fold cross-validation and external data verification were applied to verify the model reliability. The results showed a strongly negative correlation (r: -0.71 to -0.77) between NDVI and PM 2.5 while temples (r: 0.52 to 0.66) and Chinese restaurants (r: 0.31 to 0.44) were positively correlated to PM 2.5 concentrations. With the adjusted model R 2 of 0.89, a cross-validated adj-R 2 of 0.90, and external validated R 2 of 0.83, the high explanatory power of the resultant model was confirmed. Moreover, the averaged NDVI within a 1750 m circular buffer (p < 0.01), the number of Chinese restaurants within a 1750 m buffer (p < 0.01), and the number of temples within a 750 m buffer (p = 0.06) were selected as important predictors during the stepwise selection procedures. According to the partial R 2 , NDVI explained 66% of PM 2.5 variation and was the dominant variable in the developed model. We suggest future studies
Facilitating Semantic Interoperability Among Ocean Data Systems: ODIP-R2R Student Outcomes
Stocks, K. I.; Chen, Y.; Shepherd, A.; Chandler, C. L.; Dockery, N.; Elya, J. L.; Smith, S. R.; Ferreira, R.; Fu, L.; Arko, R. A.
2014-12-01
With informatics providing an increasingly important set of tools for geoscientists, it is critical to train the next generation of scientists in information and data techniques. The NSF-supported Rolling Deck to Repository (R2R) Program works with the academic fleet community to routinely document, assess, and preserve the underway sensor data from U.S. research vessels. The Ocean Data Interoperability Platform (ODIP) is an EU-US-Australian collaboration fostering interoperability among regional e-infrastructures through workshops and joint prototype development. The need to align terminology between systems is a common challenge across all of the ODIP prototypes. Five R2R students were supported to address aspects of semantic interoperability within ODIP. Developing a vocabulary matching service that links terms from different vocabularies with similar concept. The service implements Google Refine reconciliation service interface such that users can leverage Google Refine application as a friendly user interface while linking different vocabulary terms. Developing Resource Description Framework (RDF) resources that map Shipboard Automated Meteorological Oceanographic System (SAMOS) vocabularies to internationally served vocabularies. Each SAMOS vocabulary term (data parameter and quality control flag) will be described as an RDF resource page. These RDF resources allow for enhanced discoverability and retrieval of SAMOS data by enabling data searches based on parameter. Improving data retrieval and interoperability by exposing data and mapped vocabularies using Semantic Web technologies. We have collaborated with ODIP participating organizations in order to build a generalized data model that will be used to populate a SPARQL endpoint in order to provide expressive querying over our data files. Mapping local and regional vocabularies used by R2R to those used by ODIP partners. This work is described more fully in a companion poster. Making published Linked Data
BANK FAILURE PREDICTION WITH LOGISTIC REGRESSION
Directory of Open Access Journals (Sweden)
Taha Zaghdoudi
2013-04-01
Full Text Available In recent years the economic and financial world is shaken by a wave of financial crisis and resulted in violent bank fairly huge losses. Several authors have focused on the study of the crises in order to develop an early warning model. It is in the same path that our work takes its inspiration. Indeed, we have tried to develop a predictive model of Tunisian bank failures with the contribution of the binary logistic regression method. The specificity of our prediction model is that it takes into account microeconomic indicators of bank failures. The results obtained using our provisional model show that a bank's ability to repay its debt, the coefficient of banking operations, bank profitability per employee and leverage financial ratio has a negative impact on the probability of failure.
Directory of Open Access Journals (Sweden)
Gülfen TUNA
2013-03-01
Full Text Available The aim of this study is to test the validity of Downside Capital Asset Pricing Model (D-CAPM on the ISE. At the same time, the explanatory power of CAPM's traditional beta and D-CAPM's downside beta on the changes in the average return values are examined comparatively. In this context, the monthly data for seventy three stocks that are continuously traded on the ISE for the period 1991-2009 is used. Regression analysis is applied in this study. The research results have shown that D-CAPM is valid on the ISE. In addition, it is obtained that the power of downside beta coefficient is higher than traditional beta coefficient on explaining the return changes. Therefore, it can be said that the downside beta is superior to traditional beta in the ISE for chosen period.
Abstract Expression Grammar Symbolic Regression
Korns, Michael F.
This chapter examines the use of Abstract Expression Grammars to perform the entire Symbolic Regression process without the use of Genetic Programming per se. The techniques explored produce a symbolic regression engine which has absolutely no bloat, which allows total user control of the search space and output formulas, which is faster, and more accurate than the engines produced in our previous papers using Genetic Programming. The genome is an all vector structure with four chromosomes plus additional epigenetic and constraint vectors, allowing total user control of the search space and the final output formulas. A combination of specialized compiler techniques, genetic algorithms, particle swarm, aged layered populations, plus discrete and continuous differential evolution are used to produce an improved symbolic regression sytem. Nine base test cases, from the literature, are used to test the improvement in speed and accuracy. The improved results indicate that these techniques move us a big step closer toward future industrial strength symbolic regression systems.
Quantile Regression With Measurement Error
Wei, Ying; Carroll, Raymond J.
2009-01-01
. 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
From Rasch scores to regression
DEFF Research Database (Denmark)
Christensen, Karl Bang
2006-01-01
Rasch models provide a framework for measurement and modelling latent variables. Having measured a latent variable in a population a comparison of groups will often be of interest. For this purpose the use of observed raw scores will often be inadequate because these lack interval scale propertie....... This paper compares two approaches to group comparison: linear regression models using estimated person locations as outcome variables and latent regression models based on the distribution of the score....
Testing Heteroscedasticity in Robust Regression
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2011-01-01
Roč. 1, č. 4 (2011), s. 25-28 ISSN 2045-3345 Grant - others:GA ČR(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust regression * heteroscedasticity * regression quantiles * diagnostics Subject RIV: BB - Applied Statistics , Operational Research http://www.researchjournals.co.uk/documents/Vol4/06%20Kalina.pdf
Regression methods for medical research
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
Forecasting with Dynamic Regression Models
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.
Clustering Coefficients for Correlation Networks.
Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu
2018-01-01
Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly
Clustering Coefficients for Correlation Networks
Directory of Open Access Journals (Sweden)
Naoki Masuda
2018-03-01
Full Text Available Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients
Clustering Coefficients for Correlation Networks
Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu
2018-01-01
Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly
CALCULATION OF COEFFICIENT OF SHARING OCTANOL-WATER OF ORGANIC COMPOUNDS USING MOLECULAR DESCRIPTORS
Directory of Open Access Journals (Sweden)
B. Souyei
2010-12-01
Full Text Available A quantitative structure-property relationship (QSPR study is carried out to develop correlations that relate the molecular structures of organic compounds to their Octanol- Water partition coefficients, Kow , using molecular descriptors. The correlations are simple in application with good accuracy, which provide an easy, direct and relatively accurate way to calculate Kow. Such calculation gives us a model that gives results in remarkable correlation with the descriptors of blocks fragments of the atom-centered and functional groups (R2 = 0.949, δ = 0477 (R2 = 0.926,δ = 0,548 respectively.
Converting Sabine absorption coefficients to random incidence absorption coefficients
DEFF Research Database (Denmark)
Jeong, Cheol-Ho
2013-01-01
are suggested: An optimization method for the surface impedances for locally reacting absorbers, the flow resistivity for extendedly reacting absorbers, and the flow resistance for fabrics. With four porous type absorbers, the conversion methods are validated. For absorbers backed by a rigid wall, the surface...... coefficients to random incidence absorption coefficients are proposed. The overestimations of the Sabine absorption coefficient are investigated theoretically based on Miki's model for porous absorbers backed by a rigid wall or an air cavity, resulting in conversion factors. Additionally, three optimizations...... impedance optimization produces the best results, while the flow resistivity optimization also yields reasonable results. The flow resistivity and flow resistance optimization for extendedly reacting absorbers are also found to be successful. However, the theoretical conversion factors based on Miki's model...
Experience with the RE fuel transition at the Studsvik R2 reactor
International Nuclear Information System (INIS)
Pazsit, I.; Saltvedt, K.
1991-01-01
Irradiation of 7 LEU fuel elements is underway in the Studsvik R2 reactor. Four of these have 490 g U-235, and three 320 g U-235 loading, and the enrichment is 19.7% for all of them. The irradiation of LEU fuel started in 1987. The heavier elements have burnup figures 67% (CERCA), 50% (B and W), 47% (NUKEM) and 19% (B and W). One of the lighter elements has reached a burnup of 65%. To support the whole-core conversion process, reactor physical calculations were performed to see if a one-step conversion is possible with a suitable fuel management strategy such that all HEU fuel is burned up. The calculations show that it is possible to perform such a conversion with fuel elements containing 400 g U-235. (orig.)
Power cycling and ramp test in R-2 and Mihama Unit 2 for MHI PWR fuels
International Nuclear Information System (INIS)
Baba, T.; Takahashi, T.; Kubo, H.; Fujiwara, Y.; Kondo, Y.
