WorldWideScience

Sample records for variables included selection

  1. Variations in Carabidae assemblages across the farmland habitats in relation to selected environmental variables including soil properties

    Directory of Open Access Journals (Sweden)

    Beáta Baranová

    2018-03-01

    Full Text Available The variations in ground beetles (Coleoptera: Carabidae assemblages across the three types of farmland habitats, arable land, meadows and woody vegetation were studied in relation to vegetation cover structure, intensity of agrotechnical interventions and selected soil properties. Material was pitfall trapped in 2010 and 2011 on twelve sites of the agricultural landscape in the Prešov town and its near vicinity, Eastern Slovakia. A total of 14,763 ground beetle individuals were entrapped. Material collection resulted into 92 Carabidae species, with the following six species dominating: Poecilus cupreus, Pterostichus melanarius, Pseudoophonus rufipes, Brachinus crepitans, Anchomenus dorsalis and Poecilus versicolor. Studied habitats differed significantly in the number of entrapped individuals, activity abundance as well as representation of the carabids according to their habitat preferences and ability to fly. However, no significant distinction was observed in the diversity, evenness neither dominance. The most significant environmental variables affecting Carabidae assemblages species variability were soil moisture and herb layer 0-20 cm. Another best variables selected by the forward selection were intensity of agrotechnical interventions, humus content and shrub vegetation. The other from selected soil properties seem to have just secondary meaning for the adult carabids. Environmental variables have the strongest effect on the habitat specialists, whereas ground beetles without special requirements to the habitat quality seem to be affected by the studied environmental variables just little.

  2. Variable Selection via Partial Correlation.

    Science.gov (United States)

    Li, Runze; Liu, Jingyuan; Lou, Lejia

    2017-07-01

    Partial correlation based variable selection method was proposed for normal linear regression models by Bühlmann, Kalisch and Maathuis (2010) as a comparable alternative method to regularization methods for variable selection. This paper addresses two important issues related to partial correlation based variable selection method: (a) whether this method is sensitive to normality assumption, and (b) whether this method is valid when the dimension of predictor increases in an exponential rate of the sample size. To address issue (a), we systematically study this method for elliptical linear regression models. Our finding indicates that the original proposal may lead to inferior performance when the marginal kurtosis of predictor is not close to that of normal distribution. Our simulation results further confirm this finding. To ensure the superior performance of partial correlation based variable selection procedure, we propose a thresholded partial correlation (TPC) approach to select significant variables in linear regression models. We establish the selection consistency of the TPC in the presence of ultrahigh dimensional predictors. Since the TPC procedure includes the original proposal as a special case, our theoretical results address the issue (b) directly. As a by-product, the sure screening property of the first step of TPC was obtained. The numerical examples also illustrate that the TPC is competitively comparable to the commonly-used regularization methods for variable selection.

  3. Benchmarking Variable Selection in QSAR.

    Science.gov (United States)

    Eklund, Martin; Norinder, Ulf; Boyer, Scott; Carlsson, Lars

    2012-02-01

    Variable selection is important in QSAR modeling since it can improve model performance and transparency, as well as reduce the computational cost of model fitting and predictions. Which variable selection methods that perform well in QSAR settings is largely unknown. To address this question we, in a total of 1728 benchmarking experiments, rigorously investigated how eight variable selection methods affect the predictive performance and transparency of random forest models fitted to seven QSAR datasets covering different endpoints, descriptors sets, types of response variables, and number of chemical compounds. The results show that univariate variable selection methods are suboptimal and that the number of variables in the benchmarked datasets can be reduced with about 60 % without significant loss in model performance when using multivariate adaptive regression splines MARS and forward selection. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Purposeful selection of variables in logistic regression

    Directory of Open Access Journals (Sweden)

    Williams David Keith

    2008-12-01

    Full Text Available Abstract Background The main problem in many model-building situations is to choose from a large set of covariates those that should be included in the "best" model. A decision to keep a variable in the model might be based on the clinical or statistical significance. There are several variable selection algorithms in existence. Those methods are mechanical and as such carry some limitations. Hosmer and Lemeshow describe a purposeful selection of covariates within which an analyst makes a variable selection decision at each step of the modeling process. Methods In this paper we introduce an algorithm which automates that process. We conduct a simulation study to compare the performance of this algorithm with three well documented variable selection procedures in SAS PROC LOGISTIC: FORWARD, BACKWARD, and STEPWISE. Results We show that the advantage of this approach is when the analyst is interested in risk factor modeling and not just prediction. In addition to significant covariates, this variable selection procedure has the capability of retaining important confounding variables, resulting potentially in a slightly richer model. Application of the macro is further illustrated with the Hosmer and Lemeshow Worchester Heart Attack Study (WHAS data. Conclusion If an analyst is in need of an algorithm that will help guide the retention of significant covariates as well as confounding ones they should consider this macro as an alternative tool.

  5. Variable selection by lasso-type methods

    Directory of Open Access Journals (Sweden)

    Sohail Chand

    2011-09-01

    Full Text Available Variable selection is an important property of shrinkage methods. The adaptive lasso is an oracle procedure and can do consistent variable selection. In this paper, we provide an explanation that how use of adaptive weights make it possible for the adaptive lasso to satisfy the necessary and almost sufcient condition for consistent variable selection. We suggest a novel algorithm and give an important result that for the adaptive lasso if predictors are normalised after the introduction of adaptive weights, it makes the adaptive lasso performance identical to the lasso.

  6. Variable and subset selection in PLS regression

    DEFF Research Database (Denmark)

    Høskuldsson, Agnar

    2001-01-01

    The purpose of this paper is to present some useful methods for introductory analysis of variables and subsets in relation to PLS regression. We present here methods that are efficient in finding the appropriate variables or subset to use in the PLS regression. The general conclusion...... is that variable selection is important for successful analysis of chemometric data. An important aspect of the results presented is that lack of variable selection can spoil the PLS regression, and that cross-validation measures using a test set can show larger variation, when we use different subsets of X, than...

  7. SELECTING QUASARS BY THEIR INTRINSIC VARIABILITY

    International Nuclear Information System (INIS)

    Schmidt, Kasper B.; Rix, Hans-Walter; Jester, Sebastian; Hennawi, Joseph F.; Marshall, Philip J.; Dobler, Gregory

    2010-01-01

    We present a new and simple technique for selecting extensive, complete, and pure quasar samples, based on their intrinsic variability. We parameterize the single-band variability by a power-law model for the light-curve structure function, with amplitude A and power-law index γ. We show that quasars can be efficiently separated from other non-variable and variable sources by the location of the individual sources in the A-γ plane. We use ∼60 epochs of imaging data, taken over ∼5 years, from the SDSS stripe 82 (S82) survey, where extensive spectroscopy provides a reference sample of quasars, to demonstrate the power of variability as a quasar classifier in multi-epoch surveys. For UV-excess selected objects, variability performs just as well as the standard SDSS color selection, identifying quasars with a completeness of 90% and a purity of 95%. In the redshift range 2.5 < z < 3, where color selection is known to be problematic, variability can select quasars with a completeness of 90% and a purity of 96%. This is a factor of 5-10 times more pure than existing color selection of quasars in this redshift range. Selecting objects from a broad griz color box without u-band information, variability selection in S82 can afford completeness and purity of 92%, despite a factor of 30 more contaminants than quasars in the color-selected feeder sample. This confirms that the fraction of quasars hidden in the 'stellar locus' of color space is small. To test variability selection in the context of Pan-STARRS 1 (PS1) we created mock PS1 data by down-sampling the S82 data to just six epochs over 3 years. Even with this much sparser time sampling, variability is an encouragingly efficient classifier. For instance, a 92% pure and 44% complete quasar candidate sample is attainable from the above griz-selected catalog. Finally, we show that the presented A-γ technique, besides selecting clean and pure samples of quasars (which are stochastically varying objects), is also

  8. Penalized variable selection in competing risks regression.

    Science.gov (United States)

    Fu, Zhixuan; Parikh, Chirag R; Zhou, Bingqing

    2017-07-01

    Penalized variable selection methods have been extensively studied for standard time-to-event data. Such methods cannot be directly applied when subjects are at risk of multiple mutually exclusive events, known as competing risks. The proportional subdistribution hazard (PSH) model proposed by Fine and Gray (J Am Stat Assoc 94:496-509, 1999) has become a popular semi-parametric model for time-to-event data with competing risks. It allows for direct assessment of covariate effects on the cumulative incidence function. In this paper, we propose a general penalized variable selection strategy that simultaneously handles variable selection and parameter estimation in the PSH model. We rigorously establish the asymptotic properties of the proposed penalized estimators and modify the coordinate descent algorithm for implementation. Simulation studies are conducted to demonstrate the good performance of the proposed method. Data from deceased donor kidney transplants from the United Network of Organ Sharing illustrate the utility of the proposed method.

  9. Machine learning techniques to select variable stars

    Directory of Open Access Journals (Sweden)

    García-Varela Alejandro

    2017-01-01

    Full Text Available In order to perform a supervised classification of variable stars, we propose and evaluate a set of six features extracted from the magnitude density of the light curves. They are used to train automatic classification systems using state-of-the-art classifiers implemented in the R statistical computing environment. We find that random forests is the most successful method to select variables.

  10. Robust cluster analysis and variable selection

    CERN Document Server

    Ritter, Gunter

    2014-01-01

    Clustering remains a vibrant area of research in statistics. Although there are many books on this topic, there are relatively few that are well founded in the theoretical aspects. In Robust Cluster Analysis and Variable Selection, Gunter Ritter presents an overview of the theory and applications of probabilistic clustering and variable selection, synthesizing the key research results of the last 50 years. The author focuses on the robust clustering methods he found to be the most useful on simulated data and real-time applications. The book provides clear guidance for the varying needs of bot

  11. THE TIME DOMAIN SPECTROSCOPIC SURVEY: VARIABLE SELECTION AND ANTICIPATED RESULTS

    Energy Technology Data Exchange (ETDEWEB)

    Morganson, Eric; Green, Paul J. [Harvard Smithsonian Center for Astrophysics, 60 Garden St, Cambridge, MA 02138 (United States); Anderson, Scott F.; Ruan, John J. [Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195 (United States); Myers, Adam D. [Department of Physics and Astronomy, University of Wyoming, Laramie, WY 82071 (United States); Eracleous, Michael; Brandt, William Nielsen [Department of Astronomy and Astrophysics, 525 Davey Laboratory, The Pennsylvania State University, University Park, PA 16802 (United States); Kelly, Brandon [Department of Physics, Broida Hall, University of California, Santa Barbara, CA 93106-9530 (United States); Badenes, Carlos [Department of Physics and Astronomy and Pittsburgh Particle Physics, Astrophysics and Cosmology Center (PITT PACC), University of Pittsburgh, 3941 O’Hara St, Pittsburgh, PA 15260 (United States); Bañados, Eduardo [Max-Planck-Institut für Astronomie, Königstuhl 17, D-69117 Heidelberg (Germany); Blanton, Michael R. [Center for Cosmology and Particle Physics, Department of Physics, New York University, 4 Washington Place, New York, NY 10003 (United States); Bershady, Matthew A. [Department of Astronomy, University of Wisconsin, 475 N. Charter St., Madison, WI 53706 (United States); Borissova, Jura [Instituto de Física y Astronomía, Universidad de Valparaíso, Av. Gran Bretaña 1111, Playa Ancha, Casilla 5030, and Millennium Institute of Astrophysics (MAS), Santiago (Chile); Burgett, William S. [GMTO Corp, Suite 300, 251 S. Lake Ave, Pasadena, CA 91101 (United States); Chambers, Kenneth, E-mail: emorganson@cfa.harvard.edu [Institute for Astronomy, University of Hawaii at Manoa, Honolulu, HI 96822 (United States); and others

    2015-06-20

    We present the selection algorithm and anticipated results for the Time Domain Spectroscopic Survey (TDSS). TDSS is an Sloan Digital Sky Survey (SDSS)-IV Extended Baryon Oscillation Spectroscopic Survey (eBOSS) subproject that will provide initial identification spectra of approximately 220,000 luminosity-variable objects (variable stars and active galactic nuclei across 7500 deg{sup 2} selected from a combination of SDSS and multi-epoch Pan-STARRS1 photometry. TDSS will be the largest spectroscopic survey to explicitly target variable objects, avoiding pre-selection on the basis of colors or detailed modeling of specific variability characteristics. Kernel Density Estimate analysis of our target population performed on SDSS Stripe 82 data suggests our target sample will be 95% pure (meaning 95% of objects we select have genuine luminosity variability of a few magnitudes or more). Our final spectroscopic sample will contain roughly 135,000 quasars and 85,000 stellar variables, approximately 4000 of which will be RR Lyrae stars which may be used as outer Milky Way probes. The variability-selected quasar population has a smoother redshift distribution than a color-selected sample, and variability measurements similar to those we develop here may be used to make more uniform quasar samples in large surveys. The stellar variable targets are distributed fairly uniformly across color space, indicating that TDSS will obtain spectra for a wide variety of stellar variables including pulsating variables, stars with significant chromospheric activity, cataclysmic variables, and eclipsing binaries. TDSS will serve as a pathfinder mission to identify and characterize the multitude of variable objects that will be detected photometrically in even larger variability surveys such as Large Synoptic Survey Telescope.

  12. Comparison of selected variables of gaming performance in football

    OpenAIRE

    Parachin, Jiří

    2014-01-01

    Title: Comparison of selected variables of gaming performance in football Objectives: Analysis of selected variables of gaming performance in the matches of professional Czech football teams in the Champions League and UEFA Europa League in 2013. During the observation to register set variables, then evaluate obtained results and compare them. Methods: The use of observational analysis and comparison of selected variables of gaming performance in competitive matches of professional football. ...

  13. Fuzzy target selection using RFM variables

    NARCIS (Netherlands)

    Kaymak, U.

    2001-01-01

    An important data mining problem from the world of direct marketing is target selection. The main task in target selection is the determination of potential customers for a product from a client database. Target selection algorithms identify the profiles of customer groups for a particular product,

  14. 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.

  15. Variable selection in near-infrared spectroscopy: Benchmarking of feature selection methods on biodiesel data

    International Nuclear Information System (INIS)

    Balabin, Roman M.; Smirnov, Sergey V.

    2011-01-01

    During the past several years, near-infrared (near-IR/NIR) spectroscopy has increasingly been adopted as an analytical tool in various fields from petroleum to biomedical sectors. The NIR spectrum (above 4000 cm -1 ) of a sample is typically measured by modern instruments at a few hundred of wavelengths. Recently, considerable effort has been directed towards developing procedures to identify variables (wavelengths) that contribute useful information. Variable selection (VS) or feature selection, also called frequency selection or wavelength selection, is a critical step in data analysis for vibrational spectroscopy (infrared, Raman, or NIRS). In this paper, we compare the performance of 16 different feature selection methods for the prediction of properties of biodiesel fuel, including density, viscosity, methanol content, and water concentration. The feature selection algorithms tested include stepwise multiple linear regression (MLR-step), interval partial least squares regression (iPLS), backward iPLS (BiPLS), forward iPLS (FiPLS), moving window partial least squares regression (MWPLS), (modified) changeable size moving window partial least squares (CSMWPLS/MCSMWPLSR), searching combination moving window partial least squares (SCMWPLS), successive projections algorithm (SPA), uninformative variable elimination (UVE, including UVE-SPA), simulated annealing (SA), back-propagation artificial neural networks (BP-ANN), Kohonen artificial neural network (K-ANN), and genetic algorithms (GAs, including GA-iPLS). Two linear techniques for calibration model building, namely multiple linear regression (MLR) and partial least squares regression/projection to latent structures (PLS/PLSR), are used for the evaluation of biofuel properties. A comparison with a non-linear calibration model, artificial neural networks (ANN-MLP), is also provided. Discussion of gasoline, ethanol-gasoline (bioethanol), and diesel fuel data is presented. The results of other spectroscopic

  16. How to include the variability of TMS responses in simulations: a speech mapping case study

    Science.gov (United States)

    De Geeter, N.; Lioumis, P.; Laakso, A.; Crevecoeur, G.; Dupré, L.

    2016-11-01

    When delivered over a specific cortical site, TMS can temporarily disrupt the ongoing process in that area. This allows mapping of speech-related areas for preoperative evaluation purposes. We numerically explore the observed variability of TMS responses during a speech mapping experiment performed with a neuronavigation system. We selected four cases with very small perturbations in coil position and orientation. In one case (E) a naming error occurred, while in the other cases (NEA, B, C) the subject appointed the images as smoothly as without TMS. A realistic anisotropic head model was constructed of the subject from T1-weighted and diffusion-weighted MRI. The induced electric field distributions were computed, associated to the coil parameters retrieved from the neuronavigation system. Finally, the membrane potentials along relevant white matter fibre tracts, extracted from DTI-based tractography, were computed using a compartmental cable equation. While only minor differences could be noticed between the induced electric field distributions of the four cases, computing the corresponding membrane potentials revealed different subsets of tracts were activated. A single tract was activated for all coil positions. Another tract was only triggered for case E. NEA induced action potentials in 13 tracts, while NEB stimulated 11 tracts and NEC one. The calculated results are certainly sensitive to the coil specifications, demonstrating the observed variability in this study. However, even though a tract connecting Broca’s with Wernicke’s area is only triggered for the error case, further research is needed on other study cases and on refining the neural model with synapses and network connections. Case- and subject-specific modelling that includes both electromagnetic fields and neuronal activity enables demonstration of the variability in TMS experiments and can capture the interaction with complex neural networks.

  17. Selection Component Analysis of Natural Polymorphisms using Population Samples Including Mother-Offspring Combinations, II

    DEFF Research Database (Denmark)

    Jarmer, Hanne Østergaard; Christiansen, Freddy Bugge

    1981-01-01

    Population samples including mother-offspring combinations provide information on the selection components: zygotic selection, sexual selection, gametic seletion and fecundity selection, on the mating pattern, and on the deviation from linkage equilibrium among the loci studied. The theory...

  18. Bayesian Group Bridge for Bi-level Variable Selection.

    Science.gov (United States)

    Mallick, Himel; Yi, Nengjun

    2017-06-01

    A Bayesian bi-level variable selection method (BAGB: Bayesian Analysis of Group Bridge) is developed for regularized regression and classification. This new development is motivated by grouped data, where generic variables can be divided into multiple groups, with variables in the same group being mechanistically related or statistically correlated. As an alternative to frequentist group variable selection methods, BAGB incorporates structural information among predictors through a group-wise shrinkage prior. Posterior computation proceeds via an efficient MCMC algorithm. In addition to the usual ease-of-interpretation of hierarchical linear models, the Bayesian formulation produces valid standard errors, a feature that is notably absent in the frequentist framework. Empirical evidence of the attractiveness of the method is illustrated by extensive Monte Carlo simulations and real data analysis. Finally, several extensions of this new approach are presented, providing a unified framework for bi-level variable selection in general models with flexible penalties.

  19. Using variable combination population analysis for variable selection in multivariate calibration.

    Science.gov (United States)

    Yun, Yong-Huan; Wang, Wei-Ting; Deng, Bai-Chuan; Lai, Guang-Bi; Liu, Xin-bo; Ren, Da-Bing; Liang, Yi-Zeng; Fan, Wei; Xu, Qing-Song

    2015-03-03

    Variable (wavelength or feature) selection techniques have become a critical step for the analysis of datasets with high number of variables and relatively few samples. In this study, a novel variable selection strategy, variable combination population analysis (VCPA), was proposed. This strategy consists of two crucial procedures. First, the exponentially decreasing function (EDF), which is the simple and effective principle of 'survival of the fittest' from Darwin's natural evolution theory, is employed to determine the number of variables to keep and continuously shrink the variable space. Second, in each EDF run, binary matrix sampling (BMS) strategy that gives each variable the same chance to be selected and generates different variable combinations, is used to produce a population of subsets to construct a population of sub-models. Then, model population analysis (MPA) is employed to find the variable subsets with the lower root mean squares error of cross validation (RMSECV). The frequency of each variable appearing in the best 10% sub-models is computed. The higher the frequency is, the more important the variable is. The performance of the proposed procedure was investigated using three real NIR datasets. The results indicate that VCPA is a good variable selection strategy when compared with four high performing variable selection methods: genetic algorithm-partial least squares (GA-PLS), Monte Carlo uninformative variable elimination by PLS (MC-UVE-PLS), competitive adaptive reweighted sampling (CARS) and iteratively retains informative variables (IRIV). The MATLAB source code of VCPA is available for academic research on the website: http://www.mathworks.com/matlabcentral/fileexchange/authors/498750. Copyright © 2015 Elsevier B.V. All rights reserved.

