Regularized principal covariates regression and its application to finding coupled patterns in climate fields

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Fischer, M. J.

2014-02-01

There are many different methods for investigating the coupling between two climate fields, which are all based on the multivariate regression model. Each different method of solving the multivariate model has its own attractive characteristics, but often the suitability of a particular method for a particular problem is not clear. Continuum regression methods search the solution space between the conventional methods and thus can find regression model subspaces that mix the attractive characteristics of the end-member subspaces. Principal covariates regression is a continuum regression method that is easily applied to climate fields and makes use of two end-members: principal components regression and redundancy analysis. In this study, principal covariates regression is extended to additionally span a third end-member (partial least squares or maximum covariance analysis). The new method, regularized principal covariates regression, has several attractive features including the following: it easily applies to problems in which the response field has missing values or is temporally sparse, it explores a wide range of model spaces, and it seeks a model subspace that will, for a set number of components, have a predictive skill that is the same or better than conventional regression methods. The new method is illustrated by applying it to the problem of predicting the southern Australian winter rainfall anomaly field using the regional atmospheric pressure anomaly field. Regularized principal covariates regression identifies four major coupled patterns in these two fields. The two leading patterns, which explain over half the variance in the rainfall field, are related to the subtropical ridge and features of the zonally asymmetric circulation.

A method for the selection of a functional form for a thermodynamic equation of state using weighted linear least squares stepwise regression

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Jacobsen, R. T.; Stewart, R. B.; Crain, R. W., Jr.; Rose, G. L.; Myers, A. F.

1976-01-01

A method was developed for establishing a rational choice of the terms to be included in an equation of state with a large number of adjustable coefficients. The methods presented were developed for use in the determination of an equation of state for oxygen and nitrogen. However, a general application of the methods is possible in studies involving the determination of an optimum polynomial equation for fitting a large number of data points. The data considered in the least squares problem are experimental thermodynamic pressure-density-temperature data. Attention is given to a description of stepwise multiple regression and the use of stepwise regression in the determination of an equation of state for oxygen and nitrogen.

Selective principal component regression analysis of fluorescence hyperspectral image to assess aflatoxin contamination in corn

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Selective principal component regression analysis (SPCR) uses a subset of the original image bands for principal component transformation and regression. For optimal band selection before the transformation, this paper used genetic algorithms (GA). In this case, the GA process used the regression co...

Application of principal component regression and partial least squares regression in ultraviolet spectrum water quality detection

Science.gov (United States)

Li, Jiangtong; Luo, Yongdao; Dai, Honglin

2018-01-01

Water is the source of life and the essential foundation of all life. With the development of industrialization, the phenomenon of water pollution is becoming more and more frequent, which directly affects the survival and development of human. Water quality detection is one of the necessary measures to protect water resources. Ultraviolet (UV) spectral analysis is an important research method in the field of water quality detection, which partial least squares regression (PLSR) analysis method is becoming predominant technology, however, in some special cases, PLSR's analysis produce considerable errors. In order to solve this problem, the traditional principal component regression (PCR) analysis method was improved by using the principle of PLSR in this paper. The experimental results show that for some special experimental data set, improved PCR analysis method performance is better than PLSR. The PCR and PLSR is the focus of this paper. Firstly, the principal component analysis (PCA) is performed by MATLAB to reduce the dimensionality of the spectral data; on the basis of a large number of experiments, the optimized principal component is extracted by using the principle of PLSR, which carries most of the original data information. Secondly, the linear regression analysis of the principal component is carried out with statistic package for social science (SPSS), which the coefficients and relations of principal components can be obtained. Finally, calculating a same water spectral data set by PLSR and improved PCR, analyzing and comparing two results, improved PCR and PLSR is similar for most data, but improved PCR is better than PLSR for data near the detection limit. Both PLSR and improved PCR can be used in Ultraviolet spectral analysis of water, but for data near the detection limit, improved PCR's result better than PLSR.

Application of the step-wise regression procedure to the semi-empirical formulae of the nuclear binding energy

International Nuclear Information System (INIS)

Eissa, E.A.; Ayad, M.; Gashier, F.A.B.

1984-01-01

Most of the binding energy semi-empirical terms without the deformation corrections used by P.A. Seeger are arranged in a multiple linear regression form. The stepwise regression procedure with 95% confidence levels for acceptance and rejection of variables is applied for seeking a model for calculating binding energies of even-even (E-E) nuclei through a significance testing of each basic term. Partial F-values are taken as estimates for the significance of each term. The residual standard deviation and the overall F-value are used for selecting the best linear regression model. (E-E) nuclei are taken into sets lying between two successive proton and neutron magic numbers. The present work is in favour of the magic number 126 followed by 164 for the neutrons and indecisive in supporting the recently predicted proton magic number 114 rather than the previous one, 126. (author)

Multiple linear stepwise regression of liver lipid levels: proton MR spectroscopy study in vivo at 3.0 T

International Nuclear Information System (INIS)

Xu Li; Liang Changhong; Xiao Yuanqiu; Zhang Zhonglin

2010-01-01

Objective: To analyze the correlations between liver lipid level determined by liver 3.0 T 1 H-MRS in vivo and influencing factors using multiple linear stepwise regression. Methods: The prospective study of liver 1 H-MRS was performed with 3.0 T system and eight-channel torso phased-array coils using PRESS sequence. Forty-four volunteers were enrolled in this study. Liver spectra were collected with a TR of 1500 ms, TE of 30 ms, volume of interest of 2 cm×2 cm×2 cm, NSA of 64 times. The acquired raw proton MRS data were processed by using a software program SAGE. For each MRS measurement, using water as the internal reference, the amplitude of the lipid signal was normalized to the sum of the signal from lipid and water to obtain percentage lipid within the liver. The statistical description of height, weight, age and BMI, Line width and water suppression were recorded, and Pearson analysis was applied to test their relationships. Multiple linear stepwise regression was used to set the statistical model for the prediction of Liver lipid content. Results: Age (39.1±12.6) years, body weight (64.4±10.4) kg, BMI (23.3±3.1) kg/m 2 , linewidth (18.9±4.4) and the water suppression (90.7±6.5)% had significant correlation with liver lipid content (0.00 to 0.96%, median 0.02%), r were 0.11, 0.44, 0.40, 0.52, -0.73 respectively (P<0.05). But only age, BMI, line width, and the water suppression entered into the multiple linear regression equation. Liver lipid content prediction equation was as follows: Y= 1.395 - (0.021×water suppression) + (0.022×BMI) + (0.014×line width) - (0.004×age), and the coefficient of determination was 0. 613, corrected coefficient of determination was 0.59. Conclusion: The regression model fitted well, since the variables of age, BMI, width, and water suppression can explain about 60% of liver lipid content changes. (authors)

Retro-regression--another important multivariate regression improvement.

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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.

Stepwise versus Hierarchical Regression: Pros and Cons

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Lewis, Mitzi

2007-01-01

Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested…

Predicting Insolvency : A comparison between discriminant analysis and logistic regression using principal components

OpenAIRE

Geroukis, Asterios; Brorson, Erik

2014-01-01

In this study, we compare the two statistical techniques logistic regression and discriminant analysis to see how well they classify companies based on clusters – made from the solvency ratio ­– using principal components as independent variables. The principal components are made with different financial ratios. We use cluster analysis to find groups with low, medium and high solvency ratio of 1200 different companies found on the NASDAQ stock market and use this as an apriori definition of ...

QUANTITATIVE ELECTRONIC STRUCTURE - ACTIVITY RELATIONSHIP OF ANTIMALARIAL COMPOUND OF ARTEMISININ DERIVATIVES USING PRINCIPAL COMPONENT REGRESSION APPROACH

Directory of Open Access Journals (Sweden)

Paul Robert Martin Werfette

2010-06-01

Full Text Available Analysis of quantitative structure - activity relationship (QSAR for a series of antimalarial compound artemisinin derivatives has been done using principal component regression. The descriptors for QSAR study were representation of electronic structure i.e. atomic net charges of the artemisinin skeleton calculated by AM1 semi-empirical method. The antimalarial activity of the compound was expressed in log 1/IC50 which is an experimental data. The main purpose of the principal component analysis approach is to transform a large data set of atomic net charges to simplify into a data set which known as latent variables. The best QSAR equation to analyze of log 1/IC50 can be obtained from the regression method as a linear function of several latent variables i.e. x1, x2, x3, x4 and x5. The best QSAR model is expressed in the following equation,  (;;   Keywords: QSAR, antimalarial, artemisinin, principal component regression

Estimating leaf photosynthetic pigments information by stepwise multiple linear regression analysis and a leaf optical model

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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.

A stepwise model to predict monthly streamflow

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Mahmood Al-Juboori, Anas; Guven, Aytac

2016-12-01

In this study, a stepwise model empowered with genetic programming is developed to predict the monthly flows of Hurman River in Turkey and Diyalah and Lesser Zab Rivers in Iraq. The model divides the monthly flow data to twelve intervals representing the number of months in a year. The flow of a month, t is considered as a function of the antecedent month's flow (t - 1) and it is predicted by multiplying the antecedent monthly flow by a constant value called K. The optimum value of K is obtained by a stepwise procedure which employs Gene Expression Programming (GEP) and Nonlinear Generalized Reduced Gradient Optimization (NGRGO) as alternative to traditional nonlinear regression technique. The degree of determination and root mean squared error are used to evaluate the performance of the proposed models. The results of the proposed model are compared with the conventional Markovian and Auto Regressive Integrated Moving Average (ARIMA) models based on observed monthly flow data. The comparison results based on five different statistic measures show that the proposed stepwise model performed better than Markovian model and ARIMA model. The R2 values of the proposed model range between 0.81 and 0.92 for the three rivers in this study.

Principal Covariates Clusterwise Regression (PCCR): Accounting for Multicollinearity and Population Heterogeneity in Hierarchically Organized Data.

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Wilderjans, Tom Frans; Vande Gaer, Eva; Kiers, Henk A L; Van Mechelen, Iven; Ceulemans, Eva

2017-03-01

In the behavioral sciences, many research questions pertain to a regression problem in that one wants to predict a criterion on the basis of a number of predictors. Although in many cases, ordinary least squares regression will suffice, sometimes the prediction problem is more challenging, for three reasons: first, multiple highly collinear predictors can be available, making it difficult to grasp their mutual relations as well as their relations to the criterion. In that case, it may be very useful to reduce the predictors to a few summary variables, on which one regresses the criterion and which at the same time yields insight into the predictor structure. Second, the population under study may consist of a few unknown subgroups that are characterized by different regression models. Third, the obtained data are often hierarchically structured, with for instance, observations being nested into persons or participants within groups or countries. Although some methods have been developed that partially meet these challenges (i.e., principal covariates regression (PCovR), clusterwise regression (CR), and structural equation models), none of these methods adequately deals with all of them simultaneously. To fill this gap, we propose the principal covariates clusterwise regression (PCCR) method, which combines the key idea's behind PCovR (de Jong & Kiers in Chemom Intell Lab Syst 14(1-3):155-164, 1992) and CR (Späth in Computing 22(4):367-373, 1979). The PCCR method is validated by means of a simulation study and by applying it to cross-cultural data regarding satisfaction with life.

Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland.

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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.

The role of multicollinearity in landslide susceptibility assessment by means of Binary Logistic Regression: comparison between VIF and AIC stepwise selection

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Cama, Mariaelena; Cristi Nicu, Ionut; Conoscenti, Christian; Quénéhervé, Geraldine; Maerker, Michael

2016-04-01

Landslide susceptibility can be defined as the likelihood of a landslide occurring in a given area on the basis of local terrain conditions. In the last decades many research focused on its evaluation by means of stochastic approaches under the assumption that 'the past is the key to the future' which means that if a model is able to reproduce a known landslide spatial distribution, it will be able to predict the future locations of new (i.e. unknown) slope failures. Among the various stochastic approaches, Binary Logistic Regression (BLR) is one of the most used because it calculates the susceptibility in probabilistic terms and its results are easily interpretable from a geomorphological point of view. However, very often not much importance is given to multicollinearity assessment whose effect is that the coefficient estimates are unstable, with opposite sign and therefore difficult to interpret. Therefore, it should be evaluated every time in order to make a model whose results are geomorphologically correct. In this study the effects of multicollinearity in the predictive performance and robustness of landslide susceptibility models are analyzed. In particular, the multicollinearity is estimated by means of Variation Inflation Index (VIF) which is also used as selection criterion for the independent variables (VIF Stepwise Selection) and compared to the more commonly used AIC Stepwise Selection. The robustness of the results is evaluated through 100 replicates of the dataset. The study area selected to perform this analysis is the Moldavian Plateau where landslides are among the most frequent geomorphological processes. This area has an increasing trend of urbanization and a very high potential regarding the cultural heritage, being the place of discovery of the largest settlement belonging to the Cucuteni Culture from Eastern Europe (that led to the development of the great complex Cucuteni-Tripyllia). Therefore, identifying the areas susceptible to

Resource Loss and Depressive Symptoms Following Hurricane Katrina: A Principal Component Regression Study

OpenAIRE

Liang L; Hayashi K; Bennett P; Johnson T. J; Aten J. D

2015-01-01

To understand the relationship between the structure of resource loss and depression after disaster exposure, the components of resource loss and the impact of these resource loss components on depression was examined among college students (N=654) at two universities who were affected by Hurricane Katrina. The component of resource loss was analyzed by principal component analysis first. Gender, social relationship loss, and financial loss were then examined with the regression model on depr...

Retrieving relevant factors with exploratory SEM and principal-covariate regression: A comparison.

Science.gov (United States)

Vervloet, Marlies; Van den Noortgate, Wim; Ceulemans, Eva

2018-02-12

Behavioral researchers often linearly regress a criterion on multiple predictors, aiming to gain insight into the relations between the criterion and predictors. Obtaining this insight from the ordinary least squares (OLS) regression solution may be troublesome, because OLS regression weights show only the effect of a predictor on top of the effects of other predictors. Moreover, when the number of predictors grows larger, it becomes likely that the predictors will be highly collinear, which makes the regression weights' estimates unstable (i.e., the "bouncing beta" problem). Among other procedures, dimension-reduction-based methods have been proposed for dealing with these problems. These methods yield insight into the data by reducing the predictors to a smaller number of summarizing variables and regressing the criterion on these summarizing variables. Two promising methods are principal-covariate regression (PCovR) and exploratory structural equation modeling (ESEM). Both simultaneously optimize reduction and prediction, but they are based on different frameworks. The resulting solutions have not yet been compared; it is thus unclear what the strengths and weaknesses are of both methods. In this article, we focus on the extents to which PCovR and ESEM are able to extract the factors that truly underlie the predictor scores and can predict a single criterion. The results of two simulation studies showed that for a typical behavioral dataset, ESEM (using the BIC for model selection) in this regard is successful more often than PCovR. Yet, in 93% of the datasets PCovR performed equally well, and in the case of 48 predictors, 100 observations, and large differences in the strengths of the factors, PCovR even outperformed ESEM.

Combining multiple regression and principal component analysis for accurate predictions for column ozone in Peninsular Malaysia

Science.gov (United States)

Rajab, Jasim M.; MatJafri, M. Z.; Lim, H. S.

2013-06-01

This study encompasses columnar ozone modelling in the peninsular Malaysia. Data of eight atmospheric parameters [air surface temperature (AST), carbon monoxide (CO), methane (CH4), water vapour (H2Ovapour), skin surface temperature (SSKT), atmosphere temperature (AT), relative humidity (RH), and mean surface pressure (MSP)] data set, retrieved from NASA's Atmospheric Infrared Sounder (AIRS), for the entire period (2003-2008) was employed to develop models to predict the value of columnar ozone (O3) in study area. The combined method, which is based on using both multiple regressions combined with principal component analysis (PCA) modelling, was used to predict columnar ozone. This combined approach was utilized to improve the prediction accuracy of columnar ozone. Separate analysis was carried out for north east monsoon (NEM) and south west monsoon (SWM) seasons. The O3 was negatively correlated with CH4, H2Ovapour, RH, and MSP, whereas it was positively correlated with CO, AST, SSKT, and AT during both the NEM and SWM season periods. Multiple regression analysis was used to fit the columnar ozone data using the atmospheric parameter's variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to acquire subsets of the predictor variables to be comprised in the linear regression model of the atmospheric parameter's variables. It was found that the increase in columnar O3 value is associated with an increase in the values of AST, SSKT, AT, and CO and with a drop in the levels of CH4, H2Ovapour, RH, and MSP. The result of fitting the best models for the columnar O3 value using eight of the independent variables gave about the same values of the R (≈0.93) and R2 (≈0.86) for both the NEM and SWM seasons. The common variables that appeared in both regression equations were SSKT, CH4 and RH, and the principal precursor of the columnar O3 value in both the NEM and SWM seasons was SSKT.

Principal components and iterative regression analysis of geophysical series: Application to Sunspot number (1750 2004)

Science.gov (United States)

Nordemann, D. J. R.; Rigozo, N. R.; de Souza Echer, M. P.; Echer, E.

2008-11-01

We present here an implementation of a least squares iterative regression method applied to the sine functions embedded in the principal components extracted from geophysical time series. This method seems to represent a useful improvement for the non-stationary time series periodicity quantitative analysis. The principal components determination followed by the least squares iterative regression method was implemented in an algorithm written in the Scilab (2006) language. The main result of the method is to obtain the set of sine functions embedded in the series analyzed in decreasing order of significance, from the most important ones, likely to represent the physical processes involved in the generation of the series, to the less important ones that represent noise components. Taking into account the need of a deeper knowledge of the Sun's past history and its implication to global climate change, the method was applied to the Sunspot Number series (1750-2004). With the threshold and parameter values used here, the application of the method leads to a total of 441 explicit sine functions, among which 65 were considered as being significant and were used for a reconstruction that gave a normalized mean squared error of 0.146.

Information fusion via constrained principal component regression for robust quantification with incomplete calibrations

International Nuclear Information System (INIS)

Vogt, Frank

2013-01-01

Graphical abstract: Analysis Task: Determine the albumin (= protein) concentration in microalgae cells as a function of the cells’ nutrient availability. Left Panel: The predicted albumin concentrations as obtained by conventional principal component regression features low reproducibility and are partially higher than the concentrations of algae in which albumin is contained. Right Panel: Augmenting an incomplete PCR calibration with additional expert information derives reasonable albumin concentrations which now reveal a significant dependency on the algae's nutrient situation. -- Highlights: •Make quantitative analyses of compounds embedded in largely unknown chemical matrices robust. •Improved concentration prediction with originally insufficient calibration models. •Chemometric approach for incorporating expertise from other fields and/or researchers. •Ensure chemical, biological, or medicinal meaningfulness of quantitative analyses. -- Abstract: Incomplete calibrations are encountered in many applications and hamper chemometric data analyses. Such situations arise when target analytes are embedded in a chemically complex matrix from which calibration concentrations cannot be determined with reasonable efforts. In other cases, the samples’ chemical composition may fluctuate in an unpredictable way and thus cannot be comprehensively covered by calibration samples. The reason for calibration model to fail is the regression principle itself which seeks to explain measured data optimally in terms of the (potentially incomplete) calibration model but does not consider chemical meaningfulness. This study presents a novel chemometric approach which is based on experimentally feasible calibrations, i.e. concentration series of the target analytes outside the chemical matrix (‘ex situ calibration’). The inherent lack-of-information is then compensated by incorporating additional knowledge in form of regression constraints. Any outside knowledge can be

Boosted regression trees, multivariate adaptive regression splines and their two-step combinations with multiple linear regression or partial least squares to predict blood-brain barrier passage: a case study.

Science.gov (United States)

Deconinck, E; Zhang, M H; Petitet, F; Dubus, E; Ijjaali, I; Coomans, D; Vander Heyden, Y

2008-02-18

The use of some unconventional non-linear modeling techniques, i.e. classification and regression trees and multivariate adaptive regression splines-based methods, was explored to model the blood-brain barrier (BBB) passage of drugs and drug-like molecules. The data set contains BBB passage values for 299 structural and pharmacological diverse drugs, originating from a structured knowledge-based database. Models were built using boosted regression trees (BRT) and multivariate adaptive regression splines (MARS), as well as their respective combinations with stepwise multiple linear regression (MLR) and partial least squares (PLS) regression in two-step approaches. The best models were obtained using combinations of MARS with either stepwise MLR or PLS. It could be concluded that the use of combinations of a linear with a non-linear modeling technique results in some improved properties compared to the individual linear and non-linear models and that, when the use of such a combination is appropriate, combinations using MARS as non-linear technique should be preferred over those with BRT, due to some serious drawbacks of the BRT approaches.

A New Model for Birth Weight Prediction Using 2- and 3-Dimensional Ultrasonography by Principal Component Analysis: A Chinese Population Study.

Science.gov (United States)

Liao, Shuxin; Wang, Yunfang; Xiao, Shufang; Deng, Xujie; Fang, Bimei; Yang, Fang

2018-03-30

To establish a new model for birth weight prediction using 2- and 3-dimensional ultrasonography (US) by principal component analysis (PCA). Two- and 3-dimensional US was prospectively performed in women with normal singleton pregnancies within 7 days before delivery (37-41 weeks' gestation). The participants were divided into a development group (n = 600) and a validation group (n = 597). Principal component analysis and stepwise linear regression analysis were used to develop a new prediction model. The new model's accuracy in predicting fetal birth weight was confirmed by the validation group through comparisons with previously published formulas. A total of 1197 cases were recruited in this study. All interclass and intraclass correlation coefficients of US measurements were greater than 0.75. Two principal components (PCs) were considered primary in determining estimated fetal birth weight, which were derived from 9 US measurements. Stepwise linear regression analysis showed a positive association between birth weight and PC1 and PC2. In the development group, our model had a small mean percentage error (mean ± SD, 3.661% ± 3.161%). At least a 47.558% decrease in the mean percentage error and a 57.421% decrease in the standard deviation of the new model compared with previously published formulas were noted. The results were similar to those in the validation group, and the new model covered 100% of birth weights within 10% of actual birth weights. The birth weight prediction model based on 2- and 3-dimensional US by PCA could help improve the precision of estimated fetal birth weight. © 2018 by the American Institute of Ultrasound in Medicine.

A Simulation Investigation of Principal Component Regression.

Science.gov (United States)

Allen, David E.

Regression analysis is one of the more common analytic tools used by researchers. However, multicollinearity between the predictor variables can cause problems in using the results of regression analyses. Problems associated with multicollinearity include entanglement of relative influences of variables due to reduced precision of estimation,…

INDIA’S ELECTRICITY DEMAND FORECAST USING REGRESSION ANALYSIS AND ARTIFICIAL NEURAL NETWORKS BASED ON PRINCIPAL COMPONENTS

Directory of Open Access Journals (Sweden)

S. Saravanan

2012-07-01

Full Text Available Power System planning starts with Electric load (demand forecasting. Accurate electricity load forecasting is one of the most important challenges in managing supply and demand of the electricity, since the electricity demand is volatile in nature; it cannot be stored and has to be consumed instantly. The aim of this study deals with electricity consumption in India, to forecast future projection of demand for a period of 19 years from 2012 to 2030. The eleven input variables used are Amount of CO2 emission, Population, Per capita GDP, Per capita gross national income, Gross Domestic savings, Industry, Consumer price index, Wholesale price index, Imports, Exports and Per capita power consumption. A new methodology based on Artificial Neural Networks (ANNs using principal components is also used. Data of 29 years used for training and data of 10 years used for testing the ANNs. Comparison made with multiple linear regression (based on original data and the principal components and ANNs with original data as input variables. The results show that the use of ANNs with principal components (PC is more effective.

Use of the stepwise progression return-to-play protocol following concussion among practicing athletic trainers

Directory of Open Access Journals (Sweden)

Jessica Wallace

2018-04-01

Full Text Available Purpose: The purpose of this study was to determine whether practicing athletic trainers (ATs were using the stepwise progression to make return-to-play (RTP decisions after concussion and to determine what factors influenced their decision to use the stepwise progression. Methods: A total of 166 ATs (response rate = 16.6% completed a 21-item questionnaire that evaluated participant demographics, methods of concussion management, and RTP decision-making using the stepwise progression. Descriptive statistics and a logistic regression were completed to analyze data. Results: Factors such as education level (p = 0.05 and number of concussions treated (p = 0.05 predicted use of the stepwise progression, whereas sex (p = 0.17, employment setting (p = 0.17, state law (p = 0.86, and years practicing (p = 0.17 did not predict whether ATs were following the stepwise progression. Conclusion: The majority of the ATs from this study are employing the stepwise progression to safely return athletes to play after sustaining a concussion. This demonstrates that ATs are providing a standard of care for concussed athletes across various athletic training settings; however, having a graduate degree and treating more concussions per year are predictors of whether an AT follows all steps of the stepwise progression. Keywords: Athletic trainers, Concussion, Concussion management, Graduate degree, Return to play, Sports medicine, Stepwise progression

Variable Selection for Regression Models of Percentile Flows

Science.gov (United States)

Fouad, G.

2017-12-01

Percentile flows describe the flow magnitude equaled or exceeded for a given percent of time, and are widely used in water resource management. However, these statistics are normally unavailable since most basins are ungauged. Percentile flows of ungauged basins are often predicted using regression models based on readily observable basin characteristics, such as mean elevation. The number of these independent variables is too large to evaluate all possible models. A subset of models is typically evaluated using automatic procedures, like stepwise regression. This ignores a large variety of methods from the field of feature (variable) selection and physical understanding of percentile flows. A study of 918 basins in the United States was conducted to compare an automatic regression procedure to the following variable selection methods: (1) principal component analysis, (2) correlation analysis, (3) random forests, (4) genetic programming, (5) Bayesian networks, and (6) physical understanding. The automatic regression procedure only performed better than principal component analysis. Poor performance of the regression procedure was due to a commonly used filter for multicollinearity, which rejected the strongest models because they had cross-correlated independent variables. Multicollinearity did not decrease model performance in validation because of a representative set of calibration basins. Variable selection methods based strictly on predictive power (numbers 2-5 from above) performed similarly, likely indicating a limit to the predictive power of the variables. Similar performance was also reached using variables selected based on physical understanding, a finding that substantiates recent calls to emphasize physical understanding in modeling for predictions in ungauged basins. The strongest variables highlighted the importance of geology and land cover, whereas widely used topographic variables were the weakest predictors. Variables suffered from a high

Modelling Monthly Mental Sickness Cases Using Principal ...

African Journals Online (AJOL)

The methodology was principal component analysis (PCA) using data obtained from the hospital to estimate regression coefficients and parameters. It was found that the principal component regression model that was derived was good predictive tool. The principal component regression model obtained was okay and this ...

Relationships between each part of the spinal curves and upright posture using Multiple stepwise linear regression analysis.

Science.gov (United States)

Boulet, Sebastien; Boudot, Elsa; Houel, Nicolas

2016-05-03

Back pain is a common reason for consultation in primary healthcare clinical practice, and has effects on daily activities and posture. Relationships between the whole spine and upright posture, however, remain unknown. The aim of this study was to identify the relationship between each spinal curve and centre of pressure position as well as velocity for healthy subjects. Twenty-one male subjects performed quiet stance in natural position. Each upright posture was then recorded using an optoelectronics system (Vicon Nexus) synchronized with two force plates. At each moment, polynomial interpolations of markers attached on the spine segment were used to compute cervical lordosis, thoracic kyphosis and lumbar lordosis angle curves. Mean of centre of pressure position and velocity was then computed. Multiple stepwise linear regression analysis showed that the position and velocity of centre of pressure associated with each part of the spinal curves were defined as best predictors of the lumbar lordosis angle (R(2)=0.45; p=1.65*10-10) and the thoracic kyphosis angle (R(2)=0.54; p=4.89*10-13) of healthy subjects in quiet stance. This study showed the relationships between each of cervical, thoracic, lumbar curvatures, and centre of pressure's fluctuation during free quiet standing using non-invasive full spinal curve exploration. Copyright © 2016 Elsevier Ltd. All rights reserved.

Impact of multicollinearity on small sample hydrologic regression models

Science.gov (United States)

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.

Local Prediction Models on Mid-Atlantic Ridge MORB by Principal Component Regression

Science.gov (United States)

Ling, X.; Snow, J. E.; Chin, W.

2017-12-01

The isotopic compositions of the daughter isotopes of long-lived radioactive systems (Sr, Nd, Hf and Pb ) can be used to map the scale and history of mantle heterogeneities beneath mid-ocean ridges. Our goal is to relate the multidimensional structure in the existing isotopic dataset with an underlying physical reality of mantle sources. The numerical technique of Principal Component Analysis is useful to reduce the linear dependence of the data to a minimum set of orthogonal eigenvectors encapsulating the information contained (cf Agranier et al 2005). The dataset used for this study covers almost all the MORBs along mid-Atlantic Ridge (MAR), from 54oS to 77oN and 8.8oW to -46.7oW, including replicating the dataset of Agranier et al., 2005 published plus 53 basalt samples dredged and analyzed since then (data from PetDB). The principal components PC1 and PC2 account for 61.56% and 29.21%, respectively, of the total isotope ratios variability. The samples with similar compositions to HIMU and EM and DM are identified to better understand the PCs. PC1 and PC2 are accountable for HIMU and EM whereas PC2 has limited control over the DM source. PC3 is more strongly controlled by the depleted mantle source than PC2. What this means is that all three principal components have a high degree of significance relevant to the established mantle sources. We also tested the relationship between mantle heterogeneity and sample locality. K-means clustering algorithm is a type of unsupervised learning to find groups in the data based on feature similarity. The PC factor scores of each sample are clustered into three groups. Cluster one and three are alternating on the north and south MAR. Cluster two exhibits on 45.18oN to 0.79oN and -27.9oW to -30.40oW alternating with cluster one. The ridge has been preliminarily divided into 16 sections considering both the clusters and ridge segments. The principal component regression models the section based on 6 isotope ratios and PCs. The

Step-wise stimulated martensitic transformations

International Nuclear Information System (INIS)

Airoldi, G.; Riva, G.

1991-01-01

NiTi alloys, widely known both for their shape memory properties and for unusual pseudoelastic behaviour, are now on the forefront attention for step-wise induced memory processes, thermal or stress stimulated. Literature results related to step-wise stimulated martensite (direct transformation) are examined and contrasted with step-wise thermal stimulated parent phase (reverse transformation). Hypothesis are given to explain the key characters of both transformations, a thermodynamic model from first principles being till now lacking

Delineating chalk sand distribution of Ekofisk formation using probabilistic neural network (PNN) and stepwise regression (SWR): Case study Danish North Sea field

Science.gov (United States)

Haris, A.; Nafian, M.; Riyanto, A.

2017-07-01

Danish North Sea Fields consist of several formations (Ekofisk, Tor, and Cromer Knoll) that was started from the age of Paleocene to Miocene. In this study, the integration of seismic and well log data set is carried out to determine the chalk sand distribution in the Danish North Sea field. The integration of seismic and well log data set is performed by using the seismic inversion analysis and seismic multi-attribute. The seismic inversion algorithm, which is used to derive acoustic impedance (AI), is model-based technique. The derived AI is then used as external attributes for the input of multi-attribute analysis. Moreover, the multi-attribute analysis is used to generate the linear and non-linear transformation of among well log properties. In the case of the linear model, selected transformation is conducted by weighting step-wise linear regression (SWR), while for the non-linear model is performed by using probabilistic neural networks (PNN). The estimated porosity, which is resulted by PNN shows better suited to the well log data compared with the results of SWR. This result can be understood since PNN perform non-linear regression so that the relationship between the attribute data and predicted log data can be optimized. The distribution of chalk sand has been successfully identified and characterized by porosity value ranging from 23% up to 30%.

Multiple linear regression analysis

Science.gov (United States)

Edwards, T. R.

1980-01-01

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

Causal correlation of foliar biochemical concentrations with AVIRIS spectra using forced entry linear regression

Science.gov (United States)

Dawson, Terence P.; Curran, Paul J.; Kupiec, John A.

1995-01-01

A major goal of airborne imaging spectrometry is to estimate the biochemical composition of vegetation canopies from reflectance spectra. Remotely-sensed estimates of foliar biochemical concentrations of forests would provide valuable indicators of ecosystem function at regional and eventually global scales. Empirical research has shown a relationship exists between the amount of radiation reflected from absorption features and the concentration of given biochemicals in leaves and canopies (Matson et al., 1994, Johnson et al., 1994). A technique commonly used to determine which wavelengths have the strongest correlation with the biochemical of interest is unguided (stepwise) multiple regression. Wavelengths are entered into a multivariate regression equation, in their order of importance, each contributing to the reduction of the variance in the measured biochemical concentration. A significant problem with the use of stepwise regression for determining the correlation between biochemical concentration and spectra is that of 'overfitting' as there are significantly more wavebands than biochemical measurements. This could result in the selection of wavebands which may be more accurately attributable to noise or canopy effects. In addition, there is a real problem of collinearity in that the individual biochemical concentrations may covary. A strong correlation between the reflectance at a given wavelength and the concentration of a biochemical of interest, therefore, may be due to the effect of another biochemical which is closely related. Furthermore, it is not always possible to account for potentially suitable waveband omissions in the stepwise selection procedure. This concern about the suitability of stepwise regression has been identified and acknowledged in a number of recent studies (Wessman et al., 1988, Curran, 1989, Curran et al., 1992, Peterson and Hubbard, 1992, Martine and Aber, 1994, Kupiec, 1994). These studies have pointed to the lack of a physical

Step-wise refolding of recombinant proteins.

Science.gov (United States)

Tsumoto, Kouhei; Arakawa, Tsutomu; Chen, Linda

2010-04-01

Protein refolding is still on trial-and-error basis. Here we describe step-wise dialysis refolding, in which denaturant concentration is altered in step-wise fashion. This technology controls the folding pathway by adjusting the concentrations of the denaturant and other solvent additives to induce sequential folding or disulfide formation.

Source apportionment of soil heavy metals using robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR) receptor model.

Science.gov (United States)

Qu, Mingkai; Wang, Yan; Huang, Biao; Zhao, Yongcun

2018-06-01

The traditional source apportionment models, such as absolute principal component scores-multiple linear regression (APCS-MLR), are usually susceptible to outliers, which may be widely present in the regional geochemical dataset. Furthermore, the models are merely built on variable space instead of geographical space and thus cannot effectively capture the local spatial characteristics of each source contributions. To overcome the limitations, a new receptor model, robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR), was proposed based on the traditional APCS-MLR model. Then, the new method was applied to the source apportionment of soil metal elements in a region of Wuhan City, China as a case study. Evaluations revealed that: (i) RAPCS-RGWR model had better performance than APCS-MLR model in the identification of the major sources of soil metal elements, and (ii) source contributions estimated by RAPCS-RGWR model were more close to the true soil metal concentrations than that estimated by APCS-MLR model. It is shown that the proposed RAPCS-RGWR model is a more effective source apportionment method than APCS-MLR (i.e., non-robust and global model) in dealing with the regional geochemical dataset. Copyright © 2018 Elsevier B.V. All rights reserved.

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.)

Predicting Dropouts of University Freshmen: A Logit Regression Analysis.

Science.gov (United States)

Lam, Y. L. Jack

1984-01-01

Stepwise discriminant analysis coupled with logit regression analysis of freshmen data from Brandon University (Manitoba) indicated that six tested variables drawn from research on university dropouts were useful in predicting attrition: student status, residence, financial sources, distance from home town, goal fulfillment, and satisfaction with…

The relative importance of imaging markers for the prediction of Alzheimer's disease dementia in mild cognitive impairment — Beyond classical regression

Directory of Open Access Journals (Sweden)

Stefan J. Teipel

2015-01-01

Penalized regression yielded more parsimonious models than unpenalized stepwise regression for the integration of multiregional and multimodal imaging information. The advantage of penalized regression was particularly strong with a high number of collinear predictors.

Using synthetic data to evaluate multiple regression and principal component analyses for statistical modeling of daily building energy consumption

Energy Technology Data Exchange (ETDEWEB)

Reddy, T.A. (Energy Systems Lab., Texas A and M Univ., College Station, TX (United States)); Claridge, D.E. (Energy Systems Lab., Texas A and M Univ., College Station, TX (United States))

1994-01-01

Multiple regression modeling of monitored building energy use data is often faulted as a reliable means of predicting energy use on the grounds that multicollinearity between the regressor variables can lead both to improper interpretation of the relative importance of the various physical regressor parameters and to a model with unstable regressor coefficients. Principal component analysis (PCA) has the potential to overcome such drawbacks. While a few case studies have already attempted to apply this technique to building energy data, the objectives of this study were to make a broader evaluation of PCA and multiple regression analysis (MRA) and to establish guidelines under which one approach is preferable to the other. Four geographic locations in the US with different climatic conditions were selected and synthetic data sequence representative of daily energy use in large institutional buildings were generated in each location using a linear model with outdoor temperature, outdoor specific humidity and solar radiation as the three regression variables. MRA and PCA approaches were then applied to these data sets and their relative performances were compared. Conditions under which PCA seems to perform better than MRA were identified and preliminary recommendations on the use of either modeling approach formulated. (orig.)

An Efficient Stepwise Statistical Test to Identify Multiple Linked Human Genetic Variants Associated with Specific Phenotypic Traits.

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Iksoo Huh

Full Text Available Recent advances in genotyping methodologies have allowed genome-wide association studies (GWAS to accurately identify genetic variants that associate with common or pathological complex traits. Although most GWAS have focused on associations with single genetic variants, joint identification of multiple genetic variants, and how they interact, is essential for understanding the genetic architecture of complex phenotypic traits. Here, we propose an efficient stepwise method based on the Cochran-Mantel-Haenszel test (for stratified categorical data to identify causal joint multiple genetic variants in GWAS. This method combines the CMH statistic with a stepwise procedure to detect multiple genetic variants associated with specific categorical traits, using a series of associated I × J contingency tables and a null hypothesis of no phenotype association. Through a new stratification scheme based on the sum of minor allele count criteria, we make the method more feasible for GWAS data having sample sizes of several thousands. We also examine the properties of the proposed stepwise method via simulation studies, and show that the stepwise CMH test performs better than other existing methods (e.g., logistic regression and detection of associations by Markov blanket for identifying multiple genetic variants. Finally, we apply the proposed approach to two genomic sequencing datasets to detect linked genetic variants associated with bipolar disorder and obesity, respectively.

The Performance of Step-Wise Group Screening Designs

Directory of Open Access Journals (Sweden)

M.M. Manene

2005-06-01

Full Text Available In this paper we evaluate the performance of step-wise group screening designs in which group-factors contain an equal number of factors in the initial step.  A usual assumption in group screening designs is that the directions of possible effects are known a-priori. In practice, however, this assumption is unreasonable. We shall examine step-wise group screening designs without errors in observations when this assumption is relaxed. We shall consider cancellations of effects within group-factors. The performance of step-wise group-screening designs shall then be compared with the performance of multistage group screening designs.

Principal components based support vector regression model for on-line instrument calibration monitoring in NPPs

International Nuclear Information System (INIS)

Seo, In Yong; Ha, Bok Nam; Lee, Sung Woo; Shin, Chang Hoon; Kim, Seong Jun

2010-01-01

In nuclear power plants (NPPs), periodic sensor calibrations are required to assure that sensors are operating correctly. By checking the sensor's operating status at every fuel outage, faulty sensors may remain undetected for periods of up to 24 months. Moreover, typically, only a few faulty sensors are found to be calibrated. For the safe operation of NPP and the reduction of unnecessary calibration, on-line instrument calibration monitoring is needed. In this study, principal component based auto-associative support vector regression (PCSVR) using response surface methodology (RSM) is proposed for the sensor signal validation of NPPs. This paper describes the design of a PCSVR-based sensor validation system for a power generation system. RSM is employed to determine the optimal values of SVR hyperparameters and is compared to the genetic algorithm (GA). The proposed PCSVR model is confirmed with the actual plant data of Kori Nuclear Power Plant Unit 3 and is compared with the Auto-Associative support vector regression (AASVR) and the auto-associative neural network (AANN) model. The auto-sensitivity of AASVR is improved by around six times by using a PCA, resulting in good detection of sensor drift. Compared to AANN, accuracy and cross-sensitivity are better while the auto-sensitivity is almost the same. Meanwhile, the proposed RSM for the optimization of the PCSVR algorithm performs even better in terms of accuracy, auto-sensitivity, and averaged maximum error, except in averaged RMS error, and this method is much more time efficient compared to the conventional GA method

Real time damage detection using recursive principal components and time varying auto-regressive modeling

Science.gov (United States)

Krishnan, M.; Bhowmik, B.; Hazra, B.; Pakrashi, V.

2018-02-01

In this paper, a novel baseline free approach for continuous online damage detection of multi degree of freedom vibrating structures using Recursive Principal Component Analysis (RPCA) in conjunction with Time Varying Auto-Regressive Modeling (TVAR) is proposed. In this method, the acceleration data is used to obtain recursive proper orthogonal components online using rank-one perturbation method, followed by TVAR modeling of the first transformed response, to detect the change in the dynamic behavior of the vibrating system from its pristine state to contiguous linear/non-linear-states that indicate damage. Most of the works available in the literature deal with algorithms that require windowing of the gathered data owing to their data-driven nature which renders them ineffective for online implementation. Algorithms focussed on mathematically consistent recursive techniques in a rigorous theoretical framework of structural damage detection is missing, which motivates the development of the present framework that is amenable for online implementation which could be utilized along with suite experimental and numerical investigations. The RPCA algorithm iterates the eigenvector and eigenvalue estimates for sample covariance matrices and new data point at each successive time instants, using the rank-one perturbation method. TVAR modeling on the principal component explaining maximum variance is utilized and the damage is identified by tracking the TVAR coefficients. This eliminates the need for offline post processing and facilitates online damage detection especially when applied to streaming data without requiring any baseline data. Numerical simulations performed on a 5-dof nonlinear system under white noise excitation and El Centro (also known as 1940 Imperial Valley earthquake) excitation, for different damage scenarios, demonstrate the robustness of the proposed algorithm. The method is further validated on results obtained from case studies involving

Significance of stepwise excretion pattern in renogram

International Nuclear Information System (INIS)

Tamaki, Nagara; Ishihara, Takashi; Mori, Toru; Bito, Sanae; Ito, Hidetomi

1981-01-01

In 204 routine renogram examinations using 131 I-iodohippurate, stepwise excretion curves were observed in 22 cases (14 with chronic thyroiditis, 4 with idiopathic edema, 3 with lower urinary tract disorders, and 1 with Bartter's syndrome). Such a phenomenon was observed in 74% of euthyroid edematous patients with chronic thyroiditis and 57% of patients with idiopathic edema. The stepwise pattern was considered to have certain correlations with spasm or increased peristalsis of the urinary tract through the studies of excretory urogram, butylscopolamine treated renogram, and regional renogram. In one of these edematous patients with chronic thyroiditis, this renogram pattern could not be reproduced after bed rest corresponding with the clinical evidence that physical rest reduce the edema. Thus, the stepwise excretory pattern in renogram seemed to be a useful indicator of the fluctuating edema in patients with chronic thyroiditis and idiopathic edema. (author)

Constrained principal component analysis and related techniques

CERN Document Server

Takane, Yoshio

2013-01-01

In multivariate data analysis, regression techniques predict one set of variables from another while principal component analysis (PCA) finds a subspace of minimal dimensionality that captures the largest variability in the data. How can regression analysis and PCA be combined in a beneficial way? Why and when is it a good idea to combine them? What kind of benefits are we getting from them? Addressing these questions, Constrained Principal Component Analysis and Related Techniques shows how constrained PCA (CPCA) offers a unified framework for these approaches.The book begins with four concre

Estimating Loess Plateau Average Annual Precipitation with Multiple Linear Regression Kriging and Geographically Weighted Regression Kriging

Directory of Open Access Journals (Sweden)

Qiutong Jin

2016-06-01

Full Text Available Estimating the spatial distribution of precipitation is an important and challenging task in hydrology, climatology, ecology, and environmental science. In order to generate a highly accurate distribution map of average annual precipitation for the Loess Plateau in China, multiple linear regression Kriging (MLRK and geographically weighted regression Kriging (GWRK methods were employed using precipitation data from the period 1980–2010 from 435 meteorological stations. The predictors in regression Kriging were selected by stepwise regression analysis from many auxiliary environmental factors, such as elevation (DEM, normalized difference vegetation index (NDVI, solar radiation, slope, and aspect. All predictor distribution maps had a 500 m spatial resolution. Validation precipitation data from 130 hydrometeorological stations were used to assess the prediction accuracies of the MLRK and GWRK approaches. Results showed that both prediction maps with a 500 m spatial resolution interpolated by MLRK and GWRK had a high accuracy and captured detailed spatial distribution data; however, MLRK produced a lower prediction error and a higher variance explanation than GWRK, although the differences were small, in contrast to conclusions from similar studies.

Cushing's syndrome: Stepwise approach to diagnosis

Science.gov (United States)

Lila, Anurag R.; Sarathi, Vijaya; Jagtap, Varsha S.; Bandgar, Tushar; Menon, Padmavathy; Shah, Nalini S.

2011-01-01

The projected prevalence of Cushing's syndrome (CS) inclusive of subclinical cases in the adult population ranges from 0.2–2% and it may no longer be considered as an orphan disease (2–3 cases/million/year). The recognition of CS by physicians is important for early diagnosis and treatment. Late-night salivary cortisol, dexamethasone suppressiontesti, or 24-h urine free cortisol are good screening tests. Positively screened cases need stepwise evaluation by an endocrinologist. This paper discusses the importance of screening for CS and suggests a stepwise diagnostic approach to a case of suspected hypercortisolism. PMID:22145134

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.

Stepwise management of asthma.

Science.gov (United States)

Khalid, Ayesha N

2015-09-01

Stepwise management of asthma remains an area of evolving research. Asthma is one of the most expensive chronic diseases in the United States; stepwise management is an important area of focus, with several recent guidelines recommending management. This is a review of published English language literature, focusing on management guidelines for asthma in adult and pediatric patients. Asthma is a chronic disease whose assessment of severity allows for therapeutic goals to match the impairment noted. Good evidence exists to aid risk reduction, leading to decreased emergency room visits, preventing loss of lung function in adults and lung growth in children, and optimizing pharmacotherapy with reduced side effects profile. Recent asthma management guidelines incorporate 4 components of asthma care including: monitoring of severity, patient education, controlling external triggers, and medications, including recent attention to medication adherence. Asthma is an expensive chronic disease with preventive measures leading to reduced healthcare costs. Future targeted cytokine therapy to decrease serum and blood eosinophils may become an integral part of asthma management. © 2015 ARS-AAOA, LLC.

JT-60 configuration parameters for feedback control determined by regression analysis

Energy Technology Data Exchange (ETDEWEB)

Matsukawa, Makoto; Hosogane, Nobuyuki; Ninomiya, Hiromasa (Japan Atomic Energy Research Inst., Naka, Ibaraki (Japan). Naka Fusion Research Establishment)

1991-12-01

The stepwise regression procedure was applied to obtain measurement formulas for equilibrium parameters used in the feedback control of JT-60. This procedure automatically selects variables necessary for the measurements, and selects a set of variables which are not likely to be picked up by physical considerations. Regression equations with stable and small multicollinearity were obtained and it was experimentally confirmed that the measurement formulas obtained through this procedure were accurate enough to be applicable to the feedback control of plasma configurations in JT-60. (author).

JT-60 configuration parameters for feedback control determined by regression analysis

International Nuclear Information System (INIS)

Matsukawa, Makoto; Hosogane, Nobuyuki; Ninomiya, Hiromasa

1991-12-01

The stepwise regression procedure was applied to obtain measurement formulas for equilibrium parameters used in the feedback control of JT-60. This procedure automatically selects variables necessary for the measurements, and selects a set of variables which are not likely to be picked up by physical considerations. Regression equations with stable and small multicollinearity were obtained and it was experimentally confirmed that the measurement formulas obtained through this procedure were accurate enough to be applicable to the feedback control of plasma configurations in JT-60. (author)

Cushing′s syndrome: Stepwise approach to diagnosis

Directory of Open Access Journals (Sweden)

Anurag R Lila

2011-01-01

Full Text Available The projected prevalence of Cushing′s syndrome (CS inclusive of subclinical cases in the adult population ranges from 0.2-2% and it may no longer be considered as an orphan disease (2-3 cases/million/year. The recognition of CS by physicians is important for early diagnosis and treatment. Late-night salivary cortisol, dexamethasone suppressiontesti, or 24-h urine free cortisol are good screening tests. Positively screened cases need stepwise evaluation by an endocrinologist. This paper discusses the importance of screening for CS and suggests a stepwise diagnostic approach to a case of suspected hypercortisolism.

A robust and efficient stepwise regression method for building sparse polynomial chaos expansions

Energy Technology Data Exchange (ETDEWEB)

Abraham, Simon, E-mail: Simon.Abraham@ulb.ac.be [Vrije Universiteit Brussel (VUB), Department of Mechanical Engineering, Research Group Fluid Mechanics and Thermodynamics, Pleinlaan 2, 1050 Brussels (Belgium); Raisee, Mehrdad [School of Mechanical Engineering, College of Engineering, University of Tehran, P.O. Box: 11155-4563, Tehran (Iran, Islamic Republic of); Ghorbaniasl, Ghader; Contino, Francesco; Lacor, Chris [Vrije Universiteit Brussel (VUB), Department of Mechanical Engineering, Research Group Fluid Mechanics and Thermodynamics, Pleinlaan 2, 1050 Brussels (Belgium)

2017-03-01

Polynomial Chaos (PC) expansions are widely used in various engineering fields for quantifying uncertainties arising from uncertain parameters. The computational cost of classical PC solution schemes is unaffordable as the number of deterministic simulations to be calculated grows dramatically with the number of stochastic dimension. This considerably restricts the practical use of PC at the industrial level. A common approach to address such problems is to make use of sparse PC expansions. This paper presents a non-intrusive regression-based method for building sparse PC expansions. The most important PC contributions are detected sequentially through an automatic search procedure. The variable selection criterion is based on efficient tools relevant to probabilistic method. Two benchmark analytical functions are used to validate the proposed algorithm. The computational efficiency of the method is then illustrated by a more realistic CFD application, consisting of the non-deterministic flow around a transonic airfoil subject to geometrical uncertainties. To assess the performance of the developed methodology, a detailed comparison is made with the well established LAR-based selection technique. The results show that the developed sparse regression technique is able to identify the most significant PC contributions describing the problem. Moreover, the most important stochastic features are captured at a reduced computational cost compared to the LAR method. The results also demonstrate the superior robustness of the method by repeating the analyses using random experimental designs.