1983-01-01
Up to the present time, Mitsubishi has manufactured approximately 3000 fuel assemblies for Japanese PWRs, of which performance in reactors is satisfactory under base load operation. For the forthcoming load following age in Japan, expected in mid eighties, Mitsubishi is performing various R and D programs, so that load following operation can be smoothly introduced with current good performance maintained. R and D programs consist of two phases. One is the verification and demonstration of power ramping and cycling capability of the current design fuels, and the other is the development of remedy fuels with more operational margin. This paper describes the recent results obtained for the former phase, especially for the following two programs: (1) Power cycling and ramp test in R-2; (2) Power ramp demonstration (PRD) in Mihama Unit 2 (PRD-1). PIE works for power cycling and ramp test rods have been almost completed. The second PRD will be performed early in 1983
Micro-heterogeneities in R2O-RO-B2O3
International Nuclear Information System (INIS)
Kawazoe, H.; Kokumai, H.; Hosono, H.; Kanazawa, T.
1980-01-01
ESR of incorporated Cu 2+ was used in the detection of micro-inhomogeneity in xR 2 O x yMgO x (100-x-y)B 2 O 3 glasses. The inhomogeneous region determined by ESR was found to be far wider than that obtained by opalescence. It was concluded that in the glasses of x + y approx. 2+ tends to accelerate the simultaneous formation of boroxol and diborate groups and in the glasses of x + y approx. < 15, boroxol group and pyroborate ion. The conclusion was confirmed by laser Raman scattering. Molecular volume was measured over the whole glass-forming region to explore the correlation between the micro-structure and a macroscopic property of the glasses. It showed no marked change at the specified composition where micro-structure changed. (orig.)
pyres: a Python wrapper for electrical resistivity modeling with R2
Befus, Kevin M.
2018-04-01
A Python package, pyres, was written to handle common as well as specialized input and output tasks for the R2 electrical resistivity (ER) modeling program. Input steps including handling field data, creating quadrilateral or triangular meshes, and data filtering allow repeatable and flexible ER modeling within a programming environment. pyres includes non-trivial routines and functions for locating and constraining specific known or separately-parameterized regions in both quadrilateral and triangular meshes. Three basic examples of how to run forward and inverse models with pyres are provided. The importance of testing mesh convergence and model sensitivity are also addressed with higher-level examples that show how pyres can facilitate future research-grade ER analyses.
The essential role of AMPA receptor GluR2 subunit RNA editing in the normal and diseased brain
Directory of Open Access Journals (Sweden)
Amanda Lorraine Wright
2012-04-01
Full Text Available AMPA receptors are comprised of different combinations of GluR1-GluR4 (also known as GluA1-GluA4 and GluR-A to GluR-D subunits. The GluR2 subunit is subject to Q/R site RNA editing by the ADAR2 enzyme, which converts a codon for glutamine (Q, present in the GluR2 gene, to a codon for arginine (R found in the mRNA. AMPA receptors are calcium (Ca2+-permeable if they contain the unedited GluR2(Q subunit or if they lack the GluR2 subunit. While most AMPA receptors in the brain contain the edited GluR2(R subunit and are therefore Ca2+-impermeable, recent evidence suggests that Ca2+-permeable GluR2-lacking AMPA receptors are important in synaptic plasticity and learning. However, the presence of Ca2+-permeable AMPA receptors containing unedited GluR2 leads to excitotoxic cell loss. Recent studies have indicated that RNA editing of GluR2 is deregulated in diseases, such as amyotrophic lateral sclerosis (ALS, as well in acute neurodegenerative conditions, such as ischemia. More recently, studies have investigated the regulation of RNA editing and possible causes for its deregulation during disease. In this review, we will explore the role of GluR2 RNA editing in the healthy and diseased brain and outline new insights into the mechanisms that control this process.
EXPOSE-R2: The Astrobiological ESA Mission on Board of the International Space Station
Directory of Open Access Journals (Sweden)
Elke Rabbow
2017-08-01
Full Text Available On July 23, 2014, the Progress cargo spacecraft 56P was launched from Baikonur to the International Space Station (ISS, carrying EXPOSE-R2, the third ESA (European Space Agency EXPOSE facility, the second EXPOSE on the outside platform of the Russian Zvezda module, with four international astrobiological experiments into space. More than 600 biological samples of archaea, bacteria (as biofilms and in planktonic form, lichens, fungi, plant seeds, triops eggs, mosses and 150 samples of organic compounds were exposed to the harsh space environment and to parameters similar to those on the Mars surface. Radiation dosimeters distributed over the whole facility complemented the scientific payload. Three extravehicular activities later the chemical samples were returned to Earth on March 2, 2016, with Soyuz 44S, having spent 588 days in space. The biological samples arrived back later, on June 18, 2016, with 45S, after a total duration in space of 531 days. The exposure of the samples to Low Earth Orbit vacuum lasted for 531 days and was divided in two parts: protected against solar irradiation during the first 62 days, followed by exposure to solar radiation during the subsequent 469 days. In parallel to the space mission, a Mission Ground Reference (MGR experiment with a flight identical Hardware and a complete flight identical set of samples was performed at the premises of DLR (German Aerospace Center in Cologne by MUSC (Microgravity User Support Center, according to the mission data either downloaded from the ISS (temperature data, facility status, inner pressure status or provided by RedShift Design and Engineering BVBA, Belgium (calculated ultra violet radiation fluence data. In this paper, the EXPOSE-R2 facility, the experimental samples, mission parameters, environmental parameters, and the overall mission and MGR sequences are described, building the background for the research papers of the individual experiments, their analysis and results.
Oxaliplatin Alters Expression of T1R2 Receptor and Sensitivity to Sweet Taste in Rats.
Ohishi, Akihiro; Nishida, Kentaro; Yamanaka, Yuri; Miyata, Ai; Ikukawa, Akiko; Yabu, Miharu; Miyamoto, Karin; Bansho, Saho; Nagasawa, Kazuki
2016-01-01
As one of the adverse effects of oxaliplatin, a key agent in colon cancer chemotherapy, a taste disorder is a severe issue in a clinical situation because it decreases the quality of life of patients. However, there is little information on the mechanism underlying the oxaliplatin-induced taste disorder. Here, we examined the molecular and behavioral characteristics of the oxaliplatin-induced taste disorder in rats. Oxaliplatin (4-16 mg/kg) was administered to Sprague-Dawley (SD) rats intraperitoneally for 2 d. Expression levels of mRNA and protein of taste receptors in circumvallate papillae (CP) were measured by real-time quantitative polymerase chain reaction (PCR) and immunohistochemistry, respectively. Taste sensitivity was assessed by their behavioral change using a brief-access test. Morphological change of the taste buds in CP was evaluated by hematoxyline-eosin (HE) staining, and the number of taste cells in taste buds was counted by immunohistochemical analysis. Among taste receptors, the expression levels of mRNA and protein of T1R2, a sweet taste receptor subunit, were increased transiently in CP of oxaliplatin-administered rats on day 7. In a brief-access test, the lick ratio was decreased in oxaliplatin-administered rats on day 7 and the alteration was recovered to the control level on day 14. There was no detectable alteration in the morphology of taste buds, number of taste cells or plasma zinc level in oxaliplatin-administered rats. These results suggest that decreased sensitivity to sweet taste in oxaliplatin-administered rats is due, at least in part, to increased expression of T1R2, while these alterations are reversible.
Regression analysis of sparse asynchronous longitudinal data.
Cao, Hongyuan; Zeng, Donglin; Fine, Jason P
2015-09-01
We consider estimation of regression models for sparse asynchronous longitudinal observations, where time-dependent responses and covariates are observed intermittently within subjects. Unlike with synchronous data, where the response and covariates are observed at the same time point, with asynchronous data, the observation times are mismatched. Simple kernel-weighted estimating equations are proposed for generalized linear models with either time invariant or time-dependent coefficients under smoothness assumptions for the covariate processes which are similar to those for synchronous data. For models with either time invariant or time-dependent coefficients, the estimators are consistent and asymptotically normal but converge at slower rates than those achieved with synchronous data. Simulation studies evidence that the methods perform well with realistic sample sizes and may be superior to a naive application of methods for synchronous data based on an ad hoc last value carried forward approach. The practical utility of the methods is illustrated on data from a study on human immunodeficiency virus.
Power coefficient anomaly in JOYO
Energy Technology Data Exchange (ETDEWEB)
Yamamoto, H
1980-12-15
Operation of the JOYO experimental fast reactor with the MK-I core has been divided into two phases: (1) 50 MWt power ascension and operation; and (2) 75 MWt power ascension and operation. The 50 MWt power-up tests were conducted in August 1978. In these tests, the measured reactivity loss due to power increases from 15 MWt to 50 MWt was 0.28% ..delta.. K/K, and agreed well with the predicted value of 0.27% ..delta.. K/K. The 75 MWt power ascension tests were conducted in July-August 1979. In the process of the first power increase above 50 MWt to 65 MWt conducted on July 11, 1979, an anomalously large negative power coefficient was observed. The value was about twice the power coefficient values measured in the tests below 50 MW. In order to reproduce the anomaly, the reactor power was decreased and again increased up to the maximum power of 65 MWt. However, the large negative power coefficient was not observed at this time. In the succeeding power increase from 65 MWt to 75 MWt, a similar anomalous power coefficient was again observed. This anomaly disappeared in the subsequent power ascensions to 75 MWt, and the magnitude of the power coefficient gradually decreased with power cycles above the 50 MWt level.
An improved multiple linear regression and data analysis computer program package
Sidik, S. M.
1972-01-01
NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.
Logistic regression for dichotomized counts.