  20. Ensembling Variable Selectors by Stability Selection for the Cox Model

    Directory of Open Access Journals (Sweden)

    Qing-Yan Yin

    2017-01-01

    Full Text Available As a pivotal tool to build interpretive models, variable selection plays an increasingly important role in high-dimensional data analysis. In recent years, variable selection ensembles (VSEs have gained much interest due to their many advantages. Stability selection (Meinshausen and Bühlmann, 2010, a VSE technique based on subsampling in combination with a base algorithm like lasso, is an effective method to control false discovery rate (FDR and to improve selection accuracy in linear regression models. By adopting lasso as a base learner, we attempt to extend stability selection to handle variable selection problems in a Cox model. According to our experience, it is crucial to set the regularization region Λ in lasso and the parameter λmin properly so that stability selection can work well. To the best of our knowledge, however, there is no literature addressing this problem in an explicit way. Therefore, we first provide a detailed procedure to specify Λ and λmin. Then, some simulated and real-world data with various censoring rates are used to examine how well stability selection performs. It is also compared with several other variable selection approaches. Experimental results demonstrate that it achieves better or competitive performance in comparison with several other popular techniques.

  1. A numeric comparison of variable selection algorithms for supervised learning

    International Nuclear Information System (INIS)

    Palombo, G.; Narsky, I.

    2009-01-01

    Datasets in modern High Energy Physics (HEP) experiments are often described by dozens or even hundreds of input variables. Reducing a full variable set to a subset that most completely represents information about data is therefore an important task in analysis of HEP data. We compare various variable selection algorithms for supervised learning using several datasets such as, for instance, imaging gamma-ray Cherenkov telescope (MAGIC) data found at the UCI repository. We use classifiers and variable selection methods implemented in the statistical package StatPatternRecognition (SPR), a free open-source C++ package developed in the HEP community ( (http://sourceforge.net/projects/statpatrec/)). For each dataset, we select a powerful classifier and estimate its learning accuracy on variable subsets obtained by various selection algorithms. When possible, we also estimate the CPU time needed for the variable subset selection. The results of this analysis are compared with those published previously for these datasets using other statistical packages such as R and Weka. We show that the most accurate, yet slowest, method is a wrapper algorithm known as generalized sequential forward selection ('Add N Remove R') implemented in SPR.

  2. A Variable-Selection Heuristic for K-Means Clustering.

    Science.gov (United States)

    Brusco, Michael J.; Cradit, J. Dennis

    2001-01-01

    Presents a variable selection heuristic for nonhierarchical (K-means) cluster analysis based on the adjusted Rand index for measuring cluster recovery. Subjected the heuristic to Monte Carlo testing across more than 2,200 datasets. Results indicate that the heuristic is extremely effective at eliminating masking variables. (SLD)

  3. 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

  4. Impact of including surface currents on simulation of Indian Ocean variability with the POAMA coupled model

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Mei; Wang, Guomin; Hendon, Harry H.; Alves, Oscar [Bureau of Meteorology, Centre for Australian Weather and Climate Research, Melbourne (Australia)

    2011-04-15

    Impacts on the coupled variability of the Indo-Pacific by including the effects of surface currents on surface stress are explored in four extended integrations of an experimental version of the Bureau of Meteorology's coupled seasonal forecast model POAMA. The first pair of simulations differs only in their treatment of momentum coupling: one version includes the effects of surface currents on the surface stress computation and the other does not. The version that includes the effect of surface currents has less mean-state bias in the equatorial Pacific cold tongue but produces relatively weak coupled variability in the Tropics, especially that related to the Indian Ocean dipole (IOD) and El Nino/Southern Oscillation (ENSO). The version without the effects of surface currents has greater bias in the Pacific cold tongue but stronger IOD and ENSO variability. In order to diagnose the role of changes in local coupling from changes in remote forcing by ENSO for causing changes in IOD variability, a second set of simulations is conducted where effects of surface currents are included only in the Indian Ocean and only in the Pacific Ocean. IOD variability is found to be equally reduced by inclusion of the local effects of surface currents in the Indian Ocean and by the reduction of ENSO variability as a result of including effects of surface currents in the Pacific. Some implications of these results for predictability of the IOD and its dependence on ENSO, and for ocean subsurface data assimilation are discussed. (orig.)

  5. Variable selection and estimation for longitudinal survey data

    KAUST Repository

    Wang, Li

    2014-09-01

    There is wide interest in studying longitudinal surveys where sample subjects are observed successively over time. Longitudinal surveys have been used in many areas today, for example, in the health and social sciences, to explore relationships or to identify significant variables in regression settings. This paper develops a general strategy for the model selection problem in longitudinal sample surveys. A survey weighted penalized estimating equation approach is proposed to select significant variables and estimate the coefficients simultaneously. The proposed estimators are design consistent and perform as well as the oracle procedure when the correct submodel was known. The estimating function bootstrap is applied to obtain the standard errors of the estimated parameters with good accuracy. A fast and efficient variable selection algorithm is developed to identify significant variables for complex longitudinal survey data. Simulated examples are illustrated to show the usefulness of the proposed methodology under various model settings and sampling designs. © 2014 Elsevier Inc.

  6. Variable selection for mixture and promotion time cure rate models.

    Science.gov (United States)

    Masud, Abdullah; Tu, Wanzhu; Yu, Zhangsheng

    2016-11-16

    Failure-time data with cured patients are common in clinical studies. Data from these studies are typically analyzed with cure rate models. Variable selection methods have not been well developed for cure rate models. In this research, we propose two least absolute shrinkage and selection operators based methods, for variable selection in mixture and promotion time cure models with parametric or nonparametric baseline hazards. We conduct an extensive simulation study to assess the operating characteristics of the proposed methods. We illustrate the use of the methods using data from a study of childhood wheezing. © The Author(s) 2016.

  7. A novel variable selection approach that iteratively optimizes variable space using weighted binary matrix sampling.

    Science.gov (United States)

    Deng, Bai-chuan; Yun, Yong-huan; Liang, Yi-zeng; Yi, Lun-zhao

    2014-10-07

    In this study, a new optimization algorithm called the Variable Iterative Space Shrinkage Approach (VISSA) that is based on the idea of model population analysis (MPA) is proposed for variable selection. Unlike most of the existing optimization methods for variable selection, VISSA statistically evaluates the performance of variable space in each step of optimization. Weighted binary matrix sampling (WBMS) is proposed to generate sub-models that span the variable subspace. Two rules are highlighted during the optimization procedure. First, the variable space shrinks in each step. Second, the new variable space outperforms the previous one. The second rule, which is rarely satisfied in most of the existing methods, is the core of the VISSA strategy. Compared with some promising variable selection methods such as competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variable elimination (MCUVE) and iteratively retaining informative variables (IRIV), VISSA showed better prediction ability for the calibration of NIR data. In addition, VISSA is user-friendly; only a few insensitive parameters are needed, and the program terminates automatically without any additional conditions. The Matlab codes for implementing VISSA are freely available on the website: https://sourceforge.net/projects/multivariateanalysis/files/VISSA/.

  8. Variable selection and model choice in geoadditive regression models.

    Science.gov (United States)

    Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard

    2009-06-01

    Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.

  9. The Properties of Model Selection when Retaining Theory Variables

    DEFF Research Database (Denmark)

    Hendry, David F.; Johansen, Søren

    Economic theories are often fitted directly to data to avoid possible model selection biases. We show that embedding a theory model that specifies the correct set of m relevant exogenous variables, x{t}, within the larger set of m+k candidate variables, (x{t},w{t}), then selection over the second...... set by their statistical significance can be undertaken without affecting the estimator distribution of the theory parameters. This strategy returns the theory-parameter estimates when the theory is correct, yet protects against the theory being under-specified because some w{t} are relevant....

  10. Exhaustive Search for Sparse Variable Selection in Linear Regression

    Science.gov (United States)

    Igarashi, Yasuhiko; Takenaka, Hikaru; Nakanishi-Ohno, Yoshinori; Uemura, Makoto; Ikeda, Shiro; Okada, Masato

    2018-04-01

    We propose a K-sparse exhaustive search (ES-K) method and a K-sparse approximate exhaustive search method (AES-K) for selecting variables in linear regression. With these methods, K-sparse combinations of variables are tested exhaustively assuming that the optimal combination of explanatory variables is K-sparse. By collecting the results of exhaustively computing ES-K, various approximate methods for selecting sparse variables can be summarized as density of states. With this density of states, we can compare different methods for selecting sparse variables such as relaxation and sampling. For large problems where the combinatorial explosion of explanatory variables is crucial, the AES-K method enables density of states to be effectively reconstructed by using the replica-exchange Monte Carlo method and the multiple histogram method. Applying the ES-K and AES-K methods to type Ia supernova data, we confirmed the conventional understanding in astronomy when an appropriate K is given beforehand. However, we found the difficulty to determine K from the data. Using virtual measurement and analysis, we argue that this is caused by data shortage.

  11. Variable selection in multivariate calibration based on clustering of variable concept.

    Science.gov (United States)

    Farrokhnia, Maryam; Karimi, Sadegh

    2016-01-01

    Recently we have proposed a new variable selection algorithm, based on clustering of variable concept (CLoVA) in classification problem. With the same idea, this new concept has been applied to a regression problem and then the obtained results have been compared with conventional variable selection strategies for PLS. The basic idea behind the clustering of variable is that, the instrument channels are clustered into different clusters via clustering algorithms. Then, the spectral data of each cluster are subjected to PLS regression. Different real data sets (Cargill corn, Biscuit dough, ACE QSAR, Soy, and Tablet) have been used to evaluate the influence of the clustering of variables on the prediction performances of PLS. Almost in the all cases, the statistical parameter especially in prediction error shows the superiority of CLoVA-PLS respect to other variable selection strategies. Finally the synergy clustering of variable (sCLoVA-PLS), which is used the combination of cluster, has been proposed as an efficient and modification of CLoVA algorithm. The obtained statistical parameter indicates that variable clustering can split useful part from redundant ones, and then based on informative cluster; stable model can be reached. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. Taylor Series Trajectory Calculations Including Oblateness Effects and Variable Atmospheric Density

    Science.gov (United States)

    Scott, James R.

    2011-01-01

    Taylor series integration is implemented in NASA Glenn's Spacecraft N-body Analysis Program, and compared head-to-head with the code's existing 8th- order Runge-Kutta Fehlberg time integration scheme. This paper focuses on trajectory problems that include oblateness and/or variable atmospheric density. Taylor series is shown to be significantly faster and more accurate for oblateness problems up through a 4x4 field, with speedups ranging from a factor of 2 to 13. For problems with variable atmospheric density, speedups average 24 for atmospheric density alone, and average 1.6 to 8.2 when density and oblateness are combined.

  13. ENSEMBLE VARIABILITY OF NEAR-INFRARED-SELECTED ACTIVE GALACTIC NUCLEI

    International Nuclear Information System (INIS)

    Kouzuma, S.; Yamaoka, H.

    2012-01-01

    We present the properties of the ensemble variability V for nearly 5000 near-infrared active galactic nuclei (AGNs) selected from the catalog of Quasars and Active Galactic Nuclei (13th Edition) and the SDSS-DR7 quasar catalog. From three near-infrared point source catalogs, namely, Two Micron All Sky Survey (2MASS), Deep Near Infrared Survey (DENIS), and UKIDSS/LAS catalogs, we extract 2MASS-DENIS and 2MASS-UKIDSS counterparts for cataloged AGNs by cross-identification between catalogs. We further select variable AGNs based on an optimal criterion for selecting the variable sources. The sample objects are divided into subsets according to whether near-infrared light originates by optical emission or by near-infrared emission in the rest frame; and we examine the correlations of the ensemble variability with the rest-frame wavelength, redshift, luminosity, and rest-frame time lag. In addition, we also examine the correlations of variability amplitude with optical variability, radio intensity, and radio-to-optical flux ratio. The rest-frame optical variability of our samples shows negative correlations with luminosity and positive correlations with rest-frame time lag (i.e., the structure function, SF), and this result is consistent with previous analyses. However, no well-known negative correlation exists between the rest-frame wavelength and optical variability. This inconsistency might be due to a biased sampling of high-redshift AGNs. Near-infrared variability in the rest frame is anticorrelated with the rest-frame wavelength, which is consistent with previous suggestions. However, correlations of near-infrared variability with luminosity and rest-frame time lag are the opposite of these correlations of the optical variability; that is, the near-infrared variability is positively correlated with luminosity but negatively correlated with the rest-frame time lag. Because these trends are qualitatively consistent with the properties of radio-loud quasars reported

  14. A Case for Including Atmospheric Thermodynamic Variables in Wind Turbine Fatigue Loading Parameter Identification

    International Nuclear Information System (INIS)

    Kelley, Neil D.

    1999-01-01

    This paper makes the case for establishing efficient predictor variables for atmospheric thermodynamics that can be used to statistically correlate the fatigue accumulation seen on wind turbines. Recently, two approaches to this issue have been reported. One uses multiple linear-regression analysis to establish the relative causality between a number of predictors related to the turbulent inflow and turbine loads. The other approach, using many of the same predictors, applies the technique of principal component analysis. An examination of the ensemble of predictor variables revealed that they were all kinematic in nature; i.e., they were only related to the description of the velocity field. Boundary-layer turbulence dynamics depends upon a description of the thermal field and its interaction with the velocity distribution. We used a series of measurements taken within a multi-row wind farm to demonstrate the need to include atmospheric thermodynamic variables as well as velocity-related ones in the search for efficient turbulence loading predictors in various turbine-operating environments. Our results show that a combination of vertical stability and hub-height mean shearing stress variables meet this need over a period of 10 minutes

  15. CHARACTERIZING THE OPTICAL VARIABILITY OF BRIGHT BLAZARS: VARIABILITY-BASED SELECTION OF FERMI ACTIVE GALACTIC NUCLEI

    International Nuclear Information System (INIS)

    Ruan, John J.; Anderson, Scott F.; MacLeod, Chelsea L.; Becker, Andrew C.; Davenport, James R. A.; Ivezić, Željko; Burnett, T. H.; Kochanek, Christopher S.; Plotkin, Richard M.; Sesar, Branimir; Stuart, J. Scott

    2012-01-01

    We investigate the use of optical photometric variability to select and identify blazars in large-scale time-domain surveys, in part to aid in the identification of blazar counterparts to the ∼30% of γ-ray sources in the Fermi 2FGL catalog still lacking reliable associations. Using data from the optical LINEAR asteroid survey, we characterize the optical variability of blazars by fitting a damped random walk model to individual light curves with two main model parameters, the characteristic timescales of variability τ, and driving amplitudes on short timescales σ-circumflex. Imposing cuts on minimum τ and σ-circumflex allows for blazar selection with high efficiency E and completeness C. To test the efficacy of this approach, we apply this method to optically variable LINEAR objects that fall within the several-arcminute error ellipses of γ-ray sources in the Fermi 2FGL catalog. Despite the extreme stellar contamination at the shallow depth of the LINEAR survey, we are able to recover previously associated optical counterparts to Fermi active galactic nuclei with E ≥ 88% and C = 88% in Fermi 95% confidence error ellipses having semimajor axis r < 8'. We find that the suggested radio counterpart to Fermi source 2FGL J1649.6+5238 has optical variability consistent with other γ-ray blazars and is likely to be the γ-ray source. Our results suggest that the variability of the non-thermal jet emission in blazars is stochastic in nature, with unique variability properties due to the effects of relativistic beaming. After correcting for beaming, we estimate that the characteristic timescale of blazar variability is ∼3 years in the rest frame of the jet, in contrast with the ∼320 day disk flux timescale observed in quasars. The variability-based selection method presented will be useful for blazar identification in time-domain optical surveys and is also a probe of jet physics.

  16. Portfolio Selection Based on Distance between Fuzzy Variables

    Directory of Open Access Journals (Sweden)

    Weiyi Qian

    2014-01-01

    Full Text Available This paper researches portfolio selection problem in fuzzy environment. We introduce a new simple method in which the distance between fuzzy variables is used to measure the divergence of fuzzy investment return from a prior one. Firstly, two new mathematical models are proposed by expressing divergence as distance, investment return as expected value, and risk as variance and semivariance, respectively. Secondly, the crisp forms of the new models are also provided for different types of fuzzy variables. Finally, several numerical examples are given to illustrate the effectiveness of the proposed approach.

  17. Protein construct storage: Bayesian variable selection and prediction with mixtures.

    Science.gov (United States)

    Clyde, M A; Parmigiani, G

    1998-07-01

    Determining optimal conditions for protein storage while maintaining a high level of protein activity is an important question in pharmaceutical research. A designed experiment based on a space-filling design was conducted to understand the effects of factors affecting protein storage and to establish optimal storage conditions. Different model-selection strategies to identify important factors may lead to very different answers about optimal conditions. Uncertainty about which factors are important, or model uncertainty, can be a critical issue in decision-making. We use Bayesian variable selection methods for linear models to identify important variables in the protein storage data, while accounting for model uncertainty. We also use the Bayesian framework to build predictions based on a large family of models, rather than an individual model, and to evaluate the probability that certain candidate storage conditions are optimal.

  18. Mahalanobis distance and variable selection to optimize dose response

    International Nuclear Information System (INIS)

    Moore, D.H. II; Bennett, D.E.; Wyrobek, A.J.; Kranzler, D.

    1979-01-01

    A battery of statistical techniques are combined to improve detection of low-level dose response. First, Mahalanobis distances are used to classify objects as normal or abnormal. Then the proportion classified abnormal is regressed on dose. Finally, a subset of regressor variables is selected which maximizes the slope of the dose response line. Use of the techniques is illustrated by application to mouse sperm damaged by low doses of x-rays

  19. Direct-phase-variable model of a synchronous reluctance motor including all slot and winding harmonics

    International Nuclear Information System (INIS)

    Obe, Emeka S.; Binder, A.

    2011-01-01

    A detailed model in direct-phase variables of a synchronous reluctance motor operating at mains voltage and frequency is presented. The model includes the stator and rotor slot openings, the actual winding layout and the reluctance rotor geometry. Hence, all mmf and permeance harmonics are taken into account. It is seen that non-negligible harmonics introduced by slots are present in the inductances computed by the winding function procedure. These harmonics are usually ignored in d-q models. The machine performance is simulated in the stator reference frame to depict the difference between this new direct-phase model including all harmonics and the conventional rotor reference frame d-q model. Saturation is included by using a polynomial fitting the variation of d-axis inductance with stator current obtained by finite-element software FEMAG DC (registered) . The detailed phase-variable model can yield torque pulsations comparable to those obtained from finite elements while the d-q model cannot.

  20. STEPWISE SELECTION OF VARIABLES IN DEA USING CONTRIBUTION LOADS

    Directory of Open Access Journals (Sweden)

    Fernando Fernandez-Palacin

    Full Text Available ABSTRACT In this paper, we propose a new methodology for variable selection in Data Envelopment Analysis (DEA. The methodology is based on an internal measure which evaluates the contribution of each variable in the calculation of the efficiency scores of DMUs. In order to apply the proposed method, an algorithm, known as “ADEA”, was developed and implemented in R. Step by step, the algorithm maximizes the load of the variable (input or output which contribute least to the calculation of the efficiency scores, redistributing the weights of the variables without altering the efficiency scores of the DMUs. Once the weights have been redistributed, if the lower contribution does not reach a previously given critical value, a variable with minimum contribution will be removed from the model and, as a result, the DEA will be solved again. The algorithm will stop when all variables reach a given contribution load to the DEA or until no more variables can be removed. In this way and contrary to what is usual, the algorithm provides a clear stop rule. In both cases, the efficiencies obtained from the DEA will be considered suitable and rightly interpreted in terms of the remaining variables, indicating the load themselves; moreover, the algorithm will provide a sequence of alternative nested models - potential solutions - that could be evaluated according to external criterion. To illustrate the procedure, we have applied the methodology proposed to obtain a research ranking of Spanish public universities. In this case, at each step of the algorithm, the critical value is obtained based on a simulation study.