COPD: A stepwise or a hit hard approach?

Directory of Open Access Journals (Sweden)

A.J. Ferreira

2016-07-01

Full Text Available Current guidelines differ slightly on the recommendations for treatment of Chronic Obstructive Pulmonary Disease (COPD patients, and although there are some undisputed recommendations, there is still debate regarding the management of COPD. One of the hindrances to deciding which therapeutic approach to choose is late diagnosis or misdiagnosis of COPD. After a proper diagnosis is achieved and severity assessed, the choice between a stepwise or “hit hard” approach has to be made. For GOLD A patients the stepwise approach is recommended, whilst for B, C and D patients this remains debatable. Moreover, in patients for whom inhaled corticosteroids (ICS are recommended, a step-up or “hit hard” approach with triple therapy will depend on the patient's characteristics and, for patients who are being over-treated with ICS, ICS withdrawal should be performed, in order to optimize therapy and reduce excessive medications.This paper discusses and proposes stepwise, “hit hard”, step-up and ICS withdrawal therapeutic approaches for COPD patients based on their GOLD group. We conclude that all approaches have benefits, and only a careful patient selection will determine which approach is better, and which patients will benefit the most from each approach. Keywords: COPD, Stepwise, Hit hard, Step-up, ICS withdrawal, Bronchodilators, ICS

Melanin fluorescence spectra by step-wise three photon excitation

Science.gov (United States)

Lai, Zhenhua; Kerimo, Josef; DiMarzio, Charles A.

2012-03-01

Melanin is the characteristic chromophore of human skin with various potential biological functions. Kerimo discovered enhanced melanin fluorescence by stepwise three-photon excitation in 2011. In this article, step-wise three-photon excited fluorescence (STPEF) spectrum between 450 nm -700 nm of melanin is reported. The melanin STPEF spectrum exhibited an exponential increase with wavelength. However, there was a probability of about 33% that another kind of step-wise multi-photon excited fluorescence (SMPEF) that peaks at 525 nm, shown by previous research, could also be generated using the same process. Using an excitation source at 920 nm as opposed to 830 nm increased the potential for generating SMPEF peaks at 525 nm. The SMPEF spectrum peaks at 525 nm photo-bleached faster than STPEF spectrum.

Coupled variable selection for regression modeling of complex treatment patterns in a clinical cancer registry.

Science.gov (United States)

Schmidtmann, I; Elsäßer, A; Weinmann, A; Binder, H

2014-12-30

For determining a manageable set of covariates potentially influential with respect to a time-to-event endpoint, Cox proportional hazards models can be combined with variable selection techniques, such as stepwise forward selection or backward elimination based on p-values, or regularized regression techniques such as component-wise boosting. Cox regression models have also been adapted for dealing with more complex event patterns, for example, for competing risks settings with separate, cause-specific hazard models for each event type, or for determining the prognostic effect pattern of a variable over different landmark times, with one conditional survival model for each landmark. Motivated by a clinical cancer registry application, where complex event patterns have to be dealt with and variable selection is needed at the same time, we propose a general approach for linking variable selection between several Cox models. Specifically, we combine score statistics for each covariate across models by Fisher's method as a basis for variable selection. This principle is implemented for a stepwise forward selection approach as well as for a regularized regression technique. In an application to data from hepatocellular carcinoma patients, the coupled stepwise approach is seen to facilitate joint interpretation of the different cause-specific Cox models. In conditional survival models at landmark times, which address updates of prediction as time progresses and both treatment and other potential explanatory variables may change, the coupled regularized regression approach identifies potentially important, stably selected covariates together with their effect time pattern, despite having only a small number of events. These results highlight the promise of the proposed approach for coupling variable selection between Cox models, which is particularly relevant for modeling for clinical cancer registries with their complex event patterns. Copyright © 2014 John Wiley & Sons

Stepwise introduction of laparoscopic liver surgery: validation of guideline recommendations.

Science.gov (United States)

van der Poel, Marcel J; Huisman, Floor; Busch, Olivier R; Abu Hilal, Mohammad; van Gulik, Thomas M; Tanis, Pieter J; Besselink, Marc G

2017-10-01

Uncontrolled introduction of laparoscopic liver surgery (LLS) could compromise postoperative outcomes. A stepwise introduction of LLS combined with structured training is advised. This study aimed to evaluate the impact of such a stepwise introduction. A retrospective, single-center case series assessing short term outcomes of all consecutive LLS in the period November 2006-January 2017. The technique was implemented in a stepwise fashion. To evaluate the impact of this stepwise approach combined with structured training, outcomes of LLS before and after a laparoscopic HPB fellowship were compared. A total of 135 laparoscopic resections were performed. Overall conversion rate was 4% (n = 5), clinically relevant complication rate 13% (n = 18) and mortality 0.7% (n = 1). A significant increase in patients with major LLS, multiple liver resections, previous abdominal surgery, malignancies and lesions located in posterior segments was observed after the fellowship as well as a decrease in the use of hand-assistance. Increasing complexity in the post fellowship period was reflected by an increase in operating times, but without comprising other surgical outcomes. A stepwise introduction of LLS combined with structured training reduced the clinical impact of the learning curve, thereby confirming guideline recommendations. Copyright © 2017 International Hepato-Pancreato-Biliary Association Inc. Published by Elsevier Ltd. All rights reserved.

Does Stepwise Voltage Ramping Protect the Kidney from Injury During Extracorporeal Shockwave Lithotripsy? Results of a Prospective Randomized Trial.

Science.gov (United States)

Skuginna, Veronika; Nguyen, Daniel P; Seiler, Roland; Kiss, Bernhard; Thalmann, George N; Roth, Beat

2016-02-01

Renal damage is more frequent with new-generation lithotripters. However, animal studies suggest that voltage ramping minimizes the risk of complications following extracorporeal shock wave lithotripsy (SWL). In the clinical setting, the optimal voltage strategy remains unclear. To evaluate whether stepwise voltage ramping can protect the kidney from damage during SWL. A total of 418 patients with solitary or multiple unilateral kidney stones were randomized to receive SWL using a Modulith SLX-F2 lithotripter with either stepwise voltage ramping (n=213) or a fixed maximal voltage (n=205). SWL. The primary outcome was sonographic evidence of renal hematomas. Secondary outcomes included levels of urinary markers of renal damage, stone disintegration, stone-free rate, and rates of secondary interventions within 3 mo of SWL. Descriptive statistics were used to compare clinical outcomes between the two groups. A logistic regression model was generated to assess predictors of hematomas. Significantly fewer hematomas occurred in the ramping group(12/213, 5.6%) than in the fixed group (27/205, 13%; p=0.008). There was some evidence that the fixed group had higher urinary β2-microglobulin levels after SWL compared to the ramping group (p=0.06). Urinary microalbumin levels, stone disintegration, stone-free rate, and rates of secondary interventions did not significantly differ between the groups. The logistic regression model showed a significantly higher risk of renal hematomas in older patients (odds ratio [OR] 1.03, 95% confidence interval [CI] 1.00-1.05; p=0.04). Stepwise voltage ramping was associated with a lower risk of hematomas (OR 0.39, 95% CI 0.19-0.80; p=0.01). The study was limited by the use of ultrasound to detect hematomas. In this prospective randomized study, stepwise voltage ramping during SWL was associated with a lower risk of renal damage compared to a fixed maximal voltage without compromising treatment effectiveness. Lithotripsy is a noninvasive

Functional data analysis of generalized regression quantiles

KAUST Repository

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

2013-01-01

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

Functional data analysis of generalized regression quantiles

KAUST Repository

Guo, Mengmeng

2013-11-05

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

Stepwise Decision Making for Long-Term Radioactive Waste Management

International Nuclear Information System (INIS)

Pescatore, Claudio; Vari, Anna

2003-01-01

Consideration is increasingly being given, in radioactive waste management (RWM), to concepts such as 'stepwise decision making' and 'adaptive staging' in which the public, and especially the local communities, are also meaningfully involved in the review and planning of developments. The key feature of these concepts is development by steps or stages that are reversible, within the limits of practicability and provided they meet the requirements of an acceptable safety case. Stepwise decisions are designed to provide reassurance that actions can be reversed if experience shows them to have adverse or unwanted effects. Stepwise decision making has thus come to the fore as being especially important for making progress for radioactive waste management in a manner which is acceptable to large sectors of society. Despite its early identification within the RWM community as an important means for reaching decision in which there is broad-based confidence, stepwise decision making has not been widely debated. Accepted guiding principles of any such process have not yet been formulated, its roots in empirical social science research have not been fully reviewed, nor the difficulties of its implementation analysed. This paper reviews the current developments regarding stepwise decision making in RWM with the aim to pinpoint where it stands, to highlight its societal dimension, to analyse its roots in social sciences, and to identify guiding principles and issues in implementation. It is observed that there is convergence between the approach taken by the practitioners of RWM and the indications received from field studies in social research, and that general guiding principles can be proposed at least as a basis for further discussion. A strong basis for dialogue across disciplines thus exists. General methodological issues are also identified. This paper was developed in the framework of the activities of the NEA Forum on Stakeholder Confidence, which is presented in a

Stepwise transformation behavior of the strain-induced martensitic transformation in a metastable stainless steel

International Nuclear Information System (INIS)

Hedstroem, Peter; Lienert, Ulrich; Almer, Jon; Oden, Magnus

2007-01-01

In situ high-energy X-ray diffraction during tensile loading has been used to investigate the evolution of lattice strains and the accompanying strain-induced martensitic transformation in cold-rolled sheets of a metastable stainless steel. At high applied strains the transformation to α-martensite occurs in stepwise bursts. These stepwise transformation events are correlated with stepwise increased lattice strains and peak broadening in the austenite phase. The stepwise transformation arises from growth of α-martensite embryos by autocatalytic transformation

Analysis of γ spectra in airborne radioactivity measurements using multiple linear regressions

International Nuclear Information System (INIS)

Bao Min; Shi Quanlin; Zhang Jiamei

2004-01-01

This paper describes the net peak counts calculating of nuclide 137 Cs at 662 keV of γ spectra in airborne radioactivity measurements using multiple linear regressions. Mathematic model is founded by analyzing every factor that has contribution to Cs peak counts in spectra, and multiple linear regression function is established. Calculating process adopts stepwise regression, and the indistinctive factors are eliminated by F check. The regression results and its uncertainty are calculated using Least Square Estimation, then the Cs peak net counts and its uncertainty can be gotten. The analysis results for experimental spectrum are displayed. The influence of energy shift and energy resolution on the analyzing result is discussed. In comparison with the stripping spectra method, multiple linear regression method needn't stripping radios, and the calculating result has relation with the counts in Cs peak only, and the calculating uncertainty is reduced. (authors)

School Principals' Job Satisfaction: The Effects of Work Intensification

Science.gov (United States)

Wang, Fei; Pollock, Katina; Hauseman, Cameron

2018-01-01

This study examines principals' job satisfaction in relation to their work intensification. Frederick Herzberg's two-factor theory was used to shed light on how motivating and maintenance factors affect principals' job satisfaction. Logistic multiple regressions were used in the analysis of survey data that were collected from 2,701 elementary and…

A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis.

Science.gov (United States)

Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga

2006-08-01

A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.

Principal Component Regression Analysis of the Relation Between CIELAB Color and Monomeric Anthocyanins in Young Cabernet Sauvignon Wines

Directory of Open Access Journals (Sweden)

Chang-Qing Duan

2008-11-01

Full Text Available Color is one of the key characteristics used to evaluate the sensory quality of red wine, and anthocyanins are the main contributors to color. Monomeric anthocyanins and CIELAB color values were investigated by HPLC-MS and spectrophotometry during fermentation of Cabernet Sauvignon red wine, and principal component regression (PCR, a statistical tool, was used to establish a linkage between the detected anthocyanins and wine coloring. The results showed that 14 monomeric anthocyanins could be identified in wine samples, and all of these anthocyanins were negatively correlated with the L*, b* and H*ab values, but positively correlated with a* and C*ab values. On an equal concentration basis for each detected anthocyanin, cyanidin-3-O-glucoside (Cy3-glu had the most influence on CIELAB color value, while malvidin 3-O-glucoside (Mv3-glu had the least. The color values of various monomeric anthocyanins were influenced by their structures, substituents on the B-ring, acyl groups on the glucoside and the molecular steric structure. This work develops a statistical method for evaluating correlation between wine color and monomeric anthocyanins, and also provides a basis for elucidating the effect of intramolecular copigmentation on wine coloring.

Crude Oil Price Forecasting Based on Hybridizing Wavelet Multiple Linear Regression Model, Particle Swarm Optimization Techniques, and Principal Component Analysis

Science.gov (United States)

Shabri, Ani; Samsudin, Ruhaidah

2014-01-01

Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series. PMID:24895666

Crude oil price forecasting based on hybridizing wavelet multiple linear regression model, particle swarm optimization techniques, and principal component analysis.

Science.gov (United States)

Shabri, Ani; Samsudin, Ruhaidah

2014-01-01

Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.

Group-wise partial least square regression

NARCIS (Netherlands)

Camacho, José; Saccenti, Edoardo

2018-01-01

This paper introduces the group-wise partial least squares (GPLS) regression. GPLS is a new sparse PLS technique where the sparsity structure is defined in terms of groups of correlated variables, similarly to what is done in the related group-wise principal component analysis. These groups are

Dependence between fusion temperatures and chemical components of a certain type of coal using classical, non-parametric and bootstrap techniques

Energy Technology Data Exchange (ETDEWEB)

Gonzalez-Manteiga, W.; Prada-Sanchez, J.M.; Fiestras-Janeiro, M.G.; Garcia-Jurado, I. (Universidad de Santiago de Compostela, Santiago de Compostela (Spain). Dept. de Estadistica e Investigacion Operativa)

1990-11-01

A statistical study of the dependence between various critical fusion temperatures of a certain kind of coal and its chemical components is carried out. As well as using classical dependence techniques (multiple, stepwise and PLS regression, principal components, canonical correlation, etc.) together with the corresponding inference on the parameters of interest, non-parametric regression and bootstrap inference are also performed. 11 refs., 3 figs., 8 tabs.

Determinants of job satisfaction in Spain before and during the economic crisis of 2008

Directory of Open Access Journals (Sweden)

María Carmen Sánchez-Sellero

2016-10-01

Originality/value: We have compared the results of stepwise regression made with the original variables and the factors of principal component analysis. The combination of these methodologies is new in studies of job satisfaction, as well as the original combination of 14 variables related to work.

Consistency and Word-Frequency Effects on Spelling among First- To Fifth-Grade French Children: A Regression-Based Study

Science.gov (United States)

Lete, Bernard; Peereman, Ronald; Fayol, Michel

2008-01-01

We describe a large-scale regression study that examines the influence of lexical (word frequency, lexical neighborhood) and sublexical (feedforward and feedback consistency) variables on spelling accuracy among first, second, and third- to fifth-graders. The wordset analyzed contained 3430 French words. Predictors in the stepwise regression…

Stepwise Nanopore Evolution in One-Dimensional Nanostructures

KAUST Repository

Choi, Jang Wook

2010-04-14

We report that established simple lithium (Li) ion battery cycles can be used to produce nanopores inside various useful one-dimensional (1D) nanostructures such as zinc oxide, silicon, and silver nanowires. Moreover, porosities of these 1D nanomaterials can be controlled in a stepwise manner by the number of Li-battery cycles. Subsequent pore characterization at the end of each cycle allows us to obtain detailed snapshots of the distinct pore evolution properties in each material due to their different atomic diffusion rates and types of chemical bonds. Also, this stepwise characterization led us to the first observation of pore size increases during cycling, which can be interpreted as a similar phenomenon to Ostwald ripening in analogous nanoparticle cases. Finally, we take advantage of the unique combination of nanoporosity and 1D materials and demonstrate nanoporous silicon nanowires (poSiNWs) as excellent supercapacitor (SC) electrodes in high power operations compared to existing devices with activated carbon. © 2010 American Chemical Society.

Principals' instructional management skills and middle school science teacher job satisfaction

Science.gov (United States)

Gibbs-Harper, Nzinga A.

The purpose of this research study was to determine if a relationship exists between teachers' perceptions of principals' instructional leadership behaviors and middle school teacher job satisfaction. Additionally, this study sought to assess whether principal's instructional leadership skills were predictors of middle school teachers' satisfaction with work itself. This study drew from 13 middle schools in an urban Mississippi school district. Participants included teachers who taught science. Each teacher was given the Principal Instructional Management Rating Scale (PIMRS; Hallinger, 2011) and the Teacher Job Satisfaction Questionnaire (TJSQ; Lester, 1987) to answer the research questions. The study was guided by two research questions: (a) Is there a relationship between the independent variables Defining the School's Mission, Managing the Instructional Program, and Developing the School Learning Climate Program and the dependent variable Work Itself?; (b) Are Defining the School's Mission, Managing the Instructional Program, and Developing the School Learning Climate Program predictors of Work Itself? The Pearson's correlation and multiple regression analysis were utilized to examine the relationship between the three dimensions of principals' instructional leadership and teacher satisfaction with work itself. The data revealed that there was a strong, positive correlation between all three dimensions of principals' instructional leadership and teacher satisfaction with work itself. However, the multiple regression analysis determined that teachers' perceptions of principals' instructional management skills is a slight predictor of Defining the School's Mission only.

Journal of Earth System Science | Indian Academy of Sciences

Indian Academy of Sciences (India)

Then the most effective independent variables were selected by using principal component analysis (PCA), Gamma test (GT) and stepwise regression (SR) techniques. After reducing 14 input variables to five (using PCA and GT) and two (using SR techniques), they are divided into homogeneous areas by Andrew curve ...

A regression approach for Zircaloy-2 in-reactor creep constitutive equations

International Nuclear Information System (INIS)

Yung Liu, Y.; Bement, A.L.

1977-01-01

In this paper the methodology of multiple regressions as applied to Zircaloy-2 in-reactor creep data analysis and construction of constitutive equation are illustrated. While the resulting constitutive equation can be used in creep analysis of in-reactor Zircaloy structural components, the methodology itself is entirely general and can be applied to any creep data analysis. The promising aspects of multiple regression creep data analysis are briefly outlined as follows: (1) When there are more than one variable involved, there is no need to make the assumption that each variable affects the response independently. No separate normalizations are required either and the estimation of parameters is obtained by solving many simultaneous equations. The number of simultaneous equations is equal to the number of data sets. (2) Regression statistics such as R 2 - and F-statistics provide measures of the significance of regression creep equation in correlating the overall data. The relative weights of each variable on the response can also be obtained. (3) Special regression techniques such as step-wise, ridge, and robust regressions and residual plots, etc., provide diagnostic tools for model selections. Multiple regression analysis performed on a set of carefully selected Zircaloy-2 in-reactor creep data leads to a model which provides excellent correlations for the data. (Auth.)

PRINCIPAL COMPONENT ANALYSIS OF FACTORS DETERMINING PHOSPHATE ROCK DISSOLUTION ON ACID SOILS

Directory of Open Access Journals (Sweden)

Yusdar Hilman

2016-10-01

Full Text Available Many of the agricultural soils in Indonesia are acidic and low in both total and available phosphorus which severely limits their potential for crops production. These problems can be corrected by application of chemical fertilizers. However, these fertilizers are expensive, and cheaper alternatives such as phosphate rock (PR have been considered. Several soil factors may influence the dissolution of PR in soils, including both chemical and physical properties. The study aimed to identify PR dissolution factors and evaluate their relative magnitude. The experiment was conducted in Soil Chemical Laboratory, Universiti Putra Malaysia and Indonesian Center for Agricultural Land Resources Research and Development from January to April 2002. The principal component analysis (PCA was used to characterize acid soils in an incubation system into a number of factors that may affect PR dissolution. Three major factors selected were soil texture, soil acidity, and fertilization. Using the scores of individual factors as independent variables, stepwise regression analysis was performed to derive a PR dissolution function. The factors influencing PR dissolution in order of importance were soil texture, soil acidity, then fertilization. Soil texture factors including clay content and organic C, and soil acidity factor such as P retention capacity interacted positively with P dissolution and promoted PR dissolution effectively. Soil texture factors, such as sand and silt content, soil acidity factors such as pH, and exchangeable Ca decreased PR dissolution.

Concerted and stepwise mechanisms in cycloaddition reactions: potential surfaces and isotope effects

International Nuclear Information System (INIS)

Houk, K.N.; Yi Li; Storer, Joey; Raimondi, Laura; Beno, Brett

1994-01-01

CASSCF/6-31G * calculations have been performed on concerted and stepwise Diels-Alder reactions of butadiene with ethene, the dimerization of butadiene, and the dimerization of cyclobutadiene. The relative energies of concerted and stepwise mechanisms are compared, and the factors influencing these ''energies of concert'' are discussed. The comparison of calculated isotope effects to experimental data provides support for theoretical results. (Author)

A water quality index model using stepwise regression and neural networks models for the Piabanha River basin in Rio de Janeiro, Brazil

Science.gov (United States)

Villas Boas, M. D.; Olivera, F.; Azevedo, J. S.

2013-12-01

The evaluation of water quality through 'indexes' is widely used in environmental sciences. There are a number of methods available for calculating water quality indexes (WQI), usually based on site-specific parameters. In Brazil, WQI were initially used in the 1970s and were adapted from the methodology developed in association with the National Science Foundation (Brown et al, 1970). Specifically, the WQI 'IQA/SCQA', developed by the Institute of Water Management of Minas Gerais (IGAM), is estimated based on nine parameters: Temperature Range, Biochemical Oxygen Demand, Fecal Coliforms, Nitrate, Phosphate, Turbidity, Dissolved Oxygen, pH and Electrical Conductivity. The goal of this study was to develop a model for calculating the IQA/SCQA, for the Piabanha River basin in the State of Rio de Janeiro (Brazil), using only the parameters measurable by a Multiparameter Water Quality Sonde (MWQS) available in the study area. These parameters are: Dissolved Oxygen, pH and Electrical Conductivity. The use of this model will allow to further the water quality monitoring network in the basin, without requiring significant increases of resources. The water quality measurement with MWQS is less expensive than the laboratory analysis required for the other parameters. The water quality data used in the study were obtained by the Geological Survey of Brazil in partnership with other public institutions (i.e. universities and environmental institutes) as part of the project "Integrated Studies in Experimental and Representative Watersheds". Two models were developed to correlate the values of the three measured parameters and the IQA/SCQA values calculated based on all nine parameters. The results were evaluated according to the following validation statistics: coefficient of determination (R2), Root Mean Square Error (RMSE), Akaike information criterion (AIC) and Final Prediction Error (FPE). The first model was a linear stepwise regression between three independent variables

Crude Oil Price Forecasting Based on Hybridizing Wavelet Multiple Linear Regression Model, Particle Swarm Optimization Techniques, and Principal Component Analysis

Directory of Open Access Journals (Sweden)

Ani Shabri

2014-01-01

Full Text Available Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI, has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.

Cytopathologic differential diagnosis of low-grade urothelial carcinoma and reactive urothelial proliferation in bladder washings: a logistic regression analysis.

Science.gov (United States)

Cakir, Ebru; Kucuk, Ulku; Pala, Emel Ebru; Sezer, Ozlem; Ekin, Rahmi Gokhan; Cakmak, Ozgur

2017-05-01

Conventional cytomorphologic assessment is the first step to establish an accurate diagnosis in urinary cytology. In cytologic preparations, the separation of low-grade urothelial carcinoma (LGUC) from reactive urothelial proliferation (RUP) can be exceedingly difficult. The bladder washing cytologies of 32 LGUC and 29 RUP were reviewed. The cytologic slides were examined for the presence or absence of the 28 cytologic features. The cytologic criteria showing statistical significance in LGUC were increased numbers of monotonous single (non-umbrella) cells, three-dimensional cellular papillary clusters without fibrovascular cores, irregular bordered clusters, atypical single cells, irregular nuclear overlap, cytoplasmic homogeneity, increased N/C ratio, pleomorphism, nuclear border irregularity, nuclear eccentricity, elongated nuclei, and hyperchromasia (p ˂ 0.05), and the cytologic criteria showing statistical significance in RUP were inflammatory background, mixture of small and large urothelial cells, loose monolayer aggregates, and vacuolated cytoplasm (p ˂ 0.05). When these variables were subjected to a stepwise logistic regression analysis, four features were selected to distinguish LGUC from RUP: increased numbers of monotonous single (non-umbrella) cells, increased nuclear cytoplasmic ratio, hyperchromasia, and presence of small and large urothelial cells (p = 0.0001). By this logistic model of the 32 cases with proven LGUC, the stepwise logistic regression analysis correctly predicted 31 (96.9%) patients with this diagnosis, and of the 29 patients with RUP, the logistic model correctly predicted 26 (89.7%) patients as having this disease. There are several cytologic features to separate LGUC from RUP. Stepwise logistic regression analysis is a valuable tool for determining the most useful cytologic criteria to distinguish these entities. © 2017 APMIS. Published by John Wiley & Sons Ltd.

In vitro production of buffalo embryos from stepwise vitrified immature oocytes.

Science.gov (United States)

Abd-Allah, Saber Mohammed

2009-01-01

This study was conducted to produce buffalo embryos in vitro from stepwise vitrified immature oocytes. Cumulus oocyte complexes (COCs) were obtained from the ovaries of slaughtered buffalo and were collected from the local abattoir. Selected COCs were exposed to a vitrification solution consisting of 40% ethylene glycol (EG) plus 0.3 M trehalose and 20% polyvinyl pyrrolidone (PVP) for 1 min and loaded in 0.25 ml plastic mini-straws containing 100 microl of 10% sucrose. The loaded cryostraws were cryopreserved by stepwise vitrification and were stored in liquid nitrogen for 4 to 6 months. Data analysis revealed a high percentage of post-thawing morphologically normal immature oocytes (80.7%) with a low percentage of damaged oocytes. There were no significant differences in the maturation (82.1%), cleavage (47.6%) and buffalo embryo development (15.4%) produced by the stepwise vitrified immature oocytes in comparison to the three observations in fresh oocytes (88.3%, 50.4% and 19.4%, respectively, p<0.05).

In vitro production of buffalo embryos from stepwise vitrified immature oocytes

Directory of Open Access Journals (Sweden)

Saber Mohammed Abd-Allah

2009-09-01

Full Text Available This study was conducted to produce buffalo embryos in vitro from stepwise vitrified immature oocytes. Cumulus oocyte complexes (COCs were obtained from the ovaries of slaughtered buffalo and were collected from the local abattoir. Selected COCs were exposed to a vitrification solution consisting of 40% ethylene glycol (EG plus 0.3 M trehalose and 20% polyvinyl pyrrolidone (PVP for 1 min and loaded in 0.25 ml plastic mini-straws containing 100 µl of 10% sucrose. The loaded cryostraws were cryopreserved by stepwise vitrification and were stored in liquid nitrogen for 4 to 6 months. Data analysis revealed a high percentage of post-thawing morphologically normal immature oocytes (80.7% with a low percentage of damaged oocytes. There were no significant differences in the maturation (82.1%, cleavage (47.6% and buffalo embryo development (15.4% produced by the stepwise vitrified immature oocytes in comparison to the three observations in fresh oocytes (88.3%, 50.4% and 19.4%, respectively, p<0.05.

A Data Forward Stepwise Fitting Algorithm Based on Orthogonal Function System

Directory of Open Access Journals (Sweden)

Li Han-Ju

2017-01-01

Full Text Available Data fitting is the main method of functional data analysis, and it is widely used in the fields of economy, social science, engineering technology and so on. Least square method is the main method of data fitting, but the least square method is not convergent, no memory property, big fitting error and it is easy to over fitting. Based on the orthogonal trigonometric function system, this paper presents a data forward stepwise fitting algorithm. This algorithm takes forward stepwise fitting strategy, each time using the nearest base function to fit the residual error generated by the previous base function fitting, which makes the residual mean square error minimum. In this paper, we theoretically prove the convergence, the memory property and the fitting error diminishing character for the algorithm. Experimental results show that the proposed algorithm is effective, and the fitting performance is better than that of the least square method and the forward stepwise fitting algorithm based on the non-orthogonal function system.

Stepwise Analysis of Differential Item Functioning Based on Multiple-Group Partial Credit Model.

Science.gov (United States)

Muraki, Eiji

1999-01-01

Extended an Item Response Theory (IRT) method for detection of differential item functioning to the partial credit model and applied the method to simulated data using a stepwise procedure. Then applied the stepwise DIF analysis based on the multiple-group partial credit model to writing trend data from the National Assessment of Educational…

Identification of cotton properties to improve yarn count quality by using regression analysis

International Nuclear Information System (INIS)

Amin, M.; Ullah, M.; Akbar, A.

2014-01-01

Identification of raw material characteristics towards yarn count variation was studied by using statistical techniques. Regression analysis is used to meet the objective. Stepwise regression is used for mode) selection, and coefficient of determination and mean squared error (MSE) criteria are used to identify the contributing factors of cotton properties for yam count. Statistical assumptions of normality, autocorrelation and multicollinearity are evaluated by using probability plot, Durbin Watson test, variance inflation factor (VIF), and then model fitting is carried out. It is found that, invisible (INV), nepness (Nep), grayness (RD), cotton trash (TR) and uniformity index (VI) are the main contributing cotton properties for yarn count variation. The results are also verified by Pareto chart. (author)

Cushing's syndrome: Stepwise approach to diagnosis

OpenAIRE

Lila, Anurag R.; Sarathi, Vijaya; Jagtap, Varsha S.; Bandgar, Tushar; Menon, Padmavathy; Shah, Nalini S.

2011-01-01

The projected prevalence of Cushing′s syndrome (CS) inclusive of subclinical cases in the adult population ranges from 0.2-2% and it may no longer be considered as an orphan disease (2-3 cases/million/year). The recognition of CS by physicians is important for early diagnosis and treatment. Late-night salivary cortisol, dexamethasone suppressiontesti, or 24-h urine free cortisol are good screening tests. Positively screened cases need stepwise evaluation by an endocrinologist. This paper disc...

Principal Covariates Clusterwise Regression (PCCR) : Accounting for multicollinearity and population heterogeneity in hierarchically organized data.

NARCIS (Netherlands)

Wilderjans, Tom F.; Van de Gaer, E.; Kiers, H.A.L.; Van Mechelen, Iven; Ceulemans, Eva

In the behavioral sciences, many research questions pertain to a regression problem in that one wants to predict a criterion on the basis of a number of predictors. Although in many cases, ordinary least squares regression will suffice, sometimes the prediction problem is more challenging, for three

Non-Invasive Methodology to Estimate Polyphenol Content in Extra Virgin Olive Oil Based on Stepwise Multilinear Regression.

Science.gov (United States)

Martínez Gila, Diego Manuel; Cano Marchal, Pablo; Gómez Ortega, Juan; Gámez García, Javier

2018-03-25

Normally the olive oil quality is assessed by chemical analysis according to international standards. These norms define chemical and organoleptic markers, and depending on the markers, the olive oil can be labelled as lampante, virgin, or extra virgin olive oil (EVOO), the last being an indicator of top quality. The polyphenol content is related to EVOO organoleptic features, and different scientific works have studied the positive influence that these compounds have on human health. The works carried out in this paper are focused on studying relations between the polyphenol content in olive oil samples and its spectral response in the near infrared spectra. In this context, several acquisition parameters have been assessed to optimize the measurement process within the virgin olive oil production process. The best regression model reached a mean error value of 156.14 mg/kg in leave one out cross validation, and the higher regression coefficient was 0.81 through holdout validation.

Non-Invasive Methodology to Estimate Polyphenol Content in Extra Virgin Olive Oil Based on Stepwise Multilinear Regression

Directory of Open Access Journals (Sweden)

Diego Manuel Martínez Gila

2018-03-01

Full Text Available Normally the olive oil quality is assessed by chemical analysis according to international standards. These norms define chemical and organoleptic markers, and depending on the markers, the olive oil can be labelled as lampante, virgin, or extra virgin olive oil (EVOO, the last being an indicator of top quality. The polyphenol content is related to EVOO organoleptic features, and different scientific works have studied the positive influence that these compounds have on human health. The works carried out in this paper are focused on studying relations between the polyphenol content in olive oil samples and its spectral response in the near infrared spectra. In this context, several acquisition parameters have been assessed to optimize the measurement process within the virgin olive oil production process. The best regression model reached a mean error value of 156.14 mg/kg in leave one out cross validation, and the higher regression coefficient was 0.81 through holdout validation.

BRGLM, Interactive Linear Regression Analysis by Least Square Fit

International Nuclear Information System (INIS)

Ringland, J.T.; Bohrer, R.E.; Sherman, M.E.

1985-01-01

1 - Description of program or function: BRGLM is an interactive program written to fit general linear regression models by least squares and to provide a variety of statistical diagnostic information about the fit. Stepwise and all-subsets regression can be carried out also. There are facilities for interactive data management (e.g. setting missing value flags, data transformations) and tools for constructing design matrices for the more commonly-used models such as factorials, cubic Splines, and auto-regressions. 2 - Method of solution: The least squares computations are based on the orthogonal (QR) decomposition of the design matrix obtained using the modified Gram-Schmidt algorithm. 3 - Restrictions on the complexity of the problem: The current release of BRGLM allows maxima of 1000 observations, 99 variables, and 3000 words of main memory workspace. For a problem with N observations and P variables, the number of words of main memory storage required is MAX(N*(P+6), N*P+P*P+3*N, and 3*P*P+6*N). Any linear model may be fit although the in-memory workspace will have to be increased for larger problems

Principal components analysis in clinical studies.

Science.gov (United States)

Zhang, Zhongheng; Castelló, Adela

2017-09-01

In multivariate analysis, independent variables are usually correlated to each other which can introduce multicollinearity in the regression models. One approach to solve this problem is to apply principal components analysis (PCA) over these variables. This method uses orthogonal transformation to represent sets of potentially correlated variables with principal components (PC) that are linearly uncorrelated. PCs are ordered so that the first PC has the largest possible variance and only some components are selected to represent the correlated variables. As a result, the dimension of the variable space is reduced. This tutorial illustrates how to perform PCA in R environment, the example is a simulated dataset in which two PCs are responsible for the majority of the variance in the data. Furthermore, the visualization of PCA is highlighted.

Modelling subject-specific childhood growth using linear mixed-effect models with cubic regression splines.

Science.gov (United States)

Grajeda, Laura M; Ivanescu, Andrada; Saito, Mayuko; Crainiceanu, Ciprian; Jaganath, Devan; Gilman, Robert H; Crabtree, Jean E; Kelleher, Dermott; Cabrera, Lilia; Cama, Vitaliano; Checkley, William

2016-01-01

Childhood growth is a cornerstone of pediatric research. Statistical models need to consider individual trajectories to adequately describe growth outcomes. Specifically, well-defined longitudinal models are essential to characterize both population and subject-specific growth. Linear mixed-effect models with cubic regression splines can account for the nonlinearity of growth curves and provide reasonable estimators of population and subject-specific growth, velocity and acceleration. We provide a stepwise approach that builds from simple to complex models, and account for the intrinsic complexity of the data. We start with standard cubic splines regression models and build up to a model that includes subject-specific random intercepts and slopes and residual autocorrelation. We then compared cubic regression splines vis-à-vis linear piecewise splines, and with varying number of knots and positions. Statistical code is provided to ensure reproducibility and improve dissemination of methods. Models are applied to longitudinal height measurements in a cohort of 215 Peruvian children followed from birth until their fourth year of life. Unexplained variability, as measured by the variance of the regression model, was reduced from 7.34 when using ordinary least squares to 0.81 (p linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p modeled with a first order continuous autoregressive error term as evidenced by the variogram of the residuals and by a lack of association among residuals. The final model provides a parametric linear regression equation for both estimation and prediction of population- and individual-level growth in height. We show that cubic regression splines are superior to linear regression splines for the case of a small number of knots in both estimation and prediction with the full linear mixed effect model (AIC 19,352 vs. 19

Research on the multiple linear regression in non-invasive blood glucose measurement.

Science.gov (United States)

Zhu, Jianming; Chen, Zhencheng

2015-01-01

A non-invasive blood glucose measurement sensor and the data process algorithm based on the metabolic energy conservation (MEC) method are presented in this paper. The physiological parameters of human fingertip can be measured by various sensing modalities, and blood glucose value can be evaluated with the physiological parameters by the multiple linear regression analysis. Five methods such as enter, remove, forward, backward and stepwise in multiple linear regression were compared, and the backward method had the best performance. The best correlation coefficient was 0.876 with the standard error of the estimate 0.534, and the significance was 0.012 (sig. regression equation was valid. The Clarke error grid analysis was performed to compare the MEC method with the hexokinase method, using 200 data points. The correlation coefficient R was 0.867 and all of the points were located in Zone A and Zone B, which shows the MEC method provides a feasible and valid way for non-invasive blood glucose measurement.

The comparison of partial least squares and principal component regression in simultaneous spectrophotometric determination of ascorbic acid, dopamine and uric acid in real samples

Directory of Open Access Journals (Sweden)

Habiboallah Khajehsharifi

2017-05-01

Full Text Available Partial least squares (PLS1 and principal component regression (PCR are two multivariate calibration methods that allow simultaneous determination of several analytes in spite of their overlapping spectra. In this research, a spectrophotometric method using PLS1 is proposed for the simultaneous determination of ascorbic acid (AA, dopamine (DA and uric acid (UA. The linear concentration ranges for AA, DA and UA were 1.76–47.55, 0.57–22.76 and 1.68–28.58 (in μg mL−1, respectively. However, PLS1 and PCR were applied to design calibration set based on absorption spectra in the 250–320 nm range for 36 different mixtures of AA, DA and UA, in all cases, the PLS1 calibration method showed more quantitative prediction ability than PCR method. Cross validation method was used to select the optimum number of principal components (NPC. The NPC for AA, DA and UA was found to be 4 by PLS1 and 5, 12, 8 by PCR. Prediction error sum of squares (PRESS of AA, DA and UA were 1.2461, 1.1144, 2.3104 for PLS1 and 11.0563, 1.3819, 4.0956 for PCR, respectively. Satisfactory results were achieved for the simultaneous determination of AA, DA and UA in some real samples such as human urine, serum and pharmaceutical formulations.

Stepwise Diagnosis for Rotating Machinery Using Force Identification Approach

Directory of Open Access Journals (Sweden)

Shozo Kawamura

2012-01-01

Full Text Available Machine condition monitoring and diagnosis have become increasingly important, and the application of these processes has been widely investigated. The authors previously proposed a stepwise diagnosis method for a beam structure. In that method, the location of the abnormality is first estimated using the force identification approach, and then the cause of the abnormality is identified. In this study, the stepwise diagnosis method was improved specifically for rotating machinery. The applicability of the proposed method was checked by using the experimental data. In the case of a rotor system with unbalance, it was shown that the location of the abnormality and its severity could be identified, and, in the case of a rotor system with stationary rubbing, the location of the abnormality could be accurately identified. Therefore, it was confirmed that the proposed diagnostic method is feasible for actual application.

Multiple-Objective Stepwise Calibration Using Luca

Science.gov (United States)

Hay, Lauren E.; Umemoto, Makiko

2007-01-01

This report documents Luca (Let us calibrate), a multiple-objective, stepwise, automated procedure for hydrologic model calibration and the associated graphical user interface (GUI). Luca is a wizard-style user-friendly GUI that provides an easy systematic way of building and executing a calibration procedure. The calibration procedure uses the Shuffled Complex Evolution global search algorithm to calibrate any model compiled with the U.S. Geological Survey's Modular Modeling System. This process assures that intermediate and final states of the model are simulated consistently with measured values.

Generating linear regression model to predict motor functions by use of laser range finder during TUG.

Science.gov (United States)

Adachi, Daiki; Nishiguchi, Shu; Fukutani, Naoto; Hotta, Takayuki; Tashiro, Yuto; Morino, Saori; Shirooka, Hidehiko; Nozaki, Yuma; Hirata, Hinako; Yamaguchi, Moe; Yorozu, Ayanori; Takahashi, Masaki; Aoyama, Tomoki

2017-05-01

The purpose of this study was to investigate which spatial and temporal parameters of the Timed Up and Go (TUG) test are associated with motor function in elderly individuals. This study included 99 community-dwelling women aged 72.9 ± 6.3 years. Step length, step width, single support time, variability of the aforementioned parameters, gait velocity, cadence, reaction time from starting signal to first step, and minimum distance between the foot and a marker placed to 3 in front of the chair were measured using our analysis system. The 10-m walk test, five times sit-to-stand (FTSTS) test, and one-leg standing (OLS) test were used to assess motor function. Stepwise multivariate linear regression analysis was used to determine which TUG test parameters were associated with each motor function test. Finally, we calculated a predictive model for each motor function test using each regression coefficient. In stepwise linear regression analysis, step length and cadence were significantly associated with the 10-m walk test, FTSTS and OLS test. Reaction time was associated with the FTSTS test, and step width was associated with the OLS test. Each predictive model showed a strong correlation with the 10-m walk test and OLS test (P motor function test. Moreover, the TUG test time regarded as the lower extremity function and mobility has strong predictive ability in each motor function test. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Matlab implementation of LASSO, LARS, the elastic net and SPCA

DEFF Research Database (Denmark)

2005-01-01

There are a number of interesting variable selection methods available beside the regular forward selection and stepwise selection methods. Such approaches include LASSO (Least Absolute Shrinkage and Selection Operator), least angle regression (LARS) and elastic net (LARS-EN) regression. There al...... exists a method for calculating principal components with sparse loadings. This software package contains Matlab implementations of these functions. The standard implementations of these functions are available as add-on packages in S-Plus and R....

Quantifying Parkinson's disease finger-tapping severity by extracting and synthesizing finger motion properties.

Science.gov (United States)

Sano, Yuko; Kandori, Akihiko; Shima, Keisuke; Yamaguchi, Yuki; Tsuji, Toshio; Noda, Masafumi; Higashikawa, Fumiko; Yokoe, Masaru; Sakoda, Saburo

2016-06-01

We propose a novel index of Parkinson's disease (PD) finger-tapping severity, called "PDFTsi," for quantifying the severity of symptoms related to the finger tapping of PD patients with high accuracy. To validate the efficacy of PDFTsi, the finger-tapping movements of normal controls and PD patients were measured by using magnetic sensors, and 21 characteristics were extracted from the finger-tapping waveforms. To distinguish motor deterioration due to PD from that due to aging, the aging effect on finger tapping was removed from these characteristics. Principal component analysis (PCA) was applied to the age-normalized characteristics, and principal components that represented the motion properties of finger tapping were calculated. Multiple linear regression (MLR) with stepwise variable selection was applied to the principal components, and PDFTsi was calculated. The calculated PDFTsi indicates that PDFTsi has a high estimation ability, namely a mean square error of 0.45. The estimation ability of PDFTsi is higher than that of the alternative method, MLR with stepwise regression selection without PCA, namely a mean square error of 1.30. This result suggests that PDFTsi can quantify PD finger-tapping severity accurately. Furthermore, the result of interpreting a model for calculating PDFTsi indicated that motion wideness and rhythm disorder are important for estimating PD finger-tapping severity.

Enhanced eumelanin emission by stepwise three-photon excitation

Science.gov (United States)

Kerimo, Josef; Rajadhyaksha, Milind; DiMarzio, Charles A.

2011-03-01

Eumelanin fluorescence from Sepia officinalis and black human hair was activated with near-infrared radiation and multiphoton excitation. A third order multiphoton absorption by a step-wise process appears to be the underlying mechanism. The activation was caused by a photochemical process since it could not be reproduced by simple heating. Both fluorescence and brightfield imaging indicate the near-infrared irradiation caused photodamage to the eumelanin and the activated emission originated from the photodamaged region. At least two different components with about thousand-fold enhanced fluorescence were activated and could be distinguished by their excitation properties. One component was excited with wavelengths in the visible region and exhibited linear absorption dependence. The second component could be excited with near-infrared wavelengths and had a third order dependence on the laser power. The third order dependence is explained by a step-wise excited state absorption (ESA) process since it could be observed equally with the CW and femtosecond lasers. The new method for photoactivating the eumelanin fluorescence was used to map the melanin content in human hair.

A stepwise protocol for the treatment of refractory gastroesophageal reflux-induced chronic cough

Science.gov (United States)

Xu, Xianghuai; Lv, Hanjing; Yu, Li; Chen, Qiang; Liang, Siwei

2016-01-01

Background Refractory gastroesophageal reflux-induced chronic cough (GERC) is difficult to manage. The purpose of the study is to evaluate the efficacy of a novel stepwise protocol for treating this condition. Methods A total of 103 consecutive patients with suspected refractory reflux-induced chronic cough failing to a standard anti-reflux therapy were treated with a stepwise therapy. Treatment commences with high-dose omeprazole and, if necessary, is escalated to subsequent sequential treatment with ranitidine and finally baclofen. The primary end-point was overall cough resolution, and the secondary end-point was cough resolution after each treatment step. Results High-dose omeprazole eliminated or improved cough in 28.1% of patients (n=29). Further stepwise of treatment with the addition of ranitide yielded a favorable response in an additional 12.6% (n=13) of patients, and subsequent escalation to baclofen provoked response in another 36.9% (n=38) of patients. Overall, this stepwise protocol was successful in 77.6% (n=80) of patients. The diurnal cough symptom score fell from 3 [1] to 1 [0] (Z=6.316, P=0.000), and the nocturnal cough symptom score decreased from 1 [1] to 0 [1] (Z=–4.511, P=0.000), with a corresponding reduction in the Gastroesophageal Reflux Diagnostic Questionnaire score from 8.6±1.7 to 6.8±0.7 (t=3.612, P=0.000). Conversely, the cough threshold C2 to capsaicin was increased from 0.49 (0.49) µmol/L to 1.95 (2.92) µmol/L (Z=–5.892, P=0.000), and the cough threshold C5 was increased from 1.95 (2.92) µmol/L to 7.8 (5.85) µmol/L (Z=–5.171, P=0.000). Conclusions Sequential stepwise anti-reflux therapy is a useful therapeutic strategy for refractory reflux-induced chronic cough. PMID:26904227

Fourth-order Perturbed Eigenvalue Equation for Stepwise Damage Detection of Aeroplane Wing

Directory of Open Access Journals (Sweden)

Wong Chun Nam

2016-01-01

Full Text Available Perturbed eigenvalue equations up to fourth-order are established to detect structural damage in aeroplane wing. Complete set of perturbation terms including orthogonal and non-orthogonal coefficients are computed using perturbed eigenvalue and orthonormal equations. Then the perturbed eigenparameters are optimized using BFGS approach. Finite element model with small to large stepwise damage is used to represent actual aeroplane wing. In small damaged level, termination number is the same for both approaches, while rms errors and termination d-norms are very close. For medium damaged level, termination number is larger for third-order perturbation with lower d-norm and smaller rms error. In large damaged level, termination number is much larger for third-order perturbation with same d-norm and larger rms error. These trends are more significant as the damaged level increases. As the stepwise damage effect increases with damage level, the increase in stepwise effect leads to the increase in model order. Hence, fourth-order perturbation is more accurate to estimate the model solution.

Porous media fracturing dynamics: stepwise crack advancement and fluid pressure oscillations

Science.gov (United States)

Cao, Toan D.; Hussain, Fazle; Schrefler, Bernhard A.

2018-02-01

We present new results explaining why fracturing in saturated porous media is not smooth and continuous but is a distinct stepwise process concomitant with fluid pressure oscillations. All exact solutions and almost all numerical models yield smooth fracture advancement and fluid pressure evolution, while recent experimental results, mainly from the oil industry, observation from geophysics and a very few numerical results for the quasi-static case indeed reveal the stepwise phenomenon. We summarize first these new experiments and these few numerical solutions for the quasi-static case. Both mechanical loading and pressure driven fractures are considered because their behaviours differ in the direction of the pressure jumps. Then we explore stepwise crack tip advancement and pressure fluctuations in dynamic fracturing with a hydro-mechanical model of porous media based on the Hybrid Mixture Theory. Full dynamic analyses of examples dealing with both hydraulic fracturing and mechanical loading are presented. The stepwise fracture advancement is confirmed in the dynamic setting as well as in the pressure fluctuations, but there are substantial differences in the frequency contents of the pressure waves in the two loading cases. Comparison between the quasi-static and fully dynamic solutions reveals that the dynamic response gives much more information such as the type of pressure oscillations and related frequencies and should be applied whenever there is a doubt about inertia forces playing a role - the case in most fracturing events. In the absence of direct relevant dynamic tests on saturated media some experimental results on dynamic fracture in dry materials, a fast hydraulic fracturing test and observations from geophysics confirm qualitatively the obtained results such as the type of pressure oscillations and the substantial difference in the behaviour under the two loading cases.

Cloning and Characterizing Genes Involved in Monoterpene Induced Mammary Tumor Regression.

Science.gov (United States)

1996-10-01

AD GRANT NUMBER DAMDI7-94-J-4041 TITLE: Cloning and Characterizing Genes Involved in Monoterpene Induced Mammary Tumor Regression PRINCIPAL...October 1996 Annual (1 Sep 95 - 31 Aug 96) 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS Cloning and Characterizing Genes Involved in Monoterpene Induced... Monoterpene -induced/repressed genes were identified in regressing rat mammary carcinomas treated with dietary limonene using a newly developed method

Stepwise innovation adoption : a neglected concept in innovation research

NARCIS (Netherlands)

Huizingh, K.R.E.; Brand, M.J.