Preisser, John S; Das, Kalyan; Benecha, Habtamu; Stamm, John W
2016-12-01
Sometimes there is interest in a dichotomized outcome indicating whether a count variable is positive or zero. Under this scenario, the application of ordinary logistic regression may result in efficiency loss, which is quantifiable under an assumed model for the counts. In such situations, a shared-parameter hurdle model is investigated for more efficient estimation of regression parameters relating to overall effects of covariates on the dichotomous outcome, while handling count data with many zeroes. One model part provides a logistic regression containing marginal log odds ratio effects of primary interest, while an ancillary model part describes the mean count of a Poisson or negative binomial process in terms of nuisance regression parameters. Asymptotic efficiency of the logistic model parameter estimators of the two-part models is evaluated with respect to ordinary logistic regression. Simulations are used to assess the properties of the models with respect to power and Type I error, the latter investigated under both misspecified and correctly specified models. The methods are applied to data from a randomized clinical trial of three toothpaste formulations to prevent incident dental caries in a large population of Scottish schoolchildren. © The Author(s) 2014.
Semisupervised Clustering by Iterative Partition and Regression with Neuroscience Applications
Directory of Open Access Journals (Sweden)
Guoqi Qian
2016-01-01
Full Text Available Regression clustering is a mixture of unsupervised and supervised statistical learning and data mining method which is found in a wide range of applications including artificial intelligence and neuroscience. It performs unsupervised learning when it clusters the data according to their respective unobserved regression hyperplanes. The method also performs supervised learning when it fits regression hyperplanes to the corresponding data clusters. Applying regression clustering in practice requires means of determining the underlying number of clusters in the data, finding the cluster label of each data point, and estimating the regression coefficients of the model. In this paper, we review the estimation and selection issues in regression clustering with regard to the least squares and robust statistical methods. We also provide a model selection based technique to determine the number of regression clusters underlying the data. We further develop a computing procedure for regression clustering estimation and selection. Finally, simulation studies are presented for assessing the procedure, together with analyzing a real data set on RGB cell marking in neuroscience to illustrate and interpret the method.
Analysis of internal conversion coefficients
International Nuclear Information System (INIS)
Coursol, N.; Gorozhankin, V.M.; Yakushev, E.A.; Briancon, C.; Vylov, Ts.
2000-01-01
An extensive database has been assembled that contains the three most widely used sets of calculated internal conversion coefficients (ICC): [Hager R.S., Seltzer E.C., 1968. Internal conversion tables. K-, L-, M-shell Conversion coefficients for Z=30 to Z=103, Nucl. Data Tables A4, 1-237; Band I.M., Trzhaskovskaya M.B., 1978. Tables of gamma-ray internal conversion coefficients for the K-, L- and M-shells, 10≤Z≤104, Special Report of Leningrad Nuclear Physics Institute; Roesel F., Fries H.M., Alder K., Pauli H.C., 1978. Internal conversion coefficients for all atomic shells, At. Data Nucl. Data Tables 21, 91-289] and also includes new Dirac-Fock calculations [Band I.M. and Trzhaskovskaya M.B., 1993. Internal conversion coefficients for low-energy nuclear transitions, At. Data Nucl. Data Tables 55, 43-61]. This database is linked to a computer program to plot ICCs and their combinations (sums and ratios) as a function of Z and energy, as well as relative deviations of ICC or their combinations for any pair of tabulated data. Examples of these analyses are presented for the K-shell and total ICCs of the gamma-ray standards [Hansen H.H., 1985. Evaluation of K-shell and total internal conversion coefficients for some selected nuclear transitions, Eur. Appl. Res. Rept. Nucl. Sci. Tech. 11.6 (4) 777-816] and for the K-shell and total ICCs of high multipolarity transitions (total, K-, L-, M-shells of E3 and M3 and K-shell of M4). Experimental data sets are also compared with the theoretical values of these specific calculations
Algebraic polynomials with random coefficients
Directory of Open Access Journals (Sweden)
K. Farahmand
2002-01-01
Full Text Available This paper provides an asymptotic value for the mathematical expected number of points of inflections of a random polynomial of the form a0(ω+a1(ω(n11/2x+a2(ω(n21/2x2+…an(ω(nn1/2xn when n is large. The coefficients {aj(w}j=0n, w∈Ω are assumed to be a sequence of independent normally distributed random variables with means zero and variance one, each defined on a fixed probability space (A,Ω,Pr. A special case of dependent coefficients is also studied.
Producing The New Regressive Left
DEFF Research Database (Denmark)
Crone, Christine
members, this thesis investigates a growing political trend and ideological discourse in the Arab world that I have called The New Regressive Left. On the premise that a media outlet can function as a forum for ideology production, the thesis argues that an analysis of this material can help to trace...... the contexture of The New Regressive Left. If the first part of the thesis lays out the theoretical approach and draws the contextual framework, through an exploration of the surrounding Arab media-and ideoscapes, the second part is an analytical investigation of the discourse that permeates the programmes aired...... 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...
Evaluation of SAMe-TT2R2 Score on Predicting Success With Extended-Interval Warfarin Monitoring.
Hwang, Andrew Y; Carris, Nicholas W; Dietrich, Eric A; Gums, John G; Smith, Steven M
2018-06-01
In patients with stable international normalized ratios, 12-week extended-interval warfarin monitoring can be considered; however, predictors of success with this strategy are unknown. The previously validated SAMe-TT 2 R 2 score (considering sex, age, medical history, treatment, tobacco, and race) predicts anticoagulation control during standard follow-up (every 4 weeks), with lower scores associated with greater time in therapeutic range. To evaluate the ability of the SAMe-TT 2 R 2 score in predicting success with extended-interval warfarin follow-up in patients with previously stable warfarin doses. In this post hoc analysis of a single-arm feasibility study, baseline SAMe-TT 2 R 2 scores were calculated for patients with ≥1 extended-interval follow-up visit. The primary analysis assessed achieved weeks of extended-interval follow-up according to baseline SAMe-TT 2 R 2 scores. A total of 47 patients receiving chronic anticoagulation completed a median of 36 weeks of extended-interval follow-up. The median baseline SAMe-TT 2 R 2 score was 1 (range 0-5). Lower SAMe-TT 2 R 2 scores appeared to be associated with greater duration of extended-interval follow-up achieved, though the differences between scores were not statistically significant. No individual variable of the SAMe-TT 2 R 2 score was associated with achieved weeks of extended-interval follow-up. Analysis of additional patient factors found that longer duration (≥24 weeks) of prior stable treatment was significantly associated with greater weeks of extended-interval follow-up completed ( P = 0.04). Conclusion and Relevance: This pilot study provides limited evidence that the SAMe-TT 2 R 2 score predicts success with extended-interval warfarin follow-up but requires confirmation in a larger study. Further research is also necessary to establish additional predictors of successful extended-interval warfarin follow-up.
Research and analyze of physical health using multiple regression analysis
Directory of Open Access Journals (Sweden)
T. S. Kyi
2014-01-01
Full Text Available This paper represents the research which is trying to create a mathematical model of the "healthy people" using the method of regression analysis. The factors are the physical parameters of the person (such as heart rate, lung capacity, blood pressure, breath holding, weight height coefficient, flexibility of the spine, muscles of the shoulder belt, abdominal muscles, squatting, etc.., and the response variable is an indicator of physical working capacity. After performing multiple regression analysis, obtained useful multiple regression models that can predict the physical performance of boys the aged of fourteen to seventeen years. This paper represents the development of regression model for the sixteen year old boys and analyzed results.
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.
Regression filter for signal resolution
International Nuclear Information System (INIS)
Matthes, W.
1975-01-01
The problem considered is that of resolving a measured pulse height spectrum of a material mixture, e.g. gamma ray spectrum, Raman spectrum, into a weighed sum of the spectra of the individual constituents. The model on which the analytical formulation is based is described. The problem reduces to that of a multiple linear regression. A stepwise linear regression procedure was constructed. The efficiency of this method was then tested by transforming the procedure in a computer programme which was used to unfold test spectra obtained by mixing some spectra, from a library of arbitrary chosen spectra, and adding a noise component. (U.K.)
Nonparametric Mixture of Regression Models.
Huang, Mian; Li, Runze; Wang, Shaoli
2013-07-01
Motivated by an analysis of US house price index data, we propose nonparametric finite mixture of regression models. We study the identifiability issue of the proposed models, and develop an estimation procedure by employing kernel regression. We further systematically study the sampling properties of the proposed estimators, and establish their asymptotic normality. A modified EM algorithm is proposed to carry out the estimation procedure. We show that our algorithm preserves the ascent property of the EM algorithm in an asymptotic sense. Monte Carlo simulations are conducted to examine the finite sample performance of the proposed estimation procedure. An empirical analysis of the US house price index data is illustrated for the proposed methodology.
Directory of Open Access Journals (Sweden)
Hailun Wang
2017-01-01
Full Text Available Support vector regression algorithm is widely used in fault diagnosis of rolling bearing. A new model parameter selection method for support vector regression based on adaptive fusion of the mixed kernel function is proposed in this paper. We choose the mixed kernel function as the kernel function of support vector regression. The mixed kernel function of the fusion coefficients, kernel function parameters, and regression parameters are combined together as the parameters of the state vector. Thus, the model selection problem is transformed into a nonlinear system state estimation problem. We use a 5th-degree cubature Kalman filter to estimate the parameters. In this way, we realize the adaptive selection of mixed kernel function weighted coefficients and the kernel parameters, the regression parameters. Compared with a single kernel function, unscented Kalman filter (UKF support vector regression algorithms, and genetic algorithms, the decision regression function obtained by the proposed method has better generalization ability and higher prediction accuracy.