  1. Variability-based active galactic nucleus selection using image subtraction in the SDSS and LSST era

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Yumi; Gibson, Robert R.; Becker, Andrew C.; Ivezić, Željko; Connolly, Andrew J.; Ruan, John J.; Anderson, Scott F. [Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195 (United States); MacLeod, Chelsea L., E-mail: ymchoi@astro.washington.edu [Physics Department, U.S. Naval Academy, 572 Holloway Road, Annapolis, MD 21402 (United States)

    2014-02-10

    With upcoming all-sky surveys such as LSST poised to generate a deep digital movie of the optical sky, variability-based active galactic nucleus (AGN) selection will enable the construction of highly complete catalogs with minimum contamination. In this study, we generate g-band difference images and construct light curves (LCs) for QSO/AGN candidates listed in Sloan Digital Sky Survey Stripe 82 public catalogs compiled from different methods, including spectroscopy, optical colors, variability, and X-ray detection. Image differencing excels at identifying variable sources embedded in complex or blended emission regions such as Type II AGNs and other low-luminosity AGNs that may be omitted from traditional photometric or spectroscopic catalogs. To separate QSOs/AGNs from other sources using our difference image LCs, we explore several LC statistics and parameterize optical variability by the characteristic damping timescale (τ) and variability amplitude. By virtue of distinguishable variability parameters of AGNs, we are able to select them with high completeness of 93.4% and efficiency (i.e., purity) of 71.3%. Based on optical variability, we also select highly variable blazar candidates, whose infrared colors are consistent with known blazars. One-third of them are also radio detected. With the X-ray selected AGN candidates, we probe the optical variability of X-ray detected optically extended sources using their difference image LCs for the first time. A combination of optical variability and X-ray detection enables us to select various types of host-dominated AGNs. Contrary to the AGN unification model prediction, two Type II AGN candidates (out of six) show detectable variability on long-term timescales like typical Type I AGNs. This study will provide a baseline for future optical variability studies of extended sources.

  2. Two-step variable selection in quantile regression models

    Directory of Open Access Journals (Sweden)

    FAN Yali

    2015-06-01

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

  3. Bayesian Multiresolution Variable Selection for Ultra-High Dimensional Neuroimaging Data.

    Science.gov (United States)

    Zhao, Yize; Kang, Jian; Long, Qi

    2018-01-01

    Ultra-high dimensional variable selection has become increasingly important in analysis of neuroimaging data. For example, in the Autism Brain Imaging Data Exchange (ABIDE) study, neuroscientists are interested in identifying important biomarkers for early detection of the autism spectrum disorder (ASD) using high resolution brain images that include hundreds of thousands voxels. However, most existing methods are not feasible for solving this problem due to their extensive computational costs. In this work, we propose a novel multiresolution variable selection procedure under a Bayesian probit regression framework. It recursively uses posterior samples for coarser-scale variable selection to guide the posterior inference on finer-scale variable selection, leading to very efficient Markov chain Monte Carlo (MCMC) algorithms. The proposed algorithms are computationally feasible for ultra-high dimensional data. Also, our model incorporates two levels of structural information into variable selection using Ising priors: the spatial dependence between voxels and the functional connectivity between anatomical brain regions. Applied to the resting state functional magnetic resonance imaging (R-fMRI) data in the ABIDE study, our methods identify voxel-level imaging biomarkers highly predictive of the ASD, which are biologically meaningful and interpretable. Extensive simulations also show that our methods achieve better performance in variable selection compared to existing methods.

  4. Characterizing the Optical Variability of Bright Blazars: Variability-based Selection of Fermi Active Galactic Nuclei

    Science.gov (United States)

    Ruan, John J.; Anderson, Scott F.; MacLeod, Chelsea L.; Becker, Andrew C.; Burnett, T. H.; Davenport, James R. A.; Ivezić, Željko; Kochanek, Christopher S.; Plotkin, Richard M.; Sesar, Branimir; Stuart, J. Scott

    2012-11-01

    We investigate the use of optical photometric variability to select and identify blazars in large-scale time-domain surveys, in part to aid in the identification of blazar counterparts to the ~30% of γ-ray sources in the Fermi 2FGL catalog still lacking reliable associations. Using data from the optical LINEAR asteroid survey, we characterize the optical variability of blazars by fitting a damped random walk model to individual light curves with two main model parameters, the characteristic timescales of variability τ, and driving amplitudes on short timescales \\hat{\\sigma }. Imposing cuts on minimum τ and \\hat{\\sigma } allows for blazar selection with high efficiency E and completeness C. To test the efficacy of this approach, we apply this method to optically variable LINEAR objects that fall within the several-arcminute error ellipses of γ-ray sources in the Fermi 2FGL catalog. Despite the extreme stellar contamination at the shallow depth of the LINEAR survey, we are able to recover previously associated optical counterparts to Fermi active galactic nuclei with E >= 88% and C = 88% in Fermi 95% confidence error ellipses having semimajor axis r beaming. After correcting for beaming, we estimate that the characteristic timescale of blazar variability is ~3 years in the rest frame of the jet, in contrast with the ~320 day disk flux timescale observed in quasars. The variability-based selection method presented will be useful for blazar identification in time-domain optical surveys and is also a probe of jet physics.

  5. A Simple K-Map Based Variable Selection Scheme in the Direct ...

    African Journals Online (AJOL)

    A multiplexer with (n-l) data select inputs can realise directly a function of n variables. In this paper, a simple k-map based variable selection scheme is proposed such that an n variable logic function can be synthesised using a multiplexer with (n-q) data input variables and q data select variables. The procedure is based on ...

  6. Surface Estimation, Variable Selection, and the Nonparametric Oracle Property.

    Science.gov (United States)

    Storlie, Curtis B; Bondell, Howard D; Reich, Brian J; Zhang, Hao Helen

    2011-04-01

    Variable selection for multivariate nonparametric regression is an important, yet challenging, problem due, in part, to the infinite dimensionality of the function space. An ideal selection procedure should be automatic, stable, easy to use, and have desirable asymptotic properties. In particular, we define a selection procedure to be nonparametric oracle (np-oracle) if it consistently selects the correct subset of predictors and at the same time estimates the smooth surface at the optimal nonparametric rate, as the sample size goes to infinity. In this paper, we propose a model selection procedure for nonparametric models, and explore the conditions under which the new method enjoys the aforementioned properties. Developed in the framework of smoothing spline ANOVA, our estimator is obtained via solving a regularization problem with a novel adaptive penalty on the sum of functional component norms. Theoretical properties of the new estimator are established. Additionally, numerous simulated and real examples further demonstrate that the new approach substantially outperforms other existing methods in the finite sample setting.

  7. Isoenzymatic variability in tropical maize populations under reciprocal recurrent selection

    Directory of Open Access Journals (Sweden)

    Pinto Luciana Rossini

    2003-01-01

    Full Text Available Maize (Zea mays L. is one of the crops in which the genetic variability has been extensively studied at isoenzymatic loci. The genetic variability of the maize populations BR-105 and BR-106, and the synthetics IG-3 and IG-4, obtained after one cycle of a high-intensity reciprocal recurrent selection (RRS, was investigated at seven isoenzymatic loci. A total of twenty alleles were identified, and most of the private alleles were found in the BR-106 population. One cycle of reciprocal recurrent selection (RRS caused reductions of 12% in the number of alleles in both populations. Changes in allele frequencies were also observed between populations and synthetics, mainly for the Est 2 locus. Populations presented similar values for the number of alleles per locus, percentage of polymorphic loci, and observed and expected heterozygosities. A decrease of the genetic variation values was observed for the synthetics as a consequence of genetic drift effects and reduction of the effective population sizes. The distribution of the genetic diversity within and between populations revealed that most of the diversity was maintained within them, i.e. BR-105 x BR-106 (G ST = 3.5% and IG-3 x IG-4 (G ST = 4.0%. The genetic distances between populations and synthetics increased approximately 21%. An increase in the genetic divergence between the populations occurred without limiting new selection procedures.

  8. How novice, skilled and advanced clinical researchers include variables in a case report form for clinical research: a qualitative study.

    Science.gov (United States)

    Chu, Hongling; Zeng, Lin; Fetters, Micheal D; Li, Nan; Tao, Liyuan; Shi, Yanyan; Zhang, Hua; Wang, Xiaoxiao; Li, Fengwei; Zhao, Yiming

    2017-09-18

    Despite varying degrees in research training, most academic clinicians are expected to conduct clinical research. The objective of this research was to understand how clinical researchers of different skill levels include variables in a case report form for their clinical research. The setting for this research was a major academic institution in Beijing, China. The target population was clinical researchers with three levels of experience, namely, limited clinical research experience, clinicians with rich clinical research experience and clinical research experts. Using a qualitative approach, we conducted 13 individual interviews (face to face) and one group interview (n=4) with clinical researchers from June to September 2016. Based on maximum variation sampling to identify researchers with three levels of research experience: eight clinicians with limited clinical research experience, five clinicians with rich clinical research experience and four clinical research experts. These 17 researchers had diverse hospital-based medical specialties and or specialisation in clinical research. Our analysis yields a typology of three processes developing a case report form that varies according to research experience level. Novice clinician researchers often have an incomplete protocol or none at all, and conduct data collection and publication based on a general framework. Experienced clinician researchers include variables in the case report form based on previous experience with attention to including domains or items at risk for omission and by eliminating unnecessary variables. Expert researchers consider comprehensively in advance data collection and implementation needs and plan accordingly. These results illustrate increasing levels of sophistication in research planning that increase sophistication in selection for variables in the case report form. These findings suggest that novice and intermediate-level researchers could benefit by emulating the comprehensive

  9. Chaotic Dynamical State Variables Selection Procedure Based Image Encryption Scheme

    Directory of Open Access Journals (Sweden)

    Zia Bashir

    2017-12-01

    Full Text Available Nowadays, in the modern digital era, the use of computer technologies such as smartphones, tablets and the Internet, as well as the enormous quantity of confidential information being converted into digital form have resulted in raised security issues. This, in turn, has led to rapid developments in cryptography, due to the imminent need for system security. Low-dimensional chaotic systems have low complexity and key space, yet they achieve high encryption speed. An image encryption scheme is proposed that, without compromising the security, uses reasonable resources. We introduced a chaotic dynamic state variables selection procedure (CDSVSP to use all state variables of a hyper-chaotic four-dimensional dynamical system. As a result, less iterations of the dynamical system are required, and resources are saved, thus making the algorithm fast and suitable for practical use. The simulation results of security and other miscellaneous tests demonstrate that the suggested algorithm excels at robustness, security and high speed encryption.

  10. Estimation and variable selection for generalized additive partial linear models

    KAUST Repository

    Wang, Li

    2011-08-01

    We study generalized additive partial linear models, proposing the use of polynomial spline smoothing for estimation of nonparametric functions, and deriving quasi-likelihood based estimators for the linear parameters. We establish asymptotic normality for the estimators of the parametric components. The procedure avoids solving large systems of equations as in kernel-based procedures and thus results in gains in computational simplicity. We further develop a class of variable selection procedures for the linear parameters by employing a nonconcave penalized quasi-likelihood, which is shown to have an asymptotic oracle property. Monte Carlo simulations and an empirical example are presented for illustration. © Institute of Mathematical Statistics, 2011.

  11. Predictive and Descriptive CoMFA Models: The Effect of Variable Selection.

    Science.gov (United States)

    Sepehri, Bakhtyar; Omidikia, Nematollah; Kompany-Zareh, Mohsen; Ghavami, Raouf

    2018-01-01

    Aims & Scope: In this research, 8 variable selection approaches were used to investigate the effect of variable selection on the predictive power and stability of CoMFA models. Three data sets including 36 EPAC antagonists, 79 CD38 inhibitors and 57 ATAD2 bromodomain inhibitors were modelled by CoMFA. First of all, for all three data sets, CoMFA models with all CoMFA descriptors were created then by applying each variable selection method a new CoMFA model was developed so for each data set, 9 CoMFA models were built. Obtained results show noisy and uninformative variables affect CoMFA results. Based on created models, applying 5 variable selection approaches including FFD, SRD-FFD, IVE-PLS, SRD-UVEPLS and SPA-jackknife increases the predictive power and stability of CoMFA models significantly. Among them, SPA-jackknife removes most of the variables while FFD retains most of them. FFD and IVE-PLS are time consuming process while SRD-FFD and SRD-UVE-PLS run need to few seconds. Also applying FFD, SRD-FFD, IVE-PLS, SRD-UVE-PLS protect CoMFA countor maps information for both fields. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  12. Comparison of climate envelope models developed using expert-selected variables versus statistical selection

    Science.gov (United States)

    Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.

    2017-01-01

    Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in agreement with other studies which have found that for broad-scale species distribution modeling, using statistical methods of variable

  13. Selection for altruism through random drift in variable size populations

    Directory of Open Access Journals (Sweden)

    Houchmandzadeh Bahram

    2012-05-01

    Full Text Available Abstract Background Altruistic behavior is defined as helping others at a cost to oneself and a lowered fitness. The lower fitness implies that altruists should be selected against, which is in contradiction with their widespread presence is nature. Present models of selection for altruism (kin or multilevel show that altruistic behaviors can have ‘hidden’ advantages if the ‘common good’ produced by altruists is restricted to some related or unrelated groups. These models are mostly deterministic, or assume a frequency dependent fitness. Results Evolutionary dynamics is a competition between deterministic selection pressure and stochastic events due to random sampling from one generation to the next. We show here that an altruistic allele extending the carrying capacity of the habitat can win by increasing the random drift of “selfish” alleles. In other terms, the fixation probability of altruistic genes can be higher than those of a selfish ones, even though altruists have a smaller fitness. Moreover when populations are geographically structured, the altruists advantage can be highly amplified and the fixation probability of selfish genes can tend toward zero. The above results are obtained both by numerical and analytical calculations. Analytical results are obtained in the limit of large populations. Conclusions The theory we present does not involve kin or multilevel selection, but is based on the existence of random drift in variable size populations. The model is a generalization of the original Fisher-Wright and Moran models where the carrying capacity depends on the number of altruists.

  14. Input variable selection for data-driven models of Coriolis flowmeters for two-phase flow measurement

    International Nuclear Information System (INIS)

    Wang, Lijuan; Yan, Yong; Wang, Xue; Wang, Tao

    2017-01-01

    Input variable selection is an essential step in the development of data-driven models for environmental, biological and industrial applications. Through input variable selection to eliminate the irrelevant or redundant variables, a suitable subset of variables is identified as the input of a model. Meanwhile, through input variable selection the complexity of the model structure is simplified and the computational efficiency is improved. This paper describes the procedures of the input variable selection for the data-driven models for the measurement of liquid mass flowrate and gas volume fraction under two-phase flow conditions using Coriolis flowmeters. Three advanced input variable selection methods, including partial mutual information (PMI), genetic algorithm-artificial neural network (GA-ANN) and tree-based iterative input selection (IIS) are applied in this study. Typical data-driven models incorporating support vector machine (SVM) are established individually based on the input candidates resulting from the selection methods. The validity of the selection outcomes is assessed through an output performance comparison of the SVM based data-driven models and sensitivity analysis. The validation and analysis results suggest that the input variables selected from the PMI algorithm provide more effective information for the models to measure liquid mass flowrate while the IIS algorithm provides a fewer but more effective variables for the models to predict gas volume fraction. (paper)

  15. Ethnic variability in adiposity and cardiovascular risk: the variable disease selection hypothesis.

    Science.gov (United States)

    Wells, Jonathan C K

    2009-02-01

    Evidence increasingly suggests that ethnic differences in cardiovascular risk are partly mediated by adipose tissue biology, which refers to the regional distribution of adipose tissue and its differential metabolic activity. This paper proposes a novel evolutionary hypothesis for ethnic genetic variability in adipose tissue biology. Whereas medical interest focuses on the harmful effect of excess fat, the value of adipose tissue is greatest during chronic energy insufficiency. Following Neel's influential paper on the thrifty genotype, proposed to have been favoured by exposure to cycles of feast and famine, much effort has been devoted to searching for genetic markers of 'thrifty metabolism'. However, whether famine-induced starvation was the primary selective pressure on adipose tissue biology has been questioned, while the notion that fat primarily represents a buffer against starvation appears inconsistent with historical records of mortality during famines. This paper reviews evidence for the role played by adipose tissue in immune function and proposes that adipose tissue biology responds to selective pressures acting through infectious disease. Different diseases activate the immune system in different ways and induce different metabolic costs. It is hypothesized that exposure to different infectious disease burdens has favoured ethnic genetic variability in the anatomical location of, and metabolic profile of, adipose tissue depots.

  16. Combining epidemiologic and biostatistical tools to enhance variable selection in HIV cohort analyses.

    Directory of Open Access Journals (Sweden)

    Christopher Rentsch

    Full Text Available BACKGROUND: Variable selection is an important step in building a multivariate regression model for which several methods and statistical packages are available. A comprehensive approach for variable selection in complex multivariate regression analyses within HIV cohorts is explored by utilizing both epidemiological and biostatistical procedures. METHODS: Three different methods for variable selection were illustrated in a study comparing survival time between subjects in the Department of Defense's National History Study and the Atlanta Veterans Affairs Medical Center's HIV Atlanta VA Cohort Study. The first two methods were stepwise selection procedures, based either on significance tests (Score test, or on information theory (Akaike Information Criterion, while the third method employed a Bayesian argument (Bayesian Model Averaging. RESULTS: All three methods resulted in a similar parsimonious survival model. Three of the covariates previously used in the multivariate model were not included in the final model suggested by the three approaches. When comparing the parsimonious model to the previously published model, there was evidence of less variance in the main survival estimates. CONCLUSIONS: The variable selection approaches considered in this study allowed building a model based on significance tests, on an information criterion, and on averaging models using their posterior probabilities. A parsimonious model that balanced these three approaches was found to provide a better fit than the previously reported model.

  17. Regional regression models of percentile flows for the contiguous United States: Expert versus data-driven independent variable selection

    Directory of Open Access Journals (Sweden)

    Geoffrey Fouad

    2018-06-01

    New hydrological insights for the region: A set of three variables selected based on an expert assessment of factors that influence percentile flows performed similarly to larger sets of variables selected using a data-driven method. Expert assessment variables included mean annual precipitation, potential evapotranspiration, and baseflow index. Larger sets of up to 37 variables contributed little, if any, additional predictive information. Variables used to describe the distribution of basin data (e.g. standard deviation were not useful, and average values were sufficient to characterize physical and climatic basin conditions. Effectiveness of the expert assessment variables may be due to the high degree of multicollinearity (i.e. cross-correlation among additional variables. A tool is provided in the Supplementary material to predict percentile flows based on the three expert assessment variables. Future work should develop new variables with a strong understanding of the processes related to percentile flows.

  18. Effects of selected design variables on three ramp, external compression inlet performance. [boundary layer control bypasses, and mass flow rate

    Science.gov (United States)

    Kamman, J. H.; Hall, C. L.

    1975-01-01

    Two inlet performance tests and one inlet/airframe drag test were conducted in 1969 at the NASA-Ames Research Center. The basic inlet system was two-dimensional, three ramp (overhead), external compression, with variable capture area. The data from these tests were analyzed to show the effects of selected design variables on the performance of this type of inlet system. The inlet design variables investigated include inlet bleed, bypass, operating mass flow ratio, inlet geometry, and variable capture area.

  19. Simulated selection responses for breeding programs including resistance and resilience to parasites in Creole goats.

    Science.gov (United States)

    Gunia, M; Phocas, F; Gourdine, J-L; Bijma, P; Mandonnet, N

    2013-02-01

    The Creole goat is a local breed used for meat production in Guadeloupe (French West Indies). As in other tropical countries, improvement of parasite resistance is needed. In this study, we compared predicted selection responses for alternative breeding programs with or without parasite resistance and resilience traits. The overall breeding goal included traits for production, reproduction, and parasite resilience and resistance to ensure a balanced selection outcome. The production traits were BW and dressing percentage (DP). The reproduction trait was fertility (FER), which was the number of doe kiddings per mating. The resistance trait was worm fecal egg count (FEC), which is a measurement of the number of gastro-intestinal parasite eggs found in the feces. The resilience trait was the packed cell volume (PCV), which is a measurement of the volume of red blood cells in the blood. Dressing percentage, BW, and FEC were measured at 11 mo of age, which is the mating or selling age. Fertility and PCV were measured on females at each kidding period. The breeding program accounting for the overall breeding goal and a selection index including all traits gave annual selection responses of 800 g for BW, 3.75% for FER, 0.08% for DP, -0.005 ln(eggs/g) for FEC, and 0.28% for PCV. The expected selection responses for BW and DP in this breeding program were reduced by 2% and 6%, respectively, compared with a breeding program not accounting for FEC and PCV. The overall breeding program, proposed for the Creole breed, offers the best breeding strategy in terms of expected selection responses, making it possible to improve all traits together. It offers a good balance between production and adaptation traits and may present some interest for the selection of other goat breeds in the tropics.