2009-01-01

Most innovation researchers tend to consider innovation adoption as a binary process, implying that companies have either adopted an innovation or not. In this paper we focus on e-commerce as an innovation that can be adopted stepwise. We distinguish between two levels of e-commerce, basic and

Technique of ICP monitored stepwise intracranial decompression effectively reduces postoperative complications of severe bifrontal contusion

Directory of Open Access Journals (Sweden)

Guan eSun

2016-04-01

Full Text Available Background Bifrontal contusion is a common clinical brain injury. In the early stage, it is often mild, but it progresses rapidly and frequently worsens suddenly. This condition can become life threatening and therefore requires surgery. Conventional decompression craniectomy is the commonly used treatment method. In this study, the effect of ICP monitored stepwise intracranial decompression surgery on the prognosis of patients with acute severe bifrontal contusion was investigated. Method A total of 136 patients with severe bifrontal contusion combined with deteriorated intracranial hypertension admitted from March 2001 to March 2014 in our hospital were selected and randomly divided into two groups, i.e., a conventional decompression group and an intracranial pressure (ICP monitored stepwise intracranial decompression group (68 patients each, to conduct a retrospective study. The incidence rates of acute intraoperative encephalocele, delayed hematomas, and postoperative cerebral infarctions and the Glasgow outcome scores (GOSs 6 months after the surgery were compared between the two groups.Results (1 The incidence rates of acute encephalocele and contralateral delayed epidural hematoma in the stepwise decompression surgery group were significantly lower than those in the conventional decompression group; the differences were statistically significant (P < 0.05; (2 6 months after the surgery, the incidence of vegetative state and mortality in the stepwise decompression group were significantly lower than those in the conventional decompression group (P < 0.05; the rate of favorable prognosis in the stepwise decompression group was also significantly higher than that in the conventional decompression group (P < 0.05.Conclusions The ICP monitored stepwise intracranial decompression technique reduced the perioperative complications of traumatic brain injury through the gradual release of intracranial pressure and was beneficial to the prognosis of

Stepwise radical cation Diels-Alder reaction via multiple pathways.

Science.gov (United States)

Shimizu, Ryo; Okada, Yohei; Chiba, Kazuhiro

2018-01-01

Herein we disclose the radical cation Diels-Alder reaction of aryl vinyl ethers by electrocatalysis, which is triggered by an oxidative SET process. The reaction clearly proceeds in a stepwise fashion, which is a rare mechanism in this class. We also found that two distinctive pathways, including "direct" and "indirect", are possible to construct the Diels-Alder adduct.

Visible Leading: Principal Academy Connects and Empowers Principals

Science.gov (United States)

Hindman, Jennifer; Rozzelle, Jan; Ball, Rachel; Fahey, John

2015-01-01

The School-University Research Network (SURN) Principal Academy at the College of William & Mary in Williamsburg, Virginia, has a mission to build a leadership development program that increases principals' instructional knowledge and develops mentor principals to sustain the program. The academy is designed to connect and empower principals…

Stepwise dehydrogenation of ammonia on Fcc-Co surfaces: A DFT study

Energy Technology Data Exchange (ETDEWEB)

Ma, F.F.; Ma, S.H., E-mail: mash.phy@htu.edu.cn; Jiao, Z.Y.; Dai, X.Q.

2017-05-31

Highlights: • On Co surfaces, oxygen atom not only strengthens ammonia-substrate interaction but also facilitates ammonia dissociation on the Co surfaces. • Pre-adsorbed O atom significantly promotes the stepwise dehydrogenation of ammonia on Co(110), giving rise to N atom strongly binding with the surface. • The dissociation of NH appears to be the rate-determining step on O-covered Co(111) and Co(100) surfaces. • The species N and NH produced in ammonia dehydrogenation are likely responsible for cobalt catalyst deactivation in the excess of oxygen atom. - Abstract: The stepwise dehydrogenation of ammonia on clean and O-covered Co surfaces have been studied by performing density functional theory (DFT) calculations. It is found that the interaction of species NH{sub x} (x = 0–3) with the Co surfaces become stronger with its further dehydrogenation, and oxygen atom not only strengthens ammonia-substrate interaction but also facilitates ammonia dissociation. Specifically, pre-adsorbed O atom significantly promotes the stepwise dehydrogenation of ammonia on Co(110), giving rise to N atom strongly binding with the surface. In contrast, the dissociation of NH appears to be the rate-determining step on O-covered Co(111) and Co(100) surfaces, due to the high energy barriers. And present results demonstrate that the species N and NH produced in ammonia dehydrogenation are likely responsible for cobalt catalyst deactivation in the excess of oxygen atom.

Stepwise dehydrogenation of ammonia on Fcc-Co surfaces: A DFT study

International Nuclear Information System (INIS)

Ma, F.F.; Ma, S.H.; Jiao, Z.Y.; Dai, X.Q.

2017-01-01

Highlights: • On Co surfaces, oxygen atom not only strengthens ammonia-substrate interaction but also facilitates ammonia dissociation on the Co surfaces. • Pre-adsorbed O atom significantly promotes the stepwise dehydrogenation of ammonia on Co(110), giving rise to N atom strongly binding with the surface. • The dissociation of NH appears to be the rate-determining step on O-covered Co(111) and Co(100) surfaces. • The species N and NH produced in ammonia dehydrogenation are likely responsible for cobalt catalyst deactivation in the excess of oxygen atom. - Abstract: The stepwise dehydrogenation of ammonia on clean and O-covered Co surfaces have been studied by performing density functional theory (DFT) calculations. It is found that the interaction of species NH x (x = 0–3) with the Co surfaces become stronger with its further dehydrogenation, and oxygen atom not only strengthens ammonia-substrate interaction but also facilitates ammonia dissociation. Specifically, pre-adsorbed O atom significantly promotes the stepwise dehydrogenation of ammonia on Co(110), giving rise to N atom strongly binding with the surface. In contrast, the dissociation of NH appears to be the rate-determining step on O-covered Co(111) and Co(100) surfaces, due to the high energy barriers. And present results demonstrate that the species N and NH produced in ammonia dehydrogenation are likely responsible for cobalt catalyst deactivation in the excess of oxygen atom.

An Inter-Networking Mechanism with Stepwise Synchronization for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Masayuki Murata

2011-08-01

Full Text Available To realize the ambient information society, multiple wireless networks deployed in the region and devices carried by users are required to cooperate with each other. Since duty cycles and operational frequencies are different among networks, we need a mechanism to allow networks to efficiently exchange messages. For this purpose, we propose a novel inter-networking mechanism where two networks are synchronized with each other in a moderate manner, which we call stepwise synchronization. With our proposal, to bridge the gap between intrinsic operational frequencies, nodes near the border of networks adjust their operational frequencies in a stepwise fashion based on the pulse-coupled oscillator model as a fundamental theory of synchronization. Through simulation experiments, we show that the communication delay and the energy consumption of border nodes are reduced, which enables wireless sensor networks to communicate longer with each other.

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

Directory of Open Access Journals (Sweden)

Hsin-Lun Wu

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

Productivity Enhancement of Solar Still with PV Powered Heating Coil and Chamber Step-Wise Basin

Directory of Open Access Journals (Sweden)

Salah Abdallah

2018-03-01

Full Text Available There is a strong need to improve the productivity of single slope solar still. PV generator powered electrical heater and chamber step-wise design were introduced to the conventional solar still. An experimental study was performed to investigate the effect of adding the above mentioned modifications on the output parameters of the modified solar still. The inclusion of PV-powered heating coil and chamber step-wise design enhanced the productivity of distiller by up to 1098%.

A regression approach for zircaloy-2 in-reactor creep constitutive equations

International Nuclear Information System (INIS)

Yung Liu, Y.; Bement, A.L.

1977-01-01

In this paper the methodology of multiple regressions as applied to zircaloy-2 in-reactor creep data analysis and construction of constitutive equation are illustrated. While the resulting constitutive equation can be used in creep analysis of in-reactor zircaloy structural components, the methodology itself is entirely general and can be applied to any creep data analysis. From data analysis and model development point of views, both the assumption of independence and prior committment to specific model forms are unacceptable. One would desire means which can not only estimate the required parameters directly from data but also provide basis for model selections, viz., one model against others. Basic understanding of the physics of deformation is important in choosing the forms of starting physical model equations, but the justifications must rely on their abilities in correlating the overall data. The promising aspects of multiple regression creep data analysis are briefly outlined as follows: (1) when there are more than one variable involved, there is no need to make the assumption that each variable affects the response independently. No separate normalizations are required either and the estimation of parameters is obtained by solving many simultaneous equations. The number of simultaneous equations is equal to the number of data sets, (2) regression statistics such as R 2 - and F-statistics provide measures of the significance of regression creep equation in correlating the overall data. The relative weights of each variable on the response can also be obtained. (3) Special regression techniques such as step-wise, ridge, and robust regressions and residual plots, etc., provide diagnostic tools for model selections

Aeromagnetic Compensation Algorithm Based on Principal Component Analysis

Directory of Open Access Journals (Sweden)

Peilin Wu

2018-01-01

Full Text Available Aeromagnetic exploration is an important exploration method in geophysics. The data is typically measured by optically pumped magnetometer mounted on an aircraft. But any aircraft produces significant levels of magnetic interference. Therefore, aeromagnetic compensation is important in aeromagnetic exploration. However, multicollinearity of the aeromagnetic compensation model degrades the performance of the compensation. To address this issue, a novel aeromagnetic compensation method based on principal component analysis is proposed. Using the algorithm, the correlation in the feature matrix is eliminated and the principal components are using to construct the hyperplane to compensate the platform-generated magnetic fields. The algorithm was tested using a helicopter, and the obtained improvement ratio is 9.86. The compensated quality is almost the same or slightly better than the ridge regression. The validity of the proposed method was experimentally demonstrated.

Using both principal component analysis and reduced rank regression to study dietary patterns and diabetes in Chinese adults.

Science.gov (United States)

Batis, Carolina; Mendez, Michelle A; Gordon-Larsen, Penny; Sotres-Alvarez, Daniela; Adair, Linda; Popkin, Barry

2016-02-01

We examined the association between dietary patterns and diabetes using the strengths of two methods: principal component analysis (PCA) to identify the eating patterns of the population and reduced rank regression (RRR) to derive a pattern that explains the variation in glycated Hb (HbA1c), homeostasis model assessment of insulin resistance (HOMA-IR) and fasting glucose. We measured diet over a 3 d period with 24 h recalls and a household food inventory in 2006 and used it to derive PCA and RRR dietary patterns. The outcomes were measured in 2009. Adults (n 4316) from the China Health and Nutrition Survey. The adjusted odds ratio for diabetes prevalence (HbA1c≥6·5 %), comparing the highest dietary pattern score quartile with the lowest, was 1·26 (95 % CI 0·76, 2·08) for a modern high-wheat pattern (PCA; wheat products, fruits, eggs, milk, instant noodles and frozen dumplings), 0·76 (95 % CI 0·49, 1·17) for a traditional southern pattern (PCA; rice, meat, poultry and fish) and 2·37 (95 % CI 1·56, 3·60) for the pattern derived with RRR. By comparing the dietary pattern structures of RRR and PCA, we found that the RRR pattern was also behaviourally meaningful. It combined the deleterious effects of the modern high-wheat pattern (high intakes of wheat buns and breads, deep-fried wheat and soya milk) with the deleterious effects of consuming the opposite of the traditional southern pattern (low intakes of rice, poultry and game, fish and seafood). Our findings suggest that using both PCA and RRR provided useful insights when studying the association of dietary patterns with diabetes.

Stepwise withdrawal of inhaled corticosteroids in COPD patients receiving dual bronchodilation

DEFF Research Database (Denmark)

Magnussen, Helgo; Watz, Henrik; Kirsten, Anne

2014-01-01

-controlled fashion, one group of patients continues to receive tiotropium, salmeterol and fluticasone, while the second group initiates stepwise withdrawal of fluticasone. The primary end point is time to first moderate or severe exacerbation following randomized treatment over 52 weeks. Lung function, symptoms...

Stepwise classification of cancer samples using clinical and molecular data

Directory of Open Access Journals (Sweden)

Obulkasim Askar

2011-10-01

Full Text Available Abstract Background Combining clinical and molecular data types may potentially improve prediction accuracy of a classifier. However, currently there is a shortage of effective and efficient statistical and bioinformatic tools for true integrative data analysis. Existing integrative classifiers have two main disadvantages: First, coarse combination may lead to subtle contributions of one data type to be overshadowed by more obvious contributions of the other. Second, the need to measure both data types for all patients may be both unpractical and (cost inefficient. Results We introduce a novel classification method, a stepwise classifier, which takes advantage of the distinct classification power of clinical data and high-dimensional molecular data. We apply classification algorithms to two data types independently, starting with the traditional clinical risk factors. We only turn to relatively expensive molecular data when the uncertainty of prediction result from clinical data exceeds a predefined limit. Experimental results show that our approach is adaptive: the proportion of samples that needs to be re-classified using molecular data depends on how much we expect the predictive accuracy to increase when re-classifying those samples. Conclusions Our method renders a more cost-efficient classifier that is at least as good, and sometimes better, than one based on clinical or molecular data alone. Hence our approach is not just a classifier that minimizes a particular loss function. Instead, it aims to be cost-efficient by avoiding molecular tests for a potentially large subgroup of individuals; moreover, for these individuals a test result would be quickly available, which may lead to reduced waiting times (for diagnosis and hence lower the patients distress. Stepwise classification is implemented in R-package stepwiseCM and available at the Bioconductor website.

Stellar atmospheric parameter estimation using Gaussian process regression

Science.gov (United States)

Bu, Yude; Pan, Jingchang

2015-02-01

As is well known, it is necessary to derive stellar parameters from massive amounts of spectral data automatically and efficiently. However, in traditional automatic methods such as artificial neural networks (ANNs) and kernel regression (KR), it is often difficult to optimize the algorithm structure and determine the optimal algorithm parameters. Gaussian process regression (GPR) is a recently developed method that has been proven to be capable of overcoming these difficulties. Here we apply GPR to derive stellar atmospheric parameters from spectra. Through evaluating the performance of GPR on Sloan Digital Sky Survey (SDSS) spectra, Medium resolution Isaac Newton Telescope Library of Empirical Spectra (MILES) spectra, ELODIE spectra and the spectra of member stars of galactic globular clusters, we conclude that GPR can derive stellar parameters accurately and precisely, especially when we use data preprocessed with principal component analysis (PCA). We then compare the performance of GPR with that of several widely used regression methods (ANNs, support-vector regression and KR) and find that with GPR it is easier to optimize structures and parameters and more efficient and accurate to extract atmospheric parameters.

Stepwise commissioning of a steam boiler with stability guarantees

DEFF Research Database (Denmark)

Johansen, Simon Vestergaard; Kallesøe, Carsten Skovmose; Bendtsen, Jan Dimon

2016-01-01

This paper aims to make the commissioning of an industrial MIMO controller more straightforward by gradually commissioning it from a set of SISO controllers, after the system has been started. For this purpose a stepwise commissioning strategy based on the Youla-Kucera parametrization has been de...... been commissioned from a SISO controller using the developed method on a real steam boiler and measurements show a clear performance improvement after transition....

Step-wise and punctuated genome evolution drive phenotype changes of tumor cells

International Nuclear Information System (INIS)

Stepanenko, Aleksei; Andreieva, Svitlana; Korets, Kateryna; Mykytenko, Dmytro; Huleyuk, Nataliya; Vassetzky, Yegor; Kavsan, Vadym

2015-01-01

Highlights: • There are the step-wise continuous and punctuated phases of cancer genome evolution. • The system stresses during the different phases may lead to very different responses. • Stable transfection of an empty vector can result in genome and phenotype changes. • Functions of a (trans)gene can be opposite/versatile in cells with different genomes. • Contextually, temozolomide can both promote and suppress tumor cell aggressiveness. - Abstract: The pattern of genome evolution can be divided into two phases: the step-wise continuous phase (step-wise clonal evolution, stable dominant clonal chromosome aberrations (CCAs), and low frequency of non-CCAs, NCCAs) and punctuated phase (marked by elevated NCCAs and transitional CCAs). Depending on the phase, system stresses (the diverse CIN promoting factors) may lead to the very different phenotype responses. To address the contribution of chromosome instability (CIN) to phenotype changes of tumor cells, we characterized CCAs/NCCAs of HeLa and HEK293 cells, and their derivatives after genotoxic stresses (a stable plasmid transfection, ectopic expression of cancer-associated CHI3L1 gene or treatment with temozolomide) by conventional cytogenetics, copy number alterations (CNAs) by array comparative genome hybridization, and phenotype changes by cell viability and soft agar assays. Transfection of either the empty vector pcDNA3.1 or pcDNA3.1-CHI3L1 into 293 cells initiated the punctuated genome changes. In contrast, HeLa-CHI3L1 cells demonstrated the step-wise genome changes. Increased CIN correlated with lower viability of 293-pcDNA3.1 cells but higher colony formation efficiency (CFE). Artificial CHI3L1 production in 293-CHI3L1 cells increased viability and further contributed to CFE. The opposite growth characteristics of 293-CHI3L1 and HeLa-CHI3L1 cells were revealed. The effect and function of a (trans)gene can be opposite and versatile in cells with different genetic network, which is defined by

Step-wise and punctuated genome evolution drive phenotype changes of tumor cells

Energy Technology Data Exchange (ETDEWEB)

Stepanenko, Aleksei, E-mail: a.a.stepanenko@gmail.com [Department of Biosynthesis of Nucleic Acids, Institute of Molecular Biology and Genetics, National Academy of Sciences of Ukraine, Kyiv 03680 (Ukraine); Andreieva, Svitlana; Korets, Kateryna; Mykytenko, Dmytro [Department of Biosynthesis of Nucleic Acids, Institute of Molecular Biology and Genetics, National Academy of Sciences of Ukraine, Kyiv 03680 (Ukraine); Huleyuk, Nataliya [Institute of Hereditary Pathology, National Academy of Medical Sciences of Ukraine, Lviv 79008 (Ukraine); Vassetzky, Yegor [CNRS UMR8126, Université Paris-Sud 11, Institut de Cancérologie Gustave Roussy, Villejuif 94805 (France); Kavsan, Vadym [Department of Biosynthesis of Nucleic Acids, Institute of Molecular Biology and Genetics, National Academy of Sciences of Ukraine, Kyiv 03680 (Ukraine)

2015-01-15

Highlights: • There are the step-wise continuous and punctuated phases of cancer genome evolution. • The system stresses during the different phases may lead to very different responses. • Stable transfection of an empty vector can result in genome and phenotype changes. • Functions of a (trans)gene can be opposite/versatile in cells with different genomes. • Contextually, temozolomide can both promote and suppress tumor cell aggressiveness. - Abstract: The pattern of genome evolution can be divided into two phases: the step-wise continuous phase (step-wise clonal evolution, stable dominant clonal chromosome aberrations (CCAs), and low frequency of non-CCAs, NCCAs) and punctuated phase (marked by elevated NCCAs and transitional CCAs). Depending on the phase, system stresses (the diverse CIN promoting factors) may lead to the very different phenotype responses. To address the contribution of chromosome instability (CIN) to phenotype changes of tumor cells, we characterized CCAs/NCCAs of HeLa and HEK293 cells, and their derivatives after genotoxic stresses (a stable plasmid transfection, ectopic expression of cancer-associated CHI3L1 gene or treatment with temozolomide) by conventional cytogenetics, copy number alterations (CNAs) by array comparative genome hybridization, and phenotype changes by cell viability and soft agar assays. Transfection of either the empty vector pcDNA3.1 or pcDNA3.1-CHI3L1 into 293 cells initiated the punctuated genome changes. In contrast, HeLa-CHI3L1 cells demonstrated the step-wise genome changes. Increased CIN correlated with lower viability of 293-pcDNA3.1 cells but higher colony formation efficiency (CFE). Artificial CHI3L1 production in 293-CHI3L1 cells increased viability and further contributed to CFE. The opposite growth characteristics of 293-CHI3L1 and HeLa-CHI3L1 cells were revealed. The effect and function of a (trans)gene can be opposite and versatile in cells with different genetic network, which is defined by

Use of geophysical survey as a predictor of the edaphic properties variability in soils used for livestock production

Directory of Open Access Journals (Sweden)

Nahuel R. Peralta

2015-12-01

Full Text Available The spatial variability in soils used for livestock production (i.e. Natraquoll and Natraqualf at farm and paddock scale is usually very high. Understanding this spatial variation within a field is the first step for site-specific crop management. For this reason, we evaluated whether apparent electrical conductivity (ECa, a widely used proximal soil sensing technology, is a potential estimator of the edaphic variability in these types of soils. ECa and elevation data were collected in a paddock of 16 ha. Elevation was negatively associated with ECa. Geo-referenced soil samples were collected and analyzed for soil organic matter (OM content, pH, the saturation extract electrical conductivity (ECext, available phosphorous (P, and anaerobically incubated Nitrogen (Nan. Relationships between soil properties and ECa were analyzed using regression analysis, principal components analysis (PCA, and stepwise regression. Principal components (PC and the PC-stepwise were used to determine which soil properties have an important influence on ECa. In this experiment elevation was negatively associated with ECa. The data showed that pH, OM, and ECext exhibited a high correlation with ECa (R2=0.76; 0.70 and 0.65, respectively. Whereas P and Nan showed a lower correlation (R2=0.54 and 0.11 respectively. The model resulting from the PC-stepwise regression analysis explained slightly more than 69% of the total variation of the measured ECa, only retaining PC1. Therefore, ECext, pH and OM were considered key latent variables because they substantially influence the relationship between the PC1 and the ECa (loading factors>0.4. Results showed that ECa is associated with the spatial distribution of some important soil properties. Thus, ECa can be used as a support tool to implement site-specific management in soils for livestock use.

Use of geophysical survey as a predictor of the edaphic properties variability in soils used for livestock production

Energy Technology Data Exchange (ETDEWEB)

Peralta, N.R.; Cicore, P.L.; Marino, M.A.; Marques da Silva, J. R.; Costa, J.L.

2015-07-01

The spatial variability in soils used for livestock production (i.e. Natraquoll and Natraqualf) at farm and paddock scale is usually very high. Understanding this spatial variation within a field is the first step for site-specific crop management. For this reason, we evaluated whether apparent electrical conductivity (ECa), a widely used proximal soil sensing technology, is a potential estimator of the edaphic variability in these types of soils. ECa and elevation data were collected in a paddock of 16 ha. Elevation was negatively associated with ECa. Geo-referenced soil samples were collected and analyzed for soil organic matter (OM) content, pH, the saturation extract electrical conductivity (ECext), available phosphorous (P), and anaerobically incubated Nitrogen (Nan). Relationships between soil properties and ECa were analyzed using regression analysis, principal components analysis (PCA), and stepwise regression. Principal components (PC) and the PC-stepwise were used to determine which soil properties have an important influence on ECa. In this experiment elevation was negatively associated with ECa. The data showed that pH, OM, and ECext exhibited a high correlation with ECa (R2=0.76; 0.70 and 0.65, respectively). Whereas P and Nan showed a lower correlation (R2=0.54 and 0.11 respectively). The model resulting from the PC-stepwise regression analysis explained slightly more than 69% of the total variation of the measured ECa, only retaining PC1. Therefore, ECext, pH and OM were considered key latent variables because they substantially influence the relationship between the PC1 and the ECa (loading factors>0.4). Results showed that ECa is associated with the spatial distribution of some important soil properties. Thus, ECa can be used as a support tool to implement site-specific management in soils for livestock use. (Author)

Is there a step-wise migration in Nigeria? A case study of the migrational histories of migrants in Lagos.

Science.gov (United States)

Afolayan, A A

1985-09-01

"The paper sets out to test whether or not the movement pattern of people in Nigeria is step-wise. It examines the spatial order in the country and the movement pattern of people. It then analyzes the survey data and tests for the validity of step-wise migration in the country. The findings show that step-wise migration cannot adequately describe all the patterns observed." The presence of large-scale circulatory migration between rural and urban areas is noted. Ways to decrease the pressure on Lagos by developing intermediate urban areas are considered. excerpt

A novel peak-hopping stepwise feature selection method with application to Raman spectroscopy

International Nuclear Information System (INIS)

McShane, M.J.; Cameron, B.D.; Cote, G.L.; Motamedi, M.; Spiegelman, C.H.

1999-01-01

A new stepwise approach to variable selection for spectroscopy that includes chemical information and attempts to test several spectral regions producing high ranking coefficients has been developed to improve on currently available methods. Existing selection techniques can, in general, be placed into two groups: the first, time-consuming optimization approaches that ignore available information about sample chemistry and require considerable expertise to arrive at appropriate solutions (e.g. genetic algorithms), and the second, stepwise procedures that tend to select many variables in the same area containing redundant information. The algorithm described here is a fast stepwise procedure that uses multiple ranking chains to identify several spectral regions correlated with known sample properties. The multiple-chain approach allows the generation of a final ranking vector that moves quickly away from the initial selection point, testing several areas exhibiting correlation between spectra and composition early in the stepping procedure. Quantitative evidence of the success of this approach as applied to Raman spectroscopy is given in terms of processing speed, number of selected variables, and prediction error in comparison with other selection methods. In this respect, the procedure described here may be considered as a significant evolutionary step in variable selection algorithms. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)

Effects of stepwise gas combustion on NOx generation

International Nuclear Information System (INIS)

Woperane Seredi, A.; Szepesi, E.

1999-01-01

To decrease NO x emission from gas boilers, the combustion process of gas has been modified from continuous combustion to step-wise combustion. In this process the combustion temperature, the temperature peaks in the flame, the residence time of combustion products in the high-temperature zone and the oxygen partial pressure are changed advantageously. Experiments were performed using multistage burners, and the NO x emission was recorded. It was found that the air factor of the primary combustion space has a determining effect on the NO x reduction. (R.P.)

modelling of directed evolution: Implications for experimental design and stepwise evolution

OpenAIRE

Wedge , David C.; Rowe , William; Kell , Douglas B.; Knowles , Joshua

2009-01-01

In silico modelling of directed evolution: Implications for experimental design and stepwise evolution correspondence: Corresponding author. Tel.: +441613065145. (Wedge, David C.) (Wedge, David C.) Manchester Interdisciplinary Biocentre, University of Manchester - 131 Princess Street--> , Manchester--> , M1 7ND--> - UNITED KINGDOM (Wedge, David C.) UNITED KINGDOM (Wedge, David C.) Man...

Improvement of the Performance of Scheduled Stepwise Power Programme Changes within the European Power System

DEFF Research Database (Denmark)

Welfonder, E.; Weissbach, T.; Schulz, U.

2008-01-01

Since the deregulation of the electrical energy market, the technical realisation of power transactions based on energy market contracts often effects large stepwise power programme changes – especially at the change of the hour. Due to mainly economic reasons these stepwise power programme changes...... extended discussions with power plant and power system operators as well as with power plant dispatchers the described issues will be adopted into a VGB-recommendation which shall be published by VGB Powertech for Germany and Europe. Subsequently, it is intended to include the main elements of the VGB...

Structured Additive Regression Models: An R Interface to BayesX

Directory of Open Access Journals (Sweden)

Nikolaus Umlauf

2015-02-01

Full Text Available Structured additive regression (STAR models provide a flexible framework for model- ing possible nonlinear effects of covariates: They contain the well established frameworks of generalized linear models and generalized additive models as special cases but also allow a wider class of effects, e.g., for geographical or spatio-temporal data, allowing for specification of complex and realistic models. BayesX is standalone software package providing software for fitting general class of STAR models. Based on a comprehensive open-source regression toolbox written in C++, BayesX uses Bayesian inference for estimating STAR models based on Markov chain Monte Carlo simulation techniques, a mixed model representation of STAR models, or stepwise regression techniques combining penalized least squares estimation with model selection. BayesX not only covers models for responses from univariate exponential families, but also models from less-standard regression situations such as models for multi-categorical responses with either ordered or unordered categories, continuous time survival data, or continuous time multi-state models. This paper presents a new fully interactive R interface to BayesX: the R package R2BayesX. With the new package, STAR models can be conveniently specified using Rs formula language (with some extended terms, fitted using the BayesX binary, represented in R with objects of suitable classes, and finally printed/summarized/plotted. This makes BayesX much more accessible to users familiar with R and adds extensive graphics capabilities for visualizing fitted STAR models. Furthermore, R2BayesX complements the already impressive capabilities for semiparametric regression in R by a comprehensive toolbox comprising in particular more complex response types and alternative inferential procedures such as simulation-based Bayesian inference.

Multi-type Step-wise group screening designs with unequal A-priori ...

African Journals Online (AJOL)

... design with unequal group sizes and obtain values of the group sizes that minimize the expected number of runs.. Keywords: Group Screening, Group factors, multi-type step-wise group screening, expected number of runs, Optimum group screening designs > East African Journal of Statistics Vol. 1 (1) 2005: pp. 49-67 ...

Stepwise Inquiry into Hard Water in a High School Chemistry Laboratory

Science.gov (United States)

Kakisako, Mami; Nishikawa, Kazuyuki; Nakano, Masayoshi; Harada, Kana S.; Tatsuoka, Tomoyuki; Koga, Nobuyoshi

2016-01-01

This study focuses on the design of a learning program to introduce complexometric titration as a method for determining water hardness in a high school chemistry laboratory. Students are introduced to the different properties and reactions of hard water in a stepwise manner so that they gain the necessary chemical knowledge and conceptual…

Gonadoblastoma: evidence for a stepwise progression to dysgerminoma in a dysgenetic ovary.

Science.gov (United States)

Pauls, Katharina; Franke, Folker E; Büttner, Reinhard; Zhou, Hui

2005-09-01

Gonadoblastomas are neoplasms of dysgenetic gonads which may undergo regression or become overgrown by malignant germ cell tumors (mGCTs). Since little is known about their relationship to normal gonadal development and mGCTs, we studied the phenotype and antigenic profile of gonadoblastomas in comparison with adjacent dysgerminomas and fetal gonads. Three cases of gonadoblastomas and fetal gonads of both sexes were analyzed using oncofetal markers to M2A-antigen (M2A), germ cell alkaline phosphatase (PLAP/GCAP), receptor tyrosine kinase c-kit (c-kit), and somatic angiotensin converting enzyme (sACE) as well as the proliferation marker MIB-1. Morphologically, microfollicular pattern of gonadoblastomas showed a fetal germ cell organization reminiscent of oocytic clusters of fetal ovaries. They contained both cell types, similar to oocytes (M2A-, GCAP-, c-kit+/-, sACE-) and oogonia (M2A+, GCAP+, c-kit+, sACE+). The percentage of germ cells immunoreactive for oncofetal markers and the proliferation index increased from microfollicular over coronary patterns to adjacent dysgerminomas. Supportive cells of gonadoblastomas showed a uniform phenotype (CK18+, vimentin+, sACE+, alpha-inhibin+, M2A-) but in contrast to fetal germ cells lacked a clear equivalence to fetal tissues. Our results show that gonadoblastomas mimic female fetal ovary and exhibit a stepwise progression from follicular pattern to coronary pattern and finally to dysgerminomas.

Neighborhood social capital and crime victimization: comparison of spatial regression analysis and hierarchical regression analysis.

Science.gov (United States)

Takagi, Daisuke; Ikeda, Ken'ichi; Kawachi, Ichiro

2012-11-01

Crime is an important determinant of public health outcomes, including quality of life, mental well-being, and health behavior. A body of research has documented the association between community social capital and crime victimization. The association between social capital and crime victimization has been examined at multiple levels of spatial aggregation, ranging from entire countries, to states, metropolitan areas, counties, and neighborhoods. In multilevel analysis, the spatial boundaries at level 2 are most often drawn from administrative boundaries (e.g., Census tracts in the U.S.). One problem with adopting administrative definitions of neighborhoods is that it ignores spatial spillover. We conducted a study of social capital and crime victimization in one ward of Tokyo city, using a spatial Durbin model with an inverse-distance weighting matrix that assigned each respondent a unique level of "exposure" to social capital based on all other residents' perceptions. The study is based on a postal questionnaire sent to 20-69 years old residents of Arakawa Ward, Tokyo. The response rate was 43.7%. We examined the contextual influence of generalized trust, perceptions of reciprocity, two types of social network variables, as well as two principal components of social capital (constructed from the above four variables). Our outcome measure was self-reported crime victimization in the last five years. In the spatial Durbin model, we found that neighborhood generalized trust, reciprocity, supportive networks and two principal components of social capital were each inversely associated with crime victimization. By contrast, a multilevel regression performed with the same data (using administrative neighborhood boundaries) found generally null associations between neighborhood social capital and crime. Spatial regression methods may be more appropriate for investigating the contextual influence of social capital in homogeneous cultural settings such as Japan. Copyright

Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan

Science.gov (United States)

Hassanzadeh, S.; Hosseinibalam, F.; Omidvari, M.

2008-04-01

Data of seven meteorological variables (relative humidity, wet temperature, dry temperature, maximum temperature, minimum temperature, ground temperature and sun radiation time) and ozone values have been used for statistical analysis. Meteorological variables and ozone values were analyzed using both multiple linear regression and principal component methods. Data for the period 1999-2004 are analyzed jointly using both methods. For all periods, temperature dependent variables were highly correlated, but were all negatively correlated with relative humidity. Multiple regression analysis was used to fit the meteorological variables using the meteorological variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to obtain subsets of the predictor variables to be included in the linear regression model of the meteorological variables. In 1999, 2001 and 2002 one of the meteorological variables was weakly influenced predominantly by the ozone concentrations. However, the model did not predict that the meteorological variables for the year 2000 were not influenced predominantly by the ozone concentrations that point to variation in sun radiation. This could be due to other factors that were not explicitly considered in this study.

Numerical study of radial stepwise fuel load reshuffling traveling wave reactor

International Nuclear Information System (INIS)

Zhang Dalin; Zheng Meiyin; Tian Wenxi; Qiu Suizheng; Su Guanghui

2015-01-01

Traveling wave reactor is a new conceptual fast breeder reactor, which can adopt natural uranium, depleted uranium and thorium directly to realize the self sustainable breeding and burning to achieve very high fuel utilization fraction. Based on the mechanism of traveling wave reactor, a concept of radial stepwise fuel load reshuffling traveling wave reactor was proposed for realistic application. It was combined with the typical design of sodium-cooled fast reactors, with which the asymptotic characteristics of the inwards stepwise fuel load reshuffling were studied numerically in two-dimension. The calculated results show that the asymptotic k_e_f_f parabolically varies with the reshuffling cycle length, while the burnup increases linearly. The highest burnup satisfying the reactor critical condition is 38%. The power peak shifts from the fuel discharging zone (core centre) to the fuel uploading zone (core periphery) and correspondingly the power peaking factor decreases along with the reshuffling cycle length. In addition, at the high burnup case the axial power distribution close to the core centre displays the M-shaped deformation. (authors)

Graph Regularized Meta-path Based Transductive Regression in Heterogeneous Information Network.

Science.gov (United States)

Wan, Mengting; Ouyang, Yunbo; Kaplan, Lance; Han, Jiawei

2015-01-01

A number of real-world networks are heterogeneous information networks, which are composed of different types of nodes and links. Numerical prediction in heterogeneous information networks is a challenging but significant area because network based information for unlabeled objects is usually limited to make precise estimations. In this paper, we consider a graph regularized meta-path based transductive regression model ( Grempt ), which combines the principal philosophies of typical graph-based transductive classification methods and transductive regression models designed for homogeneous networks. The computation of our method is time and space efficient and the precision of our model can be verified by numerical experiments.

Stepwise fluorination - a useful approach for the isotopic analysis of hydrous minerals

Energy Technology Data Exchange (ETDEWEB)

Haimson, M; Knauth, L P [Arizona State Univ., Tempe (USA). Dept. of Geology

1983-09-01

Analytical uncertainties in oxygen isotopic studies of hydrous silica have been investigated using a partial fluorination procedure in which fractional oxygen yields are achieved by reducing the amount of fluorine. Stepwise reaction of opaline silica results in a set of sequential oxygen fractions which show a wide range of delta/sup 18/O values due to variable amounts of water, organic matter, and other impurities. Delta-values for successive fractions in non-biogenic opal systematically increase as water is reacted away and then remain constant to within +- 0.2 per thousand as the remaining silica reacts. Delta-values in biogenic silica increase similarly but then decrease when low /sup 18/O oxide impurities begin to react. The troublesome water component in opal is readily removed by stepwise fluorination. This technique allows more precise oxygen isotope analysis of non-biogenic opal-A, and may improve the analytical precision for biogenic silica and any silicate mineral containing a significant water component.

Stepwise Assembly and Characterization of DNA Linked Two-Color Quantum Dot Clusters.

Science.gov (United States)

Coopersmith, Kaitlin; Han, Hyunjoo; Maye, Mathew M

2015-07-14

The DNA-mediated self-assembly of multicolor quantum dot (QD) clusters via a stepwise approach is described. The CdSe/ZnS QDs were synthesized and functionalized with an amphiphilic copolymer, followed by ssDNA conjugation. At each functionalization step, the QDs were purified via gradient ultracentrifugation, which was found to remove excess polymer and QD aggregates, allowing for improved conjugation yields and assembly reactivity. The QDs were then assembled and disassembled in a stepwise manner at a ssDNA functionalized magnetic colloid, which provided a convenient way to remove unreacted QDs and ssDNA impurities. After assembly/disassembly, the clusters' optical characteristics were studied by fluorescence spectroscopy and the assembly morphology and stoichiometry was imaged via electron microscopy. The results indicate that a significant amount of QD-to-QD energy transfer occurred in the clusters, which was studied as a function of increasing acceptor-to-donor ratios, resulting in increased QD acceptor emission intensities compared to controls.

Influence of plant root morphology and tissue composition on phenanthrene uptake: Stepwise multiple linear regression analysis

International Nuclear Information System (INIS)

Zhan, Xinhua; Liang, Xiao; Xu, Guohua; Zhou, Lixiang

2013-01-01

Polycyclic aromatic hydrocarbons (PAHs) are contaminants that reside mainly in surface soils. Dietary intake of plant-based foods can make a major contribution to total PAH exposure. Little information is available on the relationship between root morphology and plant uptake of PAHs. An understanding of plant root morphologic and compositional factors that affect root uptake of contaminants is important and can inform both agricultural (chemical contamination of crops) and engineering (phytoremediation) applications. Five crop plant species are grown hydroponically in solutions containing the PAH phenanthrene. Measurements are taken for 1) phenanthrene uptake, 2) root morphology – specific surface area, volume, surface area, tip number and total root length and 3) root tissue composition – water, lipid, protein and carbohydrate content. These factors are compared through Pearson's correlation and multiple linear regression analysis. The major factors which promote phenanthrene uptake are specific surface area and lipid content. -- Highlights: •There is no correlation between phenanthrene uptake and total root length, and water. •Specific surface area and lipid are the most crucial factors for phenanthrene uptake. •The contribution of specific surface area is greater than that of lipid. -- The contribution of specific surface area is greater than that of lipid in the two most important root morphological and compositional factors affecting phenanthrene uptake

Female Traditional Principals and Co-Principals: Experiences of Role Conflict and Job Satisfaction

Science.gov (United States)

Eckman, Ellen Wexler; Kelber, Sheryl Talcott

2010-01-01

This paper presents a secondary analysis of survey data focusing on role conflict and job satisfaction of 102 female principals. Data were collected from 51 female traditional principals and 51 female co-principals. By examining the traditional and co-principal leadership models as experienced by female principals, this paper addresses the impact…

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

DEFF Research Database (Denmark)

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

2012-01-01

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

Principal component approach in variance component estimation for international sire evaluation

Directory of Open Access Journals (Sweden)

Jakobsen Jette

2011-05-01

Full Text Available Abstract Background The dairy cattle breeding industry is a highly globalized business, which needs internationally comparable and reliable breeding values of sires. The international Bull Evaluation Service, Interbull, was established in 1983 to respond to this need. Currently, Interbull performs multiple-trait across country evaluations (MACE for several traits and breeds in dairy cattle and provides international breeding values to its member countries. Estimating parameters for MACE is challenging since the structure of datasets and conventional use of multiple-trait models easily result in over-parameterized genetic covariance matrices. The number of parameters to be estimated can be reduced by taking into account only the leading principal components of the traits considered. For MACE, this is readily implemented in a random regression model. Methods This article compares two principal component approaches to estimate variance components for MACE using real datasets. The methods tested were a REML approach that directly estimates the genetic principal components (direct PC and the so-called bottom-up REML approach (bottom-up PC, in which traits are sequentially added to the analysis and the statistically significant genetic principal components are retained. Furthermore, this article evaluates the utility of the bottom-up PC approach to determine the appropriate rank of the (covariance matrix. Results Our study demonstrates the usefulness of both approaches and shows that they can be applied to large multi-country models considering all concerned countries simultaneously. These strategies can thus replace the current practice of estimating the covariance components required through a series of analyses involving selected subsets of traits. Our results support the importance of using the appropriate rank in the genetic (covariance matrix. Using too low a rank resulted in biased parameter estimates, whereas too high a rank did not result in

Effects of constant and stepwise changes in temperature on the species abundance dynamics of four cladocera species

Directory of Open Access Journals (Sweden)

Verbitsky V. B.

2011-09-01

Full Text Available Laboratory experiments with natural zooplankton communities were carried out to study the effects of two contrasting temperature regimes: constant temperature (15, 20, and 25 °C and graded changes in temperature. The graded regime consisted of repeated sustained (three weeks controlled stepwise temperature changes of 5 or 10 °C within 15–25 °C on the population dynamics of four dominant species of lake littoral zooplankton, Daphnia longispina (Müller, 1785, Diaphanosoma brachyurum (Lievin, 1848, Simocephalus vetulus (Müller, 1776 and Chydorus sphaericus (Müller, 1785. The results show that controlled stepwise changes (positive or negative in temperature within the ranges of 15–20, 20–25, and 15–25 °C can exert either stimulating or inhibitory effect (direct or delayed on the development of D. longispina and S. vetulus populations. The development of D. brachyurum and Ch. sphaericus, both more steno-thermophile, was only stimulated by a stable elevated temperature (25 °C. These results support the previously formulated hypothesis that, in determining the ecological temperature optimum of a species within a natural community, it is not enough to define its optimum from constant, cyclic or random temperature fluctuations, but also from unidirectional stepwise changes in temperature. These stepwise changes may also induce prolonged or delayed effects.

Application of genetic algorithm - multiple linear regressions to predict the activity of RSK inhibitors

Directory of Open Access Journals (Sweden)

Avval Zhila Mohajeri

2015-01-01

Full Text Available This paper deals with developing a linear quantitative structure-activity relationship (QSAR model for predicting the RSK inhibition activity of some new compounds. A dataset consisting of 62 pyrazino [1,2-α] indole, diazepino [1,2-α] indole, and imidazole derivatives with known inhibitory activities was used. Multiple linear regressions (MLR technique combined with the stepwise (SW and the genetic algorithm (GA methods as variable selection tools was employed. For more checking stability, robustness and predictability of the proposed models, internal and external validation techniques were used. Comparison of the results obtained, indicate that the GA-MLR model is superior to the SW-MLR model and that it isapplicable for designing novel RSK inhibitors.

A PANEL REGRESSION ANALYSIS OF HUMAN CAPITAL RELEVANCE IN SELECTED SCANDINAVIAN AND SE EUROPEAN COUNTRIES

Directory of Open Access Journals (Sweden)

Filip Kokotovic

2016-06-01

Full Text Available The study of human capital relevance to economic growth is becoming increasingly important taking into account its relevance in many of the Sustainable Development Goals proposed by the UN. This paper conducted a panel regression analysis of selected SE European countries and Scandinavian countries using the Granger causality test and pooled panel regression. In order to test the relevance of human capital on economic growth, several human capital proxy variables were identified. Aside from the human capital proxy variables, other explanatory variables were selected using stepwise regression while the dependant variable was GDP. This paper concludes that there are significant structural differences in the economies of the two observed panels. Of the human capital proxy variables observed, for the panel of SE European countries only life expectancy was statistically significant and it had a negative impact on economic growth, while in the panel of Scandinavian countries total public expenditure on education had a statistically significant positive effect on economic growth. Based upon these results and existing studies, this paper concludes that human capital has a far more significant impact on economic growth in more developed economies.

A stepwise approach for defining the applicability domain of SAR and QSAR models

DEFF Research Database (Denmark)

Dimitrov, Sabcho; Dimitrova, Gergana; Pavlov, Todor

2005-01-01

A stepwise approach for determining the model applicability domain is proposed. Four stages are applied to account for the diversity and complexity of the current SAR/QSAR models, reflecting their mechanistic rationality (including metabolic activation of chemicals) and transparency. General para...

Stepwise radiofrequency ablation of Barrett's esophagus preserves esophageal inner diameter, compliance, and motility

NARCIS (Netherlands)

Beaumont, H.; Gondrie, J. J.; McMahon, B. P.; Pouw, R. E.; Gregersen, H.; Bergman, J. J.; Boeckxstaens, G. E.

2009-01-01

Background and aim: Stepwise endoscopic circumferential and focal radiofrequency ablation is safe and effective for the eradication of Barrett's esophagus. In contrast to other techniques, radiofrequency ablation appears to avoid significant esophageal scarring or stenosis. Our aim was to evaluate

Principal Leadership Style and Teacher Commitment among a Sample of Secondary School Teachers in Barbados

Directory of Open Access Journals (Sweden)

Ian Alwyn Marshall

2015-05-01

Full Text Available In Barbados, the issue of principal leadership and teacher productivity has occupied the attention of teacher unions and educational authorities alike.  The teachers have been calling for principals to be removed while the principals have been arguing for greater autonomy to discipline teachers. This state of affairs has, understandably, adversely impacted teacher commitment levels.  In the literature there is a clear correlation between principal leadership style and teacher commitment, however, it is important to know whether or not the relationship holds true in the context of Barbadian schools. This author is of the view that if teacher commitment levels are to return to those in evidence in effective schools, then attention must be given to the way in which principals exercise their leadership functions. This study was therefore designed to examine in greater detail the relationship between principal leadership style and teacher commitment.  The author employed purposive sampling to survey a cohort of ninety (90 teachers and eleven (11 principals drawn from eleven secondary schools. Results confirmed the relationship between principal leadership style and teacher commitment, and a statistically significant difference in the level of commitment reported by teachers at newer secondary schools and teachers at older secondary schools. Results also indicated that biographical variables moderated the relationship between principal leadership style and teacher commitment. Additionally, the regression model indicated that the principal leadership style sub-variables, in combination, accounted for some variance in the commitment demonstrated by teachers.

Stepwise mechanism of oxidative ammonolysis of propane to acrylonitrile over gallium-antimony oxide catalysts

Energy Technology Data Exchange (ETDEWEB)

Osipova, Z.G.; Sokolovskii, V.D.

1979-03-01

The stepwise mechanism of oxidative ammonolysis of propane to acrylonitrile over gallium-antimony oxide catalysts GaSb/sub 19/O/sub x/, GaSb/sub 3/Ni/sub 1.5/0/sub x/, and GaSb/sub 2.5/Ni/sub 1.5/PW/sub 0//sub 0.25/O/sub x/ was studied at 450/sup 0/ and 550/sup 0/C by introducing alternating pulses of 0.5Vertical Bar3< propane/0.6Vertical Bar3< ammonia/helium (to reduce the steady-state catalytic surface) and 0.5Vertical Bar3< propane/0.6Vertical Bar3< ammonia/1.86Vertical Bar3< oxygen/helium mixtures into a fluidized-bed catalytic reactor. Over all the catalysts studied, the rates of acrylonitrile formation during the two types of pulses were very similar, but carbon dioxide was formed much faster during the reducing pulses, particularly at 450/sup 0/C. These findings suggested that acrylonitrile is formed by a stepwise redox mechanism involving consecutive interaction of propane and ammonia with the surface oxygen of the catalysts and oxidation of the reduced catalyst surface by gas-phase oxygen. The formation of carbon dioxide proceeds by both stepwise and associative mechanisms, the latter being more important at higher temperatures. The results are similar to published results for ammoxidation of propylene and olefins.

Measuring yield performance of upland cotton varieties using adaptability, stability and principal component analyses

International Nuclear Information System (INIS)

Baloch, M.J.

2003-01-01

Nine upland cotton varieties/strains were tested over 36 environments in Pakistan so as to determine their stability in yield performance. The regression coefficient (b) was used as a measure of adaptability, whereas parameters such as coefficient of determination (r2) and sum of squared deviations from regression (s/sup 2/d) were used as measure of stability. Although the regression coefficients (b) of all varieties did not deviate significantly from the unit slope, the varieties CRIS-5A. BII-89, DNH-40 and Rehmani gave b value closer to unity implying their better adaptation. Lower s/sub 2/d and higher r/sub 2/ of CRIS- 121 and DNH-40 suggest that both of these are fairly stable. The results indicate that, generally, adaptability and stability parameters are independent of each in as much as not all of the parameters simultaneously favoured one variety over the other excepting the variety DNH-40, which was stable based on majority of the parameters. Principal component analysis revealed that the first two components (latent roots) account for about 91.4% of the total variation. The latent vectors of first principal component (PCA1) were smaller and positive which also suggest that most of the varieties were quite adaptive to all of the test environments. (author)

Stepwise integral scaling method and its application to severe accident phenomena

International Nuclear Information System (INIS)

Ishii, M.; Zhang, G.

1993-10-01

Severe accidents in light water reactors are characterized by an occurrence of multiphase flow with complicated phase changes, chemical reaction and various bifurcation phenomena. Because of the inherent difficulties associated with full-scale testing, scaled down and simulation experiments are essential part of the severe accident analyses. However, one of the most significant shortcomings in the area is the lack of well-established and reliable scaling method and scaling criteria. In view of this, the stepwise integral scaling method is developed for severe accident analyses. This new scaling method is quite different from the conventional approach. However, its focus on dominant transport mechanisms and use of the integral response of the system make this method relatively simple to apply to very complicated multi-phase flow problems. In order to demonstrate its applicability and usefulness, three case studies have been made. The phenomena considered are (1) corium dispersion in DCH, (2) corium spreading in BWR MARK-I containment, and (3) incore boil-off and heating process. The results of these studies clearly indicate the effectiveness of their stepwise integral scaling method. Such a simple and systematic scaling method has not been previously available to severe accident analyses

Efficient and Mild Microwave-Assisted Stepwise Functionalization of Naphthalenediimide with α-Amino Acids

NARCIS (Netherlands)

Pengo, Paolo; Pantoş, G. Dan; Otto, Sijbren; Sanders, Jeremy K.M.