Prediction of the glyphosate sorption coefficient across two loamy agricultural fields
DEFF Research Database (Denmark)
Paradelo Pérez, Marcos; Norgaard, Trine; Moldrup, Per
2015-01-01
, suggesting that different properties control glyphosate sorption in different locations and at different scales of analysis. Better predictions were obtained for the best-four set for the field in Estrup (R2 = 0.87) and for both fields (R2 = 0.70), while the field in Silstrup showed a lower predictability (R......2 = 0.36). Possibly, the low predictability for the field in Silstrup originated from opposing gradients in clay and oxalate-extractable Fe across the field. Also, whereas a lower clay content in Estrup may be the limiting variable for glyphosate sorption, the field in Silstrup has a higher clay...... sorption coefficient, Kd, from easily measurable soil properties in two loamy, agricultural fields in Denmark: Estrup and Silstrup. Forty-five soil samples in Estrup and 65 in Silstrup were collected fromthe surface in a rectangular grid of 15 × 15-mfromeach field, and selected soil properties...
Irrational "Coefficients" in Renaissance Algebra.
Oaks, Jeffrey A
2017-06-01
Argument From the time of al-Khwārizmī in the ninth century to the beginning of the sixteenth century algebraists did not allow irrational numbers to serve as coefficients. To multiply by x, for instance, the result was expressed as the rhetorical equivalent of . The reason for this practice has to do with the premodern concept of a monomial. The coefficient, or "number," of a term was thought of as how many of that term are present, and not as the scalar multiple that we work with today. Then, in sixteenth-century Europe, a few algebraists began to allow for irrational coefficients in their notation. Christoff Rudolff (1525) was the first to admit them in special cases, and subsequently they appear more liberally in Cardano (1539), Scheubel (1550), Bombelli (1572), and others, though most algebraists continued to ban them. We survey this development by examining the texts that show irrational coefficients and those that argue against them. We show that the debate took place entirely in the conceptual context of premodern, "cossic" algebra, and persisted in the sixteenth century independent of the development of the new algebra of Viète, Decartes, and Fermat. This was a formal innovation violating prevailing concepts that we propose could only be introduced because of the growing autonomy of notation from rhetorical text.
Integer Solutions of Binomial Coefficients
Gilbertson, Nicholas J.
2016-01-01
A good formula is like a good story, rich in description, powerful in communication, and eye-opening to readers. The formula presented in this article for determining the coefficients of the binomial expansion of (x + y)n is one such "good read." The beauty of this formula is in its simplicity--both describing a quantitative situation…
Cactus: An Introduction to Regression
Hyde, Hartley
2008-01-01
When the author first used "VisiCalc," the author thought it a very useful tool when he had the formulas. But how could he design a spreadsheet if there was no known formula for the quantities he was trying to predict? A few months later, the author relates he learned to use multiple linear regression software and suddenly it all clicked into…
Regression Models for Repairable Systems
Czech Academy of Sciences Publication Activity Database
Novák, Petr
2015-01-01
Roč. 17, č. 4 (2015), s. 963-972 ISSN 1387-5841 Institutional support: RVO:67985556 Keywords : Reliability analysis * Repair models * Regression Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.782, year: 2015 http://library.utia.cas.cz/separaty/2015/SI/novak-0450902.pdf
Survival analysis II: Cox regression
Stel, Vianda S.; Dekker, Friedo W.; Tripepi, Giovanni; Zoccali, Carmine; Jager, Kitty J.
2011-01-01
In contrast to the Kaplan-Meier method, Cox proportional hazards regression can provide an effect estimate by quantifying the difference in survival between patient groups and can adjust for confounding effects of other variables. The purpose of this article is to explain the basic concepts of the
Kernel regression with functional response
Ferraty, Frédéric; Laksaci, Ali; Tadj, Amel; Vieu, Philippe
2011-01-01
We consider kernel regression estimate when both the response variable and the explanatory one are functional. The rates of uniform almost complete convergence are stated as function of the small ball probability of the predictor and as function of the entropy of the set on which uniformity is obtained.
Determining Sample Size for Accurate Estimation of the Squared Multiple Correlation Coefficient.
Algina, James; Olejnik, Stephen
2000-01-01
Discusses determining sample size for estimation of the squared multiple correlation coefficient and presents regression equations that permit determination of the sample size for estimating this parameter for up to 20 predictor variables. (SLD)
Simple and multiple linear regression: sample size considerations.
Hanley, James A
2016-11-01
The suggested "two subjects per variable" (2SPV) rule of thumb in the Austin and Steyerberg article is a chance to bring out some long-established and quite intuitive sample size considerations for both simple and multiple linear regression. This article distinguishes two of the major uses of regression models that imply very different sample size considerations, neither served well by the 2SPV rule. The first is etiological research, which contrasts mean Y levels at differing "exposure" (X) values and thus tends to focus on a single regression coefficient, possibly adjusted for confounders. The second research genre guides clinical practice. It addresses Y levels for individuals with different covariate patterns or "profiles." It focuses on the profile-specific (mean) Y levels themselves, estimating them via linear compounds of regression coefficients and covariates. By drawing on long-established closed-form variance formulae that lie beneath the standard errors in multiple regression, and by rearranging them for heuristic purposes, one arrives at quite intuitive sample size considerations for both research genres. Copyright Â© 2016 Elsevier Inc. All rights reserved.
An R2R3-MYB transcription factor regulates carotenoid pigmentation in Mimulus lewisii flowers.
Sagawa, Janelle M; Stanley, Lauren E; LaFountain, Amy M; Frank, Harry A; Liu, Chang; Yuan, Yao-Wu
2016-02-01
Carotenoids are yellow, orange, and red pigments that contribute to the beautiful colors and nutritive value of many flowers and fruits. The structural genes in the highly conserved carotenoid biosynthetic pathway have been well characterized in multiple plant systems, but little is known about the transcription factors that control the expression of these structural genes. By analyzing a chemically induced mutant of Mimulus lewisii through bulk segregant analysis and transgenic experiments, we have identified an R2R3-MYB, Reduced Carotenoid Pigmentation 1 (RCP1), as the first transcription factor that positively regulates carotenoid biosynthesis during flower development. Loss-of-function mutations in RCP1 lead to down-regulation of all carotenoid biosynthetic genes and reduced carotenoid content in M. lewisii flowers, a phenotype recapitulated by RNA interference in the wild-type background. Overexpression of this gene in the rcp1 mutant background restores carotenoid production and, unexpectedly, results in simultaneous decrease of anthocyanin production in some transgenic lines by down-regulating the expression of an activator of anthocyanin biosynthesis. Identification of transcriptional regulators of carotenoid biosynthesis provides the 'toolbox' genes for understanding the molecular basis of flower color diversification in nature and for potential enhancement of carotenoid production in crop plants via genetic engineering. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.
Irradiation of Superheater Test Fuel Elements in the Steam Loop of the R2 Reactor
Energy Technology Data Exchange (ETDEWEB)
Ravndal, F
1967-12-15
The design, fabrication, irradiation results, and post-irradiation examination for three superheater test fuel elements are described. During the spring of 1966 these clusters, each consisting of six fuel rods, were successfully exposed in the superheater loop No. 5 in the R2 reactor for a maximum of 24 days at a maximum outer cladding surface temperature of {approx} 650 deg C. During irradiation the linear heat rating of the rods was in the range 400-535 W/cm. The diameter of the UO{sub 2} pellets was 11.5 and 13.0 mm; the wall thickness of the 20/25 Nb and 20/35 cladding was in every case 0.4 mm. The diametrical gap between fuel and cladding was one of the main parameters and was chosen to be 0.05, 0.07 and 0.10 mm. These experiments, to be followed by one high cladding temperature irradiation ({approx} 750 deg C) and one long time irradiation ({approx} 6000 MWd/tU), were carried out to demonstrate the operational capability of short superheater test fuel rods at steady and transient operational environments for the Marviken superheater fuel elements and also to provide confirmation of design criteria for the same fuel elements.
Evaluation of results from an in-pile creep test in the Studsvik R2 reactor
Energy Technology Data Exchange (ETDEWEB)
Pettersson, Kjell [Entropy Materials, Stockholm (Sweden)
2002-01-01
An in-pile creep test with bowing of cladding tubes has been performed in a hot water loop in the Studsvik R2 reactor . One test was performed in the core and one outside the core. The out-of-pile sample showed some minor primary creep strain while the in-pile specimen deformed at a steady rate of 5x10{sup -7}/h . However, when the results were compared to a broader data base of Zircaloy in-pile creep it became clear that the creep deformation observed is a primary creep which occurs before the irradiation creep in Zircaloy reaches a constant steady state creep rate. This primary stage is interpreted as a consequence of the development of an irradiation induced microstructure in Zircaloy which does not reach a steady state until a dose of about 10{sup 21} n/cm{sup 2} . At this stage the steady state irradiation creep starts. From this interpretation it is concluded that it is quite feasible to use the test method on pre-irradiated material in which it can be expected that the steady state will be reached already after short irradiation times.