  20. Sex-specific selection for MHC variability in Alpine chamois

    Directory of Open Access Journals (Sweden)

    Schaschl Helmut

    2012-02-01

    Full Text Available Abstract Background In mammals, males typically have shorter lives than females. This difference is thought to be due to behavioural traits which enhance competitive abilities, and hence male reproductive success, but impair survival. Furthermore, in many species males usually show higher parasite burden than females. Consequently, the intensity of selection for genetic factors which reduce susceptibility to pathogens may differ between sexes. High variability at the major histocompatibility complex (MHC genes is believed to be advantageous for detecting and combating the range of infectious agents present in the environment. Increased heterozygosity at these immune genes is expected to be important for individual longevity. However, whether males in natural populations benefit more from MHC heterozygosity than females has rarely been investigated. We investigated this question in a long-term study of free-living Alpine chamois (Rupicapra rupicapra, a polygynous mountain ungulate. Results Here we show that male chamois survive significantly (P = 0.022 longer if heterozygous at the MHC class II DRB locus, whereas females do not. Improved survival of males was not a result of heterozygote advantage per se, as background heterozygosity (estimated across twelve microsatellite loci did not change significantly with age. Furthermore, reproductively active males depleted their body fat reserves earlier than females leading to significantly impaired survival rates in this sex (P Conclusions Increased MHC class II DRB heterozygosity with age in males, suggests that MHC heterozygous males survive longer than homozygotes. Reproductively active males appear to be less likely to survive than females most likely because of the energetic challenge of the winter rut, accompanied by earlier depletion of their body fat stores, and a generally higher parasite burden. This scenario renders the MHC-mediated immune response more important for males than for females

  1. Birth order and selected work-related personality variables.

    Science.gov (United States)

    Phillips, A S; Bedeian, A G; Mossholder, K W; Touliatos, J

    1988-12-01

    A possible link between birth order and various individual characteristics (e. g., intelligence, potential eminence, need for achievement, sociability) has been suggested by personality theorists such as Adler for over a century. The present study examines whether birth order is associated with selected personality variables that may be related to various work outcomes. 3 of 7 hypotheses were supported and the effect sizes for these were small. Firstborns scored significantly higher than later borns on measures of dominance, good impression, and achievement via conformity. No differences between firstborns and later borns were found in managerial potential, work orientation, achievement via independence, and sociability. The study's sample consisted of 835 public, government, and industrial accountants responding to a national US survey of accounting professionals. The nature of the sample may have been partially responsible for the results obtained. Its homogeneity may have caused any birth order effects to wash out. It can be argued that successful membership in the accountancy profession requires internalization of a set of prescribed rules and standards. It may be that accountants as a group are locked in to a behavioral framework. Any differentiation would result from spurious interpersonal differences, not from predictable birth-order related characteristics. A final interpretation is that birth order effects are nonexistent or statistical artifacts. Given the present data and particularistic sample, however, the authors have insufficient information from which to draw such a conclusion.

  2. Why Include Impacts on Biodiversity from Land Use in LCIA and How to Select Useful Indicators?

    Directory of Open Access Journals (Sweden)

    Ottar Michelsen

    2015-05-01

    Full Text Available Loss of biodiversity is one of the most severe threats to sustainability, and land use and land use changes are still the single most important factor. Still, there is no sign of any consensus on how to include impacts on biodiversity from land use and land use changes in LCIA. In this paper, different characteristics of biodiversity are discussed and related to proposals on how to include land use and land use changes in LCIA. We identify the question of why we should care about biodiversity as a key question, since different motivations will result in different choices for the indicators, and we call for more openness in the motivation for indicator selection. We find a promising trend in combining pressure indicators with geographic weighting and regard this as a promising way ahead. More knowledge on the consequences of different choices, such as the selection of a reference state, is still needed.

  3. Inlet-engine matching for SCAR including application of a bicone variable geometry inlet

    Science.gov (United States)

    Wasserbauer, J. F.; Gerstenmaier, W. H.

    1978-01-01

    Airflow characteristics of variable cycle engines (VCE) designed for Mach 2.32 can have transonic airflow requirements as high as 1.6 times the cruise airflow. This is a formidable requirement for conventional, high performance, axisymmetric, translating centerbody mixed compression inlets. An alternate inlet is defined, where the second cone of a two cone center body collapses to the initial cone angle to provide a large off-design airflow capability, and incorporates modest centerbody translation to minimize spillage drag. Estimates of transonic spillage drag are competitive with those of conventional translating centerbody inlets. The inlet's cruise performance exhibits very low bleed requirements with good recovery and high angle of attack capability.

  4. Spatial modelling of marine organisms in Forsmark and Oskarshamn. Including calculation of physical predictor variables

    Energy Technology Data Exchange (ETDEWEB)

    Carlen, Ida; Nikolopoulos, Anna; Isaeus, Martin (AquaBiota Water Research, Stockholm (SE))

    2007-06-15

    GIS grids (maps) of marine parameters were created using point data from previous site investigations in the Forsmark and Oskarshamn areas. The proportion of global radiation reaching the sea bottom in Forsmark and Oskarshamn was calculated in ArcView, using Secchi depth measurements and the digital elevation models for the respective area. The number of days per year when the incoming light exceeds 5 MJ/m2 at the bottom was then calculated using the result of the previous calculations together with measured global radiation. Existing modelled grid-point data on bottom and pelagic temperature for Forsmark were interpolated to create surface covering grids. Bottom and pelagic temperature grids for Oskarshamn were calculated using point measurements to achieve yearly averages for a few points and then using regressions with existing grids to create new maps. Phytoplankton primary production in Forsmark was calculated using point measurements of chlorophyll and irradiance, and a regression with a modelled grid of Secchi depth. Distribution of biomass of macrophyte communities in Forsmark and Oskarshamn was calculated using spatial modelling in GRASP, based on field data from previous surveys. Physical parameters such as those described above were used as predictor variables. Distribution of biomass of different functional groups of fish in Forsmark was calculated using spatial modelling based on previous surveys and with predictor variables such as physical parameters and results from macrophyte modelling. All results are presented as maps in the report. The quality of the modelled predictions varies as a consequence of the quality and amount of the input data, the ecology and knowledge of the predicted phenomena, and by the modelling technique used. A substantial part of the variation is not described by the models, which should be expected for biological modelling. Therefore, the resulting grids should be used with caution and with this uncertainty kept in mind. All

  5. Spatial modelling of marine organisms in Forsmark and Oskarshamn. Including calculation of physical predictor variables

    International Nuclear Information System (INIS)

    Carlen, Ida; Nikolopoulos, Anna; Isaeus, Martin

    2007-06-01

    GIS grids (maps) of marine parameters were created using point data from previous site investigations in the Forsmark and Oskarshamn areas. The proportion of global radiation reaching the sea bottom in Forsmark and Oskarshamn was calculated in ArcView, using Secchi depth measurements and the digital elevation models for the respective area. The number of days per year when the incoming light exceeds 5 MJ/m2 at the bottom was then calculated using the result of the previous calculations together with measured global radiation. Existing modelled grid-point data on bottom and pelagic temperature for Forsmark were interpolated to create surface covering grids. Bottom and pelagic temperature grids for Oskarshamn were calculated using point measurements to achieve yearly averages for a few points and then using regressions with existing grids to create new maps. Phytoplankton primary production in Forsmark was calculated using point measurements of chlorophyll and irradiance, and a regression with a modelled grid of Secchi depth. Distribution of biomass of macrophyte communities in Forsmark and Oskarshamn was calculated using spatial modelling in GRASP, based on field data from previous surveys. Physical parameters such as those described above were used as predictor variables. Distribution of biomass of different functional groups of fish in Forsmark was calculated using spatial modelling based on previous surveys and with predictor variables such as physical parameters and results from macrophyte modelling. All results are presented as maps in the report. The quality of the modelled predictions varies as a consequence of the quality and amount of the input data, the ecology and knowledge of the predicted phenomena, and by the modelling technique used. A substantial part of the variation is not described by the models, which should be expected for biological modelling. Therefore, the resulting grids should be used with caution and with this uncertainty kept in mind. All

  6. Fatigue Behavior under Multiaxial Stress States Including Notch Effects and Variable Amplitude Loading

    Science.gov (United States)

    Gates, Nicholas R.

    The central objective of the research performed in this study was to be able to better understand and predict fatigue crack initiation and growth from stress concentrations subjected to complex service loading histories. As such, major areas of focus were related to the understanding and modeling of material deformation behavior, fatigue damage quantification, notch effects, cycle counting, damage accumulation, and crack growth behavior under multiaxial nominal loading conditions. To support the analytical work, a wide variety of deformation and fatigue tests were also performed using tubular and plate specimens made from 2024-T3 aluminum alloy, with and without the inclusion of a circular through-thickness hole. However, the analysis procedures implemented were meant to be general in nature, and applicable to a wide variety of materials and component geometries. As a result, experimental data from literature were also used, when appropriate, to supplement the findings of various analyses. Popular approaches currently used for multiaxial fatigue life analysis are based on the idea of computing an equivalent stress/strain quantity through the extension of static yield criteria. This equivalent stress/strain is then considered to be equal, in terms of fatigue damage, to a uniaxial loading of the same magnitude. However, it has often been shown, and was shown again in this study, that although equivalent stress- and strain-based analysis approaches may work well in certain situations, they lack a general robustness and offer little room for improvement. More advanced analysis techniques, on the other hand, provide an opportunity to more accurately account for various aspects of the fatigue failure process under both constant and variable amplitude loading conditions. As a result, such techniques were of primary interest in the investigations performed. By implementing more advanced life prediction methodologies, both the overall accuracy and the correlation of fatigue

  7. Understanding morphological variability in a taxonomic context in Chilean diplomystids (Teleostei: Siluriformes, including the description of a new species

    Directory of Open Access Journals (Sweden)

    Gloria Arratia

    2017-02-01

    Full Text Available Following study of the external morphology and its unmatched variability throughout ontogeny and a re-examination of selected morphological characters based on many specimens of diplomystids from Central and South Chile, we revised and emended previous specific diagnoses and consider Diplomystes chilensis, D. nahuelbutaensis, D. camposensis, and Olivaichthys viedmensis (Baker River to be valid species. Another group, previously identified as Diplomystes sp., D. spec., D. aff. chilensis, and D. cf. chilensis inhabiting rivers between Rapel and Itata Basins is given a new specific name (Diplomystes incognitus and is diagnosed. An identification key to the Chilean species, including the new species, is presented. All specific diagnoses are based on external morphological characters, such as aspects of the skin, neuromast lines, and main lateral line, and position of the anus and urogenital pore, as well as certain osteological characters to facilitate the identification of these species that previously was based on many internal characters. Diplomystids below 150 mm standard length (SL share a similar external morphology and body proportions that make identification difficult; however, specimens over 150 mm SL can be diagnosed by the position of the urogenital pore and anus, and a combination of external and internal morphological characters. According to current knowledge, diplomystid species have an allopatric distribution with each species apparently endemic to particular basins in continental Chile and one species (O. viedmensis known only from one river in the Chilean Patagonia, but distributed extensively in southern Argentina.

  8. Not accounting for interindividual variability can mask habitat selection patterns: a case study on black bears.

    Science.gov (United States)

    Lesmerises, Rémi; St-Laurent, Martin-Hugues

    2017-11-01

    Habitat selection studies conducted at the population scale commonly aim to describe general patterns that could improve our understanding of the limiting factors in species-habitat relationships. Researchers often consider interindividual variation in selection patterns to control for its effects and avoid pseudoreplication by using mixed-effect models that include individuals as random factors. Here, we highlight common pitfalls and possible misinterpretations of this strategy by describing habitat selection of 21 black bears Ursus americanus. We used Bayesian mixed-effect models and compared results obtained when using random intercept (i.e., population level) versus calculating individual coefficients for each independent variable (i.e., individual level). We then related interindividual variability to individual characteristics (i.e., age, sex, reproductive status, body condition) in a multivariate analysis. The assumption of comparable behavior among individuals was verified only in 40% of the cases in our seasonal best models. Indeed, we found strong and opposite responses among sampled bears and individual coefficients were linked to individual characteristics. For some covariates, contrasted responses canceled each other out at the population level. In other cases, interindividual variability was concealed by the composition of our sample, with the majority of the bears (e.g., old individuals and bears in good physical condition) driving the population response (e.g., selection of young forest cuts). Our results stress the need to consider interindividual variability to avoid misinterpretation and uninformative results, especially for a flexible and opportunistic species. This study helps to identify some ecological drivers of interindividual variability in bear habitat selection patterns.

  9. The Selection, Use, and Reporting of Control Variables in International Business Research

    DEFF Research Database (Denmark)

    Nielsen, Bo Bernhard; Raswant, Arpit

    2018-01-01

    This study explores the selection, use, and reporting of control variables in studies published in the leading international business (IB) research journals. We review a sample of 246 empirical studies published in the top five IB journals over the period 2012–2015 with particular emphasis...... on selection, use, and reporting of controls. Approximately 83% of studies included only half of what we consider Minimum Standard of Practice with regards to controls, whereas only 38% of the studies met the 75% threshold. We provide recommendations on how to effectively identify, use and report controls...

  10. Cleanup and treatment of radioactively contaminated land including areas near nuclear facilities. A selected bibliography

    International Nuclear Information System (INIS)

    Fore, C.S.; Faust, R.A.; Brewster, R.H.

    1982-09-01

    This annotated bibliography of 337 references summarizes the literature published on the cleanup and treatment of radioactively contaminated land. Specifically, this bibliography focuses on literature concerned with the methods of cleanup and treatment being applied - chemical, physical, or vegetative stabilization; the types of equipment being used; and the influence of climatic conditions on the method selected for use. The emphasis in such literature is placed on hazardous site cleanup efforts that have been completed as well as those that are in progress and are being planned. Appendix A includes 135 additional references to literature identified but not included in the bibliography because of time and funding constraints. Appendix B consists of a table that identifies the cleanup and treatment research conducted at specific sites. All of the information included in this bibliography is stored in a computerized form that is readily available upon request

  11. Microscopic age determination of human skeletons including an unknown but calculable variable

    DEFF Research Database (Denmark)

    Wallin, Johan Albert; Tkocz, Izabella; Kristensen, Gustav

    1994-01-01

    estimation, which includes the covariance matrix of four single equation residuals, improves the accuracy of age determination. The standard deviation, however, of age prediction remains 12.58 years. An experimental split of the data was made in order to demonstrate that the use of subgroups gives a false...

  12. Variable selection methods in PLS regression - a comparison study on metabolomics data

    DEFF Research Database (Denmark)

    Karaman, İbrahim; Hedemann, Mette Skou; Knudsen, Knud Erik Bach

    . The aim of the metabolomics study was to investigate the metabolic profile in pigs fed various cereal fractions with special attention to the metabolism of lignans using LC-MS based metabolomic approach. References 1. Lê Cao KA, Rossouw D, Robert-Granié C, Besse P: A Sparse PLS for Variable Selection when...... integrated approach. Due to the high number of variables in data sets (both raw data and after peak picking) the selection of important variables in an explorative analysis is difficult, especially when different data sets of metabolomics data need to be related. Variable selection (or removal of irrelevant...... different strategies for variable selection on PLSR method were considered and compared with respect to selected subset of variables and the possibility for biological validation. Sparse PLSR [1] as well as PLSR with Jack-knifing [2] was applied to data in order to achieve variable selection prior...

  13. Input variable selection for interpolating high-resolution climate ...

    African Journals Online (AJOL)

    Although the primary input data of climate interpolations are usually meteorological data, other related (independent) variables are frequently incorporated in the interpolation process. One such variable is elevation, which is known to have a strong influence on climate. This research investigates the potential of 4 additional ...

  14. A Study on Site Selecting for National Project including High Level Radioactive Waste Disposal

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Kilyoo [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2016-10-15

    Many national projects are stopped since sites for the projects are not determined. The sites selections are hold by NIMBY for unpleasant facilities or by PYMFY for preferable facilities among local governments. The followings are the typical ones; NIMBY projects: high level radioactive waste disposal, THAAD, Nuclear power plant(NPP), etc. PIMFY projects: South-east new airport, KTX station, Research center for NPP decommission, etc. The site selection for high level radioactive waste disposal is more difficult problem, and thus government did not decide and postpone to a dead end street. Since it seems that there is no solution for site selection for high level radioactive waste disposal due to NIMBY among local governments, a solution method is proposed in this paper. To decide a high level radioactive waste disposal, the first step is to invite a bid by suggesting a package deal including PIMFY projects such as Research Center for NPP decommission. Maybe potential host local governments are asked to submit sealed bids indicating the minimum compensation sum that they would accept the high level radioactive waste disposal site. If there are more than one local government put in a bid, then decide an adequate site by considering both the accumulated PESS point and technical evaluation results. By considering how fairly preferable national projects and unpleasant national projects are distributed among local government, sites selection for NIMBY or PIMFY facilities is suggested. For NIMBY national projects, risk, cost benefit analysis is useful and required since it generates cost value to be used in the PESS. For many cases, the suggested method may be not adequate. However, similar one should be prepared, and be basis to decide sites for NIMBY or PIMFY national projects.

  15. Selecting candidate predictor variables for the modelling of post ...

    African Journals Online (AJOL)

    Objectives: The objective of this project was to determine the variables most likely to be associated with post- .... (as defined subjectively by the research team) in global .... ed on their lack of knowledge of wealth scoring tools. ... HIV serology.

  16. A New Variable Weighting and Selection Procedure for K-Means Cluster Analysis

    Science.gov (United States)

    Steinley, Douglas; Brusco, Michael J.

    2008-01-01

    A variance-to-range ratio variable weighting procedure is proposed. We show how this weighting method is theoretically grounded in the inherent variability found in data exhibiting cluster structure. In addition, a variable selection procedure is proposed to operate in conjunction with the variable weighting technique. The performances of these…

  17. Pathogen-mediated selection for MHC variability in wild zebrafish

    Czech Academy of Sciences Publication Activity Database

    Smith, C.; Ondračková, Markéta; Spence, R.; Adams, S.; Betts, D. S.; Mallon, E.

    2011-01-01

    Roč. 13, č. 6 (2011), s. 589-605 ISSN 1522-0613 Institutional support: RVO:68081766 Keywords : digenean * frequency-dependent selection * heterozygote advantage * major histocompatibility complex * metazoan parasite * pathogen-driven selection Subject RIV: EG - Zoology Impact factor: 1.029, year: 2011

  18. Variable selection in multiple linear regression: The influence of ...

    African Journals Online (AJOL)

    provide an indication of whether the fit of the selected model improves or ... and calculate M(−i); quantify the influence of case i in terms of a function, f(•), of M and ..... [21] Venter JH & Snyman JLJ, 1997, Linear model selection based on risk ...

  19. Improving breast cancer classification with mammography, supported on an appropriate variable selection analysis

    Science.gov (United States)

    Pérez, Noel; Guevara, Miguel A.; Silva, Augusto

    2013-02-01

    This work addresses the issue of variable selection within the context of breast cancer classification with mammography. A comprehensive repository of feature vectors was used including a hybrid subset gathering image-based and clinical features. It aimed to gather experimental evidence of variable selection in terms of cardinality, type and find a classification scheme that provides the best performance over the Area Under Receiver Operating Characteristics Curve (AUC) scores using the ranked features subset. We evaluated and classified a total of 300 subsets of features formed by the application of Chi-Square Discretization, Information-Gain, One-Rule and RELIEF methods in association with Feed-Forward Backpropagation Neural Network (FFBP), Support Vector Machine (SVM) and Decision Tree J48 (DTJ48) Machine Learning Algorithms (MLA) for a comparative performance evaluation based on AUC scores. A variable selection analysis was performed for Single-View Ranking and Multi-View Ranking groups of features. Features subsets representing Microcalcifications (MCs), Masses and both MCs and Masses lesions achieved AUC scores of 0.91, 0.954 and 0.934 respectively. Experimental evidence demonstrated that classification performance was improved by combining image-based and clinical features. The most important clinical and image-based features were StromaDistortion and Circularity respectively. Other less important but worth to use due to its consistency were Contrast, Perimeter, Microcalcification, Correlation and Elongation.