2006-01-01

Microwave dielectric heating proved to be an efficient method for the one-pot and stepwise syntheses of symmetrical and unsymmetrical naphthalenediimide derivatives of α-amino acids. Acid-labile side chain protecting groups are stable under the reaction conditions; protection of the α-carboxylic

Logistic LASSO regression for the diagnosis of breast cancer using clinical demographic data and the BI-RADS lexicon for ultrasonography.

Science.gov (United States)

Kim, Sun Mi; Kim, Yongdai; Jeong, Kuhwan; Jeong, Heeyeong; Kim, Jiyoung

2018-01-01

The aim of this study was to compare the performance of image analysis for predicting breast cancer using two distinct regression models and to evaluate the usefulness of incorporating clinical and demographic data (CDD) into the image analysis in order to improve the diagnosis of breast cancer. This study included 139 solid masses from 139 patients who underwent a ultrasonography-guided core biopsy and had available CDD between June 2009 and April 2010. Three breast radiologists retrospectively reviewed 139 breast masses and described each lesion using the Breast Imaging Reporting and Data System (BI-RADS) lexicon. We applied and compared two regression methods-stepwise logistic (SL) regression and logistic least absolute shrinkage and selection operator (LASSO) regression-in which the BI-RADS descriptors and CDD were used as covariates. We investigated the performances of these regression methods and the agreement of radiologists in terms of test misclassification error and the area under the curve (AUC) of the tests. Logistic LASSO regression was superior (Pcomparable to the AUC with CDD (0.873 vs. 0.880, P=0.141). Logistic LASSO regression based on BI-RADS descriptors and CDD showed better performance than SL in predicting the presence of breast cancer. The use of CDD as a supplement to the BI-RADS descriptors significantly improved the prediction of breast cancer using logistic LASSO regression.

Communication Factors as Predictors of Relationship Quality: A National Study of Principals and School Counselors

Science.gov (United States)

Duslak, Mark; Geier, Brett

2017-01-01

This study examined the effects of meeting frequency, structured meeting times, annual agreements, and demographic variables on school counselor perceptions of their relationship with their building principal. Results of a regression analysis indicated that meeting frequency accounted for 26.7% of the variance in school counselor-reported…

An antarctic stratigraphic record of stepwise ice growth through the eocene-oligocene transition

NARCIS (Netherlands)

Passchier, Sandra; Ciarletta, Daniel J.; Miriagos, Triantafilo E.; Bijl, Peter K.; Bohaty, Steven M.

2017-01-01

Earth's current icehouse phase began ~34 m.y. ago with the onset of major Antarctic glaciation at the Eocene-Oligocene transition. Changes in ocean circulation and a decline in atmospheric greenhouse gas levels were associated with stepwise cooling and ice growth at southern high latitudes. The

A prediction model for spontaneous regression of cervical intraepithelial neoplasia grade 2, based on simple clinical parameters.

Science.gov (United States)

Koeneman, Margot M; van Lint, Freyja H M; van Kuijk, Sander M J; Smits, Luc J M; Kooreman, Loes F S; Kruitwagen, Roy F P M; Kruse, Arnold J

2017-01-01

This study aims to develop a prediction model for spontaneous regression of cervical intraepithelial neoplasia grade 2 (CIN 2) lesions based on simple clinicopathological parameters. The study was conducted at Maastricht University Medical Center, the Netherlands. The prediction model was developed in a retrospective cohort of 129 women with a histologic diagnosis of CIN 2 who were managed by watchful waiting for 6 to 24months. Five potential predictors for spontaneous regression were selected based on the literature and expert opinion and were analyzed in a multivariable logistic regression model, followed by backward stepwise deletion based on the Wald test. The prediction model was internally validated by the bootstrapping method. Discriminative capacity and accuracy were tested by assessing the area under the receiver operating characteristic curve (AUC) and a calibration plot. Disease regression within 24months was seen in 91 (71%) of 129 patients. A prediction model was developed including the following variables: smoking, Papanicolaou test outcome before the CIN 2 diagnosis, concomitant CIN 1 diagnosis in the same biopsy, and more than 1 biopsy containing CIN 2. Not smoking, Papanicolaou class predictive of disease regression. The AUC was 69.2% (95% confidence interval, 58.5%-79.9%), indicating a moderate discriminative ability of the model. The calibration plot indicated good calibration of the predicted probabilities. This prediction model for spontaneous regression of CIN 2 may aid physicians in the personalized management of these lesions. Copyright © 2016 Elsevier Inc. All rights reserved.

Laboratory quality stepwise implementation tool: National reference TB laboratory of Iran

OpenAIRE

Ali Naghi Kebriaee; Donya Malekshahian; Mojtaba Ahmadi; Parissa Farnia

2015-01-01

Background and objective: During recent years, the World Health Organization (WHO) proposed new software for improving the tuberculosis (TB) laboratory services. The protocol is known as “quality stepwise implementation tool” and is based on enforcement of quality assurance services through accreditation by the International Organization for Standardization (ISO) 15189. As a national reference TB laboratory (NRL) of Iran, the benefit and challenges of implementing this standard were analyzed....

Wheat flour dough Alveograph characteristics predicted by Mixolab regression models.

Science.gov (United States)

Codină, Georgiana Gabriela; Mironeasa, Silvia; Mironeasa, Costel; Popa, Ciprian N; Tamba-Berehoiu, Radiana

2012-02-01

In Romania, the Alveograph is the most used device to evaluate the rheological properties of wheat flour dough, but lately the Mixolab device has begun to play an important role in the breadmaking industry. These two instruments are based on different principles but there are some correlations that can be found between the parameters determined by the Mixolab and the rheological properties of wheat dough measured with the Alveograph. Statistical analysis on 80 wheat flour samples using the backward stepwise multiple regression method showed that Mixolab values using the ‘Chopin S’ protocol (40 samples) and ‘Chopin + ’ protocol (40 samples) can be used to elaborate predictive models for estimating the value of the rheological properties of wheat dough: baking strength (W), dough tenacity (P) and extensibility (L). The correlation analysis confirmed significant findings (P 0.70 for P, R²(adjusted) > 0.70 for W and R²(adjusted) > 0.38 for L, at a 95% confidence interval. Copyright © 2011 Society of Chemical Industry.

Differentiating regressed melanoma from regressed lichenoid keratosis.

Science.gov (United States)

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

2017-04-01

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

The systemic management of cutaneous dermatomyositis: Results of a stepwise strategy

Directory of Open Access Journals (Sweden)

C.O. Anyanwu

2017-12-01

Full Text Available Treatment of dermatomyositis (DM is often achieved with a stepwise algorithm. However, the literature lacks quality evidence to support the use of this therapeutic strategy. The result of a stepwise therapeutic strategy in the management of skin-only DM is presented to better understand the clinical outcomes and allow for future studies. A cohort of 102 patients with DM, 41 of whom had skin-only disease, were seen between July 2009 and April 2013 at a referral-based connective tissue disease clinic. The Cutaneous Dermatomyositis Disease Area and Severity Index was used to prospectively assess disease severity and the outcomes in 41 adult patients with skin-only DM were analyzed. Of the 41 patients with skin-only DM, 23 patients (56.1% received antimalarial medications alone and 18 patients (43.9% received second- or third-line agents. Ten patients (24.4% remained at the first level of the treatment algorithm and received only hydroxychloroquine. Prednisone was included in the treatment regimen for 11 patients with skin-only disease (26.8%. The results show that management of cutaneous DM often requires second-line agents because antimalarial medications alone are insufficient to treat most patients with skin-only disease. Keywords: dermatomyositis, antimalarial, immunosuppressive, CDASI, outcome measures, treatment

A stepwise-cluster microbial biomass inference model in food waste composting

International Nuclear Information System (INIS)

Sun Wei; Huang, Guo H.; Zeng Guangming; Qin Xiaosheng; Sun Xueling

2009-01-01

A stepwise-cluster microbial biomass inference (SMI) model was developed through introducing stepwise-cluster analysis (SCA) into composting process modeling to tackle the nonlinear relationships among state variables and microbial activities. The essence of SCA is to form a classification tree based on a series of cutting or mergence processes according to given statistical criteria. Eight runs of designed experiments in bench-scale reactors in a laboratory were constructed to demonstrate the feasibility of the proposed method. The results indicated that SMI could help establish a statistical relationship between state variables and composting microbial characteristics, where discrete and nonlinear complexities exist. Significance levels of cutting/merging were provided such that the accuracies of the developed forecasting trees were controllable. Through an attempted definition of input effects on the output in SMI, the effects of the state variables on thermophilic bacteria were ranged in a descending order as: Time (day) > moisture content (%) > ash content (%, dry) > Lower Temperature (deg. C) > pH > NH 4 + -N (mg/Kg, dry) > Total N (%, dry) > Total C (%, dry); the effects on mesophilic bacteria were ordered as: Time > Upper Temperature (deg. C) > Total N > moisture content > NH 4 + -N > Total C > pH. This study made the first attempt in applying SCA to mapping the nonlinear and discrete relationships in composting processes.

A stepwise composite echocardiographic score predicts severe pulmonary hypertension in patients with interstitial lung disease.

Science.gov (United States)

Bax, Simon; Bredy, Charlene; Kempny, Aleksander; Dimopoulos, Konstantinos; Devaraj, Anand; Walsh, Simon; Jacob, Joseph; Nair, Arjun; Kokosi, Maria; Keir, Gregory; Kouranos, Vasileios; George, Peter M; McCabe, Colm; Wilde, Michael; Wells, Athol; Li, Wei; Wort, Stephen John; Price, Laura C

2018-04-01

European Respiratory Society (ERS) guidelines recommend the assessment of patients with interstitial lung disease (ILD) and severe pulmonary hypertension (PH), as defined by a mean pulmonary artery pressure (mPAP) ≥35 mmHg at right heart catheterisation (RHC). We developed and validated a stepwise echocardiographic score to detect severe PH using the tricuspid regurgitant velocity and right atrial pressure (right ventricular systolic pressure (RVSP)) and additional echocardiographic signs. Consecutive ILD patients with suspected PH underwent RHC between 2005 and 2015. Receiver operating curve analysis tested the ability of components of the score to predict mPAP ≥35 mmHg, and a score devised using a stepwise approach. The score was tested in a contemporaneous validation cohort. The score used "additional PH signs" where RVSP was unavailable, using a bootstrapping technique. Within the derivation cohort (n=210), a score ≥7 predicted severe PH with 89% sensitivity, 71% specificity, positive predictive value 68% and negative predictive value 90%, with similar performance in the validation cohort (n=61) (area under the curve (AUC) 84.8% versus 83.1%, p=0.8). Although RVSP could be estimated in 92% of studies, reducing this to 60% maintained a fair accuracy (AUC 74.4%). This simple stepwise echocardiographic PH score can predict severe PH in patients with ILD.

Stepwise excavation may enhance pulp preservation in permanent teeth affected by dental caries

DEFF Research Database (Denmark)

Bjørndal, Lars

2011-01-01

ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Ways of enhancing pulp preservation by stepwise excavation-a systematic review. Hayashi M, Fujitani M, Yamaki C, Momoi Y. J Dent 2011;39(2):95-107. Epub 2010 Dec 3. REVIEWER: Lars Bjørndal, DDS, PhD, Dr Odont PURPOSE/QUESTION: To determine the clinical...

Efficient training of multilayer perceptrons using principal component analysis

International Nuclear Information System (INIS)

Bunzmann, Christoph; Urbanczik, Robert; Biehl, Michael

2005-01-01

A training algorithm for multilayer perceptrons is discussed and studied in detail, which relates to the technique of principal component analysis. The latter is performed with respect to a correlation matrix computed from the example inputs and their target outputs. Typical properties of the training procedure are investigated by means of a statistical physics analysis in models of learning regression and classification tasks. We demonstrate that the procedure requires by far fewer examples for good generalization than traditional online training. For networks with a large number of hidden units we derive the training prescription which achieves, within our model, the optimal generalization behavior

Stepwise Procedure for Development and Validation of a Multipesticide Method

Energy Technology Data Exchange (ETDEWEB)

Ambrus, A. [Hungarian Food Safety Office, Budapest (Hungary)

2009-07-15

The stepwise procedure for development and the validation of so called multi-pesticide methods are described. Principles, preliminary actions, criteria for the selection of chromatographic separation, detection and performance verification of multi-pesticide methods are outlined. Also the long term repeatability and reproducibility, as well as the necessity for the documentation of laboratory work are highlighted. Appendix I hereof describes in detail the calculation of calibration parameters, whereas Appendix II focuses on the calculation of the significance of differences of concentrations obtained on two different separation columns. (author)

Logistic regression model for identification of right ventricular dysfunction in patients with acute pulmonary embolism by means of computed tomography

International Nuclear Information System (INIS)

Staskiewicz, Grzegorz; Czekajska-Chehab, Elżbieta; Uhlig, Sebastian; Przegalinski, Jerzy; Maciejewski, Ryszard; Drop, Andrzej

2013-01-01

Purpose: Diagnosis of right ventricular dysfunction in patients with acute pulmonary embolism (PE) is known to be associated with increased risk of mortality. The aim of the study was to calculate a logistic regression model for reliable identification of right ventricular dysfunction (RVD) in patients diagnosed with computed tomography pulmonary angiography. Material and methods: Ninety-seven consecutive patients with acute pulmonary embolism were divided into groups with and without RVD basing upon echocardiographic measurement of pulmonary artery systolic pressure (PASP). PE severity was graded with the pulmonary obstruction score. CT measurements of heart chambers and mediastinal vessels were performed; position of interventricular septum and presence of contrast reflux into the inferior vena cava were also recorded. The logistic regression model was prepared by means of stepwise logistic regression. Results: Among the used parameters, the final model consisted of pulmonary obstruction score, short axis diameter of right ventricle and diameter of inferior vena cava. The calculated model is characterized by 79% sensitivity and 81% specificity, and its performance was significantly better than single CT-based measurements. Conclusion: Logistic regression model identifies RVD significantly better, than single CT-based measurements

Stepwise crystallization and the layered distribution in crystallization kinetics of ultra-thin poly(ethylene terephthalate) film

Energy Technology Data Exchange (ETDEWEB)

Zuo, Biao, E-mail: chemizuo@zstu.edu.cn, E-mail: wxinping@yahoo.com; Xu, Jianquan; Sun, Shuzheng; Liu, Yue; Yang, Juping; Zhang, Li; Wang, Xinping, E-mail: chemizuo@zstu.edu.cn, E-mail: wxinping@yahoo.com [Department of Chemistry, Key Laboratory of Advanced Textile Materials and Manufacturing Technology of the Education Ministry, Zhejiang Sci-Tech University, Hangzhou 310018 (China)

2016-06-21

Crystallization is an important property of polymeric materials. In conventional viewpoint, the transformation of disordered chains into crystals is usually a spatially homogeneous process (i.e., it occurs simultaneously throughout the sample), that is, the crystallization rate at each local position within the sample is almost the same. Here, we show that crystallization of ultra-thin poly(ethylene terephthalate) (PET) films can occur in the heterogeneous way, exhibiting a stepwise crystallization process. We found that the layered distribution of glass transition dynamics of thin film modifies the corresponding crystallization behavior, giving rise to the layered distribution of the crystallization kinetics of PET films, with an 11-nm-thick surface layer having faster crystallization rate and the underlying layer showing bulk-like behavior. The layered distribution in crystallization kinetics results in a particular stepwise crystallization behavior during heating the sample, with the two cold-crystallization temperatures separated by up to 20 K. Meanwhile, interfacial interaction is crucial for the occurrence of the heterogeneous crystallization, as the thin film crystallizes simultaneously if the interfacial interaction is relatively strong. We anticipate that this mechanism of stepwise crystallization of thin polymeric films will allow new insight into the chain organization in confined environments and permit independent manipulation of localized properties of nanomaterials.

Modeling the variability of solar radiation data among weather stations by means of principal components analysis

International Nuclear Information System (INIS)

Zarzo, Manuel; Marti, Pau

2011-01-01

Research highlights: →Principal components analysis was applied to R s data recorded at 30 stations. → Four principal components explain 97% of the data variability. → The latent variables can be fitted according to latitude, longitude and altitude. → The PCA approach is more effective for gap infilling than conventional approaches. → The proposed method allows daily R s estimations at locations in the area of study. - Abstract: Measurements of global terrestrial solar radiation (R s ) are commonly recorded in meteorological stations. Daily variability of R s has to be taken into account for the design of photovoltaic systems and energy efficient buildings. Principal components analysis (PCA) was applied to R s data recorded at 30 stations in the Mediterranean coast of Spain. Due to equipment failures and site operation problems, time series of R s often present data gaps or discontinuities. The PCA approach copes with this problem and allows estimation of present and past values by taking advantage of R s records from nearby stations. The gap infilling performance of this methodology is compared with neural networks and alternative conventional approaches. Four principal components explain 66% of the data variability with respect to the average trajectory (97% if non-centered values are considered). A new method based on principal components regression was also developed for R s estimation if previous measurements are not available. By means of multiple linear regression, it was found that the latent variables associated to the four relevant principal components can be fitted according to the latitude, longitude and altitude of the station where data were recorded from. Additional geographical or climatic variables did not increase the predictive goodness-of-fit. The resulting models allow the estimation of daily R s values at any location in the area under study and present higher accuracy than artificial neural networks and some conventional approaches

Stepwise cyanation of naphthalene diimide for n-channel field-effect transistors

KAUST Repository

Chang, Jingjing

2012-06-15

Stepwise cyanation of tetrabromonaphthalenediimide (NDI) 1 gave a series of cyanated NDIs 2-5 with the monocyanated NDI 2 and dicyanated NDI 3 isolated. The tri- and tetracyano- NDIs 4 and 5 show intrinsic instability toward moisture because of their extremely low-lying LUMO energy levels. The partially cyanated intermediates can be utilized as air-stable n-type semiconductors with OFET electron mobility up to 0.05 cm 2 V -1 s -1. © 2012 American Chemical Society.

The Effect of Personality Value Practice of Principals toward Attitude, Discipline, Qualities and Communications of Work

Directory of Open Access Journals (Sweden)

Muhammad Asri

2015-02-01

Full Text Available This study aims to identify the effect of personality value practice of principals toward work attitude, work discipline, work quality and work communication of teachers in senior high schools such as public senior high schools (SMA, vocational senior high schools (SMK, religion senior high schools (MAN in Makassar city, South Sulawesi province of Indonesia. The sample consisted of 295 teachers. It used random sampling method. The study used a questionnaire to collect data. Data were analyzed by the statistical inference of linear regression to test the hypotheses. Cronbach's alpha of the questionnaire is 0.879. The results showed a strong effect of personality values of principals toward work attitude, work quality and work communication of teachers at schools. While, personality value of principals have moderate influence on teachers’ work discipline.

Sparse Regression by Projection and Sparse Discriminant Analysis

KAUST Repository

Qi, Xin

2015-04-03

© 2015, © American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America. Recent years have seen active developments of various penalized regression methods, such as LASSO and elastic net, to analyze high-dimensional data. In these approaches, the direction and length of the regression coefficients are determined simultaneously. Due to the introduction of penalties, the length of the estimates can be far from being optimal for accurate 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 and the tuning parameters are determined by a cross-validation procedure to achieve the largest prediction accuracy. We provide a theoretical result for simultaneous model selection consistency and parameter estimation consistency of our method in high dimension. This new framework is then generalized such that it can be applied to principal components analysis, partial least squares, and canonical correlation analysis. We also adapt this framework for discriminant analysis. Compared with the existing methods, where there is relatively little control of the dependency among the sparse components, our method can control the relationships among the components. We present efficient algorithms and related theory for solving the sparse regression by projection problem. Based on extensive simulations and real data analysis, we demonstrate that our method achieves good predictive performance and variable selection in the regression setting, and the ability to control relationships between the sparse components leads to more accurate classification. In supplementary materials available online, the details of the algorithms and theoretical proofs, and R codes for all simulation studies are provided.

29 CFR 1471.995 - Principal.

Science.gov (United States)

2010-07-01

... SUSPENSION (NONPROCUREMENT) Definitions § 1471.995 Principal. Principal means— (a) An officer, director, owner, partner, principal investigator, or other person within a participant with management or... 29 Labor 4 2010-07-01 2010-07-01 false Principal. 1471.995 Section 1471.995 Labor Regulations...

Portraits of Principal Practice: Time Allocation and School Principal Work

Science.gov (United States)

Sebastian, James; Camburn, Eric M.; Spillane, James P.

2018-01-01

Purpose: The purpose of this study was to examine how school principals in urban settings distributed their time working on critical school functions. We also examined who principals worked with and how their time allocation patterns varied by school contextual characteristics. Research Method/Approach: The study was conducted in an urban school…

Relationship between rice yield and climate variables in southwest Nigeria using multiple linear regression and support vector machine analysis

Science.gov (United States)

Oguntunde, Philip G.; Lischeid, Gunnar; Dietrich, Ottfried

2018-03-01

This study examines the variations of climate variables and rice yield and quantifies the relationships among them using multiple linear regression, principal component analysis, and support vector machine (SVM) analysis in southwest Nigeria. The climate and yield data used was for a period of 36 years between 1980 and 2015. Similar to the observed decrease ( P 1 and explained 83.1% of the total variance of predictor variables. The SVM regression function using the scores of the first principal component explained about 75% of the variance in rice yield data and linear regression about 64%. SVM regression between annual solar radiation values and yield explained 67% of the variance. Only the first component of the principal component analysis (PCA) exhibited a clear long-term trend and sometimes short-term variance similar to that of rice yield. Short-term fluctuations of the scores of the PC1 are closely coupled to those of rice yield during the 1986-1993 and the 2006-2013 periods thereby revealing the inter-annual sensitivity of rice production to climate variability. Solar radiation stands out as the climate variable of highest influence on rice yield, and the influence was especially strong during monsoon and post-monsoon periods, which correspond to the vegetative, booting, flowering, and grain filling stages in the study area. The outcome is expected to provide more in-depth regional-specific climate-rice linkage for screening of better cultivars that can positively respond to future climate fluctuations as well as providing information that may help optimized planting dates for improved radiation use efficiency in the study area.

31 CFR 19.995 - Principal.

Science.gov (United States)

2010-07-01

... SUSPENSION (NONPROCUREMENT) Definitions § 19.995 Principal. Principal means— (a) An officer, director, owner, partner, principal investigator, or other person within a participant with management or supervisory... 31 Money and Finance: Treasury 1 2010-07-01 2010-07-01 false Principal. 19.995 Section 19.995...

22 CFR 208.995 - Principal.

Science.gov (United States)

2010-04-01

... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Principal. 208.995 Section 208.995 Foreign...) Definitions § 208.995 Principal. Principal means— (a) An officer, director, owner, partner, principal investigator, or other person within a participant with management or supervisory responsibilities related to a...

22 CFR 1006.995 - Principal.

Science.gov (United States)

2010-04-01

... 22 Foreign Relations 2 2010-04-01 2010-04-01 true Principal. 1006.995 Section 1006.995 Foreign... § 1006.995 Principal. Principal means— (a) An officer, director, owner, partner, principal investigator, or other person within a participant with management or supervisory responsibilities related to a...

2 CFR 180.995 - Principal.

Science.gov (United States)

2010-01-01

... 2 Grants and Agreements 1 2010-01-01 2010-01-01 false Principal. 180.995 Section 180.995 Grants and Agreements OFFICE OF MANAGEMENT AND BUDGET GOVERNMENTWIDE GUIDANCE FOR GRANTS AND AGREEMENTS... § 180.995 Principal. Principal means— (a) An officer, director, owner, partner, principal investigator...

22 CFR 1508.995 - Principal.

Science.gov (United States)

2010-04-01

... 22 Foreign Relations 2 2010-04-01 2010-04-01 true Principal. 1508.995 Section 1508.995 Foreign...) Definitions § 1508.995 Principal. Principal means— (a) An officer, director, owner, partner, principal investigator, or other person within a participant with management or supervisory responsibilities related to a...

Principal stratification in causal inference.

Science.gov (United States)

Frangakis, Constantine E; Rubin, Donald B

2002-03-01

Many scientific problems require that treatment comparisons be adjusted for posttreatment variables, but the estimands underlying standard methods are not causal effects. To address this deficiency, we propose a general framework for comparing treatments adjusting for posttreatment variables that yields principal effects based on principal stratification. Principal stratification with respect to a posttreatment variable is a cross-classification of subjects defined by the joint potential values of that posttreatment variable tinder each of the treatments being compared. Principal effects are causal effects within a principal stratum. The key property of principal strata is that they are not affected by treatment assignment and therefore can be used just as any pretreatment covariate. such as age category. As a result, the central property of our principal effects is that they are always causal effects and do not suffer from the complications of standard posttreatment-adjusted estimands. We discuss briefly that such principal causal effects are the link between three recent applications with adjustment for posttreatment variables: (i) treatment noncompliance, (ii) missing outcomes (dropout) following treatment noncompliance. and (iii) censoring by death. We then attack the problem of surrogate or biomarker endpoints, where we show, using principal causal effects, that all current definitions of surrogacy, even when perfectly true, do not generally have the desired interpretation as causal effects of treatment on outcome. We go on to forrmulate estimands based on principal stratification and principal causal effects and show their superiority.

Principals' Salaries, 2007-2008

Science.gov (United States)

Cooke, Willa D.; Licciardi, Chris

2008-01-01

How do salaries of elementary and middle school principals compare with those of other administrators and classroom teachers? Are increases in salaries of principals keeping pace with increases in salaries of classroom teachers? And how have principals' salaries fared over the years when the cost of living is taken into account? There are reliable…

21 CFR 1404.995 - Principal.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 9 2010-04-01 2010-04-01 false Principal. 1404.995 Section 1404.995 Food and...) Definitions § 1404.995 Principal. Principal means— (a) An officer, director, owner, partner, principal investigator, or other person within a participant with management or supervisory responsibilities related to a...

34 CFR 85.995 - Principal.

Science.gov (United States)

2010-07-01

... 34 Education 1 2010-07-01 2010-07-01 false Principal. 85.995 Section 85.995 Education Office of...) Definitions § 85.995 Principal. Principal means— (a) An officer, director, owner, partner, principal investigator, or other person within a participant with management or supervisory responsibilities related to a...

Stepwise approach to myopathy in systemic disease.

Science.gov (United States)

Chawla, Jasvinder

2011-01-01

Muscle diseases can constitute a large variety of both acquired and hereditary disorders. Myopathies in systemic disease results from several different disease processes including endocrine, inflammatory, paraneoplastic, infectious, drug- and toxin-induced, critical illness myopathy, metabolic, and myopathies with other systemic disorders. Patients with systemic myopathies often present acutely or sub acutely. On the other hand, familial myopathies or dystrophies generally present in a chronic fashion with exceptions of metabolic myopathies where symptoms on occasion can be precipitated acutely. Most of the inflammatory myopathies can have a chance association with malignant lesions; the incidence appears to be specifically increased only in patients with dermatomyositis. In dealing with myopathies associated with systemic illnesses, the focus will be on the acquired causes. Management is beyond the scope of this chapter. Prognosis is based upon the underlying cause and, most of the time, carries a good prognosis. In order to approach a patient with suspected myopathy from systemic disease, a stepwise approach is utilized.

Principal Self-Efficacy and Work Engagement: Assessing a Norwegian Principal Self-Efficacy Scale

Science.gov (United States)

Federici, Roger A.; Skaalvik, Einar M.

2011-01-01

One purpose of the present study was to develop and test the factor structure of a multidimensional and hierarchical Norwegian Principal Self-Efficacy Scale (NPSES). Another purpose of the study was to investigate the relationship between principal self-efficacy and work engagement. Principal self-efficacy was measured by the 22-item NPSES. Work…

Stepwise decision making for the long-term management of radioactive waste

International Nuclear Information System (INIS)

Pescatore, C.; Vari, A.

2003-01-01

The context of long-term radioactive waste management is being shaped by changes in modern society. Values such as health, environmental protection and safety are increasingly important. This changes in turn necessitate new forms of dialogue and decision-making processes that include a large number of stakeholders. This paper deals with the new features of a stepwise decision-making approach, taking into account the public involvement and social learning processes, and showing the complexity of the new situation. (A.L.B.)

Predicting the aquatic toxicity mode of action using logistic regression and linear discriminant analysis.

Science.gov (United States)

Ren, Y Y; Zhou, L C; Yang, L; Liu, P Y; Zhao, B W; Liu, H X

2016-09-01

The paper highlights the use of the logistic regression (LR) method in the construction of acceptable statistically significant, robust and predictive models for the classification of chemicals according to their aquatic toxic modes of action. Essentials accounting for a reliable model were all considered carefully. The model predictors were selected by stepwise forward discriminant analysis (LDA) from a combined pool of experimental data and chemical structure-based descriptors calculated by the CODESSA and DRAGON software packages. Model predictive ability was validated both internally and externally. The applicability domain was checked by the leverage approach to verify prediction reliability. The obtained models are simple and easy to interpret. In general, LR performs much better than LDA and seems to be more attractive for the prediction of the more toxic compounds, i.e. compounds that exhibit excess toxicity versus non-polar narcotic compounds and more reactive compounds versus less reactive compounds. In addition, model fit and regression diagnostics was done through the influence plot which reflects the hat-values, studentized residuals, and Cook's distance statistics of each sample. Overdispersion was also checked for the LR model. The relationships between the descriptors and the aquatic toxic behaviour of compounds are also discussed.

Comparison of some biased estimation methods (including ordinary subset regression) in the linear model

Science.gov (United States)

Sidik, S. M.

1975-01-01

Ridge, Marquardt's generalized inverse, shrunken, and principal components estimators are discussed in terms of the objectives of point estimation of parameters, estimation of the predictive regression function, and hypothesis testing. It is found that as the normal equations approach singularity, more consideration must be given to estimable functions of the parameters as opposed to estimation of the full parameter vector; that biased estimators all introduce constraints on the parameter space; that adoption of mean squared error as a criterion of goodness should be independent of the degree of singularity; and that ordinary least-squares subset regression is the best overall method.

Stepwise extraction of Lepidium sativum seed gum: Physicochemical characterization and functional properties

DEFF Research Database (Denmark)

Razmkhah, Somayeh; Razavi, Seyed Mohammad Ali; Mohammadifar, Mohammad Amin

2016-01-01

Cress seed gum (CSG) was fractionated using stepwise extraction with water, yielding three fractions (F1, F2, F3) whose average molecular weights ranged from 863 to 1080 kDa. The chemical composition (monosaccharide, ash, moisture, CHN and uronic acid contents) and molecular weight of the fractio...

Modified Regression Correlation Coefficient for Poisson Regression Model

Science.gov (United States)

Kaengthong, Nattacha; Domthong, Uthumporn

2017-09-01

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

An Investigation of Teacher, Principal, and Superintendent Perceptions on the Ability of the National Framework for Principal Evaluations to Measure Principals' Leadership Competencies

Science.gov (United States)

Lamb, Lori D.

2014-01-01

The purpose of this qualitative study was to investigate the perceptions of effective principals' leadership competencies; determine if the perceptions of teachers, principals, and superintendents aligned with the proposed National Framework for Principal Evaluations initiative. This study examined the six domains of leadership outlined by the…

Multi-layered nanoparticles for penetrating the endosome and nuclear membrane via a step-wise membrane fusion process.

Science.gov (United States)

Akita, Hidetaka; Kudo, Asako; Minoura, Arisa; Yamaguti, Masaya; Khalil, Ikramy A; Moriguchi, Rumiko; Masuda, Tomoya; Danev, Radostin; Nagayama, Kuniaki; Kogure, Kentaro; Harashima, Hideyoshi

2009-05-01

Efficient targeting of DNA to the nucleus is a prerequisite for effective gene therapy. The gene-delivery vehicle must penetrate through the plasma membrane, and the DNA-impermeable double-membraned nuclear envelope, and deposit its DNA cargo in a form ready for transcription. Here we introduce a concept for overcoming intracellular membrane barriers that involves step-wise membrane fusion. To achieve this, a nanotechnology was developed that creates a multi-layered nanoparticle, which we refer to as a Tetra-lamellar Multi-functional Envelope-type Nano Device (T-MEND). The critical structural elements of the T-MEND are a DNA-polycation condensed core coated with two nuclear membrane-fusogenic inner envelopes and two endosome-fusogenic outer envelopes, which are shed in stepwise fashion. A double-lamellar membrane structure is required for nuclear delivery via the stepwise fusion of double layered nuclear membrane structure. Intracellular membrane fusions to endosomes and nuclear membranes were verified by spectral imaging of fluorescence resonance energy transfer (FRET) between donor and acceptor fluorophores that had been dually labeled on the liposome surface. Coating the core with the minimum number of nucleus-fusogenic lipid envelopes (i.e., 2) is essential to facilitate transcription. As a result, the T-MEND achieves dramatic levels of transgene expression in non-dividing cells.

Stepwise radical endoscopic resection for Barrett's esophagus with early neoplasia: report on a Brussels' cohort

NARCIS (Netherlands)

Pouw, R. E.; Peters, F. P.; Sempoux, C.; Piessevaux, H.; Deprez, P. H.

2008-01-01

Background and study aims: The aim of this retrospective study was to assess safety and efficacy of stepwise radical endoscopic resection (SRER) in patients with Barrett's esophagus with high-grade intraepithelial neoplasia (HGIN) or early cancer. Patients and methods: Patients undergoing SRER

Stepwise synthesis and characterization of germa[4], [5], [8], and [10]pericyclynes.

Science.gov (United States)

Tanimoto, Hiroki; Nagao, Tomohiko; Fujiwara, Taro; Nishiyama, Yasuhiro; Morimoto, Tsumoru; Suzuka, Toshimasa; Tsutsumi, Ken; Kakiuchi, Kiyomi

2015-07-14

The stepwise syntheses of germa[N]pericyclynes, including [5]pericyclynes, and their characterization are described. The yields of germa[4] and [8]pericyclynes were improved significantly compared to those obtained in previous studies. The routes reported herein afforded the novel germa[5] and [10]pericyclynes, which were characterized by X-ray crystallography, UV-Vis spectroscopy, and fluorescence emission spectroscopy. A unique fluorescence emission was observed for the large germa[10]pericyclyne ring.

Relationship between rice yield and climate variables in southwest Nigeria using multiple linear regression and support vector machine analysis.

Science.gov (United States)

Oguntunde, Philip G; Lischeid, Gunnar; Dietrich, Ottfried

2018-03-01

This study examines the variations of climate variables and rice yield and quantifies the relationships among them using multiple linear regression, principal component analysis, and support vector machine (SVM) analysis in southwest Nigeria. The climate and yield data used was for a period of 36 years between 1980 and 2015. Similar to the observed decrease (P  1 and explained 83.1% of the total variance of predictor variables. The SVM regression function using the scores of the first principal component explained about 75% of the variance in rice yield data and linear regression about 64%. SVM regression between annual solar radiation values and yield explained 67% of the variance. Only the first component of the principal component analysis (PCA) exhibited a clear long-term trend and sometimes short-term variance similar to that of rice yield. Short-term fluctuations of the scores of the PC1 are closely coupled to those of rice yield during the 1986-1993 and the 2006-2013 periods thereby revealing the inter-annual sensitivity of rice production to climate variability. Solar radiation stands out as the climate variable of highest influence on rice yield, and the influence was especially strong during monsoon and post-monsoon periods, which correspond to the vegetative, booting, flowering, and grain filling stages in the study area. The outcome is expected to provide more in-depth regional-specific climate-rice linkage for screening of better cultivars that can positively respond to future climate fluctuations as well as providing information that may help optimized planting dates for improved radiation use efficiency in the study area.

Finding Structure in Diversity: A Stepwise Small-N/Medium-N Qualitative Comparative Analysis Approach for Water Resources Management Research

Directory of Open Access Journals (Sweden)

Peter P. Mollinga

2014-02-01

Full Text Available Drawing particularly on recent debates on, and development of, comparative methods in the field of comparative politics, the paper argues that stepwise small-N/medium-N qualitative comparative analysis (QCA is a particularly suitable methodological approach for water resources studies because it can make use of the rich but fragmented water resources studies literature for accumulation of knowledge and development of theory. It is suggested that taking an explicit critical realist ontological and epistemological stance allows expansion of the scope of stepwise small-N/medium-N QCA beyond what is claimed for it in Ragin’s 'configurational comparative methods (CCM' perspective for analysing the complexity of causality as 'multiple conjunctural causation'. In addition to explanation of certain sets of 'outcomes' as in CCM’s combinatorial, set-theoretic approach, embedding stepwise small-N/medium-N QCA in a critical realist ontology allows the method to contribute to development of theory on (qualitative differences between the structures in society that shape water resources use, management and governance.

Is there still a place for the concept of 'therapeutic regression' in psychoanalysis?

Science.gov (United States)

Spurling, Laurence S

2008-06-01

The author uses his own failure to find a place for the idea of therapeutic regression in his clinical thinking or practice as the basis for an investigation into its meaning and usefulness. He makes a distinction between three ways the term 'regression' is used in psychoanalytic discourse: as a way of evoking a primitive level of experience; as a reminder in some clinical situations of the value of non-intervention on the part of the analyst; and as a description of a phase of an analytic treatment with some patients where the analyst needs to put aside normal analytic technique in order to foster a regression in the patient. It is this third meaning, which the author terms "therapeutic regression" that this paper examines, principally by means of an extended discussion of two clinical examples of a patient making a so-called therapeutic regression, one given by Winnicott and the other by Masud Khan. The author argues that in these examples the introduction of the concept of therapeutic regression obscures rather than clarifies the clinical process. He concludes that, as a substantial clinical concept, the idea of therapeutic regression has outlived its usefulness. However he also notes that many psychoanalytic writers continue to find a use for the more generic concept of regression, and that the very engagement with the more particular idea of therapeutic regression has value in provoking questions as to what is truly therapeutic in psychoanalytic treatment.

Application of principal component analysis (PCA) as a sensory assessment tool for fermented food products.

Science.gov (United States)

Ghosh, Debasree; Chattopadhyay, Parimal

2012-06-01

The objective of the work was to use the method of quantitative descriptive analysis (QDA) to describe the sensory attributes of the fermented food products prepared with the incorporation of lactic cultures. Panellists were selected and trained to evaluate various attributes specially color and appearance, body texture, flavor, overall acceptability and acidity of the fermented food products like cow milk curd and soymilk curd, idli, sauerkraut and probiotic ice cream. Principal component analysis (PCA) identified the six significant principal components that accounted for more than 90% of the variance in the sensory attribute data. Overall product quality was modelled as a function of principal components using multiple least squares regression (R (2) = 0.8). The result from PCA was statistically analyzed by analysis of variance (ANOVA). These findings demonstrate the utility of quantitative descriptive analysis for identifying and measuring the fermented food product attributes that are important for consumer acceptability.

Dissipated energy and entropy production for an unconventional heat engine: the stepwise `circular cycle'

Science.gov (United States)

di Liberto, Francesco; Pastore, Raffaele; Peruggi, Fulvio

2011-05-01

When some entropy is transferred, by means of a reversible engine, from a hot heat source to a colder one, the maximum efficiency occurs, i.e. the maximum available work is obtained. Similarly, a reversible heat pumps transfer entropy from a cold heat source to a hotter one with the minimum expense of energy. In contrast, if we are faced with non-reversible devices, there is some lost work for heat engines, and some extra work for heat pumps. These quantities are both related to entropy production. The lost work, i.e. ? , is also called 'degraded energy' or 'energy unavailable to do work'. The extra work, i.e. ? , is the excess of work performed on the system in the irreversible process with respect to the reversible one (or the excess of heat given to the hotter source in the irreversible process). Both quantities are analysed in detail and are evaluated for a complex process, i.e. the stepwise circular cycle, which is similar to the stepwise Carnot cycle. The stepwise circular cycle is a cycle performed by means of N small weights, dw, which are first added and then removed from the piston of the vessel containing the gas or vice versa. The work performed by the gas can be found as the increase of the potential energy of the dw's. Each single dw is identified and its increase, i.e. its increase in potential energy, evaluated. In such a way it is found how the energy output of the cycle is distributed among the dw's. The size of the dw's affects entropy production and therefore the lost and extra work. The distribution of increases depends on the chosen removal process.

RE Rooted in Principal's Biography

NARCIS (Netherlands)

ter Avest, Ina; Bakker, C.

2017-01-01

Critical incidents in the biography of principals appear to be steering in their innovative way of constructing InterReligious Education in their schools. In this contribution, the authors present the biographical narratives of 4 principals: 1 principal introducing interreligious education in a

Impact of stepwise ablation on the biatrial substrate in patients with persistent atrial fibrillation and heart failure.

Science.gov (United States)

Jones, David G; Haldar, Shouvik K; Jarman, Julian W E; Johar, Sofian; Hussain, Wajid; Markides, Vias; Wong, Tom

2013-08-01

Ablation of persistent atrial fibrillation can be challenging, often involving not only pulmonary vein isolation (PVI) but also additional linear lesions and ablation of complex fractionated electrograms (CFE). We examined the impact of stepwise ablation on a human model of advanced atrial substrate of persistent atrial fibrillation in heart failure. In 30 patients with persistent atrial fibrillation and left ventricular ejection fraction ≤35%, high-density CFE maps were recorded biatrially at baseline, in the left atrium (LA) after PVI and linear lesions (roof and mitral isthmus), and biatrially after LA CFE ablation. Surface area of CFE (mean cycle length ≤120 ms) remote to PVI and linear lesions, defined as CFE area, was reduced after PVI (18.3±12.03 to 10.2±7.1 cm(2); Patrial CFE area was reduced by LA ablation, from 25.9±14.1 to 12.9±11.8 cm(2) (Patrial CFE area. Reduction of CFE area at sites remote from ablation would suggest either regression of the advanced atrial substrate or that these CFE were functional phenomena. Nevertheless, in an advanced atrial fibrillation substrate, linear lesions after PVI diminished the target area for CFE ablation, and complete lesions resulted in a favorable clinical outcome.

Application of logistic regression for landslide susceptibility zoning of Cekmece Area, Istanbul, Turkey

Science.gov (United States)

Duman, T. Y.; Can, T.; Gokceoglu, C.; Nefeslioglu, H. A.; Sonmez, H.

2006-11-01

As a result of industrialization, throughout the world, cities have been growing rapidly for the last century. One typical example of these growing cities is Istanbul, the population of which is over 10 million. Due to rapid urbanization, new areas suitable for settlement and engineering structures are necessary. The Cekmece area located west of the Istanbul metropolitan area is studied, because the landslide activity is extensive in this area. The purpose of this study is to develop a model that can be used to characterize landslide susceptibility in map form using logistic regression analysis of an extensive landslide database. A database of landslide activity was constructed using both aerial-photography and field studies. About 19.2% of the selected study area is covered by deep-seated landslides. The landslides that occur in the area are primarily located in sandstones with interbedded permeable and impermeable layers such as claystone, siltstone and mudstone. About 31.95% of the total landslide area is located at this unit. To apply logistic regression analyses, a data matrix including 37 variables was constructed. The variables used in the forwards stepwise analyses are different measures of slope, aspect, elevation, stream power index (SPI), plan curvature, profile curvature, geology, geomorphology and relative permeability of lithological units. A total of 25 variables were identified as exerting strong influence on landslide occurrence, and included by the logistic regression equation. Wald statistics values indicate that lithology, SPI and slope are more important than the other parameters in the equation. Beta coefficients of the 25 variables included the logistic regression equation provide a model for landslide susceptibility in the Cekmece area. This model is used to generate a landslide susceptibility map that correctly classified 83.8% of the landslide-prone areas.

Redesigning Principal Internships: Practicing Principals' Perspectives

Science.gov (United States)

Anast-May, Linda; Buckner, Barbara; Geer, Gregory

2011-01-01

Internship programs too often do not provide the types of experiences that effectively bridge the gap between theory and practice and prepare school leaders who are capable of leading and transforming schools. To help address this problem, the current study is directed at providing insight into practicing principals' views of the types of…

Development and implementation of the Caribbean Laboratory Quality Management Systems Stepwise Improvement Process (LQMS-SIP) Towards Accreditation.

Science.gov (United States)

Alemnji, George; Edghill, Lisa; Guevara, Giselle; Wallace-Sankarsingh, Sacha; Albalak, Rachel; Cognat, Sebastien; Nkengasong, John; Gabastou, Jean-Marc

2017-01-01

Implementing quality management systems and accrediting laboratories in the Caribbean has been a challenge. We report the development of a stepwise process for quality systems improvement in the Caribbean Region. The Caribbean Laboratory Stakeholders met under a joint Pan American Health Organization/US Centers for Disease Control and Prevention initiative and developed a user-friendly framework called 'Laboratory Quality Management System - Stepwise Improvement Process (LQMS-SIP) Towards Accreditation' to support countries in strengthening laboratory services through a stepwise approach toward fulfilling the ISO 15189: 2012 requirements. This approach consists of a three-tiered framework. Tier 1 represents the minimum requirements corresponding to the mandatory criteria for obtaining a licence from the Ministry of Health of the participating country. The next two tiers are quality improvement milestones that are achieved through the implementation of specific quality management system requirements. Laboratories that meet the requirements of the three tiers will be encouraged to apply for accreditation. The Caribbean Regional Organisation for Standards and Quality hosts the LQMS-SIP Secretariat and will work with countries, including the Ministry of Health and stakeholders, including laboratory staff, to coordinate and implement LQMS-SIP activities. The Caribbean Public Health Agency will coordinate and advocate for the LQMS-SIP implementation. This article presents the Caribbean LQMS-SIP framework and describes how it will be implemented among various countries in the region to achieve quality improvement.

The Future of Principal Evaluation

Science.gov (United States)

Clifford, Matthew; Ross, Steven

2012-01-01

The need to improve the quality of principal evaluation systems is long overdue. Although states and districts generally require principal evaluations, research and experience tell that many state and district evaluations do not reflect current standards and practices for principals, and that evaluation is not systematically administered. When…

Preparing Principals as Instructional Leaders: Perceptions of University Faculty, Expert Principals, and Expert Teacher Leaders

Science.gov (United States)

Taylor Backor, Karen; Gordon, Stephen P.

2015-01-01

Although research has established links between the principal's instructional leadership and student achievement, there is considerable concern in the literature concerning the capacity of principal preparation programs to prepare instructional leaders. This study interviewed educational leadership faculty as well as expert principals and teacher…

Stepwise approach to decision making for long-term radioactive waste management. Experience, issues and guiding principles

International Nuclear Information System (INIS)

2004-01-01

Radioactive waste exists as a result of both past and current practices. One of the most challenging tasks is the management of long-lived waste that must be isolated from the human environment for many thousands, or even hundreds of thousands, of years. Although significant technical progress has been made in developing management schemes that, according to technical experts, would ensure long-term safety (e.g. engineered geologic disposal), the rate of progress towards implementing such solutions has been slower than expected. The contrast between expected and observed rates may be partly attributable to an earlier technical optimism. More significant, however, are the setbacks, which have arisen mainly from an underestimation of the societal and political dimensions. In long-term radioactive waste management, consideration is increasingly being given to concepts such as stepwise decision making and adaptive staging in which the public, and especially the local public, are to be meaningfully involved in the review and planning of developments. The key feature of these concepts is development by steps or stages that are reversible, within the limits of practicability. This is designed to provide reassurance that decisions can be reversed if experience shows them to have adverse or unwanted effects. A stepwise approach to decision making has thus come to the fore as being of value in advancing long-term radioactive waste management solutions in a societally acceptable manner. Despite its early identification within the radioactive waste management community as an important means for reaching solutions and decisions in which there is broad-based confidence, the bases for and application of stepwise decision making has not been widely reviewed. Guiding principles of any such process are still being formulated, its roots in empirical social science research have not been fully reviewed, nor the difficulties of its implementation analysed. The report reviews current

School Principals' Emotional Coping Process

Science.gov (United States)

Poirel, Emmanuel; Yvon, Frédéric

2014-01-01

The present study examines the emotional coping of school principals in Quebec. Emotional coping was measured by stimulated recall; six principals were filmed during a working day and presented a week later with their video showing stressful encounters. The results show that school principals experience anger because of reproaches from staff…

Dual Regression

OpenAIRE

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...

The Swedish approach to spent fuel disposal - stepwise implementation

International Nuclear Information System (INIS)

Gustaffson, B.

1997-01-01

This presentation describes the stepwise implementation of direct disposal of spent fuel in Sweden. The present status regarding the technical development of the Swedish concept will be discussed as well the local site work made in co-operation with the affected and concerned municipalities. In this respect it should be noted that the siting work in some cases has caused heavy opposition and negative opinions. A brief review will also be given regarding the Aspo Hard Rock Laboratory. The objectives of this laboratory as well as the ongoing demo-project will be discussed. In order to give the symposium organizer a more broad view of the Swedish programme a number of recent papers has been compiled. Theses papers will be summarized in the presentation. (author). 4 tabs., 22 figs

A stepwise approach to the evaluation and treatment of subclinical hyperthyroidism.