Excitation of chiral molecules and their hydrated by clusters by R2PI studies
International Nuclear Information System (INIS)
Satta, M.; Piccirillo, S.; Scuderia, D.; Paladini, A.; Della Vedova, L.; Filippi, A.; Speranza, M.; Giardini, A.
2002-01-01
Molecular clusters play a key role in the molecular scale explanation of macroscopic phenomena, being in between the isolated gas phase and the condensed phase. Thus, allowing to obtain information on intermolecular forces simply by studying the physicochemical properties of isolated clusters and to extend them macroscopic systems. A comprehensive study of the short-range forces operating in the molecular complexes between several chiral aromatic alcohols (M) and water (solv), through the application of mass resolved REMPI technique is reported. The experimental setup was composed by a supersonic molecular beam, two Nd-YAG pumped dye lasers and a time of flight mass spectrometer. The photoionization efficiency curves were obtained as follows: a) the first exciting laser (hv 1 ) was tuned on the S 1 0 transition of the species of interest; b) the laser intensity is lowered to about 1 % of the initial fluence to minimize the hv 1 absorption; c)a second laser (hv 2 ) is scanned through the cluster ionization and fragmentation threshold regions. The binding energy of the M-solv adduct was computed from the differences between its dissociative ionization threshold and the ionization threshold of bare M. The mass-resolved one colour R2PI excitation spectra of l-tetralol (THN R ), THN R -H 2 O, l i ndanol (I R ) and I R -H 2 O are given. (nevyjel)
Anomalous magnetoresistance in antiferromagnetic polycrystalline materials R2Ni3Si5 (R=rare earth)
International Nuclear Information System (INIS)
Mazumdar, C.; Nigam, A.K.; Nagarajan, R.; Gupta, L.C.; Chandra, G.; Padalia, B.D.; Godart, C.; Vijayaraghaven, R.
1997-01-01
Magnetoresistance (MR) studies on polycrystalline R 2 Ni 3 Si 5 , (R=Y, rare earth) which order antiferromagnetically at low temperatures, are reported here. MR of the Nd, Sm, and Tb members of the series exhibit positive giant magnetoresistance, largest among polycrystalline materials (85%, 75%, and 58% for Tb 2 Ni 3 Si 5 , Sm 2 Ni 3 Si 5 , and Nd 2 Ni 3 Si 5 , respectively, at 4.4 K in a field of 45 kG). These materials have, to the best of our knowledge, the largest positive GMR reported ever for any bulk polycrystalline compounds. The magnitude of MR does not correlate with the rare earth magnetic moments. We believe that the structure of these materials, which can be considered as a naturally occurring multilayer of wavy planes of rare earth atoms separated by Ni endash Si network, plays a role. The isothermal MR of other members of this series (R=Pr,Dy,Ho) exhibits a maximum and a minimum, below their respective T N close-quote s. We interpret these in terms of a metamagnetic transition and short-range ferromagnetic correlations. The short-range ferromagnetic correlations seem to be dominant in the temperature region just above T N . copyright 1997 American Institute of Physics
Assessing and Adapting Scientific Results for Space Weather Research to Operations (R2O)
Thompson, B. J.; Friedl, L.; Halford, A. J.; Mays, M. L.; Pulkkinen, A. A.; Singer, H. J.; Stehr, J. W.
2017-12-01
Why doesn't a solid scientific paper necessarily result in a tangible improvement in space weather capability? A well-known challenge in space weather forecasting is investing effort to turn the results of basic scientific research into operational knowledge. This process is commonly known as "Research to Operations," abbreviated R2O. There are several aspects of this process: 1) How relevant is the scientific result to a particular space weather process? 2) If fully utilized, how much will that result improve the reliability of the forecast for the associated process? 3) How much effort will this transition require? Is it already in a relatively usable form, or will it require a great deal of adaptation? 4) How much burden will be placed on forecasters? Is it "plug-and-play" or will it require effort to operate? 5) How can robust space weather forecasting identify challenges for new research? This presentation will cover several approaches that have potential utility in assessing scientific results for use in space weather research. The demonstration of utility is the first step, relating to the establishment of metrics to ensure that there will be a clear benefit to the end user. The presentation will then move to means of determining cost vs. benefit, (where cost involves the full effort required to transition the science to forecasting, and benefit concerns the improvement of forecast reliability), and conclude with a discussion of the role of end users and forecasters in driving further innovation via "O2R."
Tumor VEGF-R2 imaging with Tc-99m DTPA-dextran-DC101
International Nuclear Information System (INIS)
Kim, E. M.; Jeong, H. J.; Kim, S. L.; Jeong, S. J.; Lee, C. M.; Kim, D. W.; Lim, S. T.; Sohn, M. H.
2007-01-01
Vascular endothelial growth factor (VEGF) and its receptor (fetal liver kinase 1/kinase insert domain-containing receptor) play an important role in vascular permeability and tumor angiogenesis. Here, we investigated the Tc-99m DC101-dextran for VEGF-R2 imaging in tumor xenografted mice. DTPA conjugated amino-dextran was synthesized and then this was reacted with sulfo-LC-SPDP. Synthesis was identified by 1H-NMR. DTPA-dextran-SPDP was reacted with DC101. Binding affinity was checked by ELISA assay. Female athymic nude mice bearing B16F10 tumors were each injected via the tail vein with about 18.5 MBq of the Tc-99m DTPA-dextran-DC101, Tc-99m DTPA-DC101 and I-131 DC101. Biodistribution was performed at 1, 6, and 24h. DTPA-dextran-DC101 bind to FLK-1 in a dose-dependent manner. And this was blocked by significantly by free DC101. Labeling efficiency was approximately above 99% at 24 hr. Tc-99m DTPA-DC101 and I-131 DC101 showed rapid liver uptake, whereas Tc-99m DTPA-dextran-DC101 weak liver uptake and kidney elimination. In biodistribution results, Tc-99m DTPA-dextran-DC101 showed rapid renal clearance, and increased tumor uptake according to the time. Conjugation of antibody with dextran polymer is responsible for the decreased liver uptake and increased tumor uptake
Assessment of deforestation using regression; Hodnotenie odlesnenia s vyuzitim regresie
Energy Technology Data Exchange (ETDEWEB)
Juristova, J. [Univerzita Komenskeho, Prirodovedecka fakulta, Katedra kartografie, geoinformatiky a DPZ, 84215 Bratislava (Slovakia)
2013-04-16
This work is devoted to the evaluation of deforestation using regression methods through software Idrisi Taiga. Deforestation is evaluated by the method of logistic regression. The dependent variable has discrete values '0' and '1', indicating that the deforestation occurred or not. Independent variables have continuous values, expressing the distance from the edge of the deforested areas of forests from urban areas, the river and the road network. The results were also used in predicting the probability of deforestation in subsequent periods. The result is a map showing the output probability of deforestation for the periods 1990/2000 and 200/2006 in accordance with predetermined coefficients (values of independent variables). (authors)
A Predictive Logistic Regression Model of World Conflict Using Open Source Data
2015-03-26
No correlation between the error terms and the independent variables 9. Absence of perfect multicollinearity (Menard, 2001) When assumptions are...some of the variables before initial model building. Multicollinearity , or near-linear dependence among the variables will cause problems in the...model. High multicollinearity tends to produce unreasonably high logistic regression coefficients and can result in coefficients that are not
Rafiei, Hamid; Khanzadeh, Marziyeh; Mozaffari, Shahla; Bostanifar, Mohammad Hassan; Avval, Zhila Mohajeri; Aalizadeh, Reza; Pourbasheer, Eslam
2016-01-01
Quantitative structure-activity relationship (QSAR) study has been employed for predicting the inhibitory activities of the Hepatitis C virus (HCV) NS5B polymerase inhibitors . A data set consisted of 72 compounds was selected, and then different types of molecular descriptors were calculated. The whole data set was split into a training set (80 % of the dataset) and a test set (20 % of the dataset) using principle component analysis. The stepwise (SW) and the genetic algorithm (GA) techniques were used as variable selection tools. Multiple linear regression method was then used to linearly correlate the selected descriptors with inhibitory activities. Several validation technique including leave-one-out and leave-group-out cross-validation, Y-randomization method were used to evaluate the internal capability of the derived models. The external prediction ability of the derived models was further analyzed using modified r(2), concordance correlation coefficient values and Golbraikh and Tropsha acceptable model criteria's. Based on the derived results (GA-MLR), some new insights toward molecular structural requirements for obtaining better inhibitory activity were obtained.
Tang, J. L.; Cai, C. Z.; Xiao, T. T.; Huang, S. J.
2012-07-01
The electrical conductivity of solid oxide fuel cell (SOFC) cathode is one of the most important indices affecting the efficiency of SOFC. In order to improve the performance of fuel cell system, it is advantageous to have accurate model with which one can predict the electrical conductivity. In this paper, a model utilizing support vector regression (SVR) approach combined with particle swarm optimization (PSO) algorithm for its parameter optimization was established to modeling and predicting the electrical conductivity of Ba0.5Sr0.5Co0.8Fe0.2 O3-δ-xSm0.5Sr0.5CoO3-δ (BSCF-xSSC) composite cathode under two influence factors, including operating temperature (T) and SSC content (x) in BSCF-xSSC composite cathode. The leave-one-out cross validation (LOOCV) test result by SVR strongly supports that the generalization ability of SVR model is high enough. The absolute percentage error (APE) of 27 samples does not exceed 0.05%. The mean absolute percentage error (MAPE) of all 30 samples is only 0.09% and the correlation coefficient (R2) as high as 0.999. This investigation suggests that the hybrid PSO-SVR approach may be not only a promising and practical methodology to simulate the properties of fuel cell system, but also a powerful tool to be used for optimal designing or controlling the operating process of a SOFC system.