  20. Selected Macroeconomic Variables and Stock Market Movements: Empirical evidence from Thailand

    Directory of Open Access Journals (Sweden)

    Joseph Ato Forson

    2014-06-01

    Full Text Available This paper investigates and analyzes the long-run equilibrium relationship between the Thai stock Exchange Index (SETI and selected macroeconomic variables using monthly time series data that cover a 20-year period from January 1990 to December 2009. The following macroeconomic variables are included in our analysis: money supply (MS, the consumer price index (CPI, interest rate (IR and the industrial production index (IP (as a proxy for GDP. Our findings prove that the SET Index and the selected macroeconomic variables are cointegrated at I (1 and have a significant equilibrium relationship over the long run. Money supply demonstrates a strong positive relationship with the SET Index over the long run, whereas the industrial production index and consumer price index show negative long-run relationships with the SET Index. Furthermore, in non-equilibrium situations, the error correction mechanism suggests that the consumer price index, industrial production index and money supply each contribute in some way to restore equilibrium. In addition, using Toda and Yamamoto’s augmented Granger causality test, we identify a bi-causal relationship between industrial production and money supply and unilateral causal relationships between CPI and IR, IP and CPI, MS and CPI, and IP and SETI, indicating that all of these variables are sensitive to Thai stock market movements. The policy implications of these findings are also discussed.

  1. Rainfall trends and variability in selected areas of Ethiopian Somali ...

    African Journals Online (AJOL)

    Moreover, proper spatial distribution of meteorological stations together with early warning system are required to further support local adaptive and coping strategies that the community designed towards rainfall variability in particular and climate change/disaster and risk at large. Keywords: Ethiopian Somali Region, Gode, ...

  2. Joint Variable Selection and Classification with Immunohistochemical Data

    Directory of Open Access Journals (Sweden)

    Debashis Ghosh

    2009-01-01

    Full Text Available To determine if candidate cancer biomarkers have utility in a clinical setting, validation using immunohistochemical methods is typically done. Most analyses of such data have not incorporated the multivariate nature of the staining profiles. In this article, we consider modelling such data using recently developed ideas from the machine learning community. In particular, we consider the joint goals of feature selection and classification. We develop estimation procedures for the analysis of immunohistochemical profiles using the least absolute selection and shrinkage operator. These lead to novel and flexible models and algorithms for the analysis of compositional data. The techniques are illustrated using data from a cancer biomarker study.

  3. The quasar luminosity function from a variability-selected sample

    Science.gov (United States)

    Hawkins, M. R. S.; Veron, P.

    1993-01-01

    A sample of quasars is selected from a 10-yr sequence of 30 UK Schmidt plates. Luminosity functions are derived in several redshift intervals, which in each case show a featureless power-law rise towards low luminosities. There is no sign of the 'break' found in the recent UVX sample of Boyle et al. It is suggested that reasons for the disagreement are connected with biases in the selection of the UVX sample. The question of the nature of quasar evolution appears to be still unresolved.

  4. Including Children with Selective Mutism in Mainstream Schools and Kindergartens: Problems and Possibilities

    Science.gov (United States)

    Omdal, Heidi

    2008-01-01

    There is little research on inclusion of children with selective mutism in school/kindergarten. Moreover, few studies have tried to understand selectively mute children's interactions in the natural surroundings of their home and school/kindergarten. Five children meeting the DSM-IV criteria for selective mutism were video-observed in social…

  5. Variable Selection in Time Series Forecasting Using Random Forests

    Directory of Open Access Journals (Sweden)

    Hristos Tyralis

    2017-10-01

    Full Text Available Time series forecasting using machine learning algorithms has gained popularity recently. Random forest is a machine learning algorithm implemented in time series forecasting; however, most of its forecasting properties have remained unexplored. Here we focus on assessing the performance of random forests in one-step forecasting using two large datasets of short time series with the aim to suggest an optimal set of predictor variables. Furthermore, we compare its performance to benchmarking methods. The first dataset is composed by 16,000 simulated time series from a variety of Autoregressive Fractionally Integrated Moving Average (ARFIMA models. The second dataset consists of 135 mean annual temperature time series. The highest predictive performance of RF is observed when using a low number of recent lagged predictor variables. This outcome could be useful in relevant future applications, with the prospect to achieve higher predictive accuracy.

  6. Effect of balance exercise on selected kinematic gait variables in ...

    African Journals Online (AJOL)

    The purpose of this study was to investigate the effect of balance exercise on some selected kinematic gait parameters in patients with knee joint osteoarthritis. Forty subjects (18 men and 22 women) participated in the study.They were divided into two groups: Group 1 (experimental) that was treated with balance exercises, ...

  7. The Relationship between Attitudes toward Censorship and Selected Academic Variables.

    Science.gov (United States)

    Dwyer, Edward J.; Summy, Mary K.

    1989-01-01

    To examine characteristics of subjects relative to their attitudes toward censorship, a study surveyed 98 college students selected from students in a public university in the southeastern United States. A 24-item Likert-style censorship scale was used to measure attitudes toward censorship. Strong agreement with affirmative items would suggest…

  8. [Application of characteristic NIR variables selection in portable detection of soluble solids content of apple by near infrared spectroscopy].

    Science.gov (United States)

    Fan, Shu-Xiang; Huang, Wen-Qian; Li, Jiang-Bo; Guo, Zhi-Ming; Zhaq, Chun-Jiang

    2014-10-01

    In order to detect the soluble solids content(SSC)of apple conveniently and rapidly, a ring fiber probe and a portable spectrometer were applied to obtain the spectroscopy of apple. Different wavelength variable selection methods, including unin- formative variable elimination (UVE), competitive adaptive reweighted sampling (CARS) and genetic algorithm (GA) were pro- posed to select effective wavelength variables of the NIR spectroscopy of the SSC in apple based on PLS. The back interval LS- SVM (BiLS-SVM) and GA were used to select effective wavelength variables based on LS-SVM. Selected wavelength variables and full wavelength range were set as input variables of PLS model and LS-SVM model, respectively. The results indicated that PLS model built using GA-CARS on 50 characteristic variables selected from full-spectrum which had 1512 wavelengths achieved the optimal performance. The correlation coefficient (Rp) and root mean square error of prediction (RMSEP) for prediction sets were 0.962, 0.403°Brix respectively for SSC. The proposed method of GA-CARS could effectively simplify the portable detection model of SSC in apple based on near infrared spectroscopy and enhance the predictive precision. The study can provide a reference for the development of portable apple soluble solids content spectrometer.

  9. The use of vector bootstrapping to improve variable selection precision in Lasso models

    NARCIS (Netherlands)

    Laurin, C.; Boomsma, D.I.; Lubke, G.H.

    2016-01-01

    The Lasso is a shrinkage regression method that is widely used for variable selection in statistical genetics. Commonly, K-fold cross-validation is used to fit a Lasso model. This is sometimes followed by using bootstrap confidence intervals to improve precision in the resulting variable selections.

  10. Chromospheric activity of periodic variable stars (including eclipsing binaries) observed in DR2 LAMOST stellar spectral survey

    Science.gov (United States)

    Zhang, Liyun; Lu, Hongpeng; Han, Xianming L.; Jiang, Linyan; Li, Zhongmu; Zhang, Yong; Hou, Yonghui; Wang, Yuefei; Cao, Zihuang

    2018-05-01

    The LAMOST spectral survey provides a rich databases for studying stellar spectroscopic properties and chromospheric activity. We cross-matched a total of 105,287 periodic variable stars from several photometric surveys and databases (CSS, LINEAR, Kepler, a recently updated eclipsing star catalogue, ASAS, NSVS, some part of SuperWASP survey, variable stars from the Tsinghua University-NAOC Transient Survey, and other objects from some new references) with four million stellar spectra published in the LAMOST data release 2 (DR2). We found 15,955 spectra for 11,469 stars (including 5398 eclipsing binaries). We calculated their equivalent widths (EWs) of their Hα, Hβ, Hγ, Hδ and Caii H lines. Using the Hα line EW, we found 447 spectra with emission above continuum for a total of 316 stars (178 eclipsing binaries). We identified 86 active stars (including 44 eclipsing binaries) with repeated LAMOST spectra. A total of 68 stars (including 34 eclipsing binaries) show chromospheric activity variability. We also found LAMOST spectra of 12 cataclysmic variables, five of which show chromospheric activity variability. We also made photometric follow-up studies of three short period targets (DY CVn, HAT-192-0001481, and LAMOST J164933.24+141255.0) using the Xinglong 60-cm telescope and the SARA 90-cm and 1-m telescopes, and obtained new BVRI CCD light curves. We analyzed these light curves and obtained orbital and starspot parameters. We detected the first flare event with a huge brightness increase of more than about 1.5 magnitudes in R filter in LAMOST J164933.24+141255.0.

  11. Closed-form solutions for linear regulator design of mechanical systems including optimal weighting matrix selection

    Science.gov (United States)

    Hanks, Brantley R.; Skelton, Robert E.

    1991-01-01

    Vibration in modern structural and mechanical systems can be reduced in amplitude by increasing stiffness, redistributing stiffness and mass, and/or adding damping if design techniques are available to do so. Linear Quadratic Regulator (LQR) theory in modern multivariable control design, attacks the general dissipative elastic system design problem in a global formulation. The optimal design, however, allows electronic connections and phase relations which are not physically practical or possible in passive structural-mechanical devices. The restriction of LQR solutions (to the Algebraic Riccati Equation) to design spaces which can be implemented as passive structural members and/or dampers is addressed. A general closed-form solution to the optimal free-decay control problem is presented which is tailored for structural-mechanical system. The solution includes, as subsets, special cases such as the Rayleigh Dissipation Function and total energy. Weighting matrix selection is a constrained choice among several parameters to obtain desired physical relationships. The closed-form solution is also applicable to active control design for systems where perfect, collocated actuator-sensor pairs exist.

  12. ACTIVE LEARNING TO OVERCOME SAMPLE SELECTION BIAS: APPLICATION TO PHOTOMETRIC VARIABLE STAR CLASSIFICATION

    Energy Technology Data Exchange (ETDEWEB)

    Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J. [Astronomy Department, University of California, Berkeley, CA 94720-7450 (United States); Brink, Henrik [Dark Cosmology Centre, Juliane Maries Vej 30, 2100 Copenhagen O (Denmark); Long, James P.; Rice, John, E-mail: jwrichar@stat.berkeley.edu [Statistics Department, University of California, Berkeley, CA 94720-7450 (United States)

    2012-01-10

    Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL-where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up-is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.

  13. Social variables exert selective pressures in the evolution and form of primate mimetic musculature.

    Science.gov (United States)

    Burrows, Anne M; Li, Ly; Waller, Bridget M; Micheletta, Jerome

    2016-04-01

    Mammals use their faces in social interactions more so than any other vertebrates. Primates are an extreme among most mammals in their complex, direct, lifelong social interactions and their frequent use of facial displays is a means of proximate visual communication with conspecifics. The available repertoire of facial displays is primarily controlled by mimetic musculature, the muscles that move the face. The form of these muscles is, in turn, limited by and influenced by phylogenetic inertia but here we use examples, both morphological and physiological, to illustrate the influence that social variables may exert on the evolution and form of mimetic musculature among primates. Ecomorphology is concerned with the adaptive responses of morphology to various ecological variables such as diet, foliage density, predation pressures, and time of day activity. We present evidence that social variables also exert selective pressures on morphology, specifically using mimetic muscles among primates as an example. Social variables include group size, dominance 'style', and mating systems. We present two case studies to illustrate the potential influence of social behavior on adaptive morphology of mimetic musculature in primates: (1) gross morphology of the mimetic muscles around the external ear in closely related species of macaque (Macaca mulatta and Macaca nigra) characterized by varying dominance styles and (2) comparative physiology of the orbicularis oris muscle among select ape species. This muscle is used in both facial displays/expressions and in vocalizations/human speech. We present qualitative observations of myosin fiber-type distribution in this muscle of siamang (Symphalangus syndactylus), chimpanzee (Pan troglodytes), and human to demonstrate the potential influence of visual and auditory communication on muscle physiology. In sum, ecomorphologists should be aware of social selective pressures as well as ecological ones, and that observed morphology might

  14. ACTIVE LEARNING TO OVERCOME SAMPLE SELECTION BIAS: APPLICATION TO PHOTOMETRIC VARIABLE STAR CLASSIFICATION

    International Nuclear Information System (INIS)

    Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J.; Brink, Henrik; Long, James P.; Rice, John

    2012-01-01

    Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL—where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up—is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.

  15. Active Learning to Overcome Sample Selection Bias: Application to Photometric Variable Star Classification

    Science.gov (United States)

    Richards, Joseph W.; Starr, Dan L.; Brink, Henrik; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; James, J. Berian; Long, James P.; Rice, John

    2012-01-01

    Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL—where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up—is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.

  16. Cholinergic enhancement reduces functional connectivity and BOLD variability in visual extrastriate cortex during selective attention.

    Science.gov (United States)

    Ricciardi, Emiliano; Handjaras, Giacomo; Bernardi, Giulio; Pietrini, Pietro; Furey, Maura L

    2013-01-01

    Enhancing cholinergic function improves performance on various cognitive tasks and alters neural responses in task specific brain regions. We have hypothesized that the changes in neural activity observed during increased cholinergic function reflect an increase in neural efficiency that leads to improved task performance. The current study tested this hypothesis by assessing neural efficiency based on cholinergically-mediated effects on regional brain connectivity and BOLD signal variability. Nine subjects participated in a double-blind, placebo-controlled crossover fMRI study. Following an infusion of physostigmine (1 mg/h) or placebo, echo-planar imaging (EPI) was conducted as participants performed a selective attention task. During the task, two images comprised of superimposed pictures of faces and houses were presented. Subjects were instructed periodically to shift their attention from one stimulus component to the other and to perform a matching task using hand held response buttons. A control condition included phase-scrambled images of superimposed faces and houses that were presented in the same temporal and spatial manner as the attention task; participants were instructed to perform a matching task. Cholinergic enhancement improved performance during the selective attention task, with no change during the control task. Functional connectivity analyses showed that the strength of connectivity between ventral visual processing areas and task-related occipital, parietal and prefrontal regions reduced significantly during cholinergic enhancement, exclusively during the selective attention task. Physostigmine administration also reduced BOLD signal temporal variability relative to placebo throughout temporal and occipital visual processing areas, again during the selective attention task only. Together with the observed behavioral improvement, the decreases in connectivity strength throughout task-relevant regions and BOLD variability within stimulus

  17. gamboostLSS: An R Package for Model Building and Variable Selection in the GAMLSS Framework

    Directory of Open Access Journals (Sweden)

    Benjamin Hofner

    2016-10-01

    Full Text Available Generalized additive models for location, scale and shape are a flexible class of regression models that allow to model multiple parameters of a distribution function, such as the mean and the standard deviation, simultaneously. With the R package gamboostLSS, we provide a boosting method to fit these models. Variable selection and model choice are naturally available within this regularized regression framework. To introduce and illustrate the R package gamboostLSS and its infrastructure, we use a data set on stunted growth in India. In addition to the specification and application of the model itself, we present a variety of convenience functions, including methods for tuning parameter selection, prediction and visualization of results. The package gamboostLSS is available from the Comprehensive R Archive Network (CRAN at https://CRAN.R-project.org/package=gamboostLSS.

  18. Examining Self Regulated Learning in Relation to Certain Selected Variables

    Science.gov (United States)

    Johnson, N.

    2012-01-01

    Self-regulation is the controlling of a process or activity by the students who are involved in Problem solving in Physics rather than by an external agency (Johnson, 2011). Selfregulated learning consists of three main components: cognition, metacognition, and motivation. Cognition includes skills necessary to encode, memorise, and recall…

  19. Random forest variable selection in spatial malaria transmission modelling in Mpumalanga Province, South Africa

    Directory of Open Access Journals (Sweden)

    Thandi Kapwata

    2016-11-01

    Full Text Available Malaria is an environmentally driven disease. In order to quantify the spatial variability of malaria transmission, it is imperative to understand the interactions between environmental variables and malaria epidemiology at a micro-geographic level using a novel statistical approach. The random forest (RF statistical learning method, a relatively new variable-importance ranking method, measures the variable importance of potentially influential parameters through the percent increase of the mean squared error. As this value increases, so does the relative importance of the associated variable. The principal aim of this study was to create predictive malaria maps generated using the selected variables based on the RF algorithm in the Ehlanzeni District of Mpumalanga Province, South Africa. From the seven environmental variables used [temperature, lag temperature, rainfall, lag rainfall, humidity, altitude, and the normalized difference vegetation index (NDVI], altitude was identified as the most influential predictor variable due its high selection frequency. It was selected as the top predictor for 4 out of 12 months of the year, followed by NDVI, temperature and lag rainfall, which were each selected twice. The combination of climatic variables that produced the highest prediction accuracy was altitude, NDVI, and temperature. This suggests that these three variables have high predictive capabilities in relation to malaria transmission. Furthermore, it is anticipated that the predictive maps generated from predictions made by the RF algorithm could be used to monitor the progression of malaria and assist in intervention and prevention efforts with respect to malaria.

  20. Simulated selection responses for breeding programs including resistance and resilience to parasites in Creole goats

    NARCIS (Netherlands)

    Gunia, M.; Phocas, F.; Gourdine, J.L.; Bijma, P.; Mandonnet, N.

    2013-01-01

    The Creole goat is a local breed used for meat production in Guadeloupe (French West Indies). As in other tropical countries, improvement of parasite resistance is needed. In this study, we compared predicted selection responses for alternative breeding programs with or without parasites resistance

  1. Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.

    Science.gov (United States)

    Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H

    2017-07-01

    Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in

  2. Using Random Forests to Select Optimal Input Variables for Short-Term Wind Speed Forecasting Models

    Directory of Open Access Journals (Sweden)

    Hui Wang

    2017-10-01

    Full Text Available Achieving relatively high-accuracy short-term wind speed forecasting estimates is a precondition for the construction and grid-connected operation of wind power forecasting systems for wind farms. Currently, most research is focused on the structure of forecasting models and does not consider the selection of input variables, which can have significant impacts on forecasting performance. This paper presents an input variable selection method for wind speed forecasting models. The candidate input variables for various leading periods are selected and random forests (RF is employed to evaluate the importance of all variable as features. The feature subset with the best evaluation performance is selected as the optimal feature set. Then, kernel-based extreme learning machine is constructed to evaluate the performance of input variables selection based on RF. The results of the case study show that by removing the uncorrelated and redundant features, RF effectively extracts the most strongly correlated set of features from the candidate input variables. By finding the optimal feature combination to represent the original information, RF simplifies the structure of the wind speed forecasting model, shortens the training time required, and substantially improves the model’s accuracy and generalization ability, demonstrating that the input variables selected by RF are effective.

  3. A modification of the successive projections algorithm for spectral variable selection in the presence of unknown interferents.

    Science.gov (United States)

    Soares, Sófacles Figueredo Carreiro; Galvão, Roberto Kawakami Harrop; Araújo, Mário César Ugulino; da Silva, Edvan Cirino; Pereira, Claudete Fernandes; de Andrade, Stéfani Iury Evangelista; Leite, Flaviano Carvalho

    2011-03-09

    This work proposes a modification to the successive projections algorithm (SPA) aimed at selecting spectral variables for multiple linear regression (MLR) in the presence of unknown interferents not included in the calibration data set. The modified algorithm favours the selection of variables in which the effect of the interferent is less pronounced. The proposed procedure can be regarded as an adaptive modelling technique, because the spectral features of the samples to be analyzed are considered in the variable selection process. The advantages of this new approach are demonstrated in two analytical problems, namely (1) ultraviolet-visible spectrometric determination of tartrazine, allure red and sunset yellow in aqueous solutions under the interference of erythrosine, and (2) near-infrared spectrometric determination of ethanol in gasoline under the interference of toluene. In these case studies, the performance of conventional MLR-SPA models is substantially degraded by the presence of the interferent. This problem is circumvented by applying the proposed Adaptive MLR-SPA approach, which results in prediction errors smaller than those obtained by three other multivariate calibration techniques, namely stepwise regression, full-spectrum partial-least-squares (PLS) and PLS with variables selected by a genetic algorithm. An inspection of the variable selection results reveals that the Adaptive approach successfully avoids spectral regions in which the interference is more intense. Copyright © 2011 Elsevier B.V. All rights reserved.