Science.gov (United States)

Mai, Vinh Q; Burch, Henry B

2012-01-01

To review a stepwise approach to the evaluation and treatment of subclinical hyperthyroidism. English-language articles regarding clinical management of subclinical hyperthyroidism published between 2007 and 2012 were reviewed. Subclinical hyperthyroidism is encountered on a daily basis in clinical practice. When evaluating patients with a suppressed serum thyrotropin value, it is important to exclude other potential etiologies such as overt triiodothyronine toxicosis, drug effect, nonthyroidal illness, and central hypothyroidism. In younger patients with mild thyrotropin suppression, it is acceptable to perform testing again in 3 to 6 months to assess for persistence before performing further diagnostic testing. In older patients or patients with thyrotropin values less than 0.1 mIU/L, diagnostic testing should proceed without delay. Persistence of thyrotropin suppression is more typical of nodular thyroid autonomy, whereas thyroiditis and mild Graves disease frequently resolve spontaneously. The clinical consequences of subclinical hyperthyroidism, such as atrial dysrhythmia, accelerated bone loss, increased fracture rate, and higher rates of cardiovascular mortality, are dependent on age and severity. The decision to treat subclinical hyperthyroidism is directly tied to an assessment of the potential for clinical consequences in untreated disease. Definitive therapy is generally selected for patients with nodular autonomous function, whereas antithyroid drug therapy is more appropriate for mild, persistent Graves disease. The presented stepwise approach to the care of patients presenting with an isolated suppression of serum thyrotropin focuses on the differential diagnosis, a prediction of the likelihood of persistence, an assessment of potential risks posed to the patient, and, finally, a personalized choice of therapy.

Principal Time Management Skills: Explaining Patterns in Principals' Time Use, Job Stress, and Perceived Effectiveness

Science.gov (United States)

Grissom, Jason A.; Loeb, Susanna; Mitani, Hajime

2015-01-01

Purpose: Time demands faced by school principals make principals' work increasingly difficult. Research outside education suggests that effective time management skills may help principals meet job demands, reduce job stress, and improve their performance. The purpose of this paper is to investigate these hypotheses. Design/methodology/approach:…

Stepwise or concerted? DFT study on the mechanism of ionic Diels-Alder reaction of chromanes

Directory of Open Access Journals (Sweden)

Haghdadi Mina

2016-01-01

Full Text Available The stepwise and concerted Ionic Diels-Alder reaction between phenyl (pyridin-2-ylmethylene oxonium and styrene derivatives are explored using theoretical method. The results support using computational method via persistent intermediates. The DFT method was essential to reproduce a reasonable potential energy surface for these challenging systems.

Principal Self-Efficacy, Teacher Perceptions of Principal Performance, and Teacher Job Satisfaction

Science.gov (United States)

Evans, Molly Lynn

2016-01-01

In public schools, the principal's role is of paramount importance in influencing teachers to excel and to keep their job satisfaction high. The self-efficacy of leaders is an important characteristic of leadership, but this issue has not been extensively explored in school principals. Using internet-based questionnaires, this study obtained…

Better Care Teams: A Stepwise Skill Reinforcement Model.

Science.gov (United States)

Christopher, Beth-Anne; Grantner, Mary; Coke, Lola A; Wideman, Marilyn; Kwakwa, Francis

2016-06-01

The Building Healthy Urban Communities initiative presents a path for organizations partnering to improve patient outcomes with continuing education (CE) as a key component. Components of the CE initiative included traditional CE delivery formats with an essential element of adaptability and new methods, with rigorous evaluation over time that included evaluation prior to the course, immediately following the CE session, 6 to 8 weeks after the CE session, and then subsequent monthly "testlets." Outcome measures were designed to allow for ongoing adaptation of content, reinforcement of key learning objectives, and use of innovative concordant testing and retrieval practice techniques. The results after 1 year of programming suggest the stepwise skill reinforcement model is effective for learning and is an efficient use of financial and human resources. More important, its design is one that could be adopted at low cost by organizations willing to work in close partnership. J Contin Educ Nurs. 2016;47(6):283-288. Copyright 2016, SLACK Incorporated.

Legal Problems of the Principal.

Science.gov (United States)

Stern, Ralph D.; And Others

The three talks included here treat aspects of the law--tort liability, student records, and the age of majority--as they relate to the principal. Specifically, the talk on torts deals with the consequences of principal negligence in the event of injuries to students. Assurance is given that a reasonable and prudent principal will have a minimum…

Principals Who Think Like Teachers

Science.gov (United States)

Fahey, Kevin

2013-01-01

Being a principal is a complex job, requiring quick, on-the-job learning. But many principals already have deep experience in a role at the very essence of the principalship. They know how to teach. In interviews with principals, Fahey and his colleagues learned that thinking like a teacher was key to their work. Part of thinking the way a teacher…

Trust Me, Principal, or Burn Out! The Relationship between Principals' Burnout and Trust in Students and Parents

Science.gov (United States)

Ozer, Niyazi

2013-01-01

The purpose of this study was to determine the primary school principals' views on trust in students and parents and also, to explore the relationships between principals' levels of professional burnout and their trust in students and parents. To this end, Principal Trust Survey and Friedman Principal Burnout scales were administered on 119…

Optimization of fuel recovery through the stepwise co-pyrolysis of palm shell and scrap tire

International Nuclear Information System (INIS)

Abnisa, Faisal; Wan Daud, Wan Mohd Ashri

2015-01-01

Highlights: • The co-pyrolysis of palm shell and scrap tire was studied. • The effect of stepwise co-pyrolysis temperature was investigated. • Co-pyrolysis successfully improved the quantity and quality of product yields. • Stepwise co-pyrolysis slightly increased oil and gas, and decreased char. • The co-pyrolysis of 50% biomass and 50% scrap tire is recommended. - Abstract: This study optimized the use of biomass waste to generate fuel through co-pyrolysis. In this paper, the effects of stepwise co-pyrolysis temperature and different ratios between palm shells and scrap tires in feedstock were studied to observe any improvements in the quantity and quality of the liquid yield and its byproduct. The ratio of palm shells and scrap tires varied at 100:0, 75:25, 50:50, 25:75, and 0:100. The experiment was conducted in a fixed-bed reactor. The study was divided into two scenarios. The first scenario was performed at the optimum temperature of 500 °C with a reaction time of 60 min. In the second scenario, the temperature was set at 500 °C for 60 min before the temperature was increased to 800 °C with a high heating rate. After the temperature reached 800 °C, the condition was maintained for approximately 45 min. Results showed that an increase in the liquid and gas yields was achieved when the temperature increased after optimum conditions. Increased yield was also obtained when the proportion of scrap tire was increased in the feedstock. Several other important findings are discussed in this paper, including the phases of pyrolysis oil, features of the liquid product, and characteristics of the byproducts. All products from both scenarios were analyzed by various methods to understand their fuel characteristics

[Recommendations for the Stepwise Occupational Reintegration: Can the Characteristic of the Patients Explain the Differences Between the Rehabilitation Centers?].

Science.gov (United States)

Schmid, L; Jankowiak, S; Kaluscha, R; Krischak, G

2016-06-01

The first step to initiate a stepwise occupational reintegration (SOR) is the recommendation of the rehabilitation centers. Therefore rehabilitation centers have a significant impact on the use of SOR. There is evidence that the recommendation rate between the rehabilitation centers differs clearly. The present survey therefore analyses in detail the differences of the recommendation rate and examines which patient-related factors could explain the differences. This study is based on analysis of routine data provided by the German pension insurance in Baden-Württemberg (Rehabilitationsstatistikdatenbasis 2013; RSD). In the analyses rehabilitation measures were included if they were conducted by employed patients (18-64 years) with a muscular-skeletal system disease or a disorder of the connective tissue. Logistic regression models were performed to explain the differences in the recommendation rate of the rehabilitation centers. The data of 134 853 rehabilitation measures out of 32 rehabilitation centers were available. The recommendation rate differed between the rehabilitation centers from 1.36-18.53%. The logistic regression analysis showed that the period of working incapacity 12 month before the rehabilitation and the working capacity on the current job were the most important predictors for the recommendation of a SOR by the rehabilitation centers. Also the rehabilitation centers themselves have an important influence. The results of this survey indicate that the characteristic of the patients is an important factor for the recommendation of SOR. Additionally the rehabilitation centers themselves have an influence on the recommendation of SOR. The results point to the fact that the rehabilitation centers use different criteria by making a recommendation. © Georg Thieme Verlag KG Stuttgart · New York.

Quantifying the Sub-Cellular Distributions of Gold Nanospheres Uptaken by Cells through Stepwise, Site-Selective Etching.

Science.gov (United States)

Xia, Younan; Huo, Da

2018-04-10

A quantitative understanding of the sub-cellular distributions of nanoparticles uptaken by cells is important to the development of nanomedicine. With Au nanospheres as a model system, here we demonstrate, for the first time, how to quantify the numbers of nanoparticles bound to plasma membrane, accumulated in cytosol, and entrapped in lysosomes, respectively, through stepwise, site-selective etching. Our results indicate that the chance for nanoparticles to escape from lysosomes is insensitive to the presence of targeting ligand although ligand-receptor binding has been documented as a critical factor in triggering internalization. Furthermore, the presence of serum proteins is shown to facilitate the binding of nanoparticles to plasma membrane lacking the specific receptor. Collectively, these findings confirm the potential of stepwise etching in quantitatively analyzing the sub-cellular distributions of nanoparticles uptaken by cells in an effort to optimize the therapeutic effect. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Stepwise Regression Analysis of MDOE Balance Calibration Data Acquired at DNW

Science.gov (United States)

DeLoach, RIchard; Philipsen, Iwan

2007-01-01

This paper reports a comparison of two experiment design methods applied in the calibration of a strain-gage balance. One features a 734-point test matrix in which loads are varied systematically according to a method commonly applied in aerospace research and known in the literature of experiment design as One Factor At a Time (OFAT) testing. Two variations of an alternative experiment design were also executed on the same balance, each with different features of an MDOE experiment design. The Modern Design of Experiments (MDOE) is an integrated process of experiment design, execution, and analysis applied at NASA's Langley Research Center to achieve significant reductions in cycle time, direct operating cost, and experimental uncertainty in aerospace research generally and in balance calibration experiments specifically. Personnel in the Instrumentation and Controls Department of the German Dutch Wind Tunnels (DNW) have applied MDOE methods to evaluate them in the calibration of a balance using an automated calibration machine. The data have been sent to Langley Research Center for analysis and comparison. This paper reports key findings from this analysis. The chief result is that a 100-point calibration exploiting MDOE principles delivered quality comparable to a 700+ point OFAT calibration with significantly reduced cycle time and attendant savings in direct and indirect costs. While the DNW test matrices implemented key MDOE principles and produced excellent results, additional MDOE concepts implemented in balance calibrations at Langley Research Center are also identified and described.

High performance yellow organic electroluminescent devices by doping iridium(III) complex into host materials with stepwise energy levels

Energy Technology Data Exchange (ETDEWEB)

Cui, Rongzhen; Zhou, Liang, E-mail: zhoul@ciac.ac.cn; Jiang, Yunlong; Li, Yanan; Zhao, Xuesen; Zhang, Hongjie, E-mail: hongjie@ciac.ac.cn

2015-10-15

In this work, we aim to further improve the electroluminescent (EL) performances of a yellow light-emitting iridium(III) complex by designing double light-emitting layers (EMLs) devices having stepwise energy levels. Compared with single-EML devices, these designed double-EML devices showed improved EL efficiency and brightness attributed to better balance in carriers. In addition, the stepwise distribution in energy levels of host materials is instrumental in broadening the recombination zone, thus delaying the roll-off of EL efficiency. Based on the investigation of carriers' distribution, device structure was further optimized by adjusting the thickness of deposited layers. Finally, yellow EL device (Commission Internationale de l'Eclairage (CIE) coordinates of (0.446, 0.542)) with maximum current efficiency, power efficiency and brightness up to 78.62 cd/A (external quantum efficiency (EQE) of 21.1%), 82.28 lm/W and 72,713 cd/m{sup 2}, respectively, was obtained. Even at the high brightness of 1000 cd/m{sup 2}, EL efficiency as high as 65.54 cd/A (EQE=17.6%) can be retained. - Highlights: • Yellow electroluminescent devices were designed and fabricated. • P-type and n-type materials having stepwise energy levels were chosen as host materials. • Better balance of holes and electrons causes the enhanced efficiencies. • Improved carriers' trapping suppresses the emission of host material.

Exploring the Impact of Applicants' Gender and Religion on Principals' Screening Decisions for Assistant Principal Applicants

Science.gov (United States)

Bon, Susan C.

2009-01-01

In this experimental study, a national random sample of high school principals (stratified by gender) were asked to evaluate hypothetical applicants whose resumes varied by religion (Jewish, Catholic, nondenominational) and gender (male, female) for employment as assistant principals. Results reveal that male principals rate all applicants higher…

A multiple linear regression analysis of hot corrosion attack on a series of nickel base turbine alloys

Science.gov (United States)

Barrett, C. A.

1985-01-01

Multiple linear regression analysis was used to determine an equation for estimating hot corrosion attack for a series of Ni base cast turbine alloys. The U transform (i.e., 1/sin (% A/100) to the 1/2) was shown to give the best estimate of the dependent variable, y. A complete second degree equation is described for the centered" weight chemistries for the elements Cr, Al, Ti, Mo, W, Cb, Ta, and Co. In addition linear terms for the minor elements C, B, and Zr were added for a basic 47 term equation. The best reduced equation was determined by the stepwise selection method with essentially 13 terms. The Cr term was found to be the most important accounting for 60 percent of the explained variability hot corrosion attack.

Analysis of Surface Water Pollution in the Kinta River Using Multivariate Technique

International Nuclear Information System (INIS)

Hamza Ahmad Isiyaka; Hafizan Juahir

2015-01-01

This study aims to investigate the spatial variation in the characteristics of water quality monitoring sites, identify the most significant parameters and the major possible sources of pollution, and apportion the source category in the Kinta River. 31 parameters collected from eight monitoring sites for eight years (2006-2013) were employed. The eight monitoring stations were spatially grouped into three independent clusters in a dendrogram. A drastic reduction in the number of monitored parameters from 31 to eight and nine significant parameters (P<0.05) was achieved using the forward stepwise and backward stepwise discriminate analysis (DA). Principal component analysis (PCA) accounted for more than 76 % in the total variance and attributes the source of pollution to anthropogenic and natural processes. The source apportionment using a combined multiple linear regression and principal component scores indicates that 41 % of the total pollution load is from rock weathering and untreated waste water, 26 % from waste discharge, 24 % from surface runoff and 7 % from faecal waste. This study proposes a reduction in the number of monitoring stations and parameters for a cost effective and time management in the monitoring processes and multivariate technique can provide a simple representation of complex and dynamic water quality characteristics. (author)

Principals' Perceptions of Politics

Science.gov (United States)

Tooms, Autumn K.; Kretovics, Mark A.; Smialek, Charles A.

2007-01-01

This study is an effort to examine principals' perceptions of workplace politics and its influence on their productivity and efficacy. A survey was used to explore the perceptions of current school administrators with regard to workplace politics. The instrument was disseminated to principals serving public schools in one Midwestern state in the…

Regression: A Bibliography.

Science.gov (United States)

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.…

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

Science.gov (United States)

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

2013-07-01

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

Statistical Downscaling Output GCM Modeling with Continuum Regression and Pre-Processing PCA Approach

Directory of Open Access Journals (Sweden)

Sutikno Sutikno

2010-08-01

Full Text Available One of the climate models used to predict the climatic conditions is Global Circulation Models (GCM. GCM is a computer-based model that consists of different equations. It uses numerical and deterministic equation which follows the physics rules. GCM is a main tool to predict climate and weather, also it uses as primary information source to review the climate change effect. Statistical Downscaling (SD technique is used to bridge the large-scale GCM with a small scale (the study area. GCM data is spatial and temporal data most likely to occur where the spatial correlation between different data on the grid in a single domain. Multicollinearity problems require the need for pre-processing of variable data X. Continuum Regression (CR and pre-processing with Principal Component Analysis (PCA methods is an alternative to SD modelling. CR is one method which was developed by Stone and Brooks (1990. This method is a generalization from Ordinary Least Square (OLS, Principal Component Regression (PCR and Partial Least Square method (PLS methods, used to overcome multicollinearity problems. Data processing for the station in Ambon, Pontianak, Losarang, Indramayu and Yuntinyuat show that the RMSEP values and R2 predict in the domain 8x8 and 12x12 by uses CR method produces results better than by PCR and PLS.

The Intramolecular Diels–Alder Reaction of Tryptamine-Derived Zincke Aldehydes Is a Stepwise Process

OpenAIRE

Pham, Hung V.; Martin, David B. C.; Vanderwal, Christopher D.; Houk, K. N.

2012-01-01

Computational studies show that the base-mediated intramolecular Diels–Alder of tryptamine-derived Zincke aldehydes, used as a key step in the synthesis of the Strychnos alkaloids norfluorocurarine and strychnine, proceeds via a stepwise pathway. The experimentally determined importance of a potassium counterion in the base is explained by its ability to preorganize the Zincke aldehyde diene in an s-cis conformation suitable to bicyclization. Computation also supports the thermodynamic import...

Stepwise Swelling of a Thin Film of Lamellae-Forming Poly(styrene-b-butadiene) in Cyclohexane Vapor

DEFF Research Database (Denmark)

Di, Zhenyu; Posselt, Dorthe; Smilgies, Detlef-M.

2012-01-01

We investigated the swelling of a thin film of lamellae-forming poly(styrene-b-butadiene) in cyclohexane vapor. The vapor pressure and thus the degree of swelling of the film are increased in a stepwise manner using a custom-built sample cell. The resulting structural changes during and after each...

Advanced statistics: linear regression, part I: simple linear regression.

Science.gov (United States)

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.

Renewing the Principal Pipeline

Science.gov (United States)

Turnbull, Brenda J.

2015-01-01

The work principals do has always mattered, but as the demands of the job increase, it matters even more. Perhaps once they could maintain safety and order and call it a day, but no longer. Successful principals today must also lead instruction and nurture a productive learning community for students, teachers, and staff. They set the tone for the…

Principal Ports

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Principal Ports are defined by port limits or US Army Corps of Engineers (USACE) projects, these exclude non-USACE projects not authorized for publication. The...

Perceptions of Beginning Public School Principals.

Science.gov (United States)

Lyons, James E.

1993-01-01

Summarizes a study to determine principal's perceptions of their competency in primary responsibility areas and their greatest challenges and frustrations. Beginning principals are challenged by delegating responsibilities and becoming familiar with the principal's role, the local school, and school operations. Their major frustrations are role…

Multiscale principal component analysis

International Nuclear Information System (INIS)

Akinduko, A A; Gorban, A N

2014-01-01

Principal component analysis (PCA) is an important tool in exploring data. The conventional approach to PCA leads to a solution which favours the structures with large variances. This is sensitive to outliers and could obfuscate interesting underlying structures. One of the equivalent definitions of PCA is that it seeks the subspaces that maximize the sum of squared pairwise distances between data projections. This definition opens up more flexibility in the analysis of principal components which is useful in enhancing PCA. In this paper we introduce scales into PCA by maximizing only the sum of pairwise distances between projections for pairs of datapoints with distances within a chosen interval of values [l,u]. The resulting principal component decompositions in Multiscale PCA depend on point (l,u) on the plane and for each point we define projectors onto principal components. Cluster analysis of these projectors reveals the structures in the data at various scales. Each structure is described by the eigenvectors at the medoid point of the cluster which represent the structure. We also use the distortion of projections as a criterion for choosing an appropriate scale especially for data with outliers. This method was tested on both artificial distribution of data and real data. For data with multiscale structures, the method was able to reveal the different structures of the data and also to reduce the effect of outliers in the principal component analysis

Application of the modified chi-square ratio statistic in a stepwise procedure for cascade impactor equivalence testing.

Science.gov (United States)

Weber, Benjamin; Lee, Sau L; Delvadia, Renishkumar; Lionberger, Robert; Li, Bing V; Tsong, Yi; Hochhaus, Guenther

2015-03-01

Equivalence testing of aerodynamic particle size distribution (APSD) through multi-stage cascade impactors (CIs) is important for establishing bioequivalence of orally inhaled drug products. Recent work demonstrated that the median of the modified chi-square ratio statistic (MmCSRS) is a promising metric for APSD equivalence testing of test (T) and reference (R) products as it can be applied to a reduced number of CI sites that are more relevant for lung deposition. This metric is also less sensitive to the increased variability often observed for low-deposition sites. A method to establish critical values for the MmCSRS is described here. This method considers the variability of the R product by employing a reference variance scaling approach that allows definition of critical values as a function of the observed variability of the R product. A stepwise CI equivalence test is proposed that integrates the MmCSRS as a method for comparing the relative shapes of CI profiles and incorporates statistical tests for assessing equivalence of single actuation content and impactor sized mass. This stepwise CI equivalence test was applied to 55 published CI profile scenarios, which were classified as equivalent or inequivalent by members of the Product Quality Research Institute working group (PQRI WG). The results of the stepwise CI equivalence test using a 25% difference in MmCSRS as an acceptance criterion provided the best matching with those of the PQRI WG as decisions of both methods agreed in 75% of the 55 CI profile scenarios.

Andragogical Practices of School Principals in Developing the Leadership Capacities of Assistant Principals

Science.gov (United States)

McDaniel, Luther

2017-01-01

The purpose of this mixed methods study was to assess school principals' perspectives of the extent to which they apply the principles of andragogy to the professional development of assistant principals in their schools. This study was conducted in school districts that constitute a RESA area in a southeastern state. The schools in these…

41 CFR 105-68.995 - Principal.

Science.gov (United States)

2010-07-01

... 41 Public Contracts and Property Management 3 2010-07-01 2010-07-01 false Principal. 105-68.995 Section 105-68.995 Public Contracts and Property Management Federal Property Management Regulations System...-GOVERNMENTWIDE DEBARMENT AND SUSPENSION (NONPROCUREMENT) Definitions § 105-68.995 Principal. Principal means— (a...

A modified GFP facilitates counting membrane protein subunits by step-wise photobleaching in Arabidopsis.

Science.gov (United States)

Song, Kai; Xue, Yiqun; Wang, Xiaohua; Wan, Yinglang; Deng, Xin; Lin, Jinxing

2017-06-01

Membrane proteins exert functions by forming oligomers or molecular complexes. Currently, step-wise photobleaching has been applied to count the fluorescently labelled subunits in plant cells, for which an accurate and reliable control is required to distinguish individual subunits and define the basal fluorescence. However, the common procedure using immobilized GFP molecules is obviously not applicable for analysis in living plant cells. Using the spatial intensity distribution analysis (SpIDA), we found that the A206K mutation reduced the dimerization of GFP molecules. Further ectopic expression of Myristoyl-GFP A206K driven by the endogenous AtCLC2 promoter allowed imaging of individual molecules at a low expression level. As a result, the percentage of dimers in the transgenic pCLC2::Myristoyl-mGFP A206K line was significantly reduced in comparison to that of the pCLC2::Myristoyl-GFP line, confirming its application in defining the basal fluorescence intensity of GFP. Taken together, our results demonstrated that pCLC2::Myristoyl-mGFP A206K can be used as a standard control for monomer GFP, facilitating the analysis of the step-wise photobleaching of membrane proteins in Arabidopsis thaliana. Copyright © 2017 Elsevier GmbH. All rights reserved.

Development of a PROficiency-Based StePwise Endovascular Curricular Training (PROSPECT) Program.

Science.gov (United States)

Maertens, Heidi; Aggarwal, Rajesh; Desender, Liesbeth; Vermassen, Frank; Van Herzeele, Isabelle

2016-01-01

Focus on patient safety, work-hour limitations, and cost-effective education is putting pressure to improve curricula to acquire minimally invasive techniques during surgical training. This study aimed to design a structured training program for endovascular skills and validate its assessment methods. A PROficiency-based StePwise Endovascular Curricular Training (PROSPECT) program was developed, consisting of e-learning and hands-on simulation modules, focusing on iliac and superficial femoral artery atherosclerotic disease. Construct validity was investigated. Performances were assessed using multiple-choice questionnaires, valid simulation parameters, global rating scorings, and examiner checklists. Feasibility was assessed by passage of 2 final-year medical students through this PROSPECT program. Ghent University Hospital, a tertiary clinical care and academic center in Belgium with general surgery residency program. Senior-year medical students were recruited at Ghent University Hospital. Vascular surgeons were invited to participate during conferences and meetings if they had performed at least 100 endovascular procedures as the primary operator during the last 2 years. Overall, 29 medical students and 20 vascular surgeons participated. Vascular surgeons obtained higher multiple-choice questionnaire scores (median: 24.5-22.0 vs. 15.0-12.0; p train cognitive, technical, and nontechnical endovascular skills was developed. A structured, stepwise, proficiency-based valid endovascular program to train cognitive, technical, and human factor skills has been developed and proven to be feasible. A randomized controlled trial has been initiated to investigate its effect on performances in real life, patient outcomes, and cost-effectiveness. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Principal-Counselor Collaboration and School Climate

Science.gov (United States)

Rock, Wendy D.; Remley, Theodore P.; Range, Lillian M.

2017-01-01

Examining whether principal-counselor collaboration and school climate were related, researchers sent 4,193 surveys to high school counselors in the United States and received 419 responses. As principal-counselor collaboration increased, there were increases in counselors viewing the principal as supportive, the teachers as regarding one another…

12 CFR 561.39 - Principal office.

Science.gov (United States)

2010-01-01

... 12 Banks and Banking 5 2010-01-01 2010-01-01 false Principal office. 561.39 Section 561.39 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY DEFINITIONS FOR REGULATIONS AFFECTING ALL SAVINGS ASSOCIATIONS § 561.39 Principal office. The term principal office means the home...

Teacher Supervision Practices and Principals' Characteristics

Science.gov (United States)

April, Daniel; Bouchamma, Yamina

2015-01-01

A questionnaire was used to determine the individual and collective teacher supervision practices of school principals and vice-principals in Québec (n = 39) who participated in a research-action study on pedagogical supervision. These practices were then analyzed in terms of the principals' sociodemographic and socioprofessional characteristics…

Developing Principal Instructional Leadership through Collaborative Networking

Science.gov (United States)

Cone, Mariah Bahar

2010-01-01

This study examines what occurs when principals of urban schools meet together to learn and improve their instructional leadership in collaborative principal networks designed to support, sustain, and provide ongoing principal capacity building. Principal leadership is considered second only to teaching in its ability to improve schools, yet few…

Stepwise dynamics of an anionic micellar film - Formation of crown lenses.

Science.gov (United States)

Lee, Jongju; Nikolov, Alex; Wasan, Darsh

2017-06-15

We studied the stepwise thinning of a microscopic circular foam film formed from an anionic micellar solution of sodium dodecyl sulfate (SDS). The foam film formed from the SDS micellar solution thins in a stepwise manner by the formation and expansion of a dark spot(s) of one layer less than the film thickness. During the last stages of film thinning (e.g., a film with one micellar layer), the dark spot expansion occurs via two steps. Initially, a small dark circular spot inside a film of several microns in size is formed, which expands at a constant rate. Then, a ridge along the expanding spot is formed. As the ridge grows, it becomes unstable and breaks into regular crown lenses, which are seen as white spots in the reflected light at the border of the dark spot with the surrounding thicker film. The Rayleigh type of instability contributes to the formation of the lenses, which results in the increase of the dark spot expansion rate with time. We applied the two-dimensional micellar-vacancy diffusion model and took into consideration the effects of the micellar layering and film volume on the rate of the dark spot expansion [Lee et al., 2016] to predict the rate of the dark spot expansion for a 0.06M SDS film in the presence of lenses. We briefly discuss the Rayleigh type of instability in the case of a 0.06M SDS foam film. The goals of this study are to reveal why the crown lenses are formed during the foam film stratification and to elucidate their effect on the rate of spot expansion. Copyright © 2017 Elsevier Inc. All rights reserved.

Principal Stability and the Rural Divide

Science.gov (United States)

Pendola, Andrew; Fuller, Edward J.

2018-01-01

This article examines the unique features of the rural school context and how these features are associated with the stability of principals in these schools. Given the small but growing literature on the characteristics of rural principals, this study presents an exploratory analysis of principal stability across schools located in different…

Vapor permeation-stepwise injection simultaneous determination of methanol and ethanol in biodiesel with voltammetric detection.

Science.gov (United States)

Shishov, Andrey; Penkova, Anastasia; Zabrodin, Andrey; Nikolaev, Konstantin; Dmitrenko, Maria; Ermakov, Sergey; Bulatov, Andrey

2016-02-01

A novel vapor permeation-stepwise injection (VP-SWI) method for the determination of methanol and ethanol in biodiesel samples is discussed. In the current study, stepwise injection analysis was successfully combined with voltammetric detection and vapor permeation. This method is based on the separation of methanol and ethanol from a sample using a vapor permeation module (VPM) with a selective polymer membrane based on poly(phenylene isophtalamide) (PA) containing high amounts of a residual solvent. After the evaporation into the headspace of the VPM, methanol and ethanol were transported, by gas bubbling, through a PA membrane to a mixing chamber equipped with a voltammetric detector. Ethanol was selectively detected at +0.19 V, and both compounds were detected at +1.20 V. Current subtractions (using a correction factor) were used for the selective determination of methanol. A linear range between 0.05 and 0.5% (m/m) was established for each analyte. The limits of detection were estimated at 0.02% (m/m) for ethanol and methanol. The sample throughput was 5 samples h(-1). The method was successfully applied to the analysis of biodiesel samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Trajectory modeling of gestational weight: A functional principal component analysis approach.

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Menglu Che

Full Text Available Suboptimal gestational weight gain (GWG, which is linked to increased risk of adverse outcomes for a pregnant woman and her infant, is prevalent. In the study of a large cohort of Canadian pregnant women, our goals are to estimate the individual weight growth trajectory using sparsely collected bodyweight data, and to identify the factors affecting the weight change during pregnancy, such as prepregnancy body mass index (BMI, dietary intakes and physical activity. The first goal was achieved through functional principal component analysis (FPCA by conditional expectation. For the second goal, we used linear regression with the total weight gain as the response variable. The trajectory modeling through FPCA had a significantly smaller root mean square error (RMSE and improved adaptability than the classic nonlinear mixed-effect models, demonstrating a novel tool that can be used to facilitate real time monitoring and interventions of GWG. Our regression analysis showed that prepregnancy BMI had a high predictive value for the weight changes during pregnancy, which agrees with the published weight gain guideline.

A principal-agent Model of corruption

NARCIS (Netherlands)

Groenendijk, Nico

1997-01-01

One of the new avenues in the study of political corruption is that of neo-institutional economics, of which the principal-agent theory is a part. In this article a principal-agent model of corruption is presented, in which there are two principals (one of which is corrupting), and one agent (who is

Stepwise adsorption of phenanthrene at the fly ash-water interface as affected by solution chemistry: experimental and modeling studies.

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An, Chunjiang; Huang, Guohe

2012-11-20

Fly ash (FA) is predominantly generated from coal-fired power plants. Contamination during disposal of FA can cause significant environmental problems. Knowledge about the interaction of FA and hydrophobic organic pollutants in the environment is very limited. This study investigated the adsorption of phenanthrene at the interface of FA and water. The performance of phenanthrene adsorption on FA and the effects of various aqueous chemistry conditions were evaluated. The adsorption isotherms exhibited an increasing trend in the adsorbed amounts of phenanthrene, while a stepwise pattern was apparent. A stepwise multisite Langmuir model was developed to simulate the stepwise adsorption process. The adsorption of phenanthrene onto FA was noted to be spontaneous at all temperatures. The thermodynamic results indicated that the adsorption was an exothermic process. The adsorption capacity gradually decreased as pH increased from 4 to 8; however, this trend became less significant when pH was changed from 8 to 10. The binding affinity of phenanthrene to FA increased after the addition of humic acid (HA). The pH variation was also responsible for the changes of phenanthrene adsorption on FA in the presence of HA. High ionic strength corresponded to low mobility of phenanthrene in the FA-water system. Results of this study can help reveal the migration patterns of organic contaminants in the FA-water system and facilitate environmental risk assessment at FA disposal sites.

Determinants of Return on Assets in Romania: A Principal Component Analysis

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Sorana Vatavu

2015-03-01

Full Text Available This paper examines the impact of capital structure, as well as its determinants on the financial performance of Romanian companies listed on the Bucharest Stock Exchange. The analysis is based on cross sectional regressions and factor analysis, and it refers to a ten-year period (2003-2012. Return on assets (ROA is the performance proxy, while the capital structure indicator is debt ratio. Regression results indicate that Romanian companies register higher returns when they operate with limited borrowings. Among the capital structure determinants, tangibility and business risk have a negative impact on ROA, but the level of taxation has a positive effect, showing that companies manage their assets more efficiently during times of higher fiscal pressure. Performance is sustained by sales turnover, but not significantly influenced by high levels of liquidity. Periods of unstable economic conditions, reflected by high inflation rates and the current financial crisis, have a strong negative impact on corporate performance. Based on regression results, three factors were considered through the method of iterated principal component factors: the first one incorporates debt and size, as an indicator of consumption, the second one integrates the influence of tangibility and liquidity, marking the investment potential, and the third one is an indicator of assessed risk, integrating the volatility of earnings with the level of taxation. ROA is significantly influenced by these three factors, regardless the regression method used. The consumption factor has a negative impact on performance, while the investment and risk variables positively influence ROA.

Effect of Stepwise Doping on Lifetime and Efficiency of Blue and White Phosphorescent Organic Light Emitting Diodes.

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Lee, Song Eun; Lee, Ho Won; Lee, Seok Jae; Koo, Ja-ryong; Lee, Dong Hyung; Yang, Hyung Jin; Kim, Hye Jeong; Yoon, Seung Soo; Kim, Young Kwan

2015-02-01

We investigated a light emission mechanism of blue phosphorescent organic light emitting diodes (PHOLEDs), using a stepwise doping profile of 2, 8, and 14 wt.% within the emitting layer (EML). We fabricated several blue PHOLEDs with phosphorescent blue emitter iridium(III) bis[(4,6-difluorophenyl)-pyridinato-N,C2]picolinate doped in N,N'-dicarbazolyl-3,5-benzene as a p-type host material. A blue PHOLED with the highest doping concentration as part of the EML close to an electron transporting layer showed a maximum luminous efficiency of 20.74 cd/A, and a maximum external quantum efficiency of 10.52%. This can be explained by effective electron injection through a highly doped EML side. Additionally, a white OLED based on the doping profile was fabricated with two thin red EMLs within a blue EML maintaining a thickness of 30 nm for the entire EML. Keywords: Blue Phosphorescent Organic Light Emitting Diodes, Stepwise Doping Structure, Charge Trapping Effect.

Development and Application of a Stepwise Assessment Process for Rational Redesign of Sequential Skills-Based Courses.

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Gallimore, Casey E; Porter, Andrea L; Barnett, Susanne G

2016-10-25

Objective. To develop and apply a stepwise process to assess achievement of course learning objectives related to advanced pharmacy practice experiences (APPEs) preparedness and inform redesign of sequential skills-based courses. Design. Four steps comprised the assessment and redesign process: (1) identify skills critical for APPE preparedness; (2) utilize focus groups and course evaluations to determine student competence in skill performance; (3) apply course mapping to identify course deficits contributing to suboptimal skill performance; and (4) initiate course redesign to target exposed deficits. Assessment. Focus group participants perceived students were least prepared for skills within the Accreditation Council for Pharmacy Education's pre-APPE core domains of Identification and Assessment of Drug-related Problems and General Communication Abilities. Course mapping identified gaps in instruction, performance, and assessment of skills within aforementioned domains. Conclusions. A stepwise process that identified strengths and weaknesses of a course, was used to facilitate structured course redesign. Strengths of the process included input and corroboration from both preceptors and students. Limitations included feedback from a small number of pharmacy preceptors and increased workload on course coordinators.

Prediction of periodically correlated processes by wavelet transform and multivariate methods with applications to climatological data

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Ghanbarzadeh, Mitra; Aminghafari, Mina

2015-05-01

This article studies the prediction of periodically correlated process using wavelet transform and multivariate methods with applications to climatological data. Periodically correlated processes can be reformulated as multivariate stationary processes. Considering this fact, two new prediction methods are proposed. In the first method, we use stepwise regression between the principal components of the multivariate stationary process and past wavelet coefficients of the process to get a prediction. In the second method, we propose its multivariate version without principal component analysis a priori. Also, we study a generalization of the prediction methods dealing with a deterministic trend using exponential smoothing. Finally, we illustrate the performance of the proposed methods on simulated and real climatological data (ozone amounts, flows of a river, solar radiation, and sea levels) compared with the multivariate autoregressive model. The proposed methods give good results as we expected.

Principal Curves on Riemannian Manifolds.

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Hauberg, Soren

2016-09-01

Euclidean statistics are often generalized to Riemannian manifolds by replacing straight-line interpolations with geodesic ones. While these Riemannian models are familiar-looking, they are restricted by the inflexibility of geodesics, and they rely on constructions which are optimal only in Euclidean domains. We consider extensions of Principal Component Analysis (PCA) to Riemannian manifolds. Classic Riemannian approaches seek a geodesic curve passing through the mean that optimizes a criteria of interest. The requirements that the solution both is geodesic and must pass through the mean tend to imply that the methods only work well when the manifold is mostly flat within the support of the generating distribution. We argue that instead of generalizing linear Euclidean models, it is more fruitful to generalize non-linear Euclidean models. Specifically, we extend the classic Principal Curves from Hastie & Stuetzle to data residing on a complete Riemannian manifold. We show that for elliptical distributions in the tangent of spaces of constant curvature, the standard principal geodesic is a principal curve. The proposed model is simple to compute and avoids many of the pitfalls of traditional geodesic approaches. We empirically demonstrate the effectiveness of the Riemannian principal curves on several manifolds and datasets.

Impact of Antibiotic Shortage on H. Pylori Treatment: A Step-Wise Approach for Pharmacist Management

Directory of Open Access Journals (Sweden)

Ann Lloyd, Pharm.D., BCPS

2013-01-01

Full Text Available The current drug shortage crisis involving multiple oral antibiotics has significantly impacted preferred therapeutic options for treatment of H.pylori infection. Pharmacists may help alleviate the impact of this shortage through a proposed step-wise approach which includes proper inventory management, verification of indication, evaluation of regimen, therapeutic monitoring, and communication with patients and providers regarding alternative therapy or symptomatic relief.

Ordinary least square regression, orthogonal regression, geometric mean regression and their applications in aerosol science

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

Principal Leadership for Technology-enhanced Learning in Science

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Gerard, Libby F.; Bowyer, Jane B.; Linn, Marcia C.

2008-02-01

Reforms such as technology-enhanced instruction require principal leadership. Yet, many principals report that they need help to guide implementation of science and technology reforms. We identify strategies for helping principals provide this leadership. A two-phase design is employed. In the first phase we elicit principals' varied ideas about the Technology-enhanced Learning in Science (TELS) curriculum materials being implemented by teachers in their schools, and in the second phase we engage principals in a leadership workshop designed based on the ideas they generated. Analysis uses an emergent coding scheme to categorize principals' ideas, and a knowledge integration framework to capture the development of these ideas. The analysis suggests that principals frame their thinking about the implementation of TELS in terms of: principal leadership, curriculum, educational policy, teacher learning, student outcomes and financial resources. They seek to improve their own knowledge to support this reform. The principals organize their ideas around individual school goals and current political issues. Principals prefer professional development activities that engage them in reviewing curricula and student work with other principals. Based on the analysis, this study offers guidelines for creating learning opportunities that enhance principals' leadership abilities in technology and science reform.

Adaptive evolution of Escherichia coli to Ciprofloxacin in controlled stress environments: emergence of resistance in continuous and step-wise gradients

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Deng, J.; Zhou, L.; Dong, Y.; Sanford, R. A.; Shechtman, L. A.; Alcalde, R.; Werth, C. J.; Fouke, B. W.

2017-12-01

Microorganisms in nature have evolved in response to a variety of environmental stresses, including gradients in pH, flow and chemistry. While environmental stresses are generally considered to be the driving force of adaptive evolution, the impact and extent of any specific stress needed to drive such changes has not been well characterized. In this study, a microfluidic diffusion chamber (MDC) and a batch culturing system were used to systematically study the effects of continuous versus step-wise stress increments on adaptation of E. coli to the antibiotic ciprofloxacin. In the MDC, a diffusion gradient of ciprofloxacin was established across a microfluidic well array to microscopically observe changes in Escherichia coli strain 307 replication and migration patterns that would indicate emergence of resistance due to genetic mutations. Cells recovered from the MDC only had resistance of 50-times the original minimum inhibition concentration (MICoriginal) of ciprofloxacin, although minimum exposure concentrations were over 80 × MICoriginal by the end of the experiment. In complementary batch experiments, E. coli 307 were exposed to step-wise daily increases of ciprofloxacin at rates equivalent to 0.1×, 0.2×, 0.4× or 0.8× times MICoriginal/day. Over a period of 18 days, E. coli cells were able to acquire resistance of up to 225 × MICoriginal, with exposure to ciprofloxacin concentration up to only 14.9 × MIC­original. The different levels of acquired resistance in the continuous MDC versus step-wise batch increment experiments suggests that the intrinsic rate of E. coli adaptation was exceeded in the MDC, while the step-wise experiments favor adaptation to the highest ciprofloxacin experiments. Genomic analyses of E. coli DNA extracted from the microfluidic cell and batch cultures indicated four single nucleotide polymorphism (SNP) mutations of amino acid 82, 83 and 87 in the gyrA gene. The progression of adaptation in the step-wise increments of

Logistic LASSO regression for the diagnosis of breast cancer using clinical demographic data and the BI-RADS lexicon for ultrasonography

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Sun Mi Kim

2018-01-01

Full Text Available Purpose The aim of this study was to compare the performance of image analysis for predicting breast cancer using two distinct regression models and to evaluate the usefulness of incorporating clinical and demographic data (CDD into the image analysis in order to improve the diagnosis of breast cancer. Methods This study included 139 solid masses from 139 patients who underwent a ultrasonography-guided core biopsy and had available CDD between June 2009 and April 2010. Three breast radiologists retrospectively reviewed 139 breast masses and described each lesion using the Breast Imaging Reporting and Data System (BI-RADS lexicon. We applied and compared two regression methods-stepwise logistic (SL regression and logistic least absolute shrinkage and selection operator (LASSO regression-in which the BI-RADS descriptors and CDD were used as covariates. We investigated the performances of these regression methods and the agreement of radiologists in terms of test misclassification error and the area under the curve (AUC of the tests. Results Logistic LASSO regression was superior (P<0.05 to SL regression, regardless of whether CDD was included in the covariates, in terms of test misclassification errors (0.234 vs. 0.253, without CDD; 0.196 vs. 0.258, with CDD and AUC (0.785 vs. 0.759, without CDD; 0.873 vs. 0.735, with CDD. However, it was inferior (P<0.05 to the agreement of three radiologists in terms of test misclassification errors (0.234 vs. 0.168, without CDD; 0.196 vs. 0.088, with CDD and the AUC without CDD (0.785 vs. 0.844, P<0.001, but was comparable to the AUC with CDD (0.873 vs. 0.880, P=0.141. Conclusion Logistic LASSO regression based on BI-RADS descriptors and CDD showed better performance than SL in predicting the presence of breast cancer. The use of CDD as a supplement to the BI-RADS descriptors significantly improved the prediction of breast cancer using logistic LASSO regression.

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)

Stepwise hydrochloric acid extraction of monazite hydroxides for the recovery of cerium lean rare earths, cerium, uranium and thorium

International Nuclear Information System (INIS)

Swaminathan, T.V.; Nair, V.R.; John, C.V.

1988-01-01

Monazite sand is normally processed by the caustic soda route to produce mixed rare earth chloride, thorium hydroxide and trisodium phosphate. Bulk of the mixed rare earth chloride is used for the preparation of FC catalysts. Recently some of the catalyst producers have shown preference to cerium depleted (lanthanum enriched) rare earth chloride rather than the natural rare earth chloride obtained from monazite. Therefore, a process for producing cerium depleted rare earth chloride, cerium, thorium and uranium from rare earth + thorium hydroxide obtained by treating monazite, based on stepwise hydrochloric acid extraction, was developed in the authors laboratory. The process involves drying of the mixed rare earth-thorium hydroxide cake obtained by monazite-caustic soda process followed by stepwise extraction of the dried cake with hydrochloric acid under specified conditions

Reduced Rank Regression

DEFF Research Database (Denmark)

Johansen, Søren

2008-01-01

The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

Two biased estimation techniques in linear regression: Application to aircraft

Science.gov (United States)

Klein, Vladislav

1988-01-01

Several ways for detection and assessment of collinearity in measured data are discussed. Because data collinearity usually results in poor least squares estimates, two estimation techniques which can limit a damaging effect of collinearity are presented. These two techniques, the principal components regression and mixed estimation, belong to a class of biased estimation techniques. Detection and assessment of data collinearity and the two biased estimation techniques are demonstrated in two examples using flight test data from longitudinal maneuvers of an experimental aircraft. The eigensystem analysis and parameter variance decomposition appeared to be a promising tool for collinearity evaluation. The biased estimators had far better accuracy than the results from the ordinary least squares technique.

Triangulating Principal Effectiveness: How Perspectives of Parents, Teachers, and Assistant Principals Identify the Central Importance of Managerial Skills. Working Paper 35

Science.gov (United States)

Grissom, Jason A.; Loeb, Susanna

2009-01-01

While the importance of effective principals is undisputed, few studies have addressed what specific skills principals need to promote school success. This study draws on unique data combining survey responses from principals, assistant principals, teachers and parents with rich administrative data to identify which principal skills matter most…

Principal components

NARCIS (Netherlands)

Hallin, M.; Hörmann, S.; Piegorsch, W.; El Shaarawi, A.

2012-01-01

Principal Components are probably the best known and most widely used of all multivariate analysis techniques. The essential idea consists in performing a linear transformation of the observed k-dimensional variables in such a way that the new variables are vectors of k mutually orthogonal

Measuring Principal Performance: How Rigorous Are Commonly Used Principal Performance Assessment Instruments? A Quality School Leadership Issue Brief

Science.gov (United States)

Condon, Christopher; Clifford, Matthew

2010-01-01

This brief reviews the publicly available principal assessments and points superintendents and policy makers toward strong instruments to measure principal performance. Specifically, the measures included in this review are expressly intended to evaluate principal performance and have varying degrees of publicly available evidence of psychometric…

Estimation of Geographically Weighted Regression Case Study on Wet Land Paddy Productivities in Tulungagung Regency

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Danang Ariyanto

2017-11-01

Full Text Available Regression is a method connected independent variable and dependent variable with estimation parameter as an output. Principal problem in this method is its application in spatial data. Geographically Weighted Regression (GWR method used to solve the problem. GWR  is a regression technique that extends the traditional regression framework by allowing the estimation of local rather than global parameters. In other words, GWR runs a regression for each location, instead of a sole regression for the entire study area. The purpose of this research is to analyze the factors influencing wet land paddy productivities in Tulungagung Regency. The methods used in this research is  GWR using cross validation  bandwidth and weighted by adaptive Gaussian kernel fungtion.This research using  4 variables which are presumed affecting the wet land paddy productivities such as:  the rate of rainfall(X1, the average cost of fertilizer per hectare(X2, the average cost of pestisides per hectare(X3 and Allocation of subsidized NPK fertilizer of food crops sub-sector(X4. Based on the result, X1, X2, X3 and X4  has a different effect on each Distric. So, to improve the productivity of wet land paddy in Tulungagung Regency required a special policy based on the GWR model in each distric.

Step-wise pulling protocols for non-equilibrium dynamics

Science.gov (United States)

Ngo, Van Anh

The fundamental laws of thermodynamics and statistical mechanics, and the deeper understandings of quantum mechanics have been rebuilt in recent years. It is partly because of the increasing power of computing resources nowadays, that allow shedding direct insights into the connections among the thermodynamics laws, statistical nature of our world, and the concepts of quantum mechanics, which have not yet been understood. But mostly, the most important reason, also the ultimate goal, is to understand the mechanisms, statistics and dynamics of biological systems, whose prevailing non-equilibrium processes violate the fundamental laws of thermodynamics, deviate from statistical mechanics, and finally complicate quantum effects. I believe that investigations of the fundamental laws of non-equilibrium dynamics will be a frontier research for at least several more decades. One of the fundamental laws was first discovered in 1997 by Jarzynski, so-called Jarzynski's Equality. Since then, different proofs, alternative descriptions of Jarzynski's Equality, and its further developments and applications have been quickly accumulated. My understandings, developments and applications of an alternative theory on Jarzynski's Equality form the bulk of this dissertation. The core of my theory is based on stepwise pulling protocols, which provide deeper insight into how fluctuations of reaction coordinates contribute to free-energy changes along a reaction pathway. We find that the most optimal pathways, having the largest contribution to free-energy changes, follow the principle of detailed balance. This is a glimpse of why the principle of detailed balance appears so powerful for sampling the most probable statistics of events. In a further development on Jarzynski's Equality, I have been trying to use it in the formalism of diagonal entropy to propose a way to extract useful thermodynamic quantities such temperature, work and free-energy profiles from far

Impact of Antibiotic Shortage on H. Pylori Treatment: A Step-Wise Approach for Pharmacist Management

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Michelle M. Lamb

2013-01-01

Full Text Available The current drug shortage crisis involving multiple oral antibiotics has significantly impacted preferred therapeutic options for treatment of H.pylori infection. Pharmacists may help alleviate the impact of this shortage through a proposed step-wise approach which includes proper inventory management, verification of indication, evaluation of regimen, therapeutic monitoring, and communication with patients and providers regarding alternative therapy or symptomatic relief.   Type: Original Research

Quantile Regression Methods

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...

Super-resolution fluorescence microscopy by stepwise optical saturation

Science.gov (United States)

Zhang, Yide; Nallathamby, Prakash D.; Vigil, Genevieve D.; Khan, Aamir A.; Mason, Devon E.; Boerckel, Joel D.; Roeder, Ryan K.; Howard, Scott S.