Directory of Open Access Journals (Sweden)
Andrea Luchetti
Full Text Available Retrotransposons of the R2 superclade specifically insert within the 28S ribosomal gene. They have been isolated from a variety of metazoan genomes and were found vertically inherited even if their phylogeny does not always agree with that of the host species. This was explained with the diversification/extinction of paralogous lineages, being proved the absence of horizontal transfer. We here analyze the widest available collection of R2 sequences, either newly isolated from recently sequenced genomes or drawn from public databases, in a phylogenetic framework. Results are congruent with previous analyses, but new important issues emerge. First, the N-terminal end of the R2-B clade protein, so far unknown, presents a new zinc fingers configuration. Second, the phylogenetic pattern is consistent with an ancient, rapid radiation of R2 lineages: being the estimated time of R2 origin (850-600 Million years ago placed just before the metazoan Cambrian explosion, the wide element diversity and the incongruence with the host phylogeny could be attributable to the sudden expansion of available niches represented by host's 28S ribosomal genes. Finally, we detect instances of coexisting multiple R2 lineages showing a non-random phylogenetic pattern, strongly similar to that of the "library" model known for tandem repeats: a collection of R2s were present in the ancestral genome and then differentially activated/repressed in the derived species. Models for activation/repression as well as mechanisms for sequence maintenance are also discussed within this framework.
Estimation of Electrically-Evoked Knee Torque from Mechanomyography Using Support Vector Regression
Directory of Open Access Journals (Sweden)
Morufu Olusola Ibitoye
2016-07-01
Full Text Available The difficulty of real-time muscle force or joint torque estimation during neuromuscular electrical stimulation (NMES in physical therapy and exercise science has motivated recent research interest in torque estimation from other muscle characteristics. This study investigated the accuracy of a computational intelligence technique for estimating NMES-evoked knee extension torque based on the Mechanomyographic signals (MMG of contracting muscles that were recorded from eight healthy males. Simulation of the knee torque was modelled via Support Vector Regression (SVR due to its good generalization ability in related fields. Inputs to the proposed model were MMG amplitude characteristics, the level of electrical stimulation or contraction intensity, and knee angle. Gaussian kernel function, as well as its optimal parameters were identified with the best performance measure and were applied as the SVR kernel function to build an effective knee torque estimation model. To train and test the model, the data were partitioned into training (70% and testing (30% subsets, respectively. The SVR estimation accuracy, based on the coefficient of determination (R2 between the actual and the estimated torque values was up to 94% and 89% during the training and testing cases, with root mean square errors (RMSE of 9.48 and 12.95, respectively. The knee torque estimations obtained using SVR modelling agreed well with the experimental data from an isokinetic dynamometer. These findings support the realization of a closed-loop NMES system for functional tasks using MMG as the feedback signal source and an SVR algorithm for joint torque estimation.
An eight-legged tactile sensor to estimate coefficient of static friction.
Wei Chen; Rodpongpun, Sura; Luo, William; Isaacson, Nathan; Kark, Lauren; Khamis, Heba; Redmond, Stephen J
2015-08-01
It is well known that a tangential force larger than the maximum static friction force is required to initiate the sliding motion between two objects, which is governed by a material constant called the coefficient of static friction. Therefore, knowing the coefficient of static friction is of great importance for robot grippers which wish to maintain a stable and precise grip on an object during various manipulation tasks. Importantly, it is most useful if grippers can estimate the coefficient of static friction without having to explicitly explore the object first, such as lifting the object and reducing the grip force until it slips. A novel eight-legged sensor, based on simplified theoretical principles of friction is presented here to estimate the coefficient of static friction between a planar surface and the prototype sensor. Each of the sensor's eight legs are straight and rigid, and oriented at a specified angle with respect to the vertical, allowing it to estimate one of five ranges (5 = 8/2 + 1) that the coefficient of static friction can occupy. The coefficient of friction can be estimated by determining whether the legs have slipped or not when pressed against a surface. The coefficients of static friction between the sensor and five different materials were estimated and compared to a measurement from traditional methods. A least-squares linear fit of the sensor estimated coefficient showed good correlation with the reference coefficient with a gradient close to one and an r(2) value greater than 0.9.
Quantile Regression With Measurement Error
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.
Alcantara, E.; Bernardo, N.
2016-12-01
Colored dissolved organic matter (CDOM) is the most abundant dissolved organic matter (DOM) in many natural waters and can affect the water quality, such as the light penetration and the thermal properties of water system. So the objective of this letter was to estimate the colored dissolved organic matter (CDOM) absorption coefficient at 440 nm, aCDOM(440), in Barra Bonita Reservoir (São Paulo State, Brazil) using OLI/Landsat-8 images. For this two field campaigns were conducted in May and October 2014. During the field campaigns remote sensing reflectance (Rrs) were measured using a TriOS hyperspectral radiometer. Water samples were collected and analyzed to obtain the aCDOM(440). To predict the aCDOM(440) from Rrs at two key wavelengths (650 and 480 nm) were regressed against laboratory derived aCDOM(440) values. The validation using in situ data of aCDOM(440) algorithm indicated a goodness of fit, R2 = 0.70, with a root-mean-square error (RMSE) of 10.65%. The developed algorithm was applied to the OLI/Lansat-8 images. Distribution maps were created with OLI/Landsat-8 images based on the adjusted algorithm.
Calibration factor or calibration coefficient?
International Nuclear Information System (INIS)
Meghzifene, A.; Shortt, K.R.
2002-01-01
Full text: The IAEA/WHO network of SSDLs was set up in order to establish links between SSDL members and the international measurement system. At the end of 2001, there were 73 network members in 63 Member States. The SSDL network members provide calibration services to end-users at the national or regional level. The results of the calibrations are summarized in a document called calibration report or calibration certificate. The IAEA has been using the term calibration certificate and will continue using the same terminology. The most important information in a calibration certificate is a list of calibration factors and their related uncertainties that apply to the calibrated instrument for the well-defined irradiation and ambient conditions. The IAEA has recently decided to change the term calibration factor to calibration coefficient, to be fully in line with ISO [ISO 31-0], which recommends the use of the term coefficient when it links two quantities A and B (equation 1) that have different dimensions. The term factor should only be used for k when it is used to link the terms A and B that have the same dimensions A=k.B. However, in a typical calibration, an ion chamber is calibrated in terms of a physical quantity such as air kerma, dose to water, ambient dose equivalent, etc. If the chamber is calibrated together with its electrometer, then the calibration refers to the physical quantity to be measured per electrometer unit reading. In this case, the terms referred have different dimensions. The adoption by the Agency of the term coefficient to express the results of calibrations is consistent with the 'International vocabulary of basic and general terms in metrology' prepared jointly by the BIPM, IEC, ISO, OIML and other organizations. The BIPM has changed from factor to coefficient. The authors believe that this is more than just a matter of semantics and recommend that the SSDL network members adopt this change in terminology. (author)
Extinction Coefficient of Gold Nanostars
de Puig, Helena; Tam, Justina O.; Yen, Chun-Wan; Gehrke, Lee; Hamad-Schifferli, Kimberly
2015-01-01
Gold nanostars (NStars) are highly attractive for biological applications due to their surface chemistry, facile synthesis and optical properties. Here, we synthesize NStars in HEPES buffer at different HEPES/Au ratios, producing NStars of different sizes and shapes, and therefore varying optical properties. We measure the extinction coefficient of the synthesized NStars at their maximum surface plasmon resonances (SPR), which range from 5.7 × 108 to 26.8 × 108 M−1cm−1. Measured values correl...
Directory of Open Access Journals (Sweden)
Elinalva M. Paulo
2012-06-01
Full Text Available The genus Leuconostoc belongs to a group of lactic acid bacteria usually isolated from fermented vegetables, which includes species involved in the production of exopolysaccharides (EPS. These biopolymers possess considerable commercial potential. Because of the wide variety of industrial applications of EPS, this study aimed to produce and characterize the native exopolysaccharide strain Leuconostoc pseudomesenteroides R2, which was isolated from cabbage collected in a semi-arid region of Bahia. We employed the following conditions for the production of EPS: 10.7% sucrose, pH 8.2, without agitation and incubation at 28ºC for 30 hours. The fermentation broth was treated with ethanol and generated two types of polysaccharide substances (EPS I and EPS II. The identification of EPS I and EPS II was conducted using FT-IR, ¹H, 13C and DEPT-135 NMR spectra. The two substances were identified as linear dextran α polysaccharides (1 → 6 which indicated different characteristics with respect to thermal analysis and density of free packaging, viscosity and time of solubilization. Both dextrans are of low density, possess high thermal stability and exhibited the behavior characteristic of pseudoplastic polymers.O gênero Leuconostoc pertence a um grupo de bactérias lácticas normalmente isoladas de vegetais fermentados, que inclui espécies envolvidas na produção de exopolissacarídeos (EPS. Esses biopolímeros possuem potencial comercial considerável. Devido à grande variedade de aplicações industriais, de EPS, o presente estudo teve como objetivo produzir e caracterizar o nativo exopolissacarídeo cepa Leuconostoc pseudomesenteroides R2, que foi isolado de repolho coletado em uma região semi-árida da Bahia. Utilizamos as seguintes condições para a produção de EPS: 10,7% de sacarose, pH 8,2, sem agitação e incubação a 28º C por 30 horas. O caldo fermentado foi tratado com etanol, gerando dois tipos de substâncias de polissacar
Multivariate and semiparametric kernel regression
Härdle, Wolfgang; Müller, Marlene
1997-01-01
The paper gives an introduction to theory and application of multivariate and semiparametric kernel smoothing. Multivariate nonparametric density estimation is an often used pilot tool for examining the structure of data. Regression smoothing helps in investigating the association between covariates and responses. We concentrate on kernel smoothing using local polynomial fitting which includes the Nadaraya-Watson estimator. Some theory on the asymptotic behavior and bandwidth selection is pro...