  4. Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology

    Science.gov (United States)

    Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, e...

  5. Comparison of Sparse and Jack-knife partial least squares regression methods for variable selection

    DEFF Research Database (Denmark)

    Karaman, Ibrahim; Qannari, El Mostafa; Martens, Harald

    2013-01-01

    The objective of this study was to compare two different techniques of variable selection, Sparse PLSR and Jack-knife PLSR, with respect to their predictive ability and their ability to identify relevant variables. Sparse PLSR is a method that is frequently used in genomics, whereas Jack-knife PL...

  6. Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis

    Directory of Open Access Journals (Sweden)

    Ueki Masao

    2012-05-01

    Full Text Available Abstract Background Genome-wide gene-gene interaction analysis using single nucleotide polymorphisms (SNPs is an attractive way for identification of genetic components that confers susceptibility of human complex diseases. Individual hypothesis testing for SNP-SNP pairs as in common genome-wide association study (GWAS however involves difficulty in setting overall p-value due to complicated correlation structure, namely, the multiple testing problem that causes unacceptable false negative results. A large number of SNP-SNP pairs than sample size, so-called the large p small n problem, precludes simultaneous analysis using multiple regression. The method that overcomes above issues is thus needed. Results We adopt an up-to-date method for ultrahigh-dimensional variable selection termed the sure independence screening (SIS for appropriate handling of numerous number of SNP-SNP interactions by including them as predictor variables in logistic regression. We propose ranking strategy using promising dummy coding methods and following variable selection procedure in the SIS method suitably modified for gene-gene interaction analysis. We also implemented the procedures in a software program, EPISIS, using the cost-effective GPGPU (General-purpose computing on graphics processing units technology. EPISIS can complete exhaustive search for SNP-SNP interactions in standard GWAS dataset within several hours. The proposed method works successfully in simulation experiments and in application to real WTCCC (Wellcome Trust Case–control Consortium data. Conclusions Based on the machine-learning principle, the proposed method gives powerful and flexible genome-wide search for various patterns of gene-gene interaction.

  7. Punishment induced behavioural and neurophysiological variability reveals dopamine-dependent selection of kinematic movement parameters

    Science.gov (United States)

    Galea, Joseph M.; Ruge, Diane; Buijink, Arthur; Bestmann, Sven; Rothwell, John C.

    2013-01-01

    Action selection describes the high-level process which selects between competing movements. In animals, behavioural variability is critical for the motor exploration required to select the action which optimizes reward and minimizes cost/punishment, and is guided by dopamine (DA). The aim of this study was to test in humans whether low-level movement parameters are affected by punishment and reward in ways similar to high-level action selection. Moreover, we addressed the proposed dependence of behavioural and neurophysiological variability on DA, and whether this may underpin the exploration of kinematic parameters. Participants performed an out-and-back index finger movement and were instructed that monetary reward and punishment were based on its maximal acceleration (MA). In fact, the feedback was not contingent on the participant’s behaviour but pre-determined. Blocks highly-biased towards punishment were associated with increased MA variability relative to blocks with either reward or without feedback. This increase in behavioural variability was positively correlated with neurophysiological variability, as measured by changes in cortico-spinal excitability with transcranial magnetic stimulation over the primary motor cortex. Following the administration of a DA-antagonist, the variability associated with punishment diminished and the correlation between behavioural and neurophysiological variability no longer existed. Similar changes in variability were not observed when participants executed a pre-determined MA, nor did DA influence resting neurophysiological variability. Thus, under conditions of punishment, DA-dependent processes influence the selection of low-level movement parameters. We propose that the enhanced behavioural variability reflects the exploration of kinematic parameters for less punishing, or conversely more rewarding, outcomes. PMID:23447607

  8. 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

  9. Variable selectivity and the role of nutritional quality in food selection by a planktonic rotifer

    International Nuclear Information System (INIS)

    Sierszen, M.E.

    1990-01-01

    To investigate the potential for selective feeding to enhance fitness, I test the hypothesis that an herbivorous zooplankter selects those food items that best support its reproduction. Under this hypothesis, growth and reproduction on selected food items should be higher than on less preferred items. The hypothesis is not supported. In situ selectivity by the rotifer Keratella taurocephala for Cryptomonas relative to Chlamydomonas goes through a seasonal cycle, in apparent response to fluctuating Cryptomonas populations. However, reproduction on a unialgal diet of Cryptomonas is consistently high and similar to that on Chlamydomonas. Oocystis, which also supports reproduction equivalent to that supported by Chlamydomonas, is sometimes rejected by K. taurocephala. In addition, K. taurocephala does not discriminate between Merismopedia and Chlamydomonas even though Merismopedia supports virtually no reproduction by the rotifer. Selection by K. taurocephala does not simply maximize the intake of food items that yield high reproduction. Selectivity is a complex, dynamic process, one function of which may be the exploitation of locally or seasonally abundant foods. (author)

  10. The Effects of Variability and Risk in Selection Utility Analysis: An Empirical Comparison.

    Science.gov (United States)

    Rich, Joseph R.; Boudreau, John W.

    1987-01-01

    Investigated utility estimate variability for the selection utility of using the Programmer Aptitude Test to select computer programmers. Comparison of Monte Carlo results to other risk assessment approaches (sensitivity analysis, break-even analysis, algebraic derivation of the distribtion) suggests that distribution information provided by Monte…

  11. Improvement of prediction ability for genomic selection of dairy cattle by including dominance effects.

    Directory of Open Access Journals (Sweden)

    Chuanyu Sun

    Full Text Available Dominance may be an important source of non-additive genetic variance for many traits of dairy cattle. However, nearly all prediction models for dairy cattle have included only additive effects because of the limited number of cows with both genotypes and phenotypes. The role of dominance in the Holstein and Jersey breeds was investigated for eight traits: milk, fat, and protein yields; productive life; daughter pregnancy rate; somatic cell score; fat percent and protein percent. Additive and dominance variance components were estimated and then used to estimate additive and dominance effects of single nucleotide polymorphisms (SNPs. The predictive abilities of three models with both additive and dominance effects and a model with additive effects only were assessed using ten-fold cross-validation. One procedure estimated dominance values, and another estimated dominance deviations; calculation of the dominance relationship matrix was different for the two methods. The third approach enlarged the dataset by including cows with genotype probabilities derived using genotyped ancestors. For yield traits, dominance variance accounted for 5 and 7% of total variance for Holsteins and Jerseys, respectively; using dominance deviations resulted in smaller dominance and larger additive variance estimates. For non-yield traits, dominance variances were very small for both breeds. For yield traits, including additive and dominance effects fit the data better than including only additive effects; average correlations between estimated genetic effects and phenotypes showed that prediction accuracy increased when both effects rather than just additive effects were included. No corresponding gains in prediction ability were found for non-yield traits. Including cows with derived genotype probabilities from genotyped ancestors did not improve prediction accuracy. The largest additive effects were located on chromosome 14 near DGAT1 for yield traits for both

  12. Stochastic weather inputs for improved urban water demand forecasting: application of nonlinear input variable selection and machine learning methods

    Science.gov (United States)

    Quilty, J.; Adamowski, J. F.

    2015-12-01

    Urban water supply systems are often stressed during seasonal outdoor water use as water demands related to the climate are variable in nature making it difficult to optimize the operation of the water supply system. Urban water demand forecasts (UWD) failing to include meteorological conditions as inputs to the forecast model may produce poor forecasts as they cannot account for the increase/decrease in demand related to meteorological conditions. Meteorological records stochastically simulated into the future can be used as inputs to data-driven UWD forecasts generally resulting in improved forecast accuracy. This study aims to produce data-driven UWD forecasts for two different Canadian water utilities (Montreal and Victoria) using machine learning methods by first selecting historical UWD and meteorological records derived from a stochastic weather generator using nonlinear input variable selection. The nonlinear input variable selection methods considered in this work are derived from the concept of conditional mutual information, a nonlinear dependency measure based on (multivariate) probability density functions and accounts for relevancy, conditional relevancy, and redundancy from a potential set of input variables. The results of our study indicate that stochastic weather inputs can improve UWD forecast accuracy for the two sites considered in this work. Nonlinear input variable selection is suggested as a means to identify which meteorological conditions should be utilized in the forecast.

  13. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

    Science.gov (United States)

    Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan

    2017-01-01

    Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

  14. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method

    Directory of Open Access Journals (Sweden)

    Jun-He Yang

    2017-01-01

    Full Text Available Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir’s water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir’s water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

  15. Air Emissions of Selected Substances from Particular Sectors Including Metallurgy in Poland

    Directory of Open Access Journals (Sweden)

    Kargulewicz I.

    2017-03-01

    Full Text Available This article presents data on the anthropogenic air emissions of selected substances (CO2, SO2, total suspended particles (TSP, dioxins and furans (PCDD/F, Pb and Cd subject to reporting under the Climate Convention (UNFCCC or the Convention on Long-range Transboundary Air Pollution (UNECE CLRTAP. It also presents the national emissions of these substances in 2014 by the major source categories and defines the share of metal production in these emissions. Analysis is based on national emission inventory reports. Most important source of air emission in case of CO2 and SO2 is 1.A.1 Energy industries category. TSP and PCDD/F are emitted mainly from fuel combustion in small sources (i.a. households. Emission of heavy metals (Pb and Cd is connected mostly with 1.A.2. Manufacturing industries and construction category. Metallurgy is significant source of emission only for lead and cadmium from among all considered substances. The shares of particular sectors in the national emissions of given pollutants are important, in view of the possible reduction measures and the determination in which industries they could bring about tangible results.

  16. Novel Harmonic Regularization Approach for Variable Selection in Cox’s Proportional Hazards Model

    Directory of Open Access Journals (Sweden)

    Ge-Jin Chu

    2014-01-01

    Full Text Available Variable selection is an important issue in regression and a number of variable selection methods have been proposed involving nonconvex penalty functions. In this paper, we investigate a novel harmonic regularization method, which can approximate nonconvex Lq  (1/2select key risk factors in the Cox’s proportional hazards model using microarray gene expression data. The harmonic regularization method can be efficiently solved using our proposed direct path seeking approach, which can produce solutions that closely approximate those for the convex loss function and the nonconvex regularization. Simulation results based on the artificial datasets and four real microarray gene expression datasets, such as real diffuse large B-cell lymphoma (DCBCL, the lung cancer, and the AML datasets, show that the harmonic regularization method can be more accurate for variable selection than existing Lasso series methods.

  17. A survey of variable selection methods in two Chinese epidemiology journals

    Directory of Open Access Journals (Sweden)

    Lynn Henry S

    2010-09-01

    Full Text Available Abstract Background Although much has been written on developing better procedures for variable selection, there is little research on how it is practiced in actual studies. This review surveys the variable selection methods reported in two high-ranking Chinese epidemiology journals. Methods Articles published in 2004, 2006, and 2008 in the Chinese Journal of Epidemiology and the Chinese Journal of Preventive Medicine were reviewed. Five categories of methods were identified whereby variables were selected using: A - bivariate analyses; B - multivariable analysis; e.g. stepwise or individual significance testing of model coefficients; C - first bivariate analyses, followed by multivariable analysis; D - bivariate analyses or multivariable analysis; and E - other criteria like prior knowledge or personal judgment. Results Among the 287 articles that reported using variable selection methods, 6%, 26%, 30%, 21%, and 17% were in categories A through E, respectively. One hundred sixty-three studies selected variables using bivariate analyses, 80% (130/163 via multiple significance testing at the 5% alpha-level. Of the 219 multivariable analyses, 97 (44% used stepwise procedures, 89 (41% tested individual regression coefficients, but 33 (15% did not mention how variables were selected. Sixty percent (58/97 of the stepwise routines also did not specify the algorithm and/or significance levels. Conclusions The variable selection methods reported in the two journals were limited in variety, and details were often missing. Many studies still relied on problematic techniques like stepwise procedures and/or multiple testing of bivariate associations at the 0.05 alpha-level. These deficiencies should be rectified to safeguard the scientific validity of articles published in Chinese epidemiology journals.

  18. Comparison of behavioral profiles for anxiety-related comorbidities including ADHD and selective mutism in children.

    Science.gov (United States)

    Levin-Decanini, Tal; Connolly, Sucheta D; Simpson, David; Suarez, Liza; Jacob, Suma

    2013-09-01

    Elucidating differences in social-behavioral profiles of children with comorbid presentations, utilizing caregiver as well as teacher reports, will refine our understanding of how contextual symptoms vary across anxiety-related disorders. In our pediatric anxiety clinic, the most frequent diagnoses and comorbidities were mixed anxiety (MA; ≥ 1 anxiety disorder; N = 155), anxiety with comorbid attention-deficit hyperactivity disorder (MA/ADHD, N = 47) and selective mutism (SM, N = 48). Behavioral measures (CPRS, CTRS) were analyzed using multiple one-way multivariate analyses of covariance tests. Differences between the three diagnostic groups were examined using completed parent and teacher reports (N = 135, 46, and 48 for MA, MA/ADHD, and SM groups, respectively). Comparisons across the MA, MA/ADHD, and SM groups indicate a significant multivariate main effect of group for caregiver and teacher responses (P < 0.01). Caregivers reported that children with SM are similar in profile to those with MA, and both groups were significantly different from the MA/ADHD group. Teachers reported that children with SM had more problems with social behaviors than with the MA or MA/ADHD groups. Further comparison indicates a significant main effect of group (P < 0.001), such that children with SM have the greatest differences in behavior observed by teachers versus caregivers. Clinical profiles between MA/ADHD, MA, and SM groups varied, illustrating the importance of multi-rater assessment scales to capture subtle distinctions and to inform treatment planning given that comorbidities occur frequently in children who present with anxiety. © 2013 Wiley Periodicals, Inc.

  19. QUASI-STELLAR OBJECT SELECTION ALGORITHM USING TIME VARIABILITY AND MACHINE LEARNING: SELECTION OF 1620 QUASI-STELLAR OBJECT CANDIDATES FROM MACHO LARGE MAGELLANIC CLOUD DATABASE

    International Nuclear Information System (INIS)

    Kim, Dae-Won; Protopapas, Pavlos; Alcock, Charles; Trichas, Markos; Byun, Yong-Ik; Khardon, Roni

    2011-01-01

    We present a new quasi-stellar object (QSO) selection algorithm using a Support Vector Machine, a supervised classification method, on a set of extracted time series features including period, amplitude, color, and autocorrelation value. We train a model that separates QSOs from variable stars, non-variable stars, and microlensing events using 58 known QSOs, 1629 variable stars, and 4288 non-variables in the MAssive Compact Halo Object (MACHO) database as a training set. To estimate the efficiency and the accuracy of the model, we perform a cross-validation test using the training set. The test shows that the model correctly identifies ∼80% of known QSOs with a 25% false-positive rate. The majority of the false positives are Be stars. We applied the trained model to the MACHO Large Magellanic Cloud (LMC) data set, which consists of 40 million light curves, and found 1620 QSO candidates. During the selection none of the 33,242 known MACHO variables were misclassified as QSO candidates. In order to estimate the true false-positive rate, we crossmatched the candidates with astronomical catalogs including the Spitzer Surveying the Agents of a Galaxy's Evolution LMC catalog and a few X-ray catalogs. The results further suggest that the majority of the candidates, more than 70%, are QSOs.

  20. Microbiological quality of selected spices and herbs including the presence of Cronobacter spp.

    Science.gov (United States)

    Garbowska, M; Berthold-Pluta, A; Stasiak-Różańska, L

    2015-08-01

    The cultivation of spices and herbs in parts of the world characterized by warm climate and high humidity provides excellent conditions for the development of microorganisms, including the undesirable ones. The aim of this study was to determine the microbiological quality of spices and herbs available on the Polish market, considering the occurrence of Cronobacter species bacteria. Analyses covered 60 samples of commercial spices and herbs, including 38 samples of dried herbs (basil, bay leaves, thyme, oregano, tarragon, marjoram, dill, parsley, rosemary, lovage) and 16 samples of seasoning blends as well as 6 samples of spices seeds and fruits (pimento, black pepper, coriander). All samples were tested for the total count of aerobic mesophilic bacteria (TAMB) and for the presence of Cronobacter spp. In most of the samples of spices and herbs (60.0%), the TAMB did not exceed 10(4) CFU/g, and the level regarded as unacceptable (>10(6) CFU/g) was not identified in any of the samples. The presence of Cronobacter spp. was demonstrated in 10 (16.7%) samples of the analyzed products, however these were mainly samples of herbs (basil, tarragon, parsley) and one sample of a seasoning blend (Provence herbs). The highest microbiological contamination (TAMB) was found in samples of herbs (oregano, tarragon, basil) and in ready seasoning blends, in 21.1% and 25.0% of which the total count of aerobic mesophiles was in the range of 10(5)-10(6) CFU/g. In all samples of spices seeds and fruits (coriander, black pepper and pimento), the total count of aerobic bacteria reached spices and herbs available on the Polish market. The study demonstrated also that dried spices and herbs may be carriers of Cronobacter species bacteria, though their presence in not often detected in products of this type. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Developing a spatial-statistical model and map of historical malaria prevalence in Botswana using a staged variable selection procedure

    Directory of Open Access Journals (Sweden)

    Mabaso Musawenkosi LH

    2007-09-01

    produced a highly plausible and parsimonious model of historical malaria risk for Botswana from point-referenced data from a 1961/2 prevalence survey of malaria infection in 1–14 year old children. After starting with a list of 50 potential variables we ended with three highly plausible predictors, by applying a systematic and repeatable staged variable selection procedure that included a spatial analysis, which has application for other environmentally determined infectious diseases. All this was accomplished using general-purpose statistical software.

  2. Statistical methodology for discrete fracture model - including fracture size, orientation uncertainty together with intensity uncertainty and variability

    Energy Technology Data Exchange (ETDEWEB)

    Darcel, C. (Itasca Consultants SAS (France)); Davy, P.; Le Goc, R.; Dreuzy, J.R. de; Bour, O. (Geosciences Rennes, UMR 6118 CNRS, Univ. def Rennes, Rennes (France))

    2009-11-15

    the lineament scale (k{sub t} = 2) on the other, addresses the issue of the nature of the transition. We develop a new 'mechanistic' model that could help in modeling why and where this transition can occur. The transition between both regimes would occur for a fracture length of 1-10 m and even at a smaller scale for the few outcrops that follow the self-similar density model. A consequence for the disposal issue is that the model that is likely to apply in the 'blind' scale window between 10-100 m is the self-similar model as it is defined for large-scale lineaments. The self-similar model, as it is measured for some outcrops and most lineament maps, is definitely worth being investigated as a reference for scales above 1-10 m. In the rest of the report, we develop a methodology for incorporating uncertainty and variability into the DFN modeling. Fracturing properties arise from complex processes which produce an intrinsic variability; characterizing this variability as an admissible variation of model parameter or as the division of the site into subdomains with distinct DFN models is a critical point of the modeling effort. Moreover, the DFN model encompasses a part of uncertainty, due to data inherent uncertainties and sampling limits. Both effects must be quantified and incorporated into the DFN site model definition process. In that context, all available borehole data including recording of fracture intercept positions, pole orientation and relative uncertainties are used as the basis for the methodological development and further site model assessment. An elementary dataset contains a set of discrete fracture intercepts from which a parent orientation/density distribution can be computed. The elementary bricks of the site, from which these initial parent density distributions are computed, rely on the former Single Hole Interpretation division of the boreholes into sections whose local boundaries are expected to reflect - locally - geology

  3. Statistical methodology for discrete fracture model - including fracture size, orientation uncertainty together with intensity uncertainty and variability

    International Nuclear Information System (INIS)

    Darcel, C.; Davy, P.; Le Goc, R.; Dreuzy, J.R. de; Bour, O.