2018-01-01

Super-resolution fluorescence microscopy is an important tool in biomedical research for its ability to discern features smaller than the diffraction limit. However, due to its difficult implementation and high cost, the super-resolution microscopy is not feasible in many applications. In this paper, we propose and demonstrate a saturation-based super-resolution fluorescence microscopy technique that can be easily implemented and requires neither additional hardware nor complex post-processing. The method is based on the principle of stepwise optical saturation (SOS), where M steps of raw fluorescence images are linearly combined to generate an image with a M-fold increase in resolution compared with conventional diffraction-limited images. For example, linearly combining (scaling and subtracting) two images obtained at regular powers extends the resolution by a factor of 1.4 beyond the diffraction limit. The resolution improvement in SOS microscopy is theoretically infinite but practically is limited by the signal-to-noise ratio. We perform simulations and experimentally demonstrate super-resolution microscopy with both one-photon (confocal) and multiphoton excitation fluorescence. We show that with the multiphoton modality, the SOS microscopy can provide super-resolution imaging deep in scattering samples. PMID:29675306

Principal Component Analysis-Based Pattern Analysis of Dose-Volume Histograms and Influence on Rectal Toxicity

International Nuclear Information System (INIS)

Soehn, Matthias; Alber, Markus; Yan Di

2007-01-01

Purpose: The variability of dose-volume histogram (DVH) shapes in a patient population can be quantified using principal component analysis (PCA). We applied this to rectal DVHs of prostate cancer patients and investigated the correlation of the PCA parameters with late bleeding. Methods and Materials: PCA was applied to the rectal wall DVHs of 262 patients, who had been treated with a four-field box, conformal adaptive radiotherapy technique. The correlated changes in the DVH pattern were revealed as 'eigenmodes,' which were ordered by their importance to represent data set variability. Each DVH is uniquely characterized by its principal components (PCs). The correlation of the first three PCs and chronic rectal bleeding of Grade 2 or greater was investigated with uni- and multivariate logistic regression analyses. Results: Rectal wall DVHs in four-field conformal RT can primarily be represented by the first two or three PCs, which describe ∼94% or 96% of the DVH shape variability, respectively. The first eigenmode models the total irradiated rectal volume; thus, PC1 correlates to the mean dose. Mode 2 describes the interpatient differences of the relative rectal volume in the two- or four-field overlap region. Mode 3 reveals correlations of volumes with intermediate doses (∼40-45 Gy) and volumes with doses >70 Gy; thus, PC3 is associated with the maximal dose. According to univariate logistic regression analysis, only PC2 correlated significantly with toxicity. However, multivariate logistic regression analysis with the first two or three PCs revealed an increased probability of bleeding for DVHs with more than one large PC. Conclusions: PCA can reveal the correlation structure of DVHs for a patient population as imposed by the treatment technique and provide information about its relationship to toxicity. It proves useful for augmenting normal tissue complication probability modeling approaches

Innovation Management Perceptions of Principals

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Bakir, Asli Agiroglu

2016-01-01

This study is aimed to determine the perceptions of principals about innovation management and to investigate whether there is a significant difference in this perception according to various parameters. In the study, descriptive research model is used and universe is consisted from principals who participated in "Acquiring Formation Course…

Face Hallucination with Linear Regression Model in Semi-Orthogonal Multilinear PCA Method

Science.gov (United States)

Asavaskulkiet, Krissada

2018-04-01

In this paper, we propose a new face hallucination technique, face images reconstruction in HSV color space with a semi-orthogonal multilinear principal component analysis method. This novel hallucination technique can perform directly from tensors via tensor-to-vector projection by imposing the orthogonality constraint in only one mode. In our experiments, we use facial images from FERET database to test our hallucination approach which is demonstrated by extensive experiments with high-quality hallucinated color faces. The experimental results assure clearly demonstrated that we can generate photorealistic color face images by using the SO-MPCA subspace with a linear regression model.

Using Edge Voxel Information to Improve Motion Regression for rs-fMRI Connectivity Studies.

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Patriat, Rémi; Molloy, Erin K; Birn, Rasmus M

2015-11-01

Recent fMRI studies have outlined the critical impact of in-scanner head motion, particularly on estimates of functional connectivity. Common strategies to reduce the influence of motion include realignment as well as the inclusion of nuisance regressors, such as the 6 realignment parameters, their first derivatives, time-shifted versions of the realignment parameters, and the squared parameters. However, these regressors have limited success at noise reduction. We hypothesized that using nuisance regressors consisting of the principal components (PCs) of edge voxel time series would be better able to capture slice-specific and nonlinear signal changes, thus explaining more variance, improving data quality (i.e., lower DVARS and temporal SNR), and reducing the effect of motion on default-mode network connectivity. Functional MRI data from 22 healthy adult subjects were preprocessed using typical motion regression approaches as well as nuisance regression derived from edge voxel time courses. Results were evaluated in the presence and absence of both global signal regression and motion censoring. Nuisance regressors derived from signal intensity time courses at the edge of the brain significantly improved motion correction compared to using only the realignment parameters and their derivatives. Of the models tested, only the edge voxel regression models were able to eliminate significant differences in default-mode network connectivity between high- and low-motion subjects regardless of the use of global signal regression or censoring.

A Monte Carlo simulation study comparing linear regression, beta regression, variable-dispersion beta regression and fractional logit regression at recovering average difference measures in a two sample design.

Science.gov (United States)

Meaney, Christopher; Moineddin, Rahim

2014-01-24

In biomedical research, response variables are often encountered which have bounded support on the open unit interval--(0,1). Traditionally, researchers have attempted to estimate covariate effects on these types of response data using linear regression. Alternative modelling strategies may include: beta regression, variable-dispersion beta regression, and fractional logit regression models. This study employs a Monte Carlo simulation design to compare the statistical properties of the linear regression model to that of the more novel beta regression, variable-dispersion beta regression, and fractional logit regression models. In the Monte Carlo experiment we assume a simple two sample design. We assume observations are realizations of independent draws from their respective probability models. The randomly simulated draws from the various probability models are chosen to emulate average proportion/percentage/rate differences of pre-specified magnitudes. Following simulation of the experimental data we estimate average proportion/percentage/rate differences. We compare the estimators in terms of bias, variance, type-1 error and power. Estimates of Monte Carlo error associated with these quantities are provided. If response data are beta distributed with constant dispersion parameters across the two samples, then all models are unbiased and have reasonable type-1 error rates and power profiles. If the response data in the two samples have different dispersion parameters, then the simple beta regression model is biased. When the sample size is small (N0 = N1 = 25) linear regression has superior type-1 error rates compared to the other models. Small sample type-1 error rates can be improved in beta regression models using bias correction/reduction methods. In the power experiments, variable-dispersion beta regression and fractional logit regression models have slightly elevated power compared to linear regression models. Similar results were observed if the

Time Management for New Principals

Science.gov (United States)

Ruder, Robert

2008-01-01

Becoming a principal is a milestone in an educator's professional life. The principalship is an opportunity to provide leadership that will afford students opportunities to thrive in a nurturing and supportive environment. Despite the continuously expanding demands of being a new principal, effective time management will enable an individual to be…

Can dispersion modeling of air pollution be improved by land-use regression? An example from Stockholm, Sweden.

Science.gov (United States)

Korek, Michal; Johansson, Christer; Svensson, Nina; Lind, Tomas; Beelen, Rob; Hoek, Gerard; Pershagen, Göran; Bellander, Tom

2017-11-01

Both dispersion modeling (DM) and land-use regression modeling (LUR) are often used for assessment of long-term air pollution exposure in epidemiological studies, but seldom in combination. We developed a hybrid DM-LUR model using 93 biweekly observations of NO x at 31 sites in greater Stockholm (Sweden). The DM was based on spatially resolved topographic, physiographic and emission data, and hourly meteorological data from a diagnostic wind model. Other data were from land use, meteorology and routine monitoring of NO x . We built a linear regression model for NO x , using a stepwise forward selection of covariates. The resulting model predicted observed NO x (R 2 =0.89) better than the DM without covariates (R 2 =0.68, P-interaction <0.001) and with minimal apparent bias. The model included (in descending order of importance) DM, traffic intensity on the nearest street, population (number of inhabitants) within 100 m radius, global radiation (direct sunlight plus diffuse or scattered light) and urban contribution to NO x levels (routine urban NO x , less routine rural NO x ). Our results indicate that there is a potential for improving estimates of air pollutant concentrations based on DM, by incorporating further spatial characteristics of the immediate surroundings, possibly accounting for imperfections in the emission data.

What Motivates Principals?

Science.gov (United States)

Iannone, Ron

1973-01-01

Achievement and recognition were mentioned as factors appearing with greater frequency in principal's job satisfactions; school district policy and interpersonal relations were mentioned as job dissatisfactions. (Editor)

Regression Phalanxes

OpenAIRE

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...

Bureaucratic Control and Principal Role.

Science.gov (United States)

Bezdek, Robert; And Others

The purposes of this study were to determine the manner in which the imposition of increased bureaucratic control over principals influenced their allocation of time to tasks and to investigate principals' perceptions of the changes in their roles brought about by this increased control. The specific bureaucratic control system whose effects were…

A Latent-Variable Causal Model of Faculty Reputational Ratings.

Science.gov (United States)

King, Suzanne; Wolfle, Lee M.

A reanalysis was conducted of Saunier's research (1985) on sources of variation in the National Research Council (NRC) reputational ratings of university faculty. Saunier conducted a stepwise regression analysis using 12 predictor variables. Due to problems with multicollinearity and because of the atheoretical nature of stepwise regression,…

School Principals' Sources of Knowledge

Science.gov (United States)

Perkins, Arland Early

2014-01-01

The purpose of this study was to determine what sources of professional knowledge are available to principals in 1 rural East Tennessee school district. Qualitative research methods were applied to gain an understanding of what sources of knowledge are used by school principals in 1 rural East Tennessee school district and the barriers they face…

Regression Association Analysis of Yield-Related Traits with RAPD Molecular Markers in Pistachio (Pistacia vera L.

Directory of Open Access Journals (Sweden)

Saeid Mirzaei

2017-10-01

molecular date (as independent variable and morphological data (as dependent variable was performed using multiple regression analysis to identify informative markers associated with the yield related traits. Multiple regression analysis was conducted using stepwise method of linear regression analysis option of SPSS. Student t-test was performed to assess significance difference between mean trait estimates of genotypes where specific markers were present and absent. Markers shown significant regression values were considered to be associated with the trait under consideration. Results and Discussion: Finally 11 primers were polymorphic and a total of 56 pieces (loci were amplified that among these, 36 segments (64.29% showed polymorphism with an average of 5.09% per primers and the rate of this polymorphism ranged from at least 25% for AJ05 primer up to 87.5% for OPAD02 primer. Polymorphic information content ranged from 0.095 (AJ05 and OPAD14 to 0.39 (OPC05, with an average of 0.23. Stepwise regression analysis between molecular data and traits was performed to identify informative markers associated with yield component traits. Nineteen RAPD fragments were found associated with six yield related traits. Some of RAPD markers were associated with more than one trait in multiple regression analysis that may be due to pleiotropic effect of the linked quantitative trait locus on different traits. However, to better understand these relationships, preparation of segregating population and linkage mapping is necessary. Also, these results could be useful in marker-assisted breeding programs when no other genetic information is available. Conclusion: This investigation on molecular markers associated with yield traits in Pistachio has provided clues for identification of the genotypes with higher yield value. In breeding programs selection of quality material is often a time-consuming process, and thus marker-assisted selection could be of great useful in identification of

Reduction of symplectic principal R-bundles

International Nuclear Information System (INIS)

Lacirasella, Ignazio; Marrero, Juan Carlos; Padrón, Edith

2012-01-01

We describe a reduction process for symplectic principal R-bundles in the presence of a momentum map. These types of structures play an important role in the geometric formulation of non-autonomous Hamiltonian systems. We apply this procedure to the standard symplectic principal R-bundle associated with a fibration π:M→R. Moreover, we show a reduction process for non-autonomous Hamiltonian systems on symplectic principal R-bundles. We apply these reduction processes to several examples. (paper)

New Principal Coaching as a Safety Net

Science.gov (United States)

Celoria, Davide; Roberson, Ingrid

2015-01-01

This study examines new principal coaching as an induction process and explores the emotional dimensions of educational leadership. Twelve principal coaches and new principals--six of each--participated in this qualitative study that employed emergent coding (Creswell, 2008; Denzin, 2005; Glaser & Strauss, 1998; Spradley, 1979). The major…

Importance of an Effective Principal-Counselor Relationship

Science.gov (United States)

Edwards, LaWanda; Grace, Ronald; King, Gwendolyn

2014-01-01

An effective relationship between the principal and school counselor is essential when improving student achievement. To have an effective relationship, there must be communication, trust and respect, leadership, and collaborative planning between the principal and school counselor (College Board, 2011). Principals and school counselors are both…

The best of both worlds: Phylogenetic eigenvector regression and mapping

Directory of Open Access Journals (Sweden)

José Alexandre Felizola Diniz Filho

2015-09-01

Full Text Available Eigenfunction analyses have been widely used to model patterns of autocorrelation in time, space and phylogeny. In a phylogenetic context, Diniz-Filho et al. (1998 proposed what they called Phylogenetic Eigenvector Regression (PVR, in which pairwise phylogenetic distances among species are submitted to a Principal Coordinate Analysis, and eigenvectors are then used as explanatory variables in regression, correlation or ANOVAs. More recently, a new approach called Phylogenetic Eigenvector Mapping (PEM was proposed, with the main advantage of explicitly incorporating a model-based warping in phylogenetic distance in which an Ornstein-Uhlenbeck (O-U process is fitted to data before eigenvector extraction. Here we compared PVR and PEM in respect to estimated phylogenetic signal, correlated evolution under alternative evolutionary models and phylogenetic imputation, using simulated data. Despite similarity between the two approaches, PEM has a slightly higher prediction ability and is more general than the original PVR. Even so, in a conceptual sense, PEM may provide a technique in the best of both worlds, combining the flexibility of data-driven and empirical eigenfunction analyses and the sounding insights provided by evolutionary models well known in comparative analyses.

Management Of Indiscipline Among Teachers By Principals Of ...

African Journals Online (AJOL)

This study compared the management of indiscipline among teachers by public and private school principals in Akwa Ibom State. The sample comprised four hundred and fifty (450) principals/vice principals randomly selected from a population of one thousand, four hundred and twenty eight (1,428) principals. The null ...

What Do Effective Principals Do?

Science.gov (United States)

Protheroe, Nancy

2011-01-01

Much has been written during the past decade about the changing role of the principal and the shift in emphasis from manager to instructional leader. Anyone in education, and especially principals themselves, could develop a mental list of responsibilities that fit within each of these realms. But research makes it clear that both those aspects of…

The Principal as Academician: The Renewed Voice.

Science.gov (United States)

McAvoy, Brenda, Ed.

This collection of essays was written by principals who participated in the 1986-87 Humanities Seminar sponsored by the Principals' Institute of Georgia State University. The focus was "The Evolution of Intellectual Leadership." The roles of the principal as philosopher, historian, ethnician, writer and team member are examined through…

Advanced statistics: linear regression, part II: multiple linear regression.

Science.gov (United States)

Marill, Keith A

2004-01-01

The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

The concern of emergence of multi-station reaction pathways that might make stepwise the mechanism of the 1,3-dipolar cycloadditions of azides and alkynes

Science.gov (United States)

Mohtat, Bita; Siadati, Seyyed Amir; Khalilzadeh, Mohammad Ali; Zareyee, Daryoush

2018-03-01

After hot debates on the concerted or stepwise nature of the mechanism of the catalyst-free 1,3-dipolar cycloadditions (DC)s, nowadays, it is being believed that for the reaction of each dipole and dipolarophile, there is a possibility that the reaction mechanism becomes stepwise, intermediates emerge, and the reaction becomes non-stereospecific. Yield of even minimal amounts of unwanted side products or stereoisomers as impurities could bring many troubles like difficult purification steps. In this project, we have made attempts to study all probable reaction channels of the azide cycloadditions with two functionalized alkynes, in order to answer this question: "is there any possibility that intermediates evolve in the catalyst-free click 1,3-DC reaction of azide-alkynes?". During the calculations, several multi-station reaction pathways supporting the stepwise and concerted mechanisms were detected. Also, the born-oppenheimer molecular dynamic (BOMD) simulation was used to find trustable geometries which could be emerged during the reaction coordinate.

Step-wise kinetics of natural physical ageing in arsenic selenide glasses

International Nuclear Information System (INIS)

Golovchak, R; Kozdras, A; Balitska, V; Shpotyuk, O

2012-01-01

The long-term kinetics of physical ageing at ambient temperature is studied in Se-rich As-Se glasses using the conventional differential scanning calorimetry technique. It is analysed through the changes in the structural relaxation parameters occurring during the glass-to-supercooled liquid transition in the heating mode. Along with the time dependences of the glass transition temperature (T g ) and partial area (A) under the endothermic relaxation peak, the enthalpy losses (ΔH) and calculated fictive temperature (T F ) are analysed as key parameters, characterizing the kinetics of physical ageing. The latter is shown to have step-wise character, revealing some kinds of subsequent plateaus and steep regions. A phenomenological description of physical ageing in the investigated glasses is proposed on the basis of an alignment-shrinkage mechanism and first-order kinetic equations.

Stepwise modularization in the construction industry using a bottom-up approach

DEFF Research Database (Denmark)

Kudsk, Anders; Grønvold, Martin O'Brien; Olsen, Magnus Holo

2013-01-01

The manufacturing industry has experienced a great deal of improvement in efficiency and cost reductions throughout the last centuries. But although there have been improvements in the manufacturing industry, the principles and work methods in the construction industry have stood still for more t...... than a hundred years. Based on principles of mass customization applied in the manufacturing industry, two cases of successful implementation of mass customization and modularization have been investigated as a means of showcasing the possibility to incorporate standardization in parts...... implemented stepwise. The case shows that substantial benefits can be gained through implementing modularized construction. It is especially interesting to note that these benefits are achieved through the development of a module with focus on the internal interfaces. © Kudsk et al.; Licensee Bentham Open....

A Stepwise ISO-Based TQM Implementation Approach Using ISO 9001:2015

Directory of Open Access Journals (Sweden)

Chen Chi-kuang

2016-12-01

Full Text Available The lack of an implementation roadmap always deters enterprises from choosing Total Quality Management (TQM as its major management approach. This paper proposes a stepwise ISO-based TQM implementation approach which is based on the notion of the new three-dimensional overall business excellence framework developed by Dahlgaard et al. [1]. The proposed approach consists of nine steps comprising three categories: “TQM faith building”, “TQM tools and techniques learning”, and “system development”. The steps in each of the three categories are arranged to span across the proposed nine-step approach. The ISO 9001:2015 standard is used as a case study to demonstrate the proposed approach. The ideas and benefits of the proposed approach are further discussed in relation to this illustration.

A Stepwise Fitting Procedure for automated fitting of Ecopath with Ecosim models

Directory of Open Access Journals (Sweden)

Erin Scott

2016-01-01

Full Text Available The Stepwise Fitting Procedure automates testing of alternative hypotheses used for fitting Ecopath with Ecosim (EwE models to observation reference data (Mackinson et al. 2009. The calibration of EwE model predictions to observed data is important to evaluate any model that will be used for ecosystem based management. Thus far, the model fitting procedure in EwE has been carried out manually: a repetitive task involving setting >1000 specific individual searches to find the statistically ‘best fit’ model. The novel fitting procedure automates the manual procedure therefore producing accurate results and lets the modeller concentrate on investigating the ‘best fit’ model for ecological accuracy.

Boosted beta regression.

Directory of Open Access Journals (Sweden)

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.

Leadership Coaching for Principals: A National Study

Science.gov (United States)

Wise, Donald; Cavazos, Blanca

2017-01-01

Surveys were sent to a large representative sample of public school principals in the United States asking if they had received leadership coaching. Comparison of responses to actual numbers of principals indicates that the sample represents the first national study of principal leadership coaching. Results indicate that approximately 50% of all…

Riccati transformations and principal solutions of discrete linear systems

International Nuclear Information System (INIS)

Ahlbrandt, C.D.; Hooker, J.W.

1984-01-01

Consider a second-order linear matrix difference equation. A definition of principal and anti-principal, or recessive and dominant, solutions of the equation are given and the existence of principal and anti-principal solutions and the essential uniqueness of principal solutions is proven

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...

Principal components regression of body measurements in five ...

African Journals Online (AJOL)

Username, Password, Remember me, or Register ... Body weight and seven biometric traits that are; body length (BL), breast girth (BG), wing length ... Pearson correlations between body weight and biometric traits were positive and highly ...

Principals' Collaborative Roles as Leaders for Learning

Science.gov (United States)

Kitchen, Margaret; Gray, Susan; Jeurissen, Maree

2016-01-01

This article draws on data from three multicultural New Zealand primary schools to reconceptualize principals' roles as leaders for learning. In doing so, the writers build on Sinnema and Robinson's (2012) article on goal setting in principal evaluation. Sinnema and Robinson found that even principals hand-picked for their experience fell short on…

Principals as Assessment Leaders in Rural Schools

Science.gov (United States)

Renihan, Patrick; Noonan, Brian

2012-01-01

This article reports a study of rural school principals' assessment leadership roles and the impact of rural context on their work. The study involved three focus groups of principals serving small rural schools of varied size and grade configuration in three systems. Principals viewed assessment as a matter of teacher accountability and as a…

Principals: Learn P.R. Survival Skills.

Science.gov (United States)

Reep, Beverly B.

1988-01-01

School building level public relations depends on the principal or vice principal. Strategies designed to enhance school public relations programs include linking school and community, working with the press, and keeping morale high inside the school. (MLF)

Isolation and Characterization of Chinese Standard Fulvic Acid Sub-fractions Separated from Forest Soil by Stepwise Elution with Pyrophosphate Buffer

Science.gov (United States)

Bai, Yingchen; Wu, Fengchang; Xing, Baoshan; Meng, Wei; Shi, Guolan; Ma, Yan; Giesy, John P.

2015-01-01

XAD-8 adsorption technique coupled with stepwise elution using pyrophosphate buffers with initial pH values of 3, 5, 7, 9, and 13 was developed to isolate Chinese standard fulvic acid (FA) and then separated the FA into five sub-fractions: FApH3, FApH5, FApH7, FApH9 and FApH13, respectively. Mass percentages of FApH3-FApH13 decreased from 42% to 2.5%, and the recovery ratios ranged from 99.0% to 99.5%. Earlier eluting sub-fractions contained greater proportions of carboxylic groups with greater polarity and molecular mass, and later eluting sub-fractions had greater phenolic and aliphatic content. Protein-like components, as well as amorphous and crystalline poly(methylene)-containing components were enriched using neutral and basic buffers. Three main mechanisms likely affect stepwise elution of humic components from XAD-8 resin with pyrophosphate buffers including: 1) the carboxylic-rich sub-fractions are deprotonated at lower pH values and eluted earlier, while phenolic-rich sub-fractions are deprotonated at greater pH values and eluted later. 2) protein or protein-like components can be desorbed and eluted by use of stepwise elution as progressively greater pH values exceed their isoelectric points. 3) size exclusion affects elution of FA sub-fractions. Successful isolation of FA sub-fractions will benefit exploration of the origin, structure, evolution and the investigation of interactions with environmental contaminants. PMID:25735451

Hyperspectral analysis of soil organic matter in coal mining regions using wavelets, correlations, and partial least squares regression.

Science.gov (United States)

Lin, Lixin; Wang, Yunjia; Teng, Jiyao; Wang, Xuchen

2016-02-01

Hyperspectral estimation of soil organic matter (SOM) in coal mining regions is an important tool for enhancing fertilization in soil restoration programs. The correlation--partial least squares regression (PLSR) method effectively solves the information loss problem of correlation--multiple linear stepwise regression, but results of the correlation analysis must be optimized to improve precision. This study considers the relationship between spectral reflectance and SOM based on spectral reflectance curves of soil samples collected from coal mining regions. Based on the major absorption troughs in the 400-1006 nm spectral range, PLSR analysis was performed using 289 independent bands of the second derivative (SDR) with three levels and measured SOM values. A wavelet-correlation-PLSR (W-C-PLSR) model was then constructed. By amplifying useful information that was previously obscured by noise, the W-C-PLSR model was optimal for estimating SOM content, with smaller prediction errors in both calibration (R(2) = 0.970, root mean square error (RMSEC) = 3.10, and mean relative error (MREC) = 8.75) and validation (RMSEV = 5.85 and MREV = 14.32) analyses, as compared with other models. Results indicate that W-C-PLSR has great potential to estimate SOM in coal mining regions.

Principal minors and rhombus tilings

International Nuclear Information System (INIS)

Kenyon, Richard; Pemantle, Robin

2014-01-01

The algebraic relations between the principal minors of a generic n × n matrix are somewhat mysterious, see e.g. Lin and Sturmfels (2009 J. Algebra 322 4121–31). We show, however, that by adding in certain almost principal minors, the ideal of relations is generated by translations of a single relation, the so-called hexahedron relation, which is a composition of six cluster mutations. We give in particular a Laurent-polynomial parameterization of the space of n × n matrices, whose parameters consist of certain principal and almost principal minors. The parameters naturally live on vertices and faces of the tiles in a rhombus tiling of a convex 2n-gon. A matrix is associated to an equivalence class of tilings, all related to each other by Yang–Baxter-like transformations. By specializing the initial data we can similarly parameterize the space of Hermitian symmetric matrices over R,C or H the quaternions. Moreover by further specialization we can parametrize the space of positive definite matrices over these rings. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to ‘Cluster algebras mathematical physics’. (paper)

Statewide Data on Supply and Demand of Principals after Policy Changes to Principal Preparation in Illinois

Science.gov (United States)

Haller, Alicia; Hunt, Erika

2016-01-01

Research has demonstrated that principals have a powerful impact on school improvement and student learning. Principals play a vital role in recruiting, developing, and retaining effective teachers; creating a school-wide culture of learning; and implementing a continuous improvement plan aimed at increasing student achievement. Leithwood, Louis,…

Stepwise optimization and global chaos of nonlinear parameters in exact calculations of few-particle systems

International Nuclear Information System (INIS)

Frolov, A.M.

1986-01-01

The problem of exact variational calculations of few-particle systems in the exponential basis of the relative coordinates using nonlinear parameters is studied. The techniques of stepwise optimization and global chaos of nonlinear parameters are used to calculate the S and P states of homonuclear muonic molecules with an error of no more than +0.001 eV. The global-chaos technique also has proved to be successful in the case of the nuclear systems 3 H and 3 He

The Deputy Principal Instructional Leadership Role and Professional Learning: Perceptions of Secondary Principals, Deputies and Teachers

Science.gov (United States)

Leaf, Ann; Odhiambo, George

2017-01-01

Purpose: The purpose of this paper is to report on a study examining the perceptions of secondary principals, deputies and teachers, of deputy principal (DP) instructional leadership (IL), as well as deputies' professional learning (PL) needs. Framed within an interpretivist approach, the specific objectives of this study were: to explore the…

Measuring Principals' Effectiveness: Results from New Jersey's First Year of Statewide Principal Evaluation. REL 2016-156

Science.gov (United States)

Herrmann, Mariesa; Ross, Christine

2016-01-01

States and districts across the country are implementing new principal evaluation systems that include measures of the quality of principals' school leadership practices and measures of student achievement growth. Because these evaluation systems will be used for high-stakes decisions, it is important that the component measures of the evaluation…

Differential growth of the northern Tibetan margin: evidence for oblique stepwise rise of the Tibetan Plateau

Science.gov (United States)

Wang, Fei; Shi, Wenbei; Zhang, Weibin; Wu, Lin; Yang, Liekun; Wang, Yinzhi; Zhu, Rixiang

2017-01-01

Models of how high elevations formed across Tibet predict: (a) the continuous thickening of a “viscous sheet”; (b) time-dependent, oblique stepwise growth; and (c) synchronous deformation across Tibet that accompanied collision. Our new observations may shed light on this issue. Here, we use 40Ar/39Ar and (U-Th)/He thermochronology from massifs in the hanging walls of thrust structures along the Kunlun Belt, the first-order orogenic range at the northern Tibetan margin, to elucidate the exhumation history. The results show that these massifs, and hence the plateau margin, were subject to slow, steady exhumation during the Early Cenozoic, followed by a pulse of accelerated exhumation during 40–35 Ma. The exhumation rate increases westward (from ~0.22 to 0.34 and 0.5 mm/yr). The two-fold increase in exhumation in the western part (0.5 mm/yr) compared to the eastern part suggests westward increases in exhumation and compressional stress along the Kunlun Belt. We relate these observations to the mechanisms responsible for the oblique stepwise rise of Tibet. After collision, oblique subduction beneath Kunlun caused stronger compressional deformation in the western part than in the eastern part, resulting in differential growth and lateral extrusion. PMID:28117351

Design of stepwise screening for prediabetes and type 2 diabetes based on costs and cases detected.

Science.gov (United States)

de Graaf, Gimon; Postmus, Douwe; Bakker, Stephan J L; Buskens, Erik

2015-09-01

To provide insight into the trade-off between cost per case detected (CPCD) and the detection rate in questionnaire-based stepwise screening for impaired fasting glucose and undiagnosed type 2 diabetes. We considered a stepwise screening in which individuals whose risk score exceeds a predetermined cutoff value are invited for further blood glucose testing. Using individual patient data to determine questionnaire sensitivity and specificity and external sources to determine screening costs and patient response rates, we rolled back a decision tree to estimate the CPCD and the detection rate for all possible cutoffs on the questionnaire. We found a U-shaped relation between CPCD and detection rate, with high costs per case detected at very low and very high detection rates. Changes in patient response rates had a large impact on both the detection rate and the CPCD, whereas screening costs and questionnaire accuracy mainly impacted the CPCD. Our applied method makes it possible to identify a range of efficient cutoffs where higher detection rates can be achieved at an additional cost per detected patient. This enables decision makers to choose an optimal cutoff based on their willingness to pay for additional detected patients. Copyright © 2015 Elsevier Inc. All rights reserved.

In vivo stepwise multi-photon activation fluorescence imaging of melanin in human skin

Science.gov (United States)

Lai, Zhenhua; Gu, Zetong; Abbas, Saleh; Lowe, Jared; Sierra, Heidy; Rajadhyaksha, Milind; DiMarzio, Charles

2014-03-01

The stepwise multi-photon activated fluorescence (SMPAF) of melanin is a low cost and reliable method of detecting melanin because the activation and excitation can be a continuous-wave (CW) mode near infrared (NIR) laser. Our previous work has demonstrated the melanin SMPAF images in sepia melanin, mouse hair, and mouse skin. In this study, we show the feasibility of using SMPAF to detect melanin in vivo. in vivo melanin SMPAF images of normal skin and benign nevus are demonstrated. SMPAF images add specificity for melanin detection than MPFM images and CRM images. Melanin SMPAF is a promising technology to enable early detection of melanoma for dermatologists.

Principals' Perceptions of School Public Relations

Science.gov (United States)

Morris, Robert C.; Chan, Tak Cheung; Patterson, Judith

2009-01-01

This study was designed to investigate school principals' perceptions on school public relations in five areas: community demographics, parental involvement, internal and external communications, school council issues, and community resources. Findings indicated that principals' concerns were as follows: rapid population growth, change of…

A high surface area Zr(IV)-based metal–organic framework showing stepwise gas adsorption and selective dye uptake

Energy Technology Data Exchange (ETDEWEB)

Lv, Xiu-Liang [Beijing Key Laboratory for Green Catalysis and Separation, Department of Chemistry and Chemical Engineering, Beijing University of Technology, Beijing 100124 (China); Tong, Minman; Huang, Hongliang [College of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029 (China); Wang, Bin; Gan, Lei [Beijing Key Laboratory for Green Catalysis and Separation, Department of Chemistry and Chemical Engineering, Beijing University of Technology, Beijing 100124 (China); Yang, Qingyuan [College of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029 (China); Zhong, Chongli [College of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029 (China); State Key Laboratory of Organic–Inorganic Composites, Beijing University of Chemical Technology, Beijing 100029 (China); Li, Jian-Rong, E-mail: jrli@bjut.edu.cn [Beijing Key Laboratory for Green Catalysis and Separation, Department of Chemistry and Chemical Engineering, Beijing University of Technology, Beijing 100124 (China); State Key Laboratory of Organic–Inorganic Composites, Beijing University of Chemical Technology, Beijing 100029 (China)

2015-03-15

Exploitation of new metal–organic framework (MOF) materials with high surface areas has been attracting great attention in related research communities due to their broad potential applications. In this work, a new Zr(IV)-based MOF, [Zr{sub 6}O{sub 4}(OH){sub 4}(eddb){sub 6}] (BUT-30, H{sub 2}eddb=4,4′-(ethyne-1,2-diyl)dibenzoic acid) has been solvothermally synthesized, characterized, and explored for gases and dyes adsorptions. Single-crystal X-ray diffraction analysis demonstrates a three-dimensional cubic framework structure of this MOF, in which each Zr{sub 6}O{sub 4}(OH){sub 4} building unit is linked by 12 linear eddb ligands. BUT-30 has been found stable up to 400 °C and has a Brunauer–Emmett–Teller (BET) surface area as high as 3940.6 m{sup 2} g{sup −1} (based on the N{sub 2} adsorption at 77 K) and total pore volume of 1.55 cm{sup 3} g{sup −1}. It is more interesting that this MOF exhibits stepwise adsorption behaviors for Ar, N{sub 2}, and CO{sub 2} at low temperatures, and selective uptakes towards different ionic dyes. - Graphical abstract: A new Zr(IV)-based MOF with high surface area has been synthesized and structurally characterized, which shows stepwise gas adsorption at low temperature and selective dye uptake from solution. - Highlights: • A new Zr-based MOF was synthesized and structurally characterized. • This MOF shows a higher surface area compared with its analogous UiO-67 and 68. • This MOF shows a rare stepwise adsorption towards light gases at low temperature. • This MOF performs selective uptakes towards cationic dyes over anionic ones. • Using triple-bond spacer is confirmed feasible in enhancing MOF surface areas.

Principal-vector-directed fringe-tracking technique.

Science.gov (United States)

Zhang, Zhihui; Guo, Hongwei

2014-11-01

Fringe tracking is one of the most straightforward techniques for analyzing a single fringe pattern. This work presents a principal-vector-directed fringe-tracking technique. It uses Gaussian derivatives for estimating fringe gradients and uses hysteresis thresholding for segmenting singular points, thus improving the principal component analysis method. Using it allows us to estimate the principal vectors of fringes from a pattern with high noise. The fringe-tracking procedure is directed by these principal vectors, so that erroneous results induced by noise and other error-inducing factors are avoided. At the same time, the singular point regions of the fringe pattern are identified automatically. Using them allows us to determine paths through which the "seed" point for each fringe skeleton is easy to find, thus alleviating the computational burden in processing the fringe pattern. The results of a numerical simulation and experiment demonstrate this method to be valid.

Predicting Success in Product Development: The Application of Principal Component Analysis to Categorical Data and Binomial Logistic Regression

Directory of Open Access Journals (Sweden)

Glauco H.S. Mendes

2013-09-01

Full Text Available Critical success factors in new product development (NPD in the Brazilian small and medium enterprises (SMEs are identified and analyzed. Critical success factors are best practices that can be used to improve NPD management and performance in a company. However, the traditional method for identifying these factors is survey methods. Subsequently, the collected data are reduced through traditional multivariate analysis. The objective of this work is to develop a logistic regression model for predicting the success or failure of the new product development. This model allows for an evaluation and prioritization of resource commitments. The results will be helpful for guiding management actions, as one way to improve NPD performance in those industries.

Whose Perception of Principal Instructional Leadership? Principal-Teacher Perceptual (Dis)agreement and Its Influence on Teacher Collaboration

Science.gov (United States)

Park, Joo-Ho; Ham, Seung-Hwan

2016-01-01

This study examines teacher collaboration across three Asia-Pacific countries (Australia, Malaysia, and South Korea), focusing on the possibility that principal-teacher perceptual disagreement regarding principal instructional leadership performance may impede progress toward a school organizational condition conducive to collaborative teacher…

Interaction of dependent and non-dependent regions of the acutely injured lung during a stepwise recruitment manoeuvre

International Nuclear Information System (INIS)

Gómez-Laberge, Camille; Rettig, Jordan S; Arnold, John H; Wolf, Gerhard K; Smallwood, Craig D; Boyd, Theonia K

2013-01-01

The benefit of treating acute lung injury with recruitment manoeuvres is controversial. An impediment to settling this debate is the difficulty in visualizing how distinct lung regions respond to the manoeuvre. Here, regional lung mechanics were studied by electrical impedance tomography (EIT) during a stepwise recruitment manoeuvre in a porcine model with acute lung injury. The following interaction between dependent and non-dependent regions consistently occurred: atelectasis in the most dependent region was reversed only after the non-dependent region became overdistended. EIT estimates of overdistension and atelectasis were validated by histological examination of lung tissue, confirming that the dependent region was primarily atelectatic and the non-dependent region was primarily overdistended. The pulmonary pressure–volume equation, originally designed for modelling measurements at the airway opening, was adapted for EIT-based regional estimates of overdistension and atelectasis. The adaptation accurately modelled the regional EIT data from dependent and non-dependent regions (R 2 > 0.93, P < 0.0001) and predicted their interaction during recruitment. In conclusion, EIT imaging of regional lung mechanics reveals that overdistension in the non-dependent region precedes atelectasis reversal in the dependent region during a stepwise recruitment manoeuvre. (paper)

Comparative study of biodegradability prediction of chemicals using decision trees, functional trees, and logistic regression.

Science.gov (United States)

Chen, Guangchao; Li, Xuehua; Chen, Jingwen; Zhang, Ya-Nan; Peijnenburg, Willie J G M

2014-12-01

Biodegradation is the principal environmental dissipation process of chemicals. As such, it is a dominant factor determining the persistence and fate of organic chemicals in the environment, and is therefore of critical importance to chemical management and regulation. In the present study, the authors developed in silico methods assessing biodegradability based on a large heterogeneous set of 825 organic compounds, using the techniques of the C4.5 decision tree, the functional inner regression tree, and logistic regression. External validation was subsequently carried out by 2 independent test sets of 777 and 27 chemicals. As a result, the functional inner regression tree exhibited the best predictability with predictive accuracies of 81.5% and 81.0%, respectively, on the training set (825 chemicals) and test set I (777 chemicals). Performance of the developed models on the 2 test sets was subsequently compared with that of the Estimation Program Interface (EPI) Suite Biowin 5 and Biowin 6 models, which also showed a better predictability of the functional inner regression tree model. The model built in the present study exhibits a reasonable predictability compared with existing models while possessing a transparent algorithm. Interpretation of the mechanisms of biodegradation was also carried out based on the models developed. © 2014 SETAC.

Variable selection in Logistic regression model with genetic algorithm.

Science.gov (United States)

Zhang, Zhongheng; Trevino, Victor; Hoseini, Sayed Shahabuddin; Belciug, Smaranda; Boopathi, Arumugam Manivanna; Zhang, Ping; Gorunescu, Florin; Subha, Velappan; Dai, Songshi

2018-02-01

Variable or feature selection is one of the most important steps in model specification. Especially in the case of medical-decision making, the direct use of a medical database, without a previous analysis and preprocessing step, is often counterproductive. In this way, the variable selection represents the method of choosing the most relevant attributes from the database in order to build a robust learning models and, thus, to improve the performance of the models used in the decision process. In biomedical research, the purpose of variable selection is to select clinically important and statistically significant variables, while excluding unrelated or noise variables. A variety of methods exist for variable selection, but none of them is without limitations. For example, the stepwise approach, which is highly used, adds the best variable in each cycle generally producing an acceptable set of variables. Nevertheless, it is limited by the fact that it commonly trapped in local optima. The best subset approach can systematically search the entire covariate pattern space, but the solution pool can be extremely large with tens to hundreds of variables, which is the case in nowadays clinical data. Genetic algorithms (GA) are heuristic optimization approaches and can be used for variable selection in multivariable regression models. This tutorial paper aims to provide a step-by-step approach to the use of GA in variable selection. The R code provided in the text can be extended and adapted to other data analysis needs.

Application of near-infrared spectroscopy for the rapid quality assessment of Radix Paeoniae Rubra

Science.gov (United States)

Zhan, Hao; Fang, Jing; Tang, Liying; Yang, Hongjun; Li, Hua; Wang, Zhuju; Yang, Bin; Wu, Hongwei; Fu, Meihong

2017-08-01

Near-infrared (NIR) spectroscopy with multivariate analysis was used to quantify gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra, and the feasibility to classify the samples originating from different areas was investigated. A new high-performance liquid chromatography method was developed and validated to analyze gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra as the reference. Partial least squares (PLS), principal component regression (PCR), and stepwise multivariate linear regression (SMLR) were performed to calibrate the regression model. Different data pretreatments such as derivatives (1st and 2nd), multiplicative scatter correction, standard normal variate, Savitzky-Golay filter, and Norris derivative filter were applied to remove the systematic errors. The performance of the model was evaluated according to the root mean square of calibration (RMSEC), root mean square error of prediction (RMSEP), root mean square error of cross-validation (RMSECV), and correlation coefficient (r). The results show that compared to PCR and SMLR, PLS had a lower RMSEC, RMSECV, and RMSEP and higher r for all the four analytes. PLS coupled with proper pretreatments showed good performance in both the fitting and predicting results. Furthermore, the original areas of Radix Paeoniae Rubra samples were partly distinguished by principal component analysis. This study shows that NIR with PLS is a reliable, inexpensive, and rapid tool for the quality assessment of Radix Paeoniae Rubra.

Predicting 30-day Hospital Readmission with Publicly Available Administrative Database. A Conditional Logistic Regression Modeling Approach.

Science.gov (United States)

Zhu, K; Lou, Z; Zhou, J; Ballester, N; Kong, N; Parikh, P

2015-01-01

This article is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare". Hospital readmissions raise healthcare costs and cause significant distress to providers and patients. It is, therefore, of great interest to healthcare organizations to predict what patients are at risk to be readmitted to their hospitals. However, current logistic regression based risk prediction models have limited prediction power when applied to hospital administrative data. Meanwhile, although decision trees and random forests have been applied, they tend to be too complex to understand among the hospital practitioners. Explore the use of conditional logistic regression to increase the prediction accuracy. We analyzed an HCUP statewide inpatient discharge record dataset, which includes patient demographics, clinical and care utilization data from California. We extracted records of heart failure Medicare beneficiaries who had inpatient experience during an 11-month period. We corrected the data imbalance issue with under-sampling. In our study, we first applied standard logistic regression and decision tree to obtain influential variables and derive practically meaning decision rules. We then stratified the original data set accordingly and applied logistic regression on each data stratum. We further explored the effect of interacting variables in the logistic regression modeling. We conducted cross validation to assess the overall prediction performance of conditional logistic regression (CLR) and compared it with standard classification models. The developed CLR models outperformed several standard classification models (e.g., straightforward logistic regression, stepwise logistic regression, random forest, support vector machine). For example, the best CLR model improved the classification accuracy by nearly 20% over the straightforward logistic regression model. Furthermore, the developed CLR models tend to achieve better sensitivity of

New pulser for principal PO power

International Nuclear Information System (INIS)

Coudert, G.

1984-01-01

The pulser of the principal power of the PS is the unit that makes it possible to generate the reference function of the voltage of the principal magnet. This function depends on time and on the magnetic field of the magnet. It also generates various synchronization and reference pulses

An Examination of Principal Job Satisfaction

Science.gov (United States)

Pengilly, Michelle M.

2010-01-01

As education continues to succumb to deficits in budgets and increasingly high levels of student performance to meet the federal and state mandates, the quest to sustain and retain successful principals is imperative. The National Association of School Boards (1999) portrays effective principals as "linchpins" of school improvement and…

The Succession of a School Principal.

Science.gov (United States)

Fauske, Janice R.; Ogawa, Rodney T.

Applying theory from organizational and cultural perspectives to succession of principals, this study observes and records the language and culture of a small suburban elementary school. The study's procedures included analyses of shared organizational understandings as well as identification of the principal's influence on the school. Analyses of…

Social Media Strategies for School Principals

Science.gov (United States)

Cox, Dan; McLeod, Scott

2014-01-01

The purpose of this qualitative study was to describe, analyze, and interpret the experiences of school principals who use multiple social media tools with stakeholders as part of their comprehensive communications practices. Additionally, it examined why school principals have chosen to communicate with their stakeholders through social media.…

Stepwise multi-criteria optimization for robotic radiosurgery

International Nuclear Information System (INIS)

Schlaefer, A.; Schweikard, A.

2008-01-01

Achieving good conformality and a steep dose gradient around the target volume remains a key aspect of radiosurgery. Clearly, this involves a trade-off between target coverage, conformality of the dose distribution, and sparing of critical structures. Yet, image guidance and robotic beam placement have extended highly conformal dose delivery to extracranial and moving targets. Therefore, the multi-criteria nature of the optimization problem becomes even more apparent, as multiple conflicting clinical goals need to be considered coordinate to obtain an optimal treatment plan. Typically, planning for robotic radiosurgery is based on constrained optimization, namely linear programming. An extension of that approach is presented, such that each of the clinical goals can be addressed separately and in any sequential order. For a set of common clinical goals the mapping to a mathematical objective and a corresponding constraint is defined. The trade-off among the clinical goals is explored by modifying the constraints and optimizing a simple objective, while retaining feasibility of the solution. Moreover, it becomes immediately obvious whether a desired goal can be achieved and where a trade-off is possible. No importance factors or predefined prioritizations of clinical goals are necessary. The presented framework forms the basis for interactive and automated planning procedures. It is demonstrated for a sample case that the linear programming formulation is suitable to search for a clinically optimal treatment, and that the optimization steps can be performed quickly to establish that a Pareto-efficient solution has been found. Furthermore, it is demonstrated how the stepwise approach is preferable compared to modifying importance factors

Seasonal prediction of winter extreme precipitation over Canada by support vector regression

Directory of Open Access Journals (Sweden)

Z. Zeng

2011-01-01

Full Text Available For forecasting the maximum 5-day accumulated precipitation over the winter season at lead times of 3, 6, 9 and 12 months over Canada from 1950 to 2007, two nonlinear and two linear regression models were used, where the models were support vector regression (SVR (nonlinear and linear versions, nonlinear Bayesian neural network (BNN and multiple linear regression (MLR. The 118 stations were grouped into six geographic regions by K-means clustering. For each region, the leading principal components of the winter maximum 5-d accumulated precipitation anomalies were the predictands. Potential predictors included quasi-global sea surface temperature anomalies and 500 hPa geopotential height anomalies over the Northern Hemisphere, as well as six climate indices (the Niño-3.4 region sea surface temperature, the North Atlantic Oscillation, the Pacific-North American teleconnection, the Pacific Decadal Oscillation, the Scandinavia pattern, and the East Atlantic pattern. The results showed that in general the two robust SVR models tended to have better forecast skills than the two non-robust models (MLR and BNN, and the nonlinear SVR model tended to forecast slightly better than the linear SVR model. Among the six regions, the Prairies region displayed the highest forecast skills, and the Arctic region the second highest. The strongest nonlinearity was manifested over the Prairies and the weakest nonlinearity over the Arctic.

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

Fourier transform infrared spectroscopic imaging and multivariate regression for prediction of proteoglycan content of articular cartilage.

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Lassi Rieppo

Full Text Available Fourier Transform Infrared (FT-IR spectroscopic imaging has been earlier applied for the spatial estimation of the collagen and the proteoglycan (PG contents of articular cartilage (AC. However, earlier studies have been limited to the use of univariate analysis techniques. Current analysis methods lack the needed specificity for collagen and PGs. The aim of the present study was to evaluate the suitability of partial least squares regression (PLSR and principal component regression (PCR methods for the analysis of the PG content of AC. Multivariate regression models were compared with earlier used univariate methods and tested with a sample material consisting of healthy and enzymatically degraded steer AC. Chondroitinase ABC enzyme was used to increase the variation in PG content levels as compared to intact AC. Digital densitometric measurements of Safranin O-stained sections provided the reference for PG content. The results showed that multivariate regression models predict PG content of AC significantly better than earlier used absorbance spectrum (i.e. the area of carbohydrate region with or without amide I normalization or second derivative spectrum univariate parameters. Increased molecular specificity favours the use of multivariate regression models, but they require more knowledge of chemometric analysis and extended laboratory resources for gathering reference data for establishing the models. When true molecular specificity is required, the multivariate models should be used.

Integrated Multiscale Latent Variable Regression and Application to Distillation Columns

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Muddu Madakyaru

2013-01-01

Full Text Available Proper control of distillation columns requires estimating some key variables that are challenging to measure online (such as compositions, which are usually estimated using inferential models. Commonly used inferential models include latent variable regression (LVR techniques, such as principal component regression (PCR, partial least squares (PLS, and regularized canonical correlation analysis (RCCA. Unfortunately, measured practical data are usually contaminated with errors, which degrade the prediction abilities of inferential models. Therefore, noisy measurements need to be filtered to enhance the prediction accuracy of these models. Multiscale filtering has been shown to be a powerful feature extraction tool. In this work, the advantages of multiscale filtering are utilized to enhance the prediction accuracy of LVR models by developing an integrated multiscale LVR (IMSLVR modeling algorithm that integrates modeling and feature extraction. The idea behind the IMSLVR modeling algorithm is to filter the process data at different decomposition levels, model the filtered data from each level, and then select the LVR model that optimizes a model selection criterion. The performance of the developed IMSLVR algorithm is illustrated using three examples, one using synthetic data, one using simulated distillation column data, and one using experimental packed bed distillation column data. All examples clearly demonstrate the effectiveness of the IMSLVR algorithm over the conventional methods.

The Interdependence of Principal School Leadership and Student Achievement

Science.gov (United States)

Soehner, David; Ryan, Thomas

2011-01-01

This review illuminated principal school leadership as a variable that impacted achievement. The principal as school leader and manager was explored because these roles were thought to impact student achievement both directly and indirectly. Specific principal leadership behaviors and principal effectiveness were explored as variables potentially…

Regression analysis of pulsed eddy current signals for inspection of steam generator tube support structures

International Nuclear Information System (INIS)

Buck, J.; Underhill, P.R.; Mokros, S.G.; Morelli, J.; Krause, T.W.; Babbar, V.K.; Lepine, B.