Regression algorithm for emotion detection
Berthelon , Franck; Sander , Peter
2013-01-01
International audience; We present here two components of a computational system for emotion detection. PEMs (Personalized Emotion Maps) store links between bodily expressions and emotion values, and are individually calibrated to capture each person's emotion profile. They are an implementation based on aspects of Scherer's theoretical complex system model of emotion~\\cite{scherer00, scherer09}. We also present a regression algorithm that determines a person's emotional feeling from sensor m...
Directional quantile regression in R
Czech Academy of Sciences Publication Activity Database
Boček, Pavel; Šiman, Miroslav
2017-01-01
Roč. 53, č. 3 (2017), s. 480-492 ISSN 0023-5954 R&D Projects: GA ČR GA14-07234S Institutional support: RVO:67985556 Keywords : multivariate quantile * regression quantile * halfspace depth * depth contour Subject RIV: BD - Theory of Information OBOR OECD: Applied mathematics Impact factor: 0.379, year: 2016 http://library.utia.cas.cz/separaty/2017/SI/bocek-0476587.pdf
Correlation, Regression, and Cointegration of Nonstationary Economic Time Series
DEFF Research Database (Denmark)
Johansen, Søren
), and Phillips (1986) found the limit distributions. We propose to distinguish between empirical and population correlation coefficients and show in a bivariate autoregressive model for nonstationary variables that the empirical correlation and regression coefficients do not converge to the relevant population...... values, due to the trending nature of the data. We conclude by giving a simple cointegration analysis of two interests. The analysis illustrates that much more insight can be gained about the dynamic behavior of the nonstationary variables then simply by calculating a correlation coefficient......Yule (1926) introduced the concept of spurious or nonsense correlation, and showed by simulation that for some nonstationary processes, that the empirical correlations seem not to converge in probability even if the processes were independent. This was later discussed by Granger and Newbold (1974...
Directory of Open Access Journals (Sweden)
Gholam Reza Sheykhzadeh
2017-02-01
replicates. The data were divided into two series as 78 data for training and 27 data for testing. The SPSS 18 with stepwise method and MATLAB software were used to derive the regression and artificial neural network, respectively. A feed forward three-layer (8, 11 and 15 neurons in the hidden layer perceptron network and the tangent sigmoid transfer function were used for the artificial neural network modeling. In estimating penetration resistance, The accuracy of artificial neural network and regression pedotransfer functions were evaluated by coefficient of determination (R2, root mean square error (RMSE, mean error (ME and Akaike information criterion (AIC statistics. Results and discussion: The textural classes of study soils were loamy sand (n= 8, sandy loam (n= 70, loam (n= 6 and silt loam (n= 21. The values of sand (26.26 to 87.43 %, clay (3.99 to 17.34 %, organic carbon (0.3 to 2.41 %, field moisture (4.56 to 33.18 mass percent, Db (1.02 to 1.63 g cm-3 and penetration resistance (1.1 to 6.6 MPa showed a large variations of study soils. There were found significant correlations between penetration resistance and sand (r= - 0.505**, silt (r= 0.447**, clay (r= 0.330**, organic carbon (r= - 0.465**, Db (r= 0.655**, θf (r= -0.63**, CaCO3 (r= 0.290**, total porosity (r= - 0.589** and Dp (r= 0.266*. Generally, 15 regression and artificial neural network pedotransfer functions were constructed to predict penetration resistance from measured readily available soil variables. The results of regression and artificial neural network pedotransfer functions showed that the most suitable variables to estimate penetration resistance were θf, Db and particles size distribution. The input variables were n and θf for the best regression pedotransfer function and also Db, silt, θf and σg for the best artificial neural network pedotransfer function. The values of R2, RMSE, ME and AIC were obtained equal to 0.55, 0.89 MPa, 0.05 MPa and -14.67 and 0.91, 0.37 MPa, - 0.0026 MPa and
Advanced colorectal neoplasia risk stratification by penalized logistic regression.
Lin, Yunzhi; Yu, Menggang; Wang, Sijian; Chappell, Richard; Imperiale, Thomas F
2016-08-01
Colorectal cancer is the second leading cause of death from cancer in the United States. To facilitate the efficiency of colorectal cancer screening, there is a need to stratify risk for colorectal cancer among the 90% of US residents who are considered "average risk." In this article, we investigate such risk stratification rules for advanced colorectal neoplasia (colorectal cancer and advanced, precancerous polyps). We use a recently completed large cohort study of subjects who underwent a first screening colonoscopy. Logistic regression models have been used in the literature to estimate the risk of advanced colorectal neoplasia based on quantifiable risk factors. However, logistic regression may be prone to overfitting and instability in variable selection. Since most of the risk factors in our study have several categories, it was tempting to collapse these categories into fewer risk groups. We propose a penalized logistic regression method that automatically and simultaneously selects variables, groups categories, and estimates their coefficients by penalizing the [Formula: see text]-norm of both the coefficients and their differences. Hence, it encourages sparsity in the categories, i.e. grouping of the categories, and sparsity in the variables, i.e. variable selection. We apply the penalized logistic regression method to our data. The important variables are selected, with close categories simultaneously grouped, by penalized regression models with and without the interactions terms. The models are validated with 10-fold cross-validation. The receiver operating characteristic curves of the penalized regression models dominate the receiver operating characteristic curve of naive logistic regressions, indicating a superior discriminative performance. © The Author(s) 2013.
Polylinear regression analysis in radiochemistry
International Nuclear Information System (INIS)
Kopyrin, A.A.; Terent'eva, T.N.; Khramov, N.N.
1995-01-01
A number of radiochemical problems have been formulated in the framework of polylinear regression analysis, which permits the use of conventional mathematical methods for their solution. The authors have considered features of the use of polylinear regression analysis for estimating the contributions of various sources to the atmospheric pollution, for studying irradiated nuclear fuel, for estimating concentrations from spectral data, for measuring neutron fields of a nuclear reactor, for estimating crystal lattice parameters from X-ray diffraction patterns, for interpreting data of X-ray fluorescence analysis, for estimating complex formation constants, and for analyzing results of radiometric measurements. The problem of estimating the target parameters can be incorrect at certain properties of the system under study. The authors showed the possibility of regularization by adding a fictitious set of data open-quotes obtainedclose quotes from the orthogonal design. To estimate only a part of the parameters under consideration, the authors used incomplete rank models. In this case, it is necessary to take into account the possibility of confounding estimates. An algorithm for evaluating the degree of confounding is presented which is realized using standard software or regression analysis
Weichenthal, Scott; Ryswyk, Keith Van; Goldstein, Alon; Bagg, Scott; Shekkarizfard, Maryam; Hatzopoulou, Marianne
2016-04-01
Existing evidence suggests that ambient ultrafine particles (UFPs) (regression model for UFPs in Montreal, Canada using mobile monitoring data collected from 414 road segments during the summer and winter months between 2011 and 2012. Two different approaches were examined for model development including standard multivariable linear regression and a machine learning approach (kernel-based regularized least squares (KRLS)) that learns the functional form of covariate impacts on ambient UFP concentrations from the data. The final models included parameters for population density, ambient temperature and wind speed, land use parameters (park space and open space), length of local roads and rail, and estimated annual average NOx emissions from traffic. The final multivariable linear regression model explained 62% of the spatial variation in ambient UFP concentrations whereas the KRLS model explained 79% of the variance. The KRLS model performed slightly better than the linear regression model when evaluated using an external dataset (R(2)=0.58 vs. 0.55) or a cross-validation procedure (R(2)=0.67 vs. 0.60). In general, our findings suggest that the KRLS approach may offer modest improvements in predictive performance compared to standard multivariable linear regression models used to estimate spatial variations in ambient UFPs. However, differences in predictive performance were not statistically significant when evaluated using the cross-validation procedure. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.
Rolling Deck to Repository (R2R): Products and Services for the U.S. Research Fleet Community
Arko, R. A.; Carbotte, S. M.; Chandler, C. L.; Smith, S. R.; Stocks, K. I.