    2009-11-01

    the other, addresses the issue of the nature of the transition. We develop a new 'mechanistic' model that could help in modeling why and where this transition can occur. The transition between both regimes would occur for a fracture length of 1-10 m and even at a smaller scale for the few outcrops that follow the self-similar density model. A consequence for the disposal issue is that the model that is likely to apply in the 'blind' scale window between 10-100 m is the self-similar model as it is defined for large-scale lineaments. The self-similar model, as it is measured for some outcrops and most lineament maps, is definitely worth being investigated as a reference for scales above 1-10 m. In the rest of the report, we develop a methodology for incorporating uncertainty and variability into the DFN modeling. Fracturing properties arise from complex processes which produce an intrinsic variability; characterizing this variability as an admissible variation of model parameter or as the division of the site into subdomains with distinct DFN models is a critical point of the modeling effort. Moreover, the DFN model encompasses a part of uncertainty, due to data inherent uncertainties and sampling limits. Both effects must be quantified and incorporated into the DFN site model definition process. In that context, all available borehole data including recording of fracture intercept positions, pole orientation and relative uncertainties are used as the basis for the methodological development and further site model assessment. An elementary dataset contains a set of discrete fracture intercepts from which a parent orientation/density distribution can be computed. The elementary bricks of the site, from which these initial parent density distributions are computed, rely on the former Single Hole Interpretation division of the boreholes into sections whose local boundaries are expected to reflect - locally - geology and fracturing properties main characteristics. From that

  4. Genome-wide prediction of traits with different genetic architecture through efficient variable selection.

    Science.gov (United States)

    Wimmer, Valentin; Lehermeier, Christina; Albrecht, Theresa; Auinger, Hans-Jürgen; Wang, Yu; Schön, Chris-Carolin

    2013-10-01

    In genome-based prediction there is considerable uncertainty about the statistical model and method required to maximize prediction accuracy. For traits influenced by a small number of quantitative trait loci (QTL), predictions are expected to benefit from methods performing variable selection [e.g., BayesB or the least absolute shrinkage and selection operator (LASSO)] compared to methods distributing effects across the genome [ridge regression best linear unbiased prediction (RR-BLUP)]. We investigate the assumptions underlying successful variable selection by combining computer simulations with large-scale experimental data sets from rice (Oryza sativa L.), wheat (Triticum aestivum L.), and Arabidopsis thaliana (L.). We demonstrate that variable selection can be successful when the number of phenotyped individuals is much larger than the number of causal mutations contributing to the trait. We show that the sample size required for efficient variable selection increases dramatically with decreasing trait heritabilities and increasing extent of linkage disequilibrium (LD). We contrast and discuss contradictory results from simulation and experimental studies with respect to superiority of variable selection methods over RR-BLUP. Our results demonstrate that due to long-range LD, medium heritabilities, and small sample sizes, superiority of variable selection methods cannot be expected in plant breeding populations even for traits like FRIGIDA gene expression in Arabidopsis and flowering time in rice, assumed to be influenced by a few major QTL. We extend our conclusions to the analysis of whole-genome sequence data and infer upper bounds for the number of causal mutations which can be identified by LASSO. Our results have major impact on the choice of statistical method needed to make credible inferences about genetic architecture and prediction accuracy of complex traits.

  5. Variable selection in PLSR and extensions to a multi-block setting for metabolomics data

    DEFF Research Database (Denmark)

    Karaman, İbrahim; Hedemann, Mette Skou; Knudsen, Knud Erik Bach

    When applying LC-MS or NMR spectroscopy in metabolomics studies, high-dimensional data are generated and effective tools for variable selection are needed in order to detect the important metabolites. Methods based on sparsity combined with PLSR have recently attracted attention in the field...... of genomics [1]. They became quickly well established in the field of statistics because a close relationship to elastic net has been established. In sparse variable selection combined with PLSR, a soft thresholding is applied on each loading weight separately. In the field of chemometrics Jack-knifing has...... been introduced for variable selection in PLSR [2]. Jack-knifing has been frequently applied in the field of spectroscopy and is implemented in software tools like The Unscrambler. In Jack-knifing uncertainty estimates of regression coefficients are estimated and a t-test is applied on these estimates...

  6. Auxiliary variables in multiple imputation in regression with missing X: a warning against including too many in small sample research

    Directory of Open Access Journals (Sweden)

    Hardt Jochen

    2012-12-01

    Full Text Available Abstract Background Multiple imputation is becoming increasingly popular. Theoretical considerations as well as simulation studies have shown that the inclusion of auxiliary variables is generally of benefit. Methods A simulation study of a linear regression with a response Y and two predictors X1 and X2 was performed on data with n = 50, 100 and 200 using complete cases or multiple imputation with 0, 10, 20, 40 and 80 auxiliary variables. Mechanisms of missingness were either 100% MCAR or 50% MAR + 50% MCAR. Auxiliary variables had low (r=.10 vs. moderate correlations (r=.50 with X’s and Y. Results The inclusion of auxiliary variables can improve a multiple imputation model. However, inclusion of too many variables leads to downward bias of regression coefficients and decreases precision. When the correlations are low, inclusion of auxiliary variables is not useful. Conclusion More research on auxiliary variables in multiple imputation should be performed. A preliminary rule of thumb could be that the ratio of variables to cases with complete data should not go below 1 : 3.

  7. Selection of variables for neural network analysis. Comparisons of several methods with high energy physics data

    International Nuclear Information System (INIS)

    Proriol, J.

    1994-01-01

    Five different methods are compared for selecting the most important variables with a view to classifying high energy physics events with neural networks. The different methods are: the F-test, Principal Component Analysis (PCA), a decision tree method: CART, weight evaluation, and Optimal Cell Damage (OCD). The neural networks use the variables selected with the different methods. We compare the percentages of events properly classified by each neural network. The learning set and the test set are the same for all the neural networks. (author)

  8. Curve fitting and modeling with splines using statistical variable selection techniques

    Science.gov (United States)

    Smith, P. L.

    1982-01-01

    The successful application of statistical variable selection techniques to fit splines is demonstrated. Major emphasis is given to knot selection, but order determination is also discussed. Two FORTRAN backward elimination programs, using the B-spline basis, were developed. The program for knot elimination is compared in detail with two other spline-fitting methods and several statistical software packages. An example is also given for the two-variable case using a tensor product basis, with a theoretical discussion of the difficulties of their use.

  9. Seleção de variáveis em QSAR Variable selection in QSAR

    Directory of Open Access Journals (Sweden)

    Márcia Miguel Castro Ferreira

    2002-05-01

    Full Text Available The process of building mathematical models in quantitative structure-activity relationship (QSAR studies is generally limited by the size of the dataset used to select variables from. For huge datasets, the task of selecting a given number of variables that produces the best linear model can be enormous, if not unfeasible. In this case, some methods can be used to separate good parameter combinations from the bad ones. In this paper three methodologies are analyzed: systematic search, genetic algorithm and chemometric methods. These methods have been exposed and discussed through practical examples.

  10. Sparse Reduced-Rank Regression for Simultaneous Dimension Reduction and Variable Selection

    KAUST Repository

    Chen, Lisha

    2012-12-01

    The reduced-rank regression is an effective method in predicting multiple response variables from the same set of predictor variables. It reduces the number of model parameters and takes advantage of interrelations between the response variables and hence improves predictive accuracy. We propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty. We apply a group-lasso type penalty that treats each row of the matrix of the regression coefficients as a group and show that this penalty satisfies certain desirable invariance properties. We develop two numerical algorithms to solve the penalized regression problem and establish the asymptotic consistency of the proposed method. In particular, the manifold structure of the reduced-rank regression coefficient matrix is considered and studied in our theoretical analysis. In our simulation study and real data analysis, the new method is compared with several existing variable selection methods for multivariate regression and exhibits competitive performance in prediction and variable selection. © 2012 American Statistical Association.

  11. Current Debates on Variability in Child Welfare Decision-Making: A Selected Literature Review

    Directory of Open Access Journals (Sweden)

    Emily Keddell

    2014-11-01

    Full Text Available This article considers selected drivers of decision variability in child welfare decision-making and explores current debates in relation to these drivers. Covering the related influences of national orientation, risk and responsibility, inequality and poverty, evidence-based practice, constructions of abuse and its causes, domestic violence and cognitive processes, it discusses the literature in regards to how each of these influences decision variability. It situates these debates in relation to the ethical issue of variability and the equity issues that variability raises. I propose that despite the ecological complexity that drives decision variability, that improving internal (within-country decision consistency is still a valid goal. It may be that the use of annotated case examples, kind learning systems, and continued commitments to the social justice issues of inequality and individualisation can contribute to this goal.

  12. Iwamoto-Harada coalescence/pickup model for cluster emission: state density approach including angular momentum variables

    Directory of Open Access Journals (Sweden)

    Běták Emil

    2014-04-01

    Full Text Available For low-energy nuclear reactions well above the resonance region, but still below the pion threshold, statistical pre-equilibrium models (e.g., the exciton and the hybrid ones are a frequent tool for analysis of energy spectra and the cross sections of cluster emission. For α’s, two essentially distinct approaches are popular, namely the preformed one and the different versions of coalescence approaches, whereas only the latter group of models can be used for other types of cluster ejectiles. The original Iwamoto-Harada model of pre-equilibrium cluster emission was formulated using the overlap of the cluster and its constituent nucleons in momentum space. Transforming it into level or state densities is not a straigthforward task; however, physically the same model was presented at a conference on reaction models five years earlier. At that time, only the densities without spin were used. The introduction of spin variables into the exciton model enabled detailed calculation of the γ emission and its competition with nucleon channels, and – at the same time – it stimulated further developments of the model. However – to the best of our knowledge – no spin formulation has been presented for cluster emission till recently, when the first attempts have been reported, but restricted to the first emission only. We have updated this effort now and we are able to handle (using the same simplifications as in our previous work pre-equilibrium cluster emission with spin including all nuclei in the reaction chain.

  13. Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS

    Science.gov (United States)

    Jiang, Hui; Zhang, Hang; Chen, Quansheng; Mei, Congli; Liu, Guohai

    2015-10-01

    The use of wavelength variable selection before partial least squares discriminant analysis (PLS-DA) for qualitative identification of solid state fermentation degree by FT-NIR spectroscopy technique was investigated in this study. Two wavelength variable selection methods including competitive adaptive reweighted sampling (CARS) and stability competitive adaptive reweighted sampling (SCARS) were employed to select the important wavelengths. PLS-DA was applied to calibrate identified model using selected wavelength variables by CARS and SCARS for identification of solid state fermentation degree. Experimental results showed that the number of selected wavelength variables by CARS and SCARS were 58 and 47, respectively, from the 1557 original wavelength variables. Compared with the results of full-spectrum PLS-DA, the two wavelength variable selection methods both could enhance the performance of identified models. Meanwhile, compared with CARS-PLS-DA model, the SCARS-PLS-DA model achieved better results with the identification rate of 91.43% in the validation process. The overall results sufficiently demonstrate the PLS-DA model constructed using selected wavelength variables by a proper wavelength variable method can be more accurate identification of solid state fermentation degree.

  14. Disruption of Brewers' yeast by hydrodynamic cavitation: Process variables and their influence on selective release.

    Science.gov (United States)

    Balasundaram, B; Harrison, S T L

    2006-06-05

    Intracellular products, not secreted from the microbial cell, are released by breaking the cell envelope consisting of cytoplasmic membrane and an outer cell wall. Hydrodynamic cavitation has been reported to cause microbial cell disruption. By manipulating the operating variables involved, a wide range of intensity of cavitation can be achieved resulting in a varying extent of disruption. The effect of the process variables including cavitation number, initial cell concentration of the suspension and the number of passes across the cavitation zone on the release of enzymes from various locations of the Brewers' yeast was studied. The release profile of the enzymes studied include alpha-glucosidase (periplasmic), invertase (cell wall bound), alcohol dehydrogenase (ADH; cytoplasmic) and glucose-6-phosphate dehydrogenase (G6PDH; cytoplasmic). An optimum cavitation number Cv of 0.13 for maximum disruption was observed across the range Cv 0.09-0.99. The optimum cell concentration was found to be 0.5% (w/v, wet wt) when varying over the range 0.1%-5%. The sustained effect of cavitation on the yeast cell wall when re-circulating the suspension across the cavitation zone was found to release the cell wall bound enzyme invertase (86%) to a greater extent than the enzymes from other locations of the cell (e.g. periplasmic alpha-glucosidase at 17%). Localised damage to the cell wall could be observed using transmission electron microscopy (TEM) of cells subjected to less intense cavitation conditions. Absence of the release of cytoplasmic enzymes to a significant extent, absence of micronisation as observed by TEM and presence of a lower number of proteins bands in the culture supernatant on SDS-PAGE analysis following hydrodynamic cavitation compared to disruption by high-pressure homogenisation confirmed the selective release offered by hydrodynamic cavitation. Copyright 2006 Wiley Periodicals, Inc.

  15. FCERI AND HISTAMINE METABOLISM GENE VARIABILITY IN SELECTIVE RESPONDERS TO NSAIDS

    Directory of Open Access Journals (Sweden)

    Gemma Amo

    2016-09-01

    Full Text Available The high-affinity IgE receptor (Fcε RI is a heterotetramer of three subunits: Fcε RIα, Fcε RIβ and Fcε RIγ (αβγ2 encoded by three genes designated as FCER1A, FCER1B (MS4A2 and FCER1G, respectively. Recent evidence points to FCERI gene variability as a relevant factor in the risk of developing allergic diseases. Because Fcε RI plays a key role in the events downstream of the triggering factors in immunological response, we hypothesized that FCERI gene variants might be related with the risk of, or with the clinical response to, selective (IgE mediated non-steroidal anti-inflammatory (NSAID hypersensitivity.From a cohort of 314 patients suffering from selective hypersensitivity to metamizole, ibuprofen, diclofenac, paracetamol, acetylsalicylic acid (ASA, propifenazone, naproxen, ketoprofen, dexketoprofen, etofenamate, aceclofenac, etoricoxib, dexibuprofen, indomethacin, oxyphenylbutazone or piroxicam, and 585 unrelated healthy controls that tolerated these NSAIDs, we analyzed the putative effects of the FCERI SNPs FCER1A rs2494262, rs2427837 and rs2251746; FCER1B rs1441586, rs569108 and rs512555; FCER1G rs11587213, rs2070901 and rs11421. Furthermore, in order to identify additional genetic markers which might be associated with the risk of developing selective NSAID hypersensitivity, or which may modify the putative association of FCERI gene variations with risk, we analyzed polymorphisms known to affect histamine synthesis or metabolism, such as rs17740607, rs2073440, rs1801105, rs2052129, rs10156191, rs1049742 and rs1049793 in the HDC, HNMT and DAO genes.No major genetic associations with risk or with clinical presentation, and no gene-gene interactions, or gene-phenotype interactions (including age, gender, IgE concentration, antecedents of atopy, culprit drug or clinical presentation were identified in patients. However, logistic regression analyses indicated that the presence of antecedents of atopy and the DAO SNP rs2052129 (GG

  16. EFFECT OF CORE TRAINING ON SELECTED HEMATOLOGICAL VARIABLES AMONG BASKETBALL PLAYERS

    OpenAIRE

    K. Rejinadevi; Dr. C. Ramesh

    2017-01-01

    The purpose of the study was to find out the effect of core training on selected haematological variables among basketball players. For the purpose of the study forty men basketball players were selected as subjects from S.V.N College and Arul Anandar College, Madurai, Tamilnadu at random and their age ranged from 18 to 25 years. The selected subjects are divided in to two groups of twenty subjects each. Group I acted as core training group and Group II acted as control group. The experimenta...

  17. Sparse Reduced-Rank Regression for Simultaneous Dimension Reduction and Variable Selection

    KAUST Repository

    Chen, Lisha; Huang, Jianhua Z.

    2012-01-01

    and hence improves predictive accuracy. We propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty. We apply a group-lasso type penalty that treats each row of the matrix of the regression coefficients as a group

  18. Meta-Statistics for Variable Selection: The R Package BioMark

    Directory of Open Access Journals (Sweden)

    Ron Wehrens

    2012-11-01

    Full Text Available Biomarker identification is an ever more important topic in the life sciences. With the advent of measurement methodologies based on microarrays and mass spectrometry, thousands of variables are routinely being measured on complex biological samples. Often, the question is what makes two groups of samples different. Classical hypothesis testing suffers from the multiple testing problem; however, correcting for this often leads to a lack of power. In addition, choosing α cutoff levels remains somewhat arbitrary. Also in a regression context, a model depending on few but relevant variables will be more accurate and precise, and easier to interpret biologically.We propose an R package, BioMark, implementing two meta-statistics for variable selection. The first, higher criticism, presents a data-dependent selection threshold for significance, instead of a cookbook value of α = 0.05. It is applicable in all cases where two groups are compared. The second, stability selection, is more general, and can also be applied in a regression context. This approach uses repeated subsampling of the data in order to assess the variability of the model coefficients and selects those that remain consistently important. It is shown using experimental spike-in data from the field of metabolomics that both approaches work well with real data. BioMark also contains functionality for simulating data with specific characteristics for algorithm development and testing.

  19. A Robust Supervised Variable Selection for Noisy High-Dimensional Data

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan; Schlenker, Anna

    2015-01-01

    Roč. 2015, Article 320385 (2015), s. 1-10 ISSN 2314-6133 R&D Projects: GA ČR GA13-17187S Institutional support: RVO:67985807 Keywords : dimensionality reduction * variable selection * robustness Subject RIV: BA - General Mathematics Impact factor: 2.134, year: 2015

  20. Automatic variable selection method and a comparison for quantitative analysis in laser-induced breakdown spectroscopy

    Science.gov (United States)

    Duan, Fajie; Fu, Xiao; Jiang, Jiajia; Huang, Tingting; Ma, Ling; Zhang, Cong

    2018-05-01

    In this work, an automatic variable selection method for quantitative analysis of soil samples using laser-induced breakdown spectroscopy (LIBS) is proposed, which is based on full spectrum correction (FSC) and modified iterative predictor weighting-partial least squares (mIPW-PLS). The method features automatic selection without artificial processes. To illustrate the feasibility and effectiveness of the method, a comparison with genetic algorithm (GA) and successive projections algorithm (SPA) for different elements (copper, barium and chromium) detection in soil was implemented. The experimental results showed that all the three methods could accomplish variable selection effectively, among which FSC-mIPW-PLS required significantly shorter computation time (12 s approximately for 40,000 initial variables) than the others. Moreover, improved quantification models were got with variable selection approaches. The root mean square errors of prediction (RMSEP) of models utilizing the new method were 27.47 (copper), 37.15 (barium) and 39.70 (chromium) mg/kg, which showed comparable prediction effect with GA and SPA.

  1. Sparse supervised principal component analysis (SSPCA) for dimension reduction and variable selection

    DEFF Research Database (Denmark)

    Sharifzadeh, Sara; Ghodsi, Ali; Clemmensen, Line H.

    2017-01-01

    Principal component analysis (PCA) is one of the main unsupervised pre-processing methods for dimension reduction. When the training labels are available, it is worth using a supervised PCA strategy. In cases that both dimension reduction and variable selection are required, sparse PCA (SPCA...

  2. Cataclysmic variables from a ROSAT/2MASS selection - I. Four new intermediate polars

    NARCIS (Netherlands)

    Gänsicke, B.T.; Marsh, T.R.; Edge, A.; Rodríguez-Gil, P.; Steeghs, D.; Araujo-Betancor, S.; Harlaftis, E.; Giannakis, O.; Pyrzas, S.; Morales-Rueda, L.; Aungwerojwit, A.