2015-01-01

Nuclear steam generator (SG) support structure degradation and fouling can result in damage to SG tubes and loss of SG efficiency. Conventional eddy current technology is extensively used to detect cracks, frets at supports and other flaws, but has limited capabilities in the presence of multiple degradation modes or fouling. Pulsed eddy current (PEC) combined with principal components analysis (PCA) and multiple linear regression models was examined for the inspection of support structure degradation and SG tube off-centering with the goal of extending results to include additional degradation modes. (author)

District Leadership for Effective Principal Evaluation and Support

Science.gov (United States)

Kimball, Steven M.; Arrigoni, Jessica; Clifford, Matthew; Yoder, Maureen; Milanowski, Anthony

2015-01-01

Research demonstrating principals' impact on student learning outcomes has fueled the shift from principals as facilities managers to an emphasis on instructional leadership (Hallinger & Heck, 1996; Leithwood, Louis, Anderson, & Wahlstrom, 2004; Marzano, Waters, & McNulty, 2005). Principals are under increasing pressure to carry out…

School Restructuring and the Dilemmas of Principals' Work.

Science.gov (United States)

Wildy, Helen; Louden, William

2000-01-01

The complexity of principals' work may be characterized according to three dilemmas: accountability, autonomy, and efficiency. Narrative vignettes of 74 Australian principals revealed that principals were fair and inclusive. When faced with restructuring dilemmas, however, they favored strong over shared leadership, efficiency over collaboration,…

Do Principals Fire the Worst Teachers?

Science.gov (United States)

Jacob, Brian A.

2011-01-01

This article takes advantage of a unique policy change to examine how principals make decisions regarding teacher dismissal. In 2004, the Chicago Public Schools (CPS) and Chicago Teachers Union signed a new collective bargaining agreement that gave principals the flexibility to dismiss probationary teachers for any reason and without the…

Revising the Role of Principal Supervisor

Science.gov (United States)

Saltzman, Amy

2016-01-01

In Washington, D.C., and Tulsa, Okla., districts whose efforts are supported by the Wallace Foundation, principal supervisors concentrate on bolstering their principals' work to improve instruction, as opposed to focusing on the managerial or operational aspects of running a school. Supervisors oversee fewer schools, which enables them to provide…

The Principal's Guide to Grant Success.

Science.gov (United States)

Bauer, David G.

This book provides principals of public and private elementary and middle schools with a step-by-step approach for developing a system that empowers faculty, staff, and the school community in attracting grant funds. Following the introduction, chapter 1 discusses the principal's role in supporting grantseeking. Chapter 2 describes how to…

Principals, agents and research programmes

OpenAIRE

Elizabeth Shove

2003-01-01

Research programmes appear to represent one of the more powerful instruments through which research funders (principals) steer and shape what researchers (agents) do. The fact that agents navigate between different sources and styles of programme funding and that they use programmes to their own ends is readily accommodated within principal-agent theory with the help of concepts such as shirking and defection. Taking a different route, I use three examples of research programming (by the UK, ...

Negligence--When Is the Principal Liable? A Legal Memorandum.

Science.gov (United States)

Stern, Ralph D., Ed.

Negligence, a tort liability, is defined, discussed, and reviewed in relation to several court decisions involving school principals. The history of liability suits against school principals suggests that a reasonable, prudent principal can avoid legal problems. Ten guidelines are presented to assist principals in avoiding charges of negligence.…

Statistical learning and selective inference.

Science.gov (United States)

Taylor, Jonathan; Tibshirani, Robert J

2015-06-23

We describe the problem of "selective inference." This addresses the following challenge: Having mined a set of data to find potential associations, how do we properly assess the strength of these associations? The fact that we have "cherry-picked"--searched for the strongest associations--means that we must set a higher bar for declaring significant the associations that we see. This challenge becomes more important in the era of big data and complex statistical modeling. The cherry tree (dataset) can be very large and the tools for cherry picking (statistical learning methods) are now very sophisticated. We describe some recent new developments in selective inference and illustrate their use in forward stepwise regression, the lasso, and principal components analysis.

The Principal and the Law. Elementary Principal Series No. 7.

Science.gov (United States)

Doverspike, David E.; Cone, W. Henry

Developments over the past 25 years in school-related legal issues in elementary schools have significantly changed the principal's role. In 1975, a decision of the U.S. Supreme Court established three due-process guidelines for short-term suspension. The decision requires student notification of charges, explanation of evidence, and an informal…

QSAR Modeling of COX -2 Inhibitory Activity of Some Dihydropyridine and Hydroquinoline Derivatives Using Multiple Linear Regression (MLR) Method.

Science.gov (United States)

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.

Should Principals Know More about Law?

Science.gov (United States)

Doctor, Tyrus L.

2013-01-01

Educational law is a critical piece of the education conundrum. Principals reference law books on a daily basis in order to address the wide range of complex problems in the school system. A principal's knowledge of law issues and legal decision-making are essential to provide effective feedback for a successful school.

Principal Ports and Facilities

Data.gov (United States)

California Natural Resource Agency — The Principal Port file contains USACE port codes, geographic locations (longitude, latitude), names, and commodity tonnage summaries (total tons, domestic, foreign,...

Principal Ports and Facilities

Data.gov (United States)

California Department of Resources — The Principal Port file contains USACE port codes, geographic locations (longitude, latitude), names, and commodity tonnage summaries (total tons, domestic, foreign,...

Promoting principals' managerial involvement in instructional improvement.

Science.gov (United States)

Gillat, A

1994-01-01

Studies of school leadership suggest that visiting classrooms, emphasizing achievement and training, and supporting teachers are important indicators of the effectiveness of school principals. The utility of a behavior-analytic program to support the enhancement of these behaviors in 2 school principals and the impact of their involvement upon teachers' and students' performances in three classes were examined in two experiments, one at an elementary school and another at a secondary school. Treatment conditions consisted of helping the principal or teacher to schedule his or her time and to use goal setting, feedback, and praise. A withdrawal design (Experiment 1) and a multiple baseline across classrooms (Experiment 2) showed that the principal's and teacher's rates of praise, feedback, and goal setting increased during the intervention, and were associated with improvements in the academic performance of the students. In the future, school psychologists might analyze the impact of involving themselves in supporting the principal's involvement in improving students' and teachers' performances or in playing a similar leadership role themselves.

Primary School Principals' Self-Monitoring Skills

Science.gov (United States)

Konan, Necdet

2015-01-01

The aim of the present study is to identify primary school principals' self-monitoring skills. The study adopted the general survey model and its population comprised primary school principals serving in the city of Diyarbakir, Turkey, while 292 of these constituted the sample. Self-Monitoring Scale was used as the data collection instrument. In…

How Not to Prepare School Principals

Science.gov (United States)

Davis, Stephen H.; Leon, Ronald J.

2011-01-01

Instead of focusing on how principals should be trained, an contrarian view is offered, grounded upon theoretical perspectives of experiential learning, and in particular, upon the theory of andragogy. A brief parable of the DoNoHarm School of Medicine is used as a descriptive analog for many principal preparation programs in America. The…

Stepwise circumferential and focal ablation of Barrett's esophagus with high-grade dysplasia: results of the first prospective series of 11 patients

NARCIS (Netherlands)

Gondrie, J. J.; Pouw, R. E.; Sondermeijer, C. M. T.; Peters, F. P.; Curvers, W. L.; Rosmolen, W. D.; Krishnadath, K. K.; ten Kate, F.; Fockens, P.; Bergman, J. J.

2008-01-01

BACKGROUND AND STUDY AIMS: Stepwise circumferential and focal ablation of nondysplastic Barrett's esophagus has proven safe and effective. This study assessed the efficacy and safety of ablation for Barrett's esophagus with high-grade dysplasia (HGD), and residual Barrett's esophagus with dysplasia

Evaluating the Effectiveness of Traditional and Alternative Principal Preparation Programs

Science.gov (United States)

Pannell, Summer; Peltier-Glaze, Bernnell M.; Haynes, Ingrid; Davis, Delilah; Skelton, Carrie

2015-01-01

This study sought to determine the effectiveness on increasing student achievement of principals trained in a traditional principal preparation program and those trained in an alternate route principal preparation program within the same Mississippi university. Sixty-six Mississippi principals and assistant principals participated in the study. Of…

Principal Turnover: Upheaval and Uncertainty in Charter Schools?

Science.gov (United States)

Ni, Yongmei; Sun, Min; Rorrer, Andrea

2015-01-01

Purpose: Informed by literature on labor market and school choice, this study aims to examine the dynamics of principal career movements in charter schools by comparing principal turnover rates and patterns between charter schools and traditional public schools. Research Methods/Approach: This study uses longitudinal data on Utah principals and…

Principal succession: The socialisation of a primary school principal in South Africa

Directory of Open Access Journals (Sweden)

Gertruida M. Steyn

2013-04-01

Full Text Available This study focussed on the socialisation of a new principal in a South African primary school with a strong Christian culture. He was appointed when the predecessor retired after more than two decades. The conceptual framework focuses on the three phases of socialisation: professional socialisation, organisational socialisation and occupational identity, which are used to interpret the study. A qualitative study, which occurred during two phases, investigated the phenomenon, principal succession, in the particular school. The data collection methods included a number of interviews with the principal, a focus group interview with staff members who experienced the previous principal’s leadership practice, and individual interviews with staff members. The following categories emerged from the data analysis: Recalling the previous principal: ‘One sees Mr X [the predecessor] everywhere’; Entry and orientation: ‘I found it intimidating initially’; and Immersion and reshaping: ‘Reins that previously were a bit slack, he is now pulling tight’.Die sosialisering van ’n primêre skoolhoof in Suid-Afrika. Hierdie studie het gefokus op die sosialisering van ’n nuwe skoolhoof in ’n Suid-Afrikaanse primêre skool met ’n sterk Christelike kultuur. Hy is aangestel toe sy voorganger ná meer as twee dekades afgetree het. Die konseptuele raamwerk, wat gebruik is om die bevindinge te interpreteer, het op die drie fases van sosialisering gefokus, naamlik professionele sosialisering, organisatoriese sosialisering en beroepsidentiteit. ’n Kwalitatiewe ondersoek na die skoolhoofopvolgingverskynsel in die bepaalde skool is in twee fases gedoen. Die data-insamelingsmetodes het ’n aantal onderhoude met die skoolhoof, ’n fokusgroeponderhoud met personeellede wat ook onder leierskap van die vorige skoolhoof gewerk het en individuele onderhoude met personeellede ingesluit. Tydens die data-analise het die volgende kategorieë na vore gekom

Looked after or Left Behind: The Effectiveness of Principal Preparation Programs as Perceived by Generation Y Principals

Science.gov (United States)

Sledge, Chandra

2013-01-01

This research study intended to discover the perceptions of 10 Illinois Generation Y novice high school principals pertaining to the effectiveness of their principal preparation programs in terms of how well it prepared them to lead in the first three years of their principalship, and what subsequent professional development they deemed necessary…

Logistic regression analysis to predict Medical Licensing Examination of Thailand (MLET) Step1 success or failure.

Science.gov (United States)

Wanvarie, Samkaew; Sathapatayavongs, Boonmee

2007-09-01

The aim of this paper was to assess factors that predict students' performance in the Medical Licensing Examination of Thailand (MLET) Step1 examination. The hypothesis was that demographic factors and academic records would predict the students' performance in the Step1 Licensing Examination. A logistic regression analysis of demographic factors (age, sex and residence) and academic records [high school grade point average (GPA), National University Entrance Examination Score and GPAs of the pre-clinical years] with the MLET Step1 outcome was accomplished using the data of 117 third-year Ramathibodi medical students. Twenty-three (19.7%) students failed the MLET Step1 examination. Stepwise logistic regression analysis showed that the significant predictors of MLET Step1 success/failure were residence background and GPAs of the second and third preclinical years. For students whose sophomore and third-year GPAs increased by an average of 1 point, the odds of passing the MLET Step1 examination increased by a factor of 16.3 and 12.8 respectively. The minimum GPAs for students from urban and rural backgrounds to pass the examination were estimated from the equation (2.35 vs 2.65 from 4.00 scale). Students from rural backgrounds and/or low-grade point averages in their second and third preclinical years of medical school are at risk of failing the MLET Step1 examination. They should be given intensive tutorials during the second and third pre-clinical years.

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....

Stepping stones: Principal career paths and school outcomes.

Science.gov (United States)

Béteille, Tara; Kalogrides, Demetra; Loeb, Susanna

2012-07-01

More than one out of every five principals leaves their school each year. In some cases, these career changes are driven by the choices of district leadership. In other cases, principals initiate the move, often demonstrating preferences to work in schools with higher achieving students from more advantaged socioeconomic backgrounds. Principals often use schools with many poor or low-achieving students as stepping stones to what they view as more desirable assignments. We use longitudinal data from one large urban school district to study the relationship between principal turnover and school outcomes. We find that principal turnover is, on average, detrimental to school performance. Frequent turnover of school leadership results in lower teacher retention and lower student achievement gains. Leadership changes are particularly harmful for high poverty schools, low-achieving schools, and schools with many inexperienced teachers. These schools not only suffer from high rates of principal turnover but are also unable to attract experienced successors. The negative effect of leadership changes can be mitigated when vacancies are filled by individuals with prior experience leading other schools. However, the majority of new principals in high poverty and low-performing schools lack prior leadership experience and leave when more attractive positions become available in other schools. Copyright © 2012 Elsevier Inc. All rights reserved.

Nitrogen dioxide concentrations in neighborhoods adjacent to a commercial airport: a land use regression modeling study.

Science.gov (United States)

Adamkiewicz, Gary; Hsu, Hsiao-Hsien; Vallarino, Jose; Melly, Steven J; Spengler, John D; Levy, Jonathan I

2010-11-17

There is growing concern in communities surrounding airports regarding the contribution of various emission sources (such as aircraft and ground support equipment) to nearby ambient concentrations. We used extensive monitoring of nitrogen dioxide (NO2) in neighborhoods surrounding T.F. Green Airport in Warwick, RI, and land-use regression (LUR) modeling techniques to determine the impact of proximity to the airport and local traffic on these concentrations. Palmes diffusion tube samplers were deployed along the airport's fence line and within surrounding neighborhoods for one to two weeks. In total, 644 measurements were collected over three sampling campaigns (October 2007, March 2008 and June 2008) and each sampling location was geocoded. GIS-based variables were created as proxies for local traffic and airport activity. A forward stepwise regression methodology was employed to create general linear models (GLMs) of NO2 variability near the airport. The effect of local meteorology on associations with GIS-based variables was also explored. Higher concentrations of NO2 were seen near the airport terminal, entrance roads to the terminal, and near major roads, with qualitatively consistent spatial patterns between seasons. In our final multivariate model (R2 = 0.32), the local influences of highways and arterial/collector roads were statistically significant, as were local traffic density and distance to the airport terminal (all p GIS variables, and the regression model structure was robust to various model-building approaches. Our study has shown that there are clear local variations in NO2 in the neighborhoods that surround an urban airport, which are spatially consistent across seasons. LUR modeling demonstrated a strong influence of local traffic, except the smallest roads that predominate in residential areas, as well as proximity to the airport terminal.

A Review of the Literature on Principal Turnover

Science.gov (United States)

Snodgrass Rangel, Virginia

2018-01-01

Among the many challenges facing public schools are high levels of principal turnover. Given the important role that principals play and are expected to play in the improvement process, concerns about principal turnover have resulted in a growing body of research on its causes and consequences. The purpose of this review is to take stock of what…

Aerobic Physical Activity and the Leadership of Principals

Science.gov (United States)

Kiser, Kari

2016-01-01

The purpose of this study was to explore if there was a connection between regular aerobic physical activity and the stress and energy levels of principals as they reported it. To begin the research, the current aerobic physical activity level of principals was discovered. Additionally, the energy and stress levels of the principals who do engage…

Modeling of Principal Flank Wear: An Empirical Approach Combining the Effect of Tool, Environment and Workpiece Hardness

Science.gov (United States)

Mia, Mozammel; Al Bashir, Mahmood; Dhar, Nikhil Ranjan

2016-10-01

Hard turning is increasingly employed in machining, lately, to replace time-consuming conventional turning followed by grinding process. An excessive amount of tool wear in hard turning is one of the main hurdles to be overcome. Many researchers have developed tool wear model, but most of them developed it for a particular work-tool-environment combination. No aggregate model is developed that can be used to predict the amount of principal flank wear for specific machining time. An empirical model of principal flank wear (VB) has been developed for the different hardness of workpiece (HRC40, HRC48 and HRC56) while turning by coated carbide insert with different configurations (SNMM and SNMG) under both dry and high pressure coolant conditions. Unlike other developed model, this model includes the use of dummy variables along with the base empirical equation to entail the effect of any changes in the input conditions on the response. The base empirical equation for principal flank wear is formulated adopting the Exponential Associate Function using the experimental results. The coefficient of dummy variable reflects the shifting of the response from one set of machining condition to another set of machining condition which is determined by simple linear regression. The independent cutting parameters (speed, rate, depth of cut) are kept constant while formulating and analyzing this model. The developed model is validated with different sets of machining responses in turning hardened medium carbon steel by coated carbide inserts. For any particular set, the model can be used to predict the amount of principal flank wear for specific machining time. Since the predicted results exhibit good resemblance with experimental data and the average percentage error is <10 %, this model can be used to predict the principal flank wear for stated conditions.

Analysis of Moisture Content in Beetroot using Fourier Transform Infrared Spectroscopy and by Principal Component Analysis.

Science.gov (United States)

Nesakumar, Noel; Baskar, Chanthini; Kesavan, Srinivasan; Rayappan, John Bosco Balaguru; Alwarappan, Subbiah

2018-05-22

The moisture content of beetroot varies during long-term cold storage. In this work, we propose a strategy to identify the moisture content and age of beetroot using principal component analysis coupled Fourier transform infrared spectroscopy (FTIR). Frequent FTIR measurements were recorded directly from the beetroot sample surface over a period of 34 days for analysing its moisture content employing attenuated total reflectance in the spectral ranges of 2614-4000 and 1465-1853 cm -1 with a spectral resolution of 8 cm -1 . In order to estimate the transmittance peak height (T p ) and area under the transmittance curve [Formula: see text] over the spectral ranges of 2614-4000 and 1465-1853 cm -1 , Gaussian curve fitting algorithm was performed on FTIR data. Principal component and nonlinear regression analyses were utilized for FTIR data analysis. Score plot over the ranges of 2614-4000 and 1465-1853 cm -1 allowed beetroot quality discrimination. Beetroot quality predictive models were developed by employing biphasic dose response function. Validation experiment results confirmed that the accuracy of the beetroot quality predictive model reached 97.5%. This research work proves that FTIR spectroscopy in combination with principal component analysis and beetroot quality predictive models could serve as an effective tool for discriminating moisture content in fresh, half and completely spoiled stages of beetroot samples and for providing status alerts.

A Comparative Investigation of the Combined Effects of Pre-Processing, Wavelength Selection, and Regression Methods on Near-Infrared Calibration Model Performance.

Science.gov (United States)

Wan, Jian; Chen, Yi-Chieh; Morris, A Julian; Thennadil, Suresh N

2017-07-01

Near-infrared (NIR) spectroscopy is being widely used in various fields ranging from pharmaceutics to the food industry for analyzing chemical and physical properties of the substances concerned. Its advantages over other analytical techniques include available physical interpretation of spectral data, nondestructive nature and high speed of measurements, and little or no need for sample preparation. The successful application of NIR spectroscopy relies on three main aspects: pre-processing of spectral data to eliminate nonlinear variations due to temperature, light scattering effects and many others, selection of those wavelengths that contribute useful information, and identification of suitable calibration models using linear/nonlinear regression . Several methods have been developed for each of these three aspects and many comparative studies of different methods exist for an individual aspect or some combinations. However, there is still a lack of comparative studies for the interactions among these three aspects, which can shed light on what role each aspect plays in the calibration and how to combine various methods of each aspect together to obtain the best calibration model. This paper aims to provide such a comparative study based on four benchmark data sets using three typical pre-processing methods, namely, orthogonal signal correction (OSC), extended multiplicative signal correction (EMSC) and optical path-length estimation and correction (OPLEC); two existing wavelength selection methods, namely, stepwise forward selection (SFS) and genetic algorithm optimization combined with partial least squares regression for spectral data (GAPLSSP); four popular regression methods, namely, partial least squares (PLS), least absolute shrinkage and selection operator (LASSO), least squares support vector machine (LS-SVM), and Gaussian process regression (GPR). The comparative study indicates that, in general, pre-processing of spectral data can play a significant

Surface analysis the principal techniques

CERN Document Server

Vickerman, John C

2009-01-01

This completely updated and revised second edition of Surface Analysis: The Principal Techniques, deals with the characterisation and understanding of the outer layers of substrates, how they react, look and function which are all of interest to surface scientists. Within this comprehensive text, experts in each analysis area introduce the theory and practice of the principal techniques that have shown themselves to be effective in both basic research and in applied surface analysis. Examples of analysis are provided to facilitate the understanding of this topic and to show readers how they c

Application of multivariate chemometric techniques for simultaneous determination of five parameters of cottonseed oil by single bounce attenuated total reflectance Fourier transform infrared spectroscopy.

Science.gov (United States)

Talpur, M Younis; Kara, Huseyin; Sherazi, S T H; Ayyildiz, H Filiz; Topkafa, Mustafa; Arslan, Fatma Nur; Naz, Saba; Durmaz, Fatih; Sirajuddin

2014-11-01

Single bounce attenuated total reflectance (SB-ATR) Fourier transform infrared (FTIR) spectroscopy in conjunction with chemometrics was used for accurate determination of free fatty acid (FFA), peroxide value (PV), iodine value (IV), conjugated diene (CD) and conjugated triene (CT) of cottonseed oil (CSO) during potato chips frying. Partial least square (PLS), stepwise multiple linear regression (SMLR), principal component regression (PCR) and simple Beer׳s law (SBL) were applied to develop the calibrations for simultaneous evaluation of five stated parameters of cottonseed oil (CSO) during frying of French frozen potato chips at 170°C. Good regression coefficients (R(2)) were achieved for FFA, PV, IV, CD and CT with value of >0.992 by PLS, SMLR, PCR, and SBL. Root mean square error of prediction (RMSEP) was found to be less than 1.95% for all determinations. Result of the study indicated that SB-ATR FTIR in combination with multivariate chemometrics could be used for accurate and simultaneous determination of different parameters during the frying process without using any toxic organic solvent. Copyright © 2014 Elsevier B.V. All rights reserved.

Stepwise multiphoton activation fluorescence reveals a new method of melanin detection

Science.gov (United States)

Lai, Zhenhua; Kerimo, Josef; Mega, Yair; DiMarzio, Charles A.

2013-06-01

The stepwise multiphoton activated fluorescence (SMPAF) of melanin, activated by a continuous-wave mode near infrared (NIR) laser, reveals a broad spectrum extending from the visible spectra to the NIR and has potential application for a low-cost, reliable method of detecting melanin. SMPAF images of melanin in mouse hair and skin are compared with conventional multiphoton fluorescence microscopy and confocal reflectance microscopy (CRM). By combining CRM with SMPAF, we can locate melanin reliably. However, we have the added benefit of eliminating background interference from other components inside mouse hair and skin. The melanin SMPAF signal from the mouse hair is a mixture of a two-photon process and a third-order process. The melanin SMPAF emission spectrum is activated by a 1505.9-nm laser light, and the resulting spectrum has a peak at 960 nm. The discovery of the emission peak may lead to a more energy-efficient method of background-free melanin detection with less photo-bleaching.

Subjective performance evaluations and reciprocity in principal-agent relations

DEFF Research Database (Denmark)

Sebald, Alexander Christopher; Walzl, Markus

2014-01-01

. In contrast to existing models of reciprocity, we find that agents tend to sanction whenever the feedback of principals is below their subjective self-evaluations even if agents' pay-offs are independent of it. In turn, principals provide more positive feedback (relative to their actual performance assessment......We conduct a laboratory experiment with agents working on, and principals benefiting from, a real effort task in which the agents' performance can only be evaluated subjectively. Principals give subjective performance feedback to agents, and agents have an opportunity to sanction principals...... of the agent) if this does not affect their pay-off....

Regression analysis by example

CERN Document Server

Chatterjee, Samprit

2012-01-01

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

Applied logistic regression

CERN Document Server

Hosmer, David W; Sturdivant, Rodney X

2013-01-01

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

Pathways of DNA unlinking: A story of stepwise simplification.

Science.gov (United States)

Stolz, Robert; Yoshida, Masaaki; Brasher, Reuben; Flanner, Michelle; Ishihara, Kai; Sherratt, David J; Shimokawa, Koya; Vazquez, Mariel

2017-09-29

In Escherichia coli DNA replication yields interlinked chromosomes. Controlling topological changes associated with replication and returning the newly replicated chromosomes to an unlinked monomeric state is essential to cell survival. In the absence of the topoisomerase topoIV, the site-specific recombination complex XerCD- dif-FtsK can remove replication links by local reconnection. We previously showed mathematically that there is a unique minimal pathway of unlinking replication links by reconnection while stepwise reducing the topological complexity. However, the possibility that reconnection preserves or increases topological complexity is biologically plausible. In this case, are there other unlinking pathways? Which is the most probable? We consider these questions in an analytical and numerical study of minimal unlinking pathways. We use a Markov Chain Monte Carlo algorithm with Multiple Markov Chain sampling to model local reconnection on 491 different substrate topologies, 166 knots and 325 links, and distinguish between pathways connecting a total of 881 different topologies. We conclude that the minimal pathway of unlinking replication links that was found under more stringent assumptions is the most probable. We also present exact results on unlinking a 6-crossing replication link. These results point to a general process of topology simplification by local reconnection, with applications going beyond DNA.

Perceptions of Kentucky High School Principals and Superintendents on the Role of the Superintendent Influencing Principal Instructional Leadership

Science.gov (United States)

Hamilton, Charles L., Jr.

2011-01-01

This exploratory study surveyed the promotion of instructional leadership of high school principals by superintendents, as perceived by self and the principals they supervise. The two-phased study included an initial questionnaire administered to both study groups and comparisons of responses analyzed. All superintendents (N = 173), except the…

Role Perceptions and Job Stress among Special Education School Principals: Do They Differ from Principals of Regular Schools?

Science.gov (United States)

Gaziel, Haim Henry; Cohen-Azaria, Yael; Ermenc, Klara Skubic

2012-01-01

The objective of the present study was to compare principals' perceptions of their leadership roles in regular (Dovno, 1999) versus special education (Zaretzky, Faircloth & Moreau, 2005) schools, and how these perceptions affect feelings of job stress (Friedman, 2001; Margalit, 1999). We predicted that regular school principals would differ in…

Normalization Ridge Regression in Practice I: Comparisons Between Ordinary Least Squares, Ridge Regression and Normalization Ridge Regression.

Science.gov (United States)

Bulcock, J. W.

The problem of model estimation when the data are collinear was examined. Though the ridge regression (RR) outperforms ordinary least squares (OLS) regression in the presence of acute multicollinearity, it is not a problem free technique for reducing the variance of the estimates. It is a stochastic procedure when it should be nonstochastic and it…

Deformation quantization of principal fibre bundles

International Nuclear Information System (INIS)

Weiss, S.

2007-01-01

Deformation quantization is an algebraic but still geometrical way to define noncommutative spacetimes. In order to investigate corresponding gauge theories on such spaces, the geometrical formulation in terms of principal fibre bundles yields the appropriate framework. In this talk I will explain what should be understood by a deformation quantization of principal fibre bundles and how associated vector bundles arise in this context. (author)

Vector regression introduced

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.

Research and development needs in a step-wise process for the nuclear waste programme in Sweden

International Nuclear Information System (INIS)

Ström, A.; Andersson, J.; Ekeroth, E.; Hedin, A.; Pers, K.

2016-01-01

Concluding remarks: • The SKB RD&D Programme 2016 − contains an overview of all the measures that may be necessary for treatment and final disposal of nuclear waste from Swedish nuclear reactors and SKB's facilities; − clarifies how research and technology development are justified and evaluated in a step-wise procedure on the basis of the measures planned; − presents a strategic plan for the research and development necessary to establish and implement future activities; − Published as SKB TR 16-15 in December 2016

Applied linear regression

CERN Document Server

Weisberg, Sanford

2013-01-01

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

Artful Dodges Principals Use to Beat Bureaucracy.

Science.gov (United States)

Ficklen, Ellen

1982-01-01

A study of Chicago (Illinois) principals revealed many ways principals practiced "creative insubordination"--avoiding following instructions but still getting things done. Among the dodges are deliberately missing deadlines, following orders literally, ignoring channels to procure teachers or materials, and using community members to…

A study of machine learning regression methods for major elemental analysis of rocks using laser-induced breakdown spectroscopy

Science.gov (United States)

Boucher, Thomas F.; Ozanne, Marie V.; Carmosino, Marco L.; Dyar, M. Darby; Mahadevan, Sridhar; Breves, Elly A.; Lepore, Kate H.; Clegg, Samuel M.

2015-05-01

The ChemCam instrument on the Mars Curiosity rover is generating thousands of LIBS spectra and bringing interest in this technique to public attention. The key to interpreting Mars or any other types of LIBS data are calibrations that relate laboratory standards to unknowns examined in other settings and enable predictions of chemical composition. Here, LIBS spectral data are analyzed using linear regression methods including partial least squares (PLS-1 and PLS-2), principal component regression (PCR), least absolute shrinkage and selection operator (lasso), elastic net, and linear support vector regression (SVR-Lin). These were compared against results from nonlinear regression methods including kernel principal component regression (K-PCR), polynomial kernel support vector regression (SVR-Py) and k-nearest neighbor (kNN) regression to discern the most effective models for interpreting chemical abundances from LIBS spectra of geological samples. The results were evaluated for 100 samples analyzed with 50 laser pulses at each of five locations averaged together. Wilcoxon signed-rank tests were employed to evaluate the statistical significance of differences among the nine models using their predicted residual sum of squares (PRESS) to make comparisons. For MgO, SiO2, Fe2O3, CaO, and MnO, the sparse models outperform all the others except for linear SVR, while for Na2O, K2O, TiO2, and P2O5, the sparse methods produce inferior results, likely because their emission lines in this energy range have lower transition probabilities. The strong performance of the sparse methods in this study suggests that use of dimensionality-reduction techniques as a preprocessing step may improve the performance of the linear models. Nonlinear methods tend to overfit the data and predict less accurately, while the linear methods proved to be more generalizable with better predictive performance. These results are attributed to the high dimensionality of the data (6144 channels

Principal spectra describing magnetooptic permittivity tensor in cubic crystals

Energy Technology Data Exchange (ETDEWEB)

Hamrlová, Jana [Nanotechnology Centre, VSB – Technical University of Ostrava, listopadu 15, Ostrava, 708 33 Czech Republic (Czech Republic); IT4Innovations Centre, VSB – Technical University of Ostrava, listopadu 15, Ostrava, 708 33 Czech Republic (Czech Republic); Legut, Dominik [IT4Innovations Centre, VSB – Technical University of Ostrava, listopadu 15, Ostrava, 708 33 Czech Republic (Czech Republic); Veis, Martin [Faculty of Mathematics and Physics, Charles University, Ke Karlovu 3, Prague, 121 16 Czech Republic (Czech Republic); Pištora, Jaromír [Nanotechnology Centre, VSB – Technical University of Ostrava, listopadu 15, Ostrava, 708 33 Czech Republic (Czech Republic); Hamrle, Jaroslav, E-mail: jaroslav.hamrle@vsb.cz [IT4Innovations Centre, VSB – Technical University of Ostrava, listopadu 15, Ostrava, 708 33 Czech Republic (Czech Republic); Faculty of Mathematics and Physics, Charles University, Ke Karlovu 3, Prague, 121 16 Czech Republic (Czech Republic); Department of Physics, VSB – Technical University of Ostrava, 17. listopadu 15, Ostrava, 708 33 Czech Republic (Czech Republic)

2016-12-15

We provide unified phenomenological description of magnetooptic effects being linear and quadratic in magnetization. The description is based on few principal spectra, describing elements of permittivity tensor up to the second order in magnetization. Each permittivity tensor element for any magnetization direction and any sample surface orientation is simply determined by weighted summation of the principal spectra, where weights are given by crystallographic and magnetization orientations. The number of principal spectra depends on the symmetry of the crystal. In cubic crystals owning point symmetry we need only four principal spectra. Here, the principal spectra are expressed by ab initio calculations for bcc Fe, fcc Co and fcc Ni in optical range as well as in hard and soft x-ray energy range, i.e. at the 2p- and 3p-edges. We also express principal spectra analytically using modified Kubo formula.

High-Dimensional Intrinsic Interpolation Using Gaussian Process Regression and Diffusion Maps

International Nuclear Information System (INIS)

Thimmisetty, Charanraj A.; Ghanem, Roger G.; White, Joshua A.; Chen, Xiao

2017-01-01

This article considers the challenging task of estimating geologic properties of interest using a suite of proxy measurements. The current work recast this task as a manifold learning problem. In this process, this article introduces a novel regression procedure for intrinsic variables constrained onto a manifold embedded in an ambient space. The procedure is meant to sharpen high-dimensional interpolation by inferring non-linear correlations from the data being interpolated. The proposed approach augments manifold learning procedures with a Gaussian process regression. It first identifies, using diffusion maps, a low-dimensional manifold embedded in an ambient high-dimensional space associated with the data. It relies on the diffusion distance associated with this construction to define a distance function with which the data model is equipped. This distance metric function is then used to compute the correlation structure of a Gaussian process that describes the statistical dependence of quantities of interest in the high-dimensional ambient space. The proposed method is applicable to arbitrarily high-dimensional data sets. Here, it is applied to subsurface characterization using a suite of well log measurements. The predictions obtained in original, principal component, and diffusion space are compared using both qualitative and quantitative metrics. Considerable improvement in the prediction of the geological structural properties is observed with the proposed method.

Reel Principals: A Descriptive Content Analysis of the Images of School Principals Depicted in Movies from 1997-2009

Science.gov (United States)

Wolfrom, Katy J.

2010-01-01

According to Glanz's early research, school principals have been depicted as autocrats, bureaucrats, buffoons, and/or villains in movies from 1950 to 1996. The purpose of this study was to determine if these stereotypical characterizations of school principals have continued in films from 1997-2009, or if more favorable images have emerged that…

The DRE-Principal Partnership: Making It Work.

Science.gov (United States)

Davis, Barbara; Elliott, Karen

1995-01-01

Discusses the roles of the director of religious education (DRE) and the school principal at Catholic schools, viewing them as complimentary rather than competitive. Provides examples of positive cooperation between the principal and DRE at Most Pure Heart of Mary Parish, in Shelby, Ohio. (KP)

New Principals' Perspectives of Their Multifaceted Roles

Science.gov (United States)

Gentilucci, James L.; Denti, Lou; Guaglianone, Curtis L.

2013-01-01

This study utilizes Symbolic Interactionism to explore perspectives of neophyte principals. Findings explain how these perspectives are modified through complex interactions throughout the school year, and they also suggest preparation programs can help new principals most effectively by teaching "soft" skills such as active listening…

Leading Learning: First-Year Principals' Reflections on Instructional Leadership

Science.gov (United States)

O'Doherty, Ann; Ovando, Martha N.

2013-01-01

This qualitative study examined the instructional leadership perceptions of four first-year principals. Findings illuminate five themes drawn from the data: definitions of instructional leadership, challenges that first-year principals faced, how these principals addressed these challenges, how the novice principals plan to enact their…

Incorporating wind availability into land use regression modelling of air quality in mountainous high-density urban environment.

Science.gov (United States)

Shi, Yuan; Lau, Kevin Ka-Lun; Ng, Edward

2017-08-01

Urban air quality serves as an important function of the quality of urban life. Land use regression (LUR) modelling of air quality is essential for conducting health impacts assessment but more challenging in mountainous high-density urban scenario due to the complexities of the urban environment. In this study, a total of 21 LUR models are developed for seven kinds of air pollutants (gaseous air pollutants CO, NO 2 , NO x , O 3 , SO 2 and particulate air pollutants PM 2.5 , PM 10 ) with reference to three different time periods (summertime, wintertime and annual average of 5-year long-term hourly monitoring data from local air quality monitoring network) in Hong Kong. Under the mountainous high-density urban scenario, we improved the traditional LUR modelling method by incorporating wind availability information into LUR modelling based on surface geomorphometrical analysis. As a result, 269 independent variables were examined to develop the LUR models by using the "ADDRESS" independent variable selection method and stepwise multiple linear regression (MLR). Cross validation has been performed for each resultant model. The results show that wind-related variables are included in most of the resultant models as statistically significant independent variables. Compared with the traditional method, a maximum increase of 20% was achieved in the prediction performance of annual averaged NO 2 concentration level by incorporating wind-related variables into LUR model development. Copyright © 2017 Elsevier Inc. All rights reserved.

Understanding poisson regression.

Science.gov (United States)

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.

Estimating stepwise debromination pathways of polybrominated diphenyl ethers with an analogue Markov Chain Monte Carlo algorithm.

Science.gov (United States)

Zou, Yonghong; Christensen, Erik R; Zheng, Wei; Wei, Hua; Li, An

2014-11-01

A stochastic process was developed to simulate the stepwise debromination pathways for polybrominated diphenyl ethers (PBDEs). The stochastic process uses an analogue Markov Chain Monte Carlo (AMCMC) algorithm to generate PBDE debromination profiles. The acceptance or rejection of the randomly drawn stepwise debromination reactions was determined by a maximum likelihood function. The experimental observations at certain time points were used as target profiles; therefore, the stochastic processes are capable of presenting the effects of reaction conditions on the selection of debromination pathways. The application of the model is illustrated by adopting the experimental results of decabromodiphenyl ether (BDE209) in hexane exposed to sunlight. Inferences that were not obvious from experimental data were suggested by model simulations. For example, BDE206 has much higher accumulation at the first 30 min of sunlight exposure. By contrast, model simulation suggests that, BDE206 and BDE207 had comparable yields from BDE209. The reason for the higher BDE206 level is that BDE207 has the highest depletion in producing octa products. Compared to a previous version of the stochastic model based on stochastic reaction sequences (SRS), the AMCMC approach was determined to be more efficient and robust. Due to the feature of only requiring experimental observations as input, the AMCMC model is expected to be applicable to a wide range of PBDE debromination processes, e.g. microbial, photolytic, or joint effects in natural environments. Copyright © 2014 Elsevier Ltd. All rights reserved.

Alternative Methods of Regression

CERN Document Server

Birkes, David

2011-01-01

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

Selecting minimum dataset soil variables using PLSR as a regressive multivariate method

Science.gov (United States)

Stellacci, Anna Maria; Armenise, Elena; Castellini, Mirko; Rossi, Roberta; Vitti, Carolina; Leogrande, Rita; De Benedetto, Daniela; Ferrara, Rossana M.; Vivaldi, Gaetano A.

2017-04-01

Long-term field experiments and science-based tools that characterize soil status (namely the soil quality indices, SQIs) assume a strategic role in assessing the effect of agronomic techniques and thus in improving soil management especially in marginal environments. Selecting key soil variables able to best represent soil status is a critical step for the calculation of SQIs. Current studies show the effectiveness of statistical methods for variable selection to extract relevant information deriving from multivariate datasets. Principal component analysis (PCA) has been mainly used, however supervised multivariate methods and regressive techniques are progressively being evaluated (Armenise et al., 2013; de Paul Obade et al., 2016; Pulido Moncada et al., 2014). The present study explores the effectiveness of partial least square regression (PLSR) in selecting critical soil variables, using a dataset comparing conventional tillage and sod-seeding on durum wheat. The results were compared to those obtained using PCA and stepwise discriminant analysis (SDA). The soil data derived from a long-term field experiment in Southern Italy. On samples collected in April 2015, the following set of variables was quantified: (i) chemical: total organic carbon and nitrogen (TOC and TN), alkali-extractable C (TEC and humic substances - HA-FA), water extractable N and organic C (WEN and WEOC), Olsen extractable P, exchangeable cations, pH and EC; (ii) physical: texture, dry bulk density (BD), macroporosity (Pmac), air capacity (AC), and relative field capacity (RFC); (iii) biological: carbon of the microbial biomass quantified with the fumigation-extraction method. PCA and SDA were previously applied to the multivariate dataset (Stellacci et al., 2016). PLSR was carried out on mean centered and variance scaled data of predictors (soil variables) and response (wheat yield) variables using the PLS procedure of SAS/STAT. In addition, variable importance for projection (VIP

A stepwise procedure for science communication in the field

Science.gov (United States)

Nisancioglu, Kerim; Paasche, Øyvind

2017-04-01

Communicating and disseminating earth science to laypersons, high-school students and their teachers are becoming increasingly important considering the overwhelming impact human civilization have on the planet. One of the main challenges with this type of dissemination arises from the cross-disciplinary nature of the Earth system as it encompasses anything from cloud physics to the geological evidence of ice ages being played out on millennial time scales. During the last four years we have tested and developed an approach referred to as «Turspor» which can be translated to 'Trail Tracks'. The ambition with "Turspor" is to inspire participants to seek in-depth knowledge relating to observations of features made in the field (glacial moraines, active permafrost, clouds, winds and so forth) as we have come to learn that observations made in the field enhances students capability to grasp the bare essentials related to the phenomena in question. By engaging master and PhD students in the process we create a platform where students can improve their teaching and communicative skills through a stepwise procedure. The initial concept was tested on 35 high school students during the summer of 2012 in the mountainous area of Snøheim on Dovre, Southern Norway. Before the arrival of the high school students, the university students prepared one page written summaries describing relevant geological or meteorological features and trained on how to best disseminate a basic scientific understanding of these. Specific examples were patterned ground caused by permafrost, glacier flour, katabatic winds, and equilibrium line altitude of glaciers. Based on the success of the program over the past 4 years with field trips together with local schools, we are in the process of developing the concept to be offered as a course at the master and PhD level, including a week of training in didactics applied to topics in the geosciences as well as practical training in the field. The

Emission and distribution of phosphine in paddy fields and its relationship with greenhouse gases.

Science.gov (United States)

Chen, Weiyi; Niu, Xiaojun; An, Shaorong; Sheng, Hong; Tang, Zhenghua; Yang, Zhiquan; Gu, Xiaohong

2017-12-01

Phosphine (PH 3 ), as a gaseous phosphide, plays an important role in the phosphorus cycle in ecosystems. In this study, the emission and distribution of phosphine, carbon dioxide (CO 2 ) and methane (CH 4 ) in paddy fields were investigated to speculate the future potential impacts of enhanced greenhouse effect on phosphorus cycle involved in phosphine by the method of Pearson correlation analysis and multiple linear regression analysis. During the whole period of rice growth, there was a significant positive correlation between CO 2 emission flux and PH 3 emission flux (r=0.592, p=0.026, n=14). Similarly, a significant positive correlation of emission flux was also observed between CH 4 and PH 3 (r=0.563, p=0.036, n=14). The linear regression relationship was determined as [PH 3 ] flux =0.007[CO 2 ] flux +0.063[CH 4 ] flux -4.638. No significant differences were observed for all values of matrix-bound phosphine (MBP), soil carbon dioxide (SCO 2 ), and soil methane (SCH 4 ) in paddy soils. However, there was a significant positive correlation between MBP and SCO 2 at heading, flowering and ripening stage. The correlation coefficients were 0.909, 0.890 and 0.827, respectively. In vertical distribution, MBP had the analogical variation trend with SCO 2 and SCH 4 . Through Pearson correlation analysis and multiple stepwise linear regression analysis, pH, redox potential (Eh), total phosphorus (TP) and acid phosphatase (ACP) were identified as the principal factors affecting MBP levels, with correlative rankings of Eh>pH>TP>ACP. The multiple stepwise regression model ([MBP]=0.456∗[ACP]+0.235∗[TP]-1.458∗[Eh]-36.547∗[pH]+352.298) was obtained. The findings in this study hold great reference values to the global biogeochemical cycling of phosphorus in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

Honouring Roles: The Story of a Principal and a Student

Directory of Open Access Journals (Sweden)

Jerome Cranston

2012-11-01

Full Text Available The importance of the teacher-student relationship in educational practice is well established, as is the idea of principal leadership in relationship to staff. Even though principal leadership is regarded as a factor in student success, the principal’s effect is usually assumed to take place via the teaching staff. There is an absence of research about the “lived experience” of direct principal-student relationships that shed lights on the ways in which these relationships play a role in student success and principal transformation. This paper presents two narratives written about a particular set of principal-student interactions experienced by the researcher (principal and participant (student.  The analysis uses a narrative inquiry approach to explore both the individual and collective meanings of this principal-student relationship. The stories and their derived meanings have the potential to enliven and  influence educational practice as they explore the subtleties of the principal-student relationship.

The Principal's Role in Site-Based Management.

Science.gov (United States)

Drury, William R.

1993-01-01

In existing school-based management models, the principal's role ranges from chairing the local council to being a coach/facilitator. With teachers and parents assuming greater control over governance, curriculum, and budgeting, paranoid principals may establish more formal bargaining relationships with district boards. Caution is advised, because…

Theory favors a stepwise mechanism of porphyrin degradation by a ferric hydroperoxide model of the active species of heme oxygenase.

Science.gov (United States)

Kumar, Devesh; de Visser, Samuël P; Shaik, Sason

2005-06-08

The report uses density functional theory to address the mechanism of heme degradation by the enzyme heme oxygenase (HO) using a model ferric hydroperoxide complex. HO is known to trap heme molecules and degrade them to maintain iron homeostasis in the biosystem. The degradation is initiated by complexation of the heme, then formation of the iron-hydroperoxo species, which subsequently oxidizes the meso position of the porphyrin by hydroxylation, thereby enabling eventually the cleavage of the porphyrin ring. Kinetic isotope effect studies indicate that the mechanism is assisted by general acid catalysis, via a chain of water molecules, and that all the events occur in concert. However, previous theoretical treatments indicated that the concerted mechanism has a high barrier, much higher than an alternative mechanism that is initiated by O-O bond homolysis of iron-hydroperoxide. The present contribution studies the stepwise and concerted acid-catalyzed mechanisms using H(3)O(+)(H(2)O)(n)(), n = 0-2. The effect of the acid strength is tested using the H(4)N(+)(H(2)O)(2) cluster and a fully protonated ferric hydroperoxide. All the calculations show that a stepwise mechanism that involves proton relay and O-O homolysis, in the rate-determining step, has a much lower barrier (>10 kcal/mol) than the corresponding fully concerted mechanism. The best fit of the calculated solvent kinetic isotope effect, to the experimental data, is obtained for the H(3)O(+)(H(2)O)(2) cluster. The calculated alpha-deuterium secondary kinetic isotope effect is inverse (0.95-0.98), but much less so than the experimental value (0.7). Possible reasons for this quantitative difference are discussed. Some probes are suggested that may enable experiment to distinguish the stepwise from the concerted mechanism.

Leadership Standards in Action: The School Principal as Servant-Leader

Science.gov (United States)

Brumley, Cade

2011-01-01

"Leadership Standards In Action: The School Principal as Servant-Leader" is a powerful resource for aspiring principals, practicing principals, district leadership, and university faculty. The book responsibly unpacks the metaphor of principal as servant leader to the school's people and purpose. As a framework, the six ISLLC Standards of…

Introduction to regression graphics

CERN Document Server

Cook, R Dennis

2009-01-01

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

FPGA Implementation of the stepwise shutdown system

International Nuclear Information System (INIS)

Lotjonen, L.

2012-01-01

This report elaborates the design process of applications for field-programmable gate array (FPGA) devices. Brief introductions to EPGA technology and the design process are first given and then the design phases are walked through with the aid of a case study. FPGA is a programmable logic device that is programmed by the customer rather than the manufacturer. They are also usually re-programmable which enables updating their programming and otherwise modifying the design. There are also one-time programmable FPGAs that can be used when security issues require it. FPGA is said to be 'hardware designed like software', which means that the design process resembles software development but the end-product is considered a hardware application because the execution of the functions is entirely different from a microprocessor. This duality can give both the flexibility of software and the reliability of hardware. The FPGA design and verification and validation (V and V) methods for NPP safety systems have not yet matured because the technology is rather new in the field. Software development methods and standards can be used to some extent but the hardware aspects bring new challenges that cannot be tackled using purely software methods. International efforts are being made to development formal and consistent design and V and V methodology regulations for FPGA devices. A preventive safety function called Stepwise Shutdown System (SWS) was implemented on an Actel M1 IGLOO field-programmable gate array (FPGA) device. SWS is used to drive a process into a normal state if the process measurements deviate from the desired operating values. This can happen in case of process disturbances. The SWS implementation process from the requirements to the functional device is elaborated. The design is tested via simulation and hardware testing. The case study is to be further expanded as a part of a master's thesis. (orig.)

FPGA Implementation of the stepwise shutdown system

Energy Technology Data Exchange (ETDEWEB)

Lotjonen, L.

2012-07-01

This report elaborates the design process of applications for field-programmable gate array (FPGA) devices. Brief introductions to EPGA technology and the design process are first given and then the design phases are walked through with the aid of a case study. FPGA is a programmable logic device that is programmed by the customer rather than the manufacturer. They are also usually re-programmable which enables updating their programming and otherwise modifying the design. There are also one-time programmable FPGAs that can be used when security issues require it. FPGA is said to be 'hardware designed like software', which means that the design process resembles software development but the end-product is considered a hardware application because the execution of the functions is entirely different from a microprocessor. This duality can give both the flexibility of software and the reliability of hardware. The FPGA design and verification and validation (V and V) methods for NPP safety systems have not yet matured because the technology is rather new in the field. Software development methods and stanfards can be used to some extent but the hardware aspects bring new challenges that cannot be tacled using purely software methods. International efforts are being made to development formal and consistent design and V and V methodology regulations for FPGA devices. A preventive safety function called Stepwise Shutdown System (SWS) was implemented on an Actel M1 IGLOO field-programmable gate array (FPGA) device. SWS is used to drive a process into a normal state if the process measurements deviate from the desired operating values. This can happen in case of process disturbances. The SWS implementation processfrom the reguirements to the functional device is elaborated. The design is tested via simulation and hardware testing. The case study is to be further expanded as a part of a master's thesis. (orig.)