2016-02-01
The Rolling Deck to Repository (R2R) program is working to ensure open access to environmental sensor data routinely acquired by the U.S. academic research fleet. Currently 25 vessels deliver 7 TB/year of data to R2R from a suite of geophysical, oceanographic, meteorological, and navigational sensors on over 400 cruises worldwide. R2R ensures these data are preserved in trusted repositories, discoverable via standard protocols, and adequately documented for reuse. R2R has recently expanded to include the vessels Sikuliaq, operated by the University of Alaska; Falkor, operated by the Schmidt Ocean Institute; and Ronald H. Brown and Okeanos Explorer, operated by NOAA. R2R maintains a master catalog of U.S. research cruises, currently holding over 4,670 expeditions including vessel and cruise identifiers, start/end dates and ports, project titles and funding awards, science parties, dataset inventories with instrument types and file formats, data quality assessments, and links to related content at other repositories. Standard post-field cruise products are published including shiptrack navigation, near-real-time MET/TSG data, underway geophysical profiles, and CTD profiles. Software tools available to users include the R2R Event Logger and the R2R Nav Manager. A Digital Object Identifier (DOI) is published for each cruise, original field sensor dataset, standard post-field product, and document (e.g. cruise report) submitted by the science party. Scientists are linked to personal identifiers such as ORCIDs where available. Using standard identifiers such as DOIs and ORCIDs facilitates linking with journal publications and generation of citation metrics. R2R collaborates in the Ocean Data Interoperability Platform (ODIP) to strengthen links among regional and national data systems, populates U.S. cruises in the POGO global catalog, and is working toward membership in the DataONE alliance. It is a lead partner in the EarthCube GeoLink project, developing Semantic Web
Earning on Response Coefficient in Automobile and Go Public Companies
Directory of Open Access Journals (Sweden)
Lisdawati Arifin
2017-09-01
Full Text Available This study aims to analyze factors that influence earnings response coefficients (ERC, simultaneously and partially, composed of leverage, the systematic risk (beta, growth opportunities (market to book value ratio, and the size of the firm (firm size, selection of the sample in this study the author take 12 automakers and components that meet the criteria of completeness of the data from the year 2008 to 2012, entirely based on consideration of the following criteria: (1 the company's automotive and components are listed on the stock exchange, (2 have the financial statements years 2008-2012 (3 has a return data (closing price the first day after the date of issuance of the financial statements. This study uses secondary data applying multiple linear regression models to analyze and test the effect of independent variables on the dependent variable partially (t-test, simultaneous (f-test, and the goodness of fit (R-square on a research model. The result shows that leverage, beta, growth opportunities (market to book value ratio and size along with (simultaneously the effect on the dependent variable (dependent variable earnings response coefficients. Partially leverage negatively affect earnings response coefficients, partially beta negatively correlated earnings response coefficients, partially growth opportunities (market to book value ratio significant effect on earnings response coefficients, partially sized companies (firm size significantly influence earnings response coefficients.
Gaussian Process Regression Model in Spatial Logistic Regression
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.
Yano, Kentaro; Mita, Suzune; Morimoto, Kaori; Haraguchi, Tamami; Arakawa, Hiroshi; Yoshida, Miyako; Yamashita, Fumiyoshi; Uchida, Takahiro; Ogihara, Takuo
2015-09-01
P-glycoprotein (P-gp) regulates absorption of many drugs in the gastrointestinal tract and their accumulation in tumor tissues, but the basis of substrate recognition by P-gp remains unclear. Bitter-tasting phenylthiocarbamide, which stimulates taste receptor 2 member 38 (T2R38), increases P-gp activity and is a substrate of P-gp. This led us to hypothesize that bitterness intensity might be a predictor of P-gp-inhibitor/substrate status. Here, we measured the bitterness intensity of a panel of P-gp substrates and nonsubstrates with various taste sensors, and used multiple linear regression analysis to examine the relationship between P-gp-inhibitor/substrate status and various physical properties, including intensity of bitter taste measured with the taste sensor. We calculated the first principal component analysis score (PC1) as the representative value of bitterness, as all taste sensor's outputs shared significant correlation. The P-gp substrates showed remarkably greater mean bitterness intensity than non-P-gp substrates. We found that Km value of P-gp substrates were correlated with molecular weight, log P, and PC1 value, and the coefficient of determination (R(2) ) of the linear regression equation was 0.63. This relationship might be useful as an aid to predict P-gp substrate status at an early stage of drug discovery. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.
Use of the p-SINE1-r2 in inferring evolutionary relationships of Thai rice varieties with AA genome
Directory of Open Access Journals (Sweden)
Preecha Prathepha
2006-01-01
Full Text Available In a previous study we described the prevalence and distribution in Thailand of the retroposon p- SINE1-r2, in the intron 10 of the waxy gene in cultivated and wild rice with the AA genome. In this study, additional varieties of rice were collected and sequencing was used to further characterize p-SINE1-r2. It was found that the length of the p-SINE1-r2 nucleotide sequences was about 125 bp, flanked by identical direct repeats of a 14 bp sequence. These sequences were compared and found to be similar to the sequences of p- SINE1-r2 found in Nipponbare, a rice strain discussed in a separate study. However, when compared the 48 DNA sequences identified in this study, much dissimilarity was found within the nucleotide sequences of p- SINE1-r2, in the form of base substitution mutations. Phylogenetic relationships inferred from the nucleotide sequences of these elements in cultivated rice (O. sativa and wild rice (O. nivara. It was found that rice accessions collected from the same geographical distribution have been placed in the same clade. The phylogenetic tree supports the origin and distribution of these rice strains.
He, Qiuling; Jones, Don C.; Li, Wei; Xie, Fuliang; Ma, Jun; Sun, Runrun; Wang, Qinglian; Zhu, Shuijin; Zhang, Baohong
2016-01-01
The R2R3-MYB is one of the largest families of transcription factors, which have been implicated in multiple biological processes. There is great diversity in the number of R2R3-MYB genes in different plants. However, there is no report on genome-wide characterization of this gene family in cotton. In the present study, a total of 205 putative R2R3-MYB genes were identified in cotton D genome (Gossypium raimondii), that are much larger than that found in other cash crops with fully sequenced genomes. These GrMYBs were classified into 13 groups with the R2R3-MYB genes from Arabidopsis and rice. The amino acid motifs and phylogenetic tree were predicted and analyzed. The sequences of GrMYBs were distributed across 13 chromosomes at various densities. The results showed that the expansion of the G. Raimondii R2R3-MYB family was mainly attributable to whole genome duplication and segmental duplication. Moreover, the expression pattern of 52 selected GrMYBs and 46 GaMYBs were tested in roots and leaves under different abiotic stress conditions. The results revealed that the MYB genes in cotton were differentially expressed under salt and drought stress treatment. Our results will be useful for determining the precise role of the MYB genes during stress responses with crop improvement. PMID:27009386
International Nuclear Information System (INIS)
Golubovskaya, Vita M.; Ho, Baotran; Conroy, Jeffrey; Liu, Song; Wang, Dan; Cance, William G.
2014-01-01
Focal Adhesion Kinase (FAK) is a non-receptor kinase that plays an important role in many cellular processes: adhesion, proliferation, invasion, angiogenesis, metastasis and survival. Recently, we have shown that Roslin 2 or R2 (1-benzyl-15,3,5,7-tetraazatricyclo[3.3.1.1~3,7~]decane) compound disrupts FAK and p53 proteins, activates p53 transcriptional activity, and blocks tumor growth. In this report we performed a microarray gene expression analysis of R2-treated HCT116 p53 +/+ and p53 −/− cells and detected 1484 genes that were significantly up- or down-regulated (p < 0.05) in HCT116 p53 +/+ cells but not in p53 −/− cells. Among up-regulated genes in HCT p53 +/+ cells we detected critical p53 targets: Mdm-2, Noxa-1, and RIP1. Among down-regulated genes, Met, PLK2, KIF14, BIRC2 and other genes were identified. In addition, a combination of R2 compound with M13 compound that disrupts FAK and Mmd-2 complex or R2 and Nutlin-1 that disrupts Mdm-2 and p53 decreased clonogenicity of HCT116 p53 +/+ colon cancer cells more significantly than each agent alone in a p53-dependent manner. Thus, the report detects gene expression profile in response to R2 treatment and demonstrates that the combination of drugs targeting FAK, Mdm-2, and p53 can be a novel therapy approach
Form of multicomponent Fickian diffusion coefficients matrix
International Nuclear Information System (INIS)
Wambui Mutoru, J.; Firoozabadi, Abbas
2011-01-01
Highlights: → Irreversible thermodynamics establishes form of multicomponent diffusion coefficients. → Phenomenological coefficients and thermodynamic factors affect sign of diffusion coefficients. → Negative diagonal elements of diffusion coefficients matrix can occur in non-ideal mixtures. → Eigenvalues of the matrix of Fickian diffusion coefficients may not be all real. - Abstract: The form of multicomponent Fickian diffusion coefficients matrix in thermodynamically stable mixtures is established based on the form of phenomenological coefficients and thermodynamic factors. While phenomenological coefficients form a symmetric positive definite matrix, the determinant of thermodynamic factors matrix is positive. As a result, the Fickian diffusion coefficients matrix has a positive determinant, but its elements - including diagonal elements - can be negative. Comprehensive survey of reported diffusion coefficients data for ternary and quaternary mixtures, confirms that invariably the determinant of the Fickian diffusion coefficients matrix is positive.
Sparse Reduced-Rank Regression for Simultaneous Dimension Reduction and Variable Selection
Chen, Lisha; Huang, Jianhua Z.
2012-01-01
and hence improves predictive accuracy. We propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty. We apply a group-lasso type penalty that treats each row of the matrix of the regression coefficients as a group