Do Qualification, Experience and Age Matter for Principals Leadership Styles?

OpenAIRE

Muhammad Javed Sawati; Saeed Anwar; Muhammad Iqbal Majoka

2013-01-01

The main focus of present study was to find out the prevalent leadership styles of principals in government schools of Khyber Pakhtunkhwa and to find relationship of leadership styles with qualifications, age and experience of the principals. On the basis of analyzed data, four major leadership styles of the principals were identified as Eclectic, Democratic, Autocratic, and Free-rein. However, a small proportion of the principal had no dominant leadership style. This study shows that princip...

Integrating Technology: The Principals' Role and Effect

Science.gov (United States)

Machado, Lucas J.; Chung, Chia-Jung

2015-01-01

There are many factors that influence technology integration in the classroom such as teacher willingness, availability of hardware, and professional development of staff. Taking into account these elements, this paper describes research on technology integration with a focus on principals' attitudes. The role of the principal in classroom…

Constructing principals' professional identities through life stories ...

African Journals Online (AJOL)

The Life History approach was used to collect data from six ... experience as the most significant leadership factors that influence principals' ... ranging from their entry into the teaching profession to their appointment as ..... teachers. I think I learnt from my principal to be strict but accommodating ..... Teachers College Press.

Women principals' reflections of curriculum management challenges ...

African Journals Online (AJOL)

This study reports the reflections of grade 6 rural primary principals in Mpumalanga province. A qualitative method of inquiry was used in this article, where data were collected using individual interviews with three principals and focus group discussions with the school management teams (SMTs) of three primary schools.

What Effective Principals Do to Improve Instruction and Increase Student Achievement

Science.gov (United States)

Turner, Elizabeth Anne

2013-01-01

The purposes of this mixed method study were to (a) Examine the relationships among principal effectiveness, principal instructional leadership, and student achievement; (b) examine the differences among principal effectiveness, principal instructional leadership and student achievement; and (c) investigate what effective principals do to improve…

Stepwise magnetic-geochemical approach for efficient assessment of heavy metal polluted sites

Science.gov (United States)

Appel, E.; Rösler, W.; Ojha, G.

2012-04-01

Previous studies have shown that magnetometry can outline the distribution of fly ash deposition in the surroundings of coal-burning power plants and steel industries. Especially the easy-to-measure magnetic susceptibility (MS) is capable to act as a proxy for heavy metal (HM) pollution caused by such kind of point source pollution. Here we present a demonstration project around the coal-burning power plant complex "Schwarze Pumpe" in eastern Germany. Before reunification of West and East Germany huge amounts of HM pollutants were emitted from the "Schwarze Pumpe" into the environment by both fly ash emission and dumped clinker. The project has been conducted as part of the TASK Centre of Competence which aims at bringing new innovative techniques closer to the market. Our project combines in situ and laboratory MS measurements and HM analyses in order to demonstrate the efficiency of a stepwise approach for site assessment of HM pollution around point sources of fly-ash emission and deposition into soil. The following scenario is played through: We assume that the "true" spatial distribution of HM pollution (given by the pollution load index PLI comprising Fe, Zn, Pb, and Cu) is represented by our entire set of 85 measured samples (XRF analyses) from forest sites around the "Schwarze Pumpe". Surface MS data (collected with a Bartington MS2D) and in situ vertical MS sections (logged by an SM400 instrument) are used to determine a qualitative overview of potentially higher and lower polluted areas. A suite of spatial HM distribution maps obtained by random selections of 30 out of the 85 analysed sites is compared to the HM map obtained from a targeted 30-sites-selection based on pre-information from the MS results. The PLI distribution map obtained from the targeted 30-sites-selection shows all essential details of the "true" pollution map, while the different random 30-sites-selections miss important features. This comparison shows that, for the same cost

Does acid-base equilibrium correlate with remnant liver volume during stepwise liver resection?

Science.gov (United States)

Golriz, Mohammad; Abbasi, Sepehr; Fathi, Parham; Majlesara, Ali; Brenner, Thorsten; Mehrabi, Arianeb

2017-10-01

Small for size and flow syndrome (SFSF) is one of the most challenging complications following extended hepatectomy (EH). After EH, hepatic artery flow decreases and portal vein flow increases per 100 g of remnant liver volume (RLV). This causes hypoxia followed by metabolic acidosis. A correlation between acidosis and posthepatectomy liver failure has been postulated but not studied systematically in a large animal model or clinical setting. In our study, we performed stepwise liver resections on nine pigs to defined SFSF limits as follows: step 1: segment II/III resection, step 2: segment IV resection, step 3: segment V/VIII resection (RLV: 75, 50, and 25%, respectively). Blood gas values were measured before and after each step using four catheters inserted into the carotid artery, internal jugular vein, hepatic artery, and portal vein. The pH, [Formula: see text], and base excess (BE) decreased, but [Formula: see text] values increased after 75% resection in the portal and jugular veins. EH correlated with reduced BE in the hepatic artery. Pco 2 values increased after 75% resection in the jugular vein. In contrast, arterial Po 2 increased after every resection, whereas the venous Po 2 decreased slightly. There were differences in venous [Formula: see text], BE in the hepatic artery, and Pco 2 in the jugular vein after 75% liver resection. Because 75% resection is the limit for SFSF, these noninvasive blood evaluations may be used to predict SFSF. Further studies with long-term follow-up are required to validate this correlation. NEW & NOTEWORTHY This is the first study to evaluate acid-base parameters in major central and hepatic vessels during stepwise liver resection. The pH, [Formula: see text], and base excess (BE) decreased, but [Formula: see text] values increased after 75% resection in the portal and jugular veins. Extended hepatectomy correlated with reduced BE in the hepatic artery. Because 75% resection is the limit for small for size and flow

Automation of peak-tracking analysis of stepwise perturbed NMR spectra

Energy Technology Data Exchange (ETDEWEB)

Banelli, Tommaso; Vuano, Marco [Università di Udine, Dipartimento di Area Medica (Italy); Fogolari, Federico [INBB (Italy); Fusiello, Andrea [Università di Udine, Dipartimento Politecnico di Ingegneria e Architettura (Italy); Esposito, Gennaro [INBB (Italy); Corazza, Alessandra, E-mail: alessandra.corazza@uniud.it [Università di Udine, Dipartimento di Area Medica (Italy)

2017-02-15

We describe a new algorithmic approach able to automatically pick and track the NMR resonances of a large number of 2D NMR spectra acquired during a stepwise variation of a physical parameter. The method has been named Trace in Track (TinT), referring to the idea that a gaussian decomposition traces peaks within the tracks recognised through 3D mathematical morphology. It is capable of determining the evolution of the chemical shifts, intensity and linewidths of each tracked peak.The performances obtained in term of track reconstruction and correct assignment on realistic synthetic spectra were high above 90% when a noise level similar to that of experimental data were considered. TinT was applied successfully to several protein systems during a temperature ramp in isotope exchange experiments. A comparison with a state-of-the-art algorithm showed promising results for great numbers of spectra and low signal to noise ratios, when the graduality of the perturbation is appropriate. TinT can be applied to different kinds of high throughput chemical shift mapping experiments, with quasi-continuous variations, in which a quantitative automated recognition is crucial.

High-intensity stepwise conditioning programme for improved exercise responses and agility performance of a badminton player with knee pain.

Science.gov (United States)

Chen, Bob; Mok, Damon; Lee, Winson C C; Lam, Wing Kai

2015-02-01

To examine the effect of a high-intensity stepwise conditioning programme combined with multiple recovery measures on physical fitness, agility, and knee pain symptoms of an injured player. A single case study. University-based conditioning training laboratory. One 26-year-old male world-class badminton player (height, 190.0 cm; weight, 79.3 kg; left dominant hand; playing experience, 16 years; former world champion) with patellar tendinosis and calcification of his left knee. The player received seven conditioning sessions over three weeks. During the programme, there was a gradual increase in training duration and load across sessions while cold therapy, manual stretches and massage were administered after each session to minimise inflammation. The training outcome was evaluated with three different testing methods: standard step test, badminton-specific agility test, and tension-pain rating. The conditioning programme reduced knee pain symptoms and improved actual performance and cardiopulmonary fitness during the agility task. The player was able to return to sport and compete within a month. A high-intensity stepwise conditioning programme improved the physical fitness while sufficient recovery measures minimised any possible undesirable effects and promoted faster return to elite level competition. Copyright © 2014 Elsevier Ltd. All rights reserved.

Contemporary Challenges and Changes: Principals' Leadership Practices in Malaysia

Science.gov (United States)

Jones, Michelle; Adams, Donnie; Joo, Mabel Tan Hwee; Muniandy, Vasu; Perera, Corinne Jaqueline; Harris, Alma

2015-01-01

This article outlines the findings from a contemporary study of principals' leadership practices in Malaysia as part of the 7 System Leadership Study. Recent policy developments within Malaysia have increased principals' accountability and have underlined the importance of the role of the principals in transforming school performance and student…

3D face recognition with asymptotic cones based principal curvatures

KAUST Repository

Tang, Yinhang

2015-05-01

The classical curvatures of smooth surfaces (Gaussian, mean and principal curvatures) have been widely used in 3D face recognition (FR). However, facial surfaces resulting from 3D sensors are discrete meshes. In this paper, we present a general framework and define three principal curvatures on discrete surfaces for the purpose of 3D FR. These principal curvatures are derived from the construction of asymptotic cones associated to any Borel subset of the discrete surface. They describe the local geometry of the underlying mesh. First two of them correspond to the classical principal curvatures in the smooth case. We isolate the third principal curvature that carries out meaningful geometric shape information. The three principal curvatures in different Borel subsets scales give multi-scale local facial surface descriptors. We combine the proposed principal curvatures with the LNP-based facial descriptor and SRC for recognition. The identification and verification experiments demonstrate the practicability and accuracy of the third principal curvature and the fusion of multi-scale Borel subset descriptors on 3D face from FRGC v2.0.

3D face recognition with asymptotic cones based principal curvatures

KAUST Repository

Tang, Yinhang; Sun, Xiang; Huang, Di; Morvan, Jean-Marie; Wang, Yunhong; Chen, Liming

2015-01-01

The classical curvatures of smooth surfaces (Gaussian, mean and principal curvatures) have been widely used in 3D face recognition (FR). However, facial surfaces resulting from 3D sensors are discrete meshes. In this paper, we present a general framework and define three principal curvatures on discrete surfaces for the purpose of 3D FR. These principal curvatures are derived from the construction of asymptotic cones associated to any Borel subset of the discrete surface. They describe the local geometry of the underlying mesh. First two of them correspond to the classical principal curvatures in the smooth case. We isolate the third principal curvature that carries out meaningful geometric shape information. The three principal curvatures in different Borel subsets scales give multi-scale local facial surface descriptors. We combine the proposed principal curvatures with the LNP-based facial descriptor and SRC for recognition. The identification and verification experiments demonstrate the practicability and accuracy of the third principal curvature and the fusion of multi-scale Borel subset descriptors on 3D face from FRGC v2.0.

Principal bundles the classical case

CERN Document Server

Sontz, Stephen Bruce

2015-01-01

This introductory graduate level text provides a relatively quick path to a special topic in classical differential geometry: principal bundles.  While the topic of principal bundles in differential geometry has become classic, even standard, material in the modern graduate mathematics curriculum, the unique approach taken in this text presents the material in a way that is intuitive for both students of mathematics and of physics. The goal of this book is to present important, modern geometric ideas in a form readily accessible to students and researchers in both the physics and mathematics communities, providing each with an understanding and appreciation of the language and ideas of the other.

Taking a Distributed Perspective to the School Principal's Workday

Science.gov (United States)

Spillane, James P.; Camburn, Eric M.; Pareja, Amber Stitziel

2007-01-01

Focusing on the school principal's day-to-day work, we examine who leads curriculum and instruction- and administration-related activities when the school principal is not leading but participating in the activity. We also explore the prevalence of coperformance of management and leadership activities in the school principal's workday. Looking…

Principal Preparation in Special Education: Building an Inclusive Culture

Science.gov (United States)

Hofreiter, Deborah

2017-01-01

The importance of principal preparation in special education has increased since the Education for All Handicapped Children Act was passed in 1975. There are significant financial reasons for preparing principals in the area of special education. Recent research also shows that all children learn better in an inclusive environment. Principals who…

Urban School Principals and Their Role as Multicultural Leaders

Science.gov (United States)

Gardiner, Mary E.; Enomoto, Ernestine K.

2006-01-01

This study focuses on the role of urban school principals as multicultural leaders. Using cross-case analysis, the authors describe what 6 practicing principals do in regard to multicultural leadership. The findings suggest that although multicultural preparation was lacking for these principals, some did engage in work that promoted diversity in…

Principals: Human Capital Managers at Every School

Science.gov (United States)

Kimball, Steven M.

2011-01-01

Being a principal is more than just being an instructional leader. Principals also must manage their schools' teaching talent in a strategic way so that it is linked to school instructional improvement strategies, to the competencies needed to enact the strategies, and to success in boosting student learning. Teacher acquisition and performance…

The Effects of Reform in Principal Selection on Leadership Behavior of General and Vocational High School Principals in Taiwan

Science.gov (United States)

Hsiao, Hsi-Chi; Lee, Ming-Chao; Tu, Ya-Ling

2013-01-01

Deregulation has formed the primary core of education reform in Taiwan in the past decade. The principal selection system was one of the specific recommendations in the deregulation of education. The method of designation of senior high school principals has changed from being "appointed" to being "selected." The issue as to…

Principal Holistic Judgments and High-Stakes Evaluations of Teachers

Science.gov (United States)

Briggs, Derek C.; Dadey, Nathan

2017-01-01

Results from a sample of 1,013 Georgia principals who rated 12,617 teachers are used to compare holistic and analytic principal judgments with indicators of student growth central to the state's teacher evaluation system. Holistic principal judgments were compared to mean student growth percentiles (MGPs) and analytic judgments from a formal…

Job Satisfaction of Elementary Principals in Large Urban Communities

Science.gov (United States)

Mitchell, Cathryn M.

2010-01-01

The purpose of this study was to determine job satisfaction levels of elementary principals in "major urban" districts in Texas and to identify strategies these principals used to cope with the demands of the position. Additionally, the project sought to find structures and supports needed to attract and retain principals in the…

Leadership Behaviors and Its Relation with Principals' Management Experience

Science.gov (United States)

Mehdinezhad, Vali; Sardarzahi, Zaid

2016-01-01

This paper aims at studying the leadership behaviors reported by principals and observed by teachers and its relationship with management experience of principals. A quantitative method was used in this study. The target population included all principals and teachers of guidance schools and high schools in the Dashtiari District, Iran. A sample…

Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis.

Science.gov (United States)

Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended.

Prediction of reported consumption of selected fat-containing foods.

Science.gov (United States)

Tuorila, H; Pangborn, R M

1988-10-01

A total of 100 American females (mean age = 20.8 years) completed a questionnaire, in which their beliefs, evaluations, liking and consumption (frequency, consumption compared to others, intention to consume) of milk, cheese, ice cream, chocolate and "high-fat foods" were measured. For the design and analysis, the basic frame of reference was the Fishbein-Ajzen model of reasoned action, but the final analyses were carried out with stepwise multiple regression analysis. In addition to the components of the Fishbein-Ajzen model, beliefs and evaluations were used as independent variables. On the average, subjects reported liking all the products but not "high-fat foods", and thought that milk and cheese were "good for you" whereas the remaining items were "bad for you". Principal component analysis for beliefs revealed factors related to pleasantness/benefit aspects, to health and weight concern and to the "functionality" of the foods. In stepwise multiple regression analyses, liking was the predominant predictor of reported consumption for all the foods, but various belief factors, particularly those related to concern with weight, also significantly predicted consumption. Social factors played only a minor role. The multiple R's of the predictive functions varied from 0.49 to 0.74. The fact that all four foods studied elicited individual sets of beliefs and belief structures, and that none of them was rated similar to the generic "high-fat foods", emphasizes that consumers attach meaning to integrated food entities rather than to ingredients.

Stillbirth evaluation: a stepwise assessment of placental pathology and autopsy.

Science.gov (United States)

Miller, Emily S; Minturn, Lucy; Linn, Rebecca; Weese-Mayer, Debra E; Ernst, Linda M

2016-01-01

The American Congress of Obstetricians and Gynecologists places special emphasis on autopsy as one of the most important tests for evaluation of stillbirth. Despite a recommendation of an autopsy, many families will decline the autopsy based on religious/cultural beliefs, fear of additional suffering for the child, or belief that no additional information will be obtained or of value. Further, many obstetric providers express a myriad of barriers limiting their recommendation for a perinatal autopsy despite their understanding of its value. Consequently, perinatal autopsy rates have been declining. Without the information provided by an autopsy, many women are left with unanswered questions regarding cause of death for their fetus and without clear management strategies to reduce the risk of stillbirth in future pregnancies. To avoid this scenario, it is imperative that clinicians are knowledgeable about the benefit of autopsy so they can provide clear information on its diagnostic utility and decrease potential barriers; in so doing the obstetrician can ensure that each family has the necessary information to make an informed decision. We sought to quantify the contribution of placental pathologic examination and autopsy in identifying a cause of stillbirth and to identify how often clinical management is modified due to each result. This is a cohort study of all cases of stillbirth from 2009 through 2013 at a single tertiary care center. Records were reviewed in a stepwise manner: first the clinical history and laboratory results, then the placental pathologic evaluation, and finally the autopsy. At each step, a cause of death and the certainty of that etiology were coded. Clinical changes that would be recommended by information available at each step were also recorded. Among the 144 cases of stillbirth examined, 104 (72%) underwent autopsy and these cases constitute the cohort of study. The clinical and laboratory information alone identified a cause of death

Land-use regression with long-term satellite-based greenness index and culture-specific sources to model PM2.5 spatial-temporal variability.

Science.gov (United States)

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

Modelos de regressão não linear aplicados a grupos de acessos de alho

OpenAIRE

Reis, Renata M; Cecon, Paulo R; Puiatti, Mário; Finger, Fernando L; Nascimento, Moysés; Silva, Fabyano F; Carneiro, Antônio PS; Silva, Anderson R

2014-01-01

O principal objetivo deste estudo foi comparar modelos de regressão não linear aptos a descreverem o acúmulo de massa seca de diferentes partes da planta do alho ao longo do tempo (60, 90, 120 e 150 dias após plantio). Objetivou-se também identificar acessos semelhantes em relação às características avaliadas por meio de análises de agrupamento. Foram utilizados 20 acessos de alho pertencentes ao Banco de Germoplasma de Hortaliças da Universidade Federal de Viçosa (BGH/UFV). O teor de massa s...

The Hexadehydro-Diels-Alder Cycloisomerization Reaction Proceeds by a Stepwise Mechanism.

Science.gov (United States)

Wang, Tao; Niu, Dawen; Hoye, Thomas R

2016-06-29

We report here experiments showing that the hexadehydro-Diels-Alder (HDDA) cycloisomerization reaction proceeds in a stepwise manner-i.e., via a diradical intermediate. Judicious use of substituent effects was decisive. We prepared (i) a series of triyne HDDA substrates that differed only in the R group present on the remote terminus of the diynophilic alkyne and (ii) an analogous series of dienophilic alkynes (n-C7H15COC≡CR) for use in classical Diels-Alder (DA) reactions (with 1,3-cyclopentadiene). The R groups were CF3, CHO, COMe/Et, CO2Me, CONMe2/Et2, H, and 1-propynyl. The relative rates of both the HDDA cyclization reactions and the simple DA cycloadditions were measured. The reactivity trends revealed a dramatic difference in the behaviors of the CF3 (slowest HDDA and nearly fastest DA) and 1-propynyl (fastest HDDA and slowest DA) containing members of each series. These differences can be explained by invoking radical-stabilizing energies rather than electron-withdrawing effects as the dominating feature of the HDDA reaction.

Boosted structured additive regression for Escherichia coli fed-batch fermentation modeling.

Science.gov (United States)

Melcher, Michael; Scharl, Theresa; Luchner, Markus; Striedner, Gerald; Leisch, Friedrich

2017-02-01

The quality of biopharmaceuticals and patients' safety are of highest priority and there are tremendous efforts to replace empirical production process designs by knowledge-based approaches. Main challenge in this context is that real-time access to process variables related to product quality and quantity is severely limited. To date comprehensive on- and offline monitoring platforms are used to generate process data sets that allow for development of mechanistic and/or data driven models for real-time prediction of these important quantities. Ultimate goal is to implement model based feed-back control loops that facilitate online control of product quality. In this contribution, we explore structured additive regression (STAR) models in combination with boosting as a variable selection tool for modeling the cell dry mass, product concentration, and optical density on the basis of online available process variables and two-dimensional fluorescence spectroscopic data. STAR models are powerful extensions of linear models allowing for inclusion of smooth effects or interactions between predictors. Boosting constructs the final model in a stepwise manner and provides a variable importance measure via predictor selection frequencies. Our results show that the cell dry mass can be modeled with a relative error of about ±3%, the optical density with ±6%, the soluble protein with ±16%, and the insoluble product with an accuracy of ±12%. Biotechnol. Bioeng. 2017;114: 321-334. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Building Leadership Capacity to Support Principal Succession

Science.gov (United States)

Escalante, Karen Elizabeth

2016-01-01

This study applies transformational leadership theory practices, specifically inspiring a shared vision, modeling the way and enabling others to act to examine the purposeful ways in which principals work to build the next generation of teacher leaders in response to the dearth of K-12 principals. The purpose of this study was to discover how one…

Aspectos histológicos e bioquímicos de Joannesia Princips e Spathodea Campanulata, crescendo em solos na capacidade de campo, encharcado e alagado

Directory of Open Access Journals (Sweden)

Maria Aparecida Correa

1985-11-01

Full Text Available An experiment was conducted involving potted plants of Joanessia princips and Spathodea campanulata in conditions of super saturated soil, and saturated soil of normal wettness. Variations in some histological and biochenical parameters were examined. It was verified that S. campanulata has greater histological plasticity than J. princips and that only S. campanulata can withs tand super saturated conditions. The histological changes of the roots and stems of S. campanulata were notable and probably are associated with the better growth of the species in soils with low concentration of oxygen. The activity of mitogenesis in the cambial cells of the bark was greatest in S. campanulata when planted in super-satured soils. Also observed were numerosis spongy lenticels related to this increased activity. A comparison of the two species in relation to the different treatments verified in levels of alcohol in the roots. Linear regression analysis revealed significant indices between alcohol concentration and histological alterations, the highest levl of alcohol was enconrentered in J. princips.Foi montado um experimento envolvendo plantas envasadas de Joannesia princips e. Spathodea campanulata, em condições de solo alagado, encharcado e na capacidade de campo, visando detectar e estudar variações de alguns parâmetros histológicos e bioquímicos. Verificou-se que S. campanulata apresentou maior plasticidade histológica que J. princips, sendo a única a suportar a condição de solo alagado. As mudanças histológicas em raízes e caules de S. campanulata foram notáveis, podendo provavelmente serem associadas à maior sobrevivência da espécie em solos com baixos teores de oxigênio. A atividade mitogênica das células cambiais da casca foi maior em S. campanulata quando ensaiada em solo alagado. Foram ainda observadas numerosas ¡entícelas esponjosas decorrentes dessa atividade aumentada. Comparando-se as duas espécies nos diferentes

Multilevel sparse functional principal component analysis.

Science.gov (United States)

Di, Chongzhi; Crainiceanu, Ciprian M; Jank, Wolfgang S

2014-01-29

We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal component scores; 3) predict the underlying curves. Through simulations the proposed method is able to discover dominating modes of variations and reconstruct underlying curves well even in sparse settings. Our approach is illustrated by two applications, the Sleep Heart Health Study and eBay auctions.

Principals, Trust, and Cultivating Vibrant Schools

Directory of Open Access Journals (Sweden)

Megan Tschannen-Moran

2015-03-01

Full Text Available Although principals are ultimately held accountable to student learning in their buildings, the most consistent research results have suggested that their impact on student achievement is largely indirect. Leithwood, Patten, and Jantzi proposed four paths through which this indirect influence would flow, and the purpose of this special issue is to examine in greater depth these mediating variables. Among mediating variables, we assert that trust is key. In this paper, we explore the evidence that points to the role that faculty trust in the principal plays in student learning and how principals can cultivate trust by attending to the five facets of trust, as well as the correlates of trust that mediate student learning, including academic press, collective teacher efficacy, and teacher professionalism. We argue that trust plays a role in each of the four paths identified by Leithwood, Patten, and Jantzi. Finally, we explore possible new directions for future research.

Principal noncommutative torus bundles

DEFF Research Database (Denmark)

Echterhoff, Siegfried; Nest, Ryszard; Oyono-Oyono, Herve

2008-01-01

of bivariant K-theory (denoted RKK-theory) due to Kasparov. Using earlier results of Echterhoff and Williams, we shall give a complete classification of principal non-commutative torus bundles up to equivariant Morita equivalence. We then study these bundles as topological fibrations (forgetting the group...

QSAR study of HCV NS5B polymerase inhibitors using the genetic algorithm-multiple linear regression (GA-MLR).

Science.gov (United States)

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.

Regression and regression analysis time series prediction modeling on climate data of quetta, pakistan

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)

Linear regression in astronomy. I

Science.gov (United States)

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.

Logic regression and its extensions.

Science.gov (United States)

Schwender, Holger; Ruczinski, Ingo

2010-01-01

Logic regression is an adaptive classification and regression procedure, initially developed to reveal interacting single nucleotide polymorphisms (SNPs) in genetic association studies. In general, this approach can be used in any setting with binary predictors, when the interaction of these covariates is of primary interest. Logic regression searches for Boolean (logic) combinations of binary variables that best explain the variability in the outcome variable, and thus, reveals variables and interactions that are associated with the response and/or have predictive capabilities. The logic expressions are embedded in a generalized linear regression framework, and thus, logic regression can handle a variety of outcome types, such as binary responses in case-control studies, numeric responses, and time-to-event data. In this chapter, we provide an introduction to the logic regression methodology, list some applications in public health and medicine, and summarize some of the direct extensions and modifications of logic regression that have been proposed in the literature. Copyright © 2010 Elsevier Inc. All rights reserved.

Solid structures of the stepwise self-assembled copillar[5]arene-based supramolecular polymers

International Nuclear Information System (INIS)

Park, Yeon Sil; Hwang, Seong Min; Shin, Jae Yeon; Paek, Kyung Soo

2016-01-01

Development of supramolecular polymer has attracted much interest because of their interesting properties such as stimuli-responsiveness, recycling, self-healing and degradability, and their consequential applications. The essential feature of this class of polymers is the self-assembly of discrete monomeric subunits via non-covalent interactions or dynamic covalent bonds. Among the many monomeric subunits, pillar[n]arenes have been ideal building blocks for the fabrication of polymeric supramolecules because of their intrinsic characteristics. The ring-shaped morphologies in supramolecular polymer P are probably due to the tendency of the end-to-end connection in the solid state of long flexible supramolecular chains. The size increase of nano-rings as the stepwise addition increases might be due to the fact that the linear supramolecular polymer P in solution seems to be maintained until the nano-ring formation by solidification

Solid structures of the stepwise self-assembled copillar[5]arene-based supramolecular polymers

Energy Technology Data Exchange (ETDEWEB)

Park, Yeon Sil; Hwang, Seong Min; Shin, Jae Yeon; Paek, Kyung Soo [Dept. of Chemistry, Soongsil University, Seoul (Korea, Republic of)

2016-10-15

Development of supramolecular polymer has attracted much interest because of their interesting properties such as stimuli-responsiveness, recycling, self-healing and degradability, and their consequential applications. The essential feature of this class of polymers is the self-assembly of discrete monomeric subunits via non-covalent interactions or dynamic covalent bonds. Among the many monomeric subunits, pillar[n]arenes have been ideal building blocks for the fabrication of polymeric supramolecules because of their intrinsic characteristics. The ring-shaped morphologies in supramolecular polymer P are probably due to the tendency of the end-to-end connection in the solid state of long flexible supramolecular chains. The size increase of nano-rings as the stepwise addition increases might be due to the fact that the linear supramolecular polymer P in solution seems to be maintained until the nano-ring formation by solidification.

Principal Investigator-in-a-Box

Science.gov (United States)

Young, Laurence R.

1999-01-01

Human performance in orbit is currently limited by several factors beyond the intrinsic awkwardness of motor control in weightlessness. Cognitive functioning can be affected by such factors as cumulative sleep loss, stress and the psychological effects of long-duration small-group isolation. When an astronaut operates a scientific experiment, the performance decrement associated with such factors can lead to lost or poor quality data and even the total loss of a scientific objective, at great cost to the sponsors and to the dismay of the Principal Investigator. In long-duration flights, as anticipated on the International Space Station and on any planetary exploration, the experimental model is further complicated by long delays between training and experiment, and the large number of experiments each crew member must perform. Although no documented studies have been published on the subject, astronauts report that an unusually large number of simple errors are made in space. Whether a result of the effects of microgravity, accumulated fatigue, stress or other factors, this pattern of increased error supports the need for a computerized decision-making aid for astronauts performing experiments. Artificial intelligence and expert systems might serve as powerful tools for assisting experiments in space. Those conducting space experiments typically need assistance exactly when the planned checklist does not apply. Expert systems, which use bits of human knowledge and human methods to respond appropriately to unusual situations, have a flexibility that is highly desirable in circumstances where an invariably predictable course of action/response does not exist. Frequently the human expert on the ground is unavailable, lacking the latest information, or not consulted by the astronaut conducting the experiment. In response to these issues, we have developed "Principal Investigator-in-a-Box," or [PI], to capture the reasoning process of the real expert, the Principal

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)

African-American Female Students and STEM: Principals' Leadership Perspectives

Science.gov (United States)

Sampson, Kristin Morgan

As the U.S. becomes more diverse, school leaders, major corporations, and areas of national defense continue to investigate science, technology, engineering and math (STEM) education issues. African-American female students have historically been underrepresented in STEM fields, yet educational leadership research, examining this population is limited. The purpose of this qualitative study was to explore how principals support African-American female students in schools with a STEM program. The Critical Race Theory (CRT)was used as a theoretical framework to highlight the inadequacies to support educational inequalities. The application of the CRT in this study is due to the embedded inequality practices within the educational system, that have resulted in the underrepresentation of African-American female students in STEM. To complement CRT, the transformative leadership model was also utilized to examine the emancipatory leadership practices principals utilized. These theories framed the context of this study by recognizing the need to address how support is actualized to African-American female students in STEM by their principals. A case study approach was an appropriate method to answer the two research questions, 1) How do principals feel they support African-American female students in their STEM programs? and 2) What practices do principals engage in that support underrepresented students in STEM? This approach intended to uncover how a principal leads a multifaceted population of underrepresented students in STEM programs. Two principals of STEM schools, where more than 50% of the population were African-American, were interviewed and observed completing daily operations at community-wide events. The STEM Coordinators and a teacher were also interviewed, and test scores were examined to provide further information about the STEM program, and public records were obtained to analyze the principals' means of communication. I found that principals supported

Incremental Tensor Principal Component Analysis for Handwritten Digit Recognition

Directory of Open Access Journals (Sweden)

Chang Liu

2014-01-01

Full Text Available To overcome the shortcomings of traditional dimensionality reduction algorithms, incremental tensor principal component analysis (ITPCA based on updated-SVD technique algorithm is proposed in this paper. This paper proves the relationship between PCA, 2DPCA, MPCA, and the graph embedding framework theoretically and derives the incremental learning procedure to add single sample and multiple samples in detail. The experiments on handwritten digit recognition have demonstrated that ITPCA has achieved better recognition performance than that of vector-based principal component analysis (PCA, incremental principal component analysis (IPCA, and multilinear principal component analysis (MPCA algorithms. At the same time, ITPCA also has lower time and space complexity.

A study of machine learning regression methods for major elemental analysis of rocks using laser-induced breakdown spectroscopy

International Nuclear Information System (INIS)

Boucher, Thomas F.; Ozanne, Marie V.; Carmosino, Marco L.; Dyar, M. Darby; Mahadevan, Sridhar; Breves, Elly A.; Lepore, Kate H.; Clegg, Samuel M.

2015-01-01

The ChemCam instrument on the Mars Curiosity rover is generating thousands of LIBS spectra and bringing interest in this technique to public attention. The key to interpreting Mars or any other types of LIBS data are calibrations that relate laboratory standards to unknowns examined in other settings and enable predictions of chemical composition. Here, LIBS spectral data are analyzed using linear regression methods including partial least squares (PLS-1 and PLS-2), principal component regression (PCR), least absolute shrinkage and selection operator (lasso), elastic net, and linear support vector regression (SVR-Lin). These were compared against results from nonlinear regression methods including kernel principal component regression (K-PCR), polynomial kernel support vector regression (SVR-Py) and k-nearest neighbor (kNN) regression to discern the most effective models for interpreting chemical abundances from LIBS spectra of geological samples. The results were evaluated for 100 samples analyzed with 50 laser pulses at each of five locations averaged together. Wilcoxon signed-rank tests were employed to evaluate the statistical significance of differences among the nine models using their predicted residual sum of squares (PRESS) to make comparisons. For MgO, SiO 2 , Fe 2 O 3 , CaO, and MnO, the sparse models outperform all the others except for linear SVR, while for Na 2 O, K 2 O, TiO 2 , and P 2 O 5 , the sparse methods produce inferior results, likely because their emission lines in this energy range have lower transition probabilities. The strong performance of the sparse methods in this study suggests that use of dimensionality-reduction techniques as a preprocessing step may improve the performance of the linear models. Nonlinear methods tend to overfit the data and predict less accurately, while the linear methods proved to be more generalizable with better predictive performance. These results are attributed to the high dimensionality of the data (6144

riskRegression

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....

An Assessment of the Perceived Instructional Leadership Behaviors of Assistant Principals

Science.gov (United States)

Atkinson, Ronald E., Jr.

2013-01-01

This study examined the extent to which the role of the assistant principal is perceived to include instructional leadership behaviors. Specifically, this study compared the perceptions of instructional leadership practices of elementary, middle, and high school assistant principals from the perspectives of assistant principals, principals, and…

Location and characterisation of pollution sites by principal ...

African Journals Online (AJOL)

Location and characterisation of pollution sites by principal component analysis of trace contaminants in a slightly polluted seasonal river: a case study of the Arenales River (Salta, Argentina) ... Keywords: trace element contamination, water quality, principal component analysis, Arenales River, Salta, Argentina ...

Two Charter School Principals' Engagement in Instructional Leadership

Science.gov (United States)

Bickmore, Dana L.; Sulentic Dowell, Margaret-Mary

2014-01-01

This comparative case (Merriam, 2009) study explored two charter school principals' engagement in instructional leadership. Analysis of three data sources--interviews, observations, and documents--revealed that principals were almost exclusively focused on state accountability and possessed limited knowledge of pedagogical practices. In…

Empowering principals to lead and manage public schools ...

African Journals Online (AJOL)

Globally, education systems have been affected by radical social, political and economic changes. Although school principals play a pivotal role in improving student learning and attaining educational outcomes, they work under strenuous conditions to deal with multifaceted transformational issues. Principals experience ...

Stepwise development of hematopoietic stem cells from embryonic stem cells.

Directory of Open Access Journals (Sweden)

Kenji Matsumoto

Full Text Available The cellular ontogeny of hematopoietic stem cells (HSCs remains poorly understood because their isolation from and their identification in early developing small embryos are difficult. We attempted to dissect early developmental stages of HSCs using an in vitro mouse embryonic stem cell (ESC differentiation system combined with inducible HOXB4 expression. Here we report the identification of pre-HSCs and an embryonic type of HSCs (embryonic HSCs as intermediate cells between ESCs and HSCs. Both pre-HSCs and embryonic HSCs were isolated by their c-Kit(+CD41(+CD45(- phenotype. Pre-HSCs did not engraft in irradiated adult mice. After co-culture with OP9 stromal cells and conditional expression of HOXB4, pre-HSCs gave rise to embryonic HSCs capable of engraftment and long-term reconstitution in irradiated adult mice. Blast colony assays revealed that most hemangioblast activity was detected apart from the pre-HSC population, implying the early divergence of pre-HSCs from hemangioblasts. Gene expression profiling suggests that a particular set of transcripts closely associated with adult HSCs is involved in the transition of pre-HSC to embryonic HSCs. We propose an HSC developmental model in which pre-HSCs and embryonic HSCs sequentially give rise to adult types of HSCs in a stepwise manner.

Euler principal component analysis

NARCIS (Netherlands)

Liwicki, Stephan; Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja

Principal Component Analysis (PCA) is perhaps the most prominent learning tool for dimensionality reduction in pattern recognition and computer vision. However, the ℓ 2-norm employed by standard PCA is not robust to outliers. In this paper, we propose a kernel PCA method for fast and robust PCA,

School Principals' Perceptions of Ethically Just Responses to a Student Sexting Vignette: Severity of Administrator Response, Principal Personality, and Offender Gender and Race

Science.gov (United States)

Moriarty, Margaret E.

2012-01-01

This mixed-methods study was designed to determine how principals perceived the ethicality of sanctions for students engaged in sexting behavior relative to the race/ethnicity and gender of the student. Personality traits of the principals were surveyed to determine if Openness and/or Conscientiousness would predict principal response. Sexting is…

Use of Sparse Principal Component Analysis (SPCA) for Fault Detection

DEFF Research Database (Denmark)

Gajjar, Shriram; Kulahci, Murat; Palazoglu, Ahmet

2016-01-01

Principal component analysis (PCA) has been widely used for data dimension reduction and process fault detection. However, interpreting the principal components and the outcomes of PCA-based monitoring techniques is a challenging task since each principal component is a linear combination of the ...

Regression in autistic spectrum disorders.

Science.gov (United States)

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.

Informing principal policy reforms in South Africa through data-based evidence

Directory of Open Access Journals (Sweden)

Gabrielle Wills

2015-12-01

Full Text Available In the past decade there has been a notable shift in South African education policy that raises the value of school leadership as a lever for learning improvements. Despite a growing discourse on school leadership, there has been a lack of empirical based evidence on principals to inform, validate or debate the efficacy of proposed policies in raising the calibre of school principals. Drawing on findings from a larger study to understand the labour market for school principals in South Africa, this paper highlights four overarching characteristics of this market with implications for informing principal policy reforms. The paper notes that improving the design and implementation of policies guiding the appointment process for principals is a matter of urgency. A substantial and increasing number of principal replacements are taking place across South African schools given a rising age profile of school principals. In a context of low levels of principal mobility and high tenure, the leadership trajectory of the average school is established for nearly a decade with each principal replacement. Evidence-based policy making has a strong role to play in getting this right.

Understanding logistic regression analysis

OpenAIRE

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...

Preschool Principal's Curriculum Leadership Indicators: A Taiwan Perspective

Science.gov (United States)

Lin, Chia-Fen; Lee, John Chi-Kin

2013-01-01

The role of a principal's curriculum leadership has become an educational issue in Taiwan's early childhood education. This study represents a pioneering attempt in adopting a target school interview, fuzzy Delphi, and analytic hierarchy process for constructing preschool principal's curriculum leadership indicators. Fifteen experts and…

Delegation of Monitoring in a Principal-Agent Relationship

NARCIS (Netherlands)

Strausz, R.G.

1995-01-01

This paper studies a principal-agent relationship with moral hazard in which the principal or the supervisor can monitor the agent's hidden action by using identical monitoring technologies. The paper shows that delegation of monitoring to the supervisor is profitable because of two effects. With

COMPETENCE OF SCHOOL PRINCIPALS REGARDING KNOWLEDGE MANAGEMENT IN ELEMENTARY SCHOOLS

Directory of Open Access Journals (Sweden)

Gökmen DAĞLI

2007-12-01

Full Text Available This research aims to determine the manner of school principals regarding knowledge managementin primary school education. The research is a subjective one conducted in general scanning method. Personal informationform and five-likert scale are the main means in which data was collected. During the data collection stage, school principalswere requested to provide information about the way in which they obtain, share, process, evaluate knowledge, take decisionand analyze problems within the scope of knowledge management. In the virtue of the data acquired, the research shows that;the school principals obtain knowledge by attending meetings with teachers, making personal observation, their personalexperience and online resources. Regarding the sharing of knowledge, the research shows the principals always shareknowledge with their assistant principals and teachers; in using of knowledge, decision making and analyzing problemsresearch also shows that principals take decisions in co-operation with assistant principals and teachers. Last but not least,research shows that in storing the knowledge principals mainly use computers and traditional filing techniques. Seminarsshould be organized periodically by specialists with respect to acquiring, sharing, using and also filling knowledge followingdecision-making in order for school administrators to keep abreast of the latest developments in knowledge management

Linear regression in astronomy. II

Science.gov (United States)

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.

Automatic scatter detection in fluorescence landscapes by means of spherical principal component analysis

DEFF Research Database (Denmark)

Kotwa, Ewelina Katarzyna; Jørgensen, Bo Munk; Brockhoff, Per B.

2013-01-01

In this paper, we introduce a new method, based on spherical principal component analysis (S‐PCA), for the identification of Rayleigh and Raman scatters in fluorescence excitation–emission data. These scatters should be found and eliminated as a prestep before fitting parallel factor analysis...... models to the data, in order to avoid model degeneracies. The work is inspired and based on a previous research, where scatter removal was automatic (based on a robust version of PCA called ROBPCA) and required no visual data inspection but appeared to be computationally intensive. To overcome...... this drawback, we implement the fast S‐PCA in the scatter identification routine. Moreover, an additional pattern interpolation step that complements the method, based on robust regression, will be applied. In this way, substantial time savings are gained, and the user's engagement is restricted to a minimum...

How the Principalship Has Changed: Lessons from Principals' Life Stories.

Science.gov (United States)

Brubaker, Dale L.

1995-01-01

The life stories of (North Carolina) principals in a graduate education class reveal vast changes over the past 20 years. "Good ol' boy" superintendents and principals have been replaced by self-interested political "sharks" concerned more with image than substance. Fortunately, principals with resiliency, caring values, and…

Effects on pain of a stepwise multidisciplinary intervention (STA OP!) that targets pain and behavior in advanced dementia: A cluster randomized controlled trial

NARCIS (Netherlands)

Pieper, Marjoleine J.C.; van der Steen, Jenny T.; Francke, Anneke L.; Scherder, Erik J.A.; Twisk, Jos W.R.; Achterberg, Wilco P.

Background: Pain in nursing home residents with advanced dementia remains a major challenge; it is difficult to detect and may be expressed as challenging behavior. STA OP! aims to identify physical and other needs as causes of behavioral changes and uses a stepwise approach for psychosocial and

Effects on pain of a stepwise multidisciplinary intervention (STA OP!) that targets pain and behavior in advanced dementia: A cluster randomized controlled trial.

NARCIS (Netherlands)

Pieper, M.J.C.; Steen, J.T. van der; Francke, A.L.; Scherder, E.J.A.; Twisk, J.W.R.; Achterberg, W.P.

2018-01-01

Background: Pain in nursing home residents with advanced dementia remains a major challenge; it is difficult to detect and may be expressed as challenging behavior. STA OP! aims to identify physical and other needs as causes of behavioral changes and uses a stepwise approach for psychosocial and

The Principal-Agent model and the European Union

NARCIS (Netherlands)

Delreux, Tom; Adriaensen, J.

2017-01-01

This book assesses the use and limitations of the principal-agent model in a context of increasingly complex political systems such as the European Union. Whilst a number of conceptual, theoretical and methodological challenges need to be addressed, the authors show that the principal-agent model

Career Paths in Educational Leadership: Examining Principals' Narratives

Science.gov (United States)

Parylo, Oksana; Zepeda, Sally J.; Bengtson, Ed

2012-01-01

This qualitative study analyzes the career path narratives of active principals. Structural narrative analysis was supplemented with sociolinguistic theory and thematic narrative analysis to discern the similarities and differences, as well as the patterns in the language used by participating principals. Thematic analysis found four major themes…

Principals' Perceptions of Their Knowledge in Special Education

Science.gov (United States)

Roberts, Maria Banda; Guerra, Federico R., Jr.

2017-01-01

With the "Every Student Succeeds Act" continuing to legislate accountability for special education and Hispanic students, the appropriate content in principal preparation programs relevant to successful leadership of special education programs is vital. This mixed methods study analyzed the survey responses of 84 principals in South…

Stepwise-activable multifunctional peptide-guided prodrug micelles for cancerous cells intracellular drug release

Energy Technology Data Exchange (ETDEWEB)

Zhang, Jing, E-mail: zhangjing@zjut.edu.cn; Li, Mengfei [Zhejiang University of Technology, College of Materials Science and Engineering (China); Yuan, Zhefan [Zhejiang University, Key Laboratory of Biomass Chemical Engineering of Ministry of Education, Department of Chemical and Biological Engineering (China); Wu, Dan; Chen, Jia-da; Feng, Jie, E-mail: fengjie@zjut.edu.cn [Zhejiang University of Technology, College of Materials Science and Engineering (China)

2016-10-15

A novel type of stepwise-activable multifunctional peptide-guided prodrug micelles (MPPM) was fabricated for cancerous cells intracellular drug release. Deca-lysine sequence (K{sub 10}), a type of cell-penetrating peptide, was synthesized and terminated with azido-glycine. Then a new kind of molecule, alkyne modified doxorubicin (DOX) connecting through disulfide bond (DOX-SS-alkyne), was synthesized. After coupling via Cu-catalyzed azide–alkyne cycloaddition (CuAAC) click chemistry reaction, reduction-sensitive peptide-guided prodrug was obtained. Due to the amphiphilic property of the prodrug, it can assemble to form micelles. To prevent the nanocarriers from unspecific cellular uptake, the prodrug micelles were subsequently modified with 2,3-dimethyl maleic anhydride to obtain MPPM with a negatively charged outer shell. In vitro studies showed that MPPM could be shielded from cells under psychological environment. However, when arriving at mild acidic tumor site, the cell-penetrating capacity of MPPM would be activated by charge reversal of the micelles via hydrolysis of acid-labile β-carboxylic amides and regeneration of K{sub 10}, which enabled efficient internalization of MPPM by tumor cells as well as following glutathione- and protease-induced drug release inside the cancerous cells. Furthermore, since the guide peptide sequences can be accurately designed and synthesized, it can be easily changed for various functions, such as targeting peptide, apoptotic peptide, even aptamers, only need to be terminated with azido-glycine. This method can be used as a template for reduction-sensitive peptide-guided prodrug for cancer therapy.Graphical abstractA novel type of stepwise-activable multifunctional peptide-guided prodrug micelles (MPPM) was fabricated for selective drug delivery in cancerous cells. MPPM could be shielded from cells under psychological environment. However, when arriving at mild acidic tumor site, the cell-penetrating capacity of MPPM would

Learning Leaders: How Do Award-Winning Principals Learn and Grow? Are There Commonalities in the Professional Development Practices of NAESP/NASSP Award-Winning Principals?

Science.gov (United States)

Hansen, Mark

2013-01-01

The role a principal plays in school improvement has evolved over time. The transition from principal as manager to principal as instructional leader began with and was driven in large part by the effective schools movement of the 1970's and 1980's (Hallinger, 2003; Zigarelli, 1996). Since the inception of NCLB in 2001, the leader's role in…

Common Core Implementation Decisions Made by Principals in Elementary Schools

Science.gov (United States)

Norman, Alexis Cienfuegos

2016-01-01

The purpose of this study was to understand the decisions elementary principals have made during the Common Core State Standards reform. Specifically, (a) what decisions principals have made to support Common Core implementation, (b) what strategies elementary principals have employed to communicate with stakeholders about Common Core State…

Morphological and molecular evidence for a stepwise evolutionary transition from teeth to baleen in mysticete whales.

Science.gov (United States)

Deméré, Thomas A; McGowen, Michael R; Berta, Annalisa; Gatesy, John

2008-02-01

The origin of baleen in mysticete whales represents a major transition in the phylogenetic history of Cetacea. This key specialization, a keratinous sieve that enables filter-feeding, permitted exploitation of a new ecological niche and heralded the evolution of modern baleen-bearing whales, the largest animals on Earth. To date, all formally described mysticete fossils conform to two types: toothed species from Oligocene-age rocks ( approximately 24 to 34 million years old) and toothless species that presumably utilized baleen to feed (Recent to approximately 30 million years old). Here, we show that several Oligocene toothed mysticetes have nutrient foramina and associated sulci on the lateral portions of their palates, homologous structures in extant mysticetes house vessels that nourish baleen. The simultaneous occurrence of teeth and nutrient foramina implies that both teeth and baleen were present in these early mysticetes. Phylogenetic analyses of a supermatrix that includes extinct taxa and new data for 11 nuclear genes consistently resolve relationships at the base of Mysticeti. The combined data set of 27,340 characters supports a stepwise transition from a toothed ancestor, to a mosaic intermediate with both teeth and baleen, to modern baleen whales that lack an adult dentition but retain developmental and genetic evidence of their ancestral toothed heritage. Comparative sequence data for ENAM (enamelin) and AMBN (ameloblastin) indicate that enamel-specific loci are present in Mysticeti but have degraded to pseudogenes in this group. The dramatic transformation in mysticete feeding anatomy documents an apparently rare, stepwise mode of evolution in which a composite phenotype bridged the gap between primitive and derived morphologies; a combination of fossil and molecular evidence provides a multifaceted record of this macroevolutionary pattern.

Principals' Perception of Educational Inputs and Students' Academic ...

African Journals Online (AJOL)

This study investigated principals' perception of the relationship between educational inputs and academic performance of students in public junior secondary schools (JSS) in the Central Senatorial District of Delta State, Nigeria. The population was all the 173 public JSS and their principals from which a sample of twenty ...