    2005-01-01

    We report the first results from a new search for cataclysmic variables (CVs) using a combined X-ray (ROSAT)/infrared (2MASS) target selection that discriminates against background active galactic nuclei. Identification spectra were obtained at the Isaac Newton Telescope for a total of 174 targets,

  3. A QSAR Study of Environmental Estrogens Based on a Novel Variable Selection Method

    Directory of Open Access Journals (Sweden)

    Aiqian Zhang

    2012-05-01

    Full Text Available A large number of descriptors were employed to characterize the molecular structure of 53 natural, synthetic, and environmental chemicals which are suspected of disrupting endocrine functions by mimicking or antagonizing natural hormones and may thus pose a serious threat to the health of humans and wildlife. In this work, a robust quantitative structure-activity relationship (QSAR model with a novel variable selection method has been proposed for the effective estrogens. The variable selection method is based on variable interaction (VSMVI with leave-multiple-out cross validation (LMOCV to select the best subset. During variable selection, model construction and assessment, the Organization for Economic Co-operation and Development (OECD principles for regulation of QSAR acceptability were fully considered, such as using an unambiguous multiple-linear regression (MLR algorithm to build the model, using several validation methods to assessment the performance of the model, giving the define of applicability domain and analyzing the outliers with the results of molecular docking. The performance of the QSAR model indicates that the VSMVI is an effective, feasible and practical tool for rapid screening of the best subset from large molecular descriptors.

  4. Variable selection in the explorative analysis of several data blocks in metabolomics

    DEFF Research Database (Denmark)

    Karaman, İbrahim; Nørskov, Natalja; Yde, Christian Clement

    highly correlated data sets in one integrated approach. Due to the high number of variables in data sets from metabolomics (both raw data and after peak picking) the selection of important variables in an explorative analysis is difficult, especially when different data sets of metabolomics data need...... to be related. Tools for the handling of mental overflow minimising false discovery rates both by using statistical and biological validation in an integrative approach are needed. In this paper different strategies for variable selection were considered with respect to false discovery and the possibility...... for biological validation. The data set used in this study is metabolomics data from an animal intervention study. The aim of the metabolomics study was to investigate the metabolic profile in pigs fed various cereal fractions with special attention to the metabolism of lignans using NMR and LC-MS based...

  5. Multivariate fault isolation of batch processes via variable selection in partial least squares discriminant analysis.

    Science.gov (United States)

    Yan, Zhengbing; Kuang, Te-Hui; Yao, Yuan

    2017-09-01

    In recent years, multivariate statistical monitoring of batch processes has become a popular research topic, wherein multivariate fault isolation is an important step aiming at the identification of the faulty variables contributing most to the detected process abnormality. Although contribution plots have been commonly used in statistical fault isolation, such methods suffer from the smearing effect between correlated variables. In particular, in batch process monitoring, the high autocorrelations and cross-correlations that exist in variable trajectories make the smearing effect unavoidable. To address such a problem, a variable selection-based fault isolation method is proposed in this research, which transforms the fault isolation problem into a variable selection problem in partial least squares discriminant analysis and solves it by calculating a sparse partial least squares model. As different from the traditional methods, the proposed method emphasizes the relative importance of each process variable. Such information may help process engineers in conducting root-cause diagnosis. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  6. Penalized regression procedures for variable selection in the potential outcomes framework.

    Science.gov (United States)

    Ghosh, Debashis; Zhu, Yeying; Coffman, Donna L

    2015-05-10

    A recent topic of much interest in causal inference is model selection. In this article, we describe a framework in which to consider penalized regression approaches to variable selection for causal effects. The framework leads to a simple 'impute, then select' class of procedures that is agnostic to the type of imputation algorithm as well as penalized regression used. It also clarifies how model selection involves a multivariate regression model for causal inference problems and that these methods can be applied for identifying subgroups in which treatment effects are homogeneous. Analogies and links with the literature on machine learning methods, missing data, and imputation are drawn. A difference least absolute shrinkage and selection operator algorithm is defined, along with its multiple imputation analogs. The procedures are illustrated using a well-known right-heart catheterization dataset. Copyright © 2015 John Wiley & Sons, Ltd.

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

    Science.gov (United States)

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

    2018-01-01

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

  8. Effects of musical tempo on physiological, affective, and perceptual variables and performance of self-selected walking pace.

    Science.gov (United States)

    Almeida, Flávia Angélica Martins; Nunes, Renan Felipe Hartmann; Ferreira, Sandro Dos Santos; Krinski, Kleverton; Elsangedy, Hassan Mohamed; Buzzachera, Cosme Franklin; Alves, Ragami Chaves; Gregorio da Silva, Sergio

    2015-06-01

    [Purpose] This study investigated the effects of musical tempo on physiological, affective, and perceptual responses as well as the performance of self-selected walking pace. [Subjects] The study included 28 adult women between 29 and 51 years old. [Methods] The subjects were divided into three groups: no musical stimulation group (control), and 90 and 140 beats per minute musical tempo groups. Each subject underwent three experimental sessions: involved familiarization with the equipment, an incremental test to exhaustion, and a 30-min walk on a treadmill at a self-selected pace, respectively. During the self-selected walking session, physiological, perceptual, and affective variables were evaluated, and walking performance was evaluated at the end. [Results] There were no significant differences in physiological variables or affective response among groups. However, there were significant differences in perceptual response and walking performance among groups. [Conclusion] Fast music (140 beats per minute) promotes a higher rating of perceived exertion and greater performance in self-selected walking pace without significantly altering physiological variables or affective response.

  9. Using Copulas in the Estimation of the Economic Project Value in the Mining Industry, Including Geological Variability

    Science.gov (United States)

    Krysa, Zbigniew; Pactwa, Katarzyna; Wozniak, Justyna; Dudek, Michal

    2017-12-01

    Geological variability is one of the main factors that has an influence on the viability of mining investment projects and on the technical risk of geology projects. In the current scenario, analyses of economic viability of new extraction fields have been performed for the KGHM Polska Miedź S.A. underground copper mine at Fore Sudetic Monocline with the assumption of constant averaged content of useful elements. Research presented in this article is aimed at verifying the value of production from copper and silver ore for the same economic background with the use of variable cash flows resulting from the local variability of useful elements. Furthermore, the ore economic model is investigated for a significant difference in model value estimated with the use of linear correlation between useful elements content and the height of mine face, and the approach in which model parameters correlation is based upon the copula best matched information capacity criterion. The use of copula allows the simulation to take into account the multi variable dependencies at the same time, thereby giving a better reflection of the dependency structure, which linear correlation does not take into account. Calculation results of the economic model used for deposit value estimation indicate that the correlation between copper and silver estimated with the use of copula generates higher variation of possible project value, as compared to modelling correlation based upon linear correlation. Average deposit value remains unchanged.

  10. Uninformative variable elimination assisted by Gram-Schmidt Orthogonalization/successive projection algorithm for descriptor selection in QSAR

    DEFF Research Database (Denmark)

    Omidikia, Nematollah; Kompany-Zareh, Mohsen

    2013-01-01

    Employment of Uninformative Variable Elimination (UVE) as a robust variable selection method is reported in this study. Each regression coefficient represents the contribution of the corresponding variable in the established model, but in the presence of uninformative variables as well as colline......Employment of Uninformative Variable Elimination (UVE) as a robust variable selection method is reported in this study. Each regression coefficient represents the contribution of the corresponding variable in the established model, but in the presence of uninformative variables as well...... as collinearity reliability of the regression coefficient's magnitude is suspicious. Successive Projection Algorithm (SPA) and Gram-Schmidt Orthogonalization (GSO) were implemented as pre-selection technique for removing collinearity and redundancy among variables in the model. Uninformative variable elimination...

  11. Resiliency and subjective health assessment. Moderating role of selected psychosocial variables

    Directory of Open Access Journals (Sweden)

    Michalina Sołtys

    2015-12-01

    Full Text Available Background Resiliency is defined as a relatively permanent personality trait, which may be assigned to the category of health resources. The aim of this study was to determine conditions in which resiliency poses a significant health resource (moderation, thereby broadening knowledge of the specifics of the relationship between resiliency and subjective health assessment. Participants and procedure The study included 142 individuals. In order to examine the level of resiliency, the Assessment Resiliency Scale (SPP-25 by N. Ogińska-Bulik and Z. Juczyński was used. Participants evaluated subjective health state by means of an analogue-visual scale. Additionally, in the research the following moderating variables were controlled: sex, objective health status, having a partner, professional activity and age. These data were obtained by personal survey. Results The results confirmed the relationship between resiliency and subjective health assessment. Multiple regression analysis revealed that sex, having a partner and professional activity are significant moderators of associations between level of resiliency and subjective health evaluation. However, statistically significant interaction effects for health status and age as a moderator were not observed. Conclusions Resiliency is associated with subjective health assessment among adults, and selected socio-demographic features (such as sex, having a partner, professional activity moderate this relationship. This confirms the significant role of resiliency as a health resource and a reason to emphasize the benefits of enhancing the potential of individuals for their psychophysical wellbeing. However, the research requires replication in a more homogeneous sample.

  12. Effects of carprofen or meloxicam on selected haemostatic variables in miniature pigs after orthopaedic surgery

    Directory of Open Access Journals (Sweden)

    Petr Raušer

    2011-01-01

    Full Text Available The aim of the study was to detect and compare the haemostatic variables and bleeding after 7‑days administration of carprofen or meloxicam in clinically healthy miniature pigs. Twenty-one clinically healthy Göttingen miniature pigs were divided into 3 groups. Selected haemostatic variables such as platelet count, prothrombin time, activated partial thromboplastin time, thrombin time, fibrinogen, serum biochemical variables such as total protein, bilirubin, urea, creatinine, alkaline phosphatase, alanine aminotransferase and gamma-glutamyltransferase and haemoglobin, haematocrit, red blood cells, white blood cells and buccal mucosal bleeding time were assessed before and 7 days after daily intramuscular administration of saline (1.5 ml per animal, control group, carprofen (2 mg·kg-1 or meloxicam (0.1 mg·kg-1. In pigs receiving carprofen or meloxicam, the thrombin time was significantly increased (p p p p < 0.05 compared to the control group. Significant differences were not detected in other haemostatic, biochemical variables or bleeding time compared to other groups or to the pretreatment values. Intramuscular administration of carprofen or meloxicam in healthy miniature pigs for 7 days causes sporadic, but not clinically important changes of selected haemostatic variables. Therefore, we can recommend them for perioperative use, e.g. for their analgesic effects, in orthopaedic or other surgical procedures without increased bleeding.

  13. 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

  14. Sensor combination and chemometric variable selection for online monitoring of Streptomyces coelicolor fed-batch cultivations

    DEFF Research Database (Denmark)

    Ödman, Peter; Johansen, C.L.; Olsson, L.

    2010-01-01

    of biomass and substrate (casamino acids) concentrations, respectively. The effect of combination of fluorescence and gas analyzer data as well as of different variable selection methods was investigated. Improved prediction models were obtained by combination of data from the two sensors and by variable......Fed-batch cultivations of Streptomyces coelicolor, producing the antibiotic actinorhodin, were monitored online by multiwavelength fluorescence spectroscopy and off-gas analysis. Partial least squares (PLS), locally weighted regression, and multilinear PLS (N-PLS) models were built for prediction...

  15. Inlet-engine matching for SCAR including application of a bicone variable geometry inlet. [Supersonic Cruise Aircraft Research

    Science.gov (United States)

    Wasserbauer, J. F.; Gerstenmaier, W. H.

    1978-01-01

    Airflow characteristics of variable cycle engines (VCE) designed for Mach 2.32 can have transonic airflow requirements as high as 1.6 times the cruise airflow. This is a formidable requirement for conventional, high performance, axisymmetric, translating centerbody mixed compression inlets. An alternate inlet is defined where the second cone of a two cone centerbody collapses to the initial cone angle to provide a large off-design airflow capability, and incorporates modest centerbody translation to minimize spillage drag. Estimates of transonic spillage drag are competitive with those of conventional translating centerbody inlets. The inlet's cruise performance exhibits very low bleed requirements with good recovery and high angle of attack capability.

  16. A New Variable Selection Method Based on Mutual Information Maximization by Replacing Collinear Variables for Nonlinear Quantitative Structure-Property Relationship Models

    Energy Technology Data Exchange (ETDEWEB)

    Ghasemi, Jahan B.; Zolfonoun, Ehsan [Toosi University of Technology, Tehran (Korea, Republic of)

    2012-05-15

    Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms.

  17. A New Variable Selection Method Based on Mutual Information Maximization by Replacing Collinear Variables for Nonlinear Quantitative Structure-Property Relationship Models

    International Nuclear Information System (INIS)

    Ghasemi, Jahan B.; Zolfonoun, Ehsan

    2012-01-01

    Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms

  18. Calibration Variable Selection and Natural Zero Determination for Semispan and Canard Balances

    Science.gov (United States)

    Ulbrich, Norbert M.

    2013-01-01

    Independent calibration variables for the characterization of semispan and canard wind tunnel balances are discussed. It is shown that the variable selection for a semispan balance is determined by the location of the resultant normal and axial forces that act on the balance. These two forces are the first and second calibration variable. The pitching moment becomes the third calibration variable after the normal and axial forces are shifted to the pitch axis of the balance. Two geometric distances, i.e., the rolling and yawing moment arms, are the fourth and fifth calibration variable. They are traditionally substituted by corresponding moments to simplify the use of calibration data during a wind tunnel test. A canard balance is related to a semispan balance. It also only measures loads on one half of a lifting surface. However, the axial force and yawing moment are of no interest to users of a canard balance. Therefore, its calibration variable set is reduced to the normal force, pitching moment, and rolling moment. The combined load diagrams of the rolling and yawing moment for a semispan balance are discussed. They may be used to illustrate connections between the wind tunnel model geometry, the test section size, and the calibration load schedule. Then, methods are reviewed that may be used to obtain the natural zeros of a semispan or canard balance. In addition, characteristics of three semispan balance calibration rigs are discussed. Finally, basic requirements for a full characterization of a semispan balance are reviewed.

  19. Joint Bayesian variable and graph selection for regression models with network-structured predictors

    Science.gov (United States)

    Peterson, C. B.; Stingo, F. C.; Vannucci, M.

    2015-01-01

    In this work, we develop a Bayesian approach to perform selection of predictors that are linked within a network. We achieve this by combining a sparse regression model relating the predictors to a response variable with a graphical model describing conditional dependencies among the predictors. The proposed method is well-suited for genomic applications since it allows the identification of pathways of functionally related genes or proteins which impact an outcome of interest. In contrast to previous approaches for network-guided variable selection, we infer the network among predictors using a Gaussian graphical model and do not assume that network information is available a priori. We demonstrate that our method outperforms existing methods in identifying network-structured predictors in simulation settings, and illustrate our proposed model with an application to inference of proteins relevant to glioblastoma survival. PMID:26514925

  20. Demographic Variables and Selective, Sustained Attention and Planning through Cognitive Tasks among Healthy Adults

    Directory of Open Access Journals (Sweden)

    Afsaneh Zarghi

    2011-04-01

    Full Text Available Introduction: Cognitive tasks are considered to be applicable and appropriate in assessing cognitive domains. The purpose of our study is to determine the relationship existence between variables of age, sex and education with selective, sustained attention and planning abilities by means of computerized cognitive tasks among healthy adults. Methods: A cross-sectional study was implemented during 6 months from June to November, 2010 on 84 healthy adults (42 male and 42 female. The whole participants performed computerized CPT, STROOP and TOL tests after being content and trained. Results: The obtained data indicate that there is a significant correlation coefficient between age, sex and education variables (p<0.05. Discussion: The above-mentioned tests can be used to assess selective, sustained attention and planning.

  1. Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification

    Directory of Open Access Journals (Sweden)

    C. Fernandez-Lozano

    2013-01-01

    Full Text Available Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM. Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA, the most representative variables for a specific classification problem can be selected.

  2. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method

    OpenAIRE

    Jun-He Yang; Ching-Hsue Cheng; Chia-Pan Chan

    2017-01-01

    Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting m...

  3. Demographic Variables and Selective, Sustained Attention and Planning through Cognitive Tasks among Healthy Adults

    OpenAIRE

    Afsaneh Zarghi; Zali; A; Tehranidost; M; Mohammad Reza Zarindast; Ashrafi; F; Doroodgar; Khodadadi

    2011-01-01

    Introduction: Cognitive tasks are considered to be applicable and appropriate in assessing cognitive domains. The purpose of our study is to determine the relationship existence between variables of age, sex and education with selective, sustained attention and planning abilities by means of computerized cognitive tasks among healthy adults. Methods: A cross-sectional study was implemented during 6 months from June to November, 2010 on 84 healthy adults (42 male and 42 female). The whole part...

  4. gamboostLSS: An R Package for Model Building and Variable Selection in the GAMLSS Framework

    OpenAIRE

    Hofner, Benjamin; Mayr, Andreas; Schmid, Matthias

    2014-01-01

    Generalized additive models for location, scale and shape are a flexible class of regression models that allow to model multiple parameters of a distribution function, such as the mean and the standard deviation, simultaneously. With the R package gamboostLSS, we provide a boosting method to fit these models. Variable selection and model choice are naturally available within this regularized regression framework. To introduce and illustrate the R package gamboostLSS and its infrastructure, we...

  5. Data re-arranging techniques leading to proper variable selections in high energy physics

    Science.gov (United States)

    Kůs, Václav; Bouř, Petr

    2017-12-01

    We introduce a new data based approach to homogeneity testing and variable selection carried out in high energy physics experiments, where one of the basic tasks is to test the homogeneity of weighted samples, mainly the Monte Carlo simulations (weighted) and real data measurements (unweighted). This technique is called ’data re-arranging’ and it enables variable selection performed by means of the classical statistical homogeneity tests such as Kolmogorov-Smirnov, Anderson-Darling, or Pearson’s chi-square divergence test. P-values of our variants of homogeneity tests are investigated and the empirical verification through 46 dimensional high energy particle physics data sets is accomplished under newly proposed (equiprobable) quantile binning. Particularly, the procedure of homogeneity testing is applied to re-arranged Monte Carlo samples and real DATA sets measured at the particle accelerator Tevatron in Fermilab at DØ experiment originating from top-antitop quark pair production in two decay channels (electron, muon) with 2, 3, or 4+ jets detected. Finally, the variable selections in the electron and muon channels induced by the re-arranging procedure for homogeneity testing are provided for Tevatron top-antitop quark data sets.

  6. The XRF spectrometer and the selection of analysis conditions (instrumental variables)

    International Nuclear Information System (INIS)

    Willis, J.P.

    2002-01-01

    Full text: This presentation will begin with a brief discussion of EDXRF and flat- and curved-crystal WDXRF spectrometers, contrasting the major differences between the three types. The remainder of the presentation will contain a detailed overview of the choice and settings of the many instrumental variables contained in a modern WDXRF spectrometer, and will discuss critically the choices facing the analyst in setting up a WDXRF spectrometer for different elements and applications. In particular it will discuss the choice of tube target (when a choice is possible), the kV and mA settings, tube filters, collimator masks, collimators, analyzing crystals, secondary collimators, detectors, pulse height selection, X-ray path medium (air, nitrogen, vacuum or helium), counting times for peak and background positions and their effect on counting statistics and lower limit of detection (LLD). The use of Figure of Merit (FOM) calculations to objectively choose the best combination of instrumental variables also will be discussed. This presentation will be followed by a shorter session on a subsequent day entitled - A Selection of XRF Conditions - Practical Session, where participants will be given the opportunity to discuss in groups the selection of the best instrumental variables for three very diverse applications. Copyright (2002) Australian X-ray Analytical Association Inc

  7. Variable selection based near infrared spectroscopy quantitative and qualitative analysis on wheat wet gluten

    Science.gov (United States)

    Lü, Chengxu; Jiang, Xunpeng; Zhou, Xingfan; Zhang, Yinqiao; Zhang, Naiqian; Wei, Chongfeng; Mao, Wenhua

    2017-10-01

    Wet gluten is a useful quality indicator for wheat, and short wave near infrared spectroscopy (NIRS) is a high performance technique with the advantage of economic rapid and nondestructive test. To study the feasibility of short wave NIRS analyzing wet gluten directly from wheat seed, 54 representative wheat seed samples were collected and scanned by spectrometer. 8 spectral pretreatment method and genetic algorithm (GA) variable selection method were used to optimize analysis. Both quantitative and qualitative model of wet gluten were built by partial least squares regression and discriminate analysis. For quantitative analysis, normalization is the optimized pretreatment method, 17 wet gluten sensitive variables are selected by GA, and GA model performs a better result than that of all variable model, with R2V=0.88, and RMSEV=1.47. For qualitative analysis, automatic weighted least squares baseline is the optimized pretreatment method, all variable models perform better results than those of GA models. The correct classification rates of 3 class of 30% wet gluten content are 95.45, 84.52, and 90.00%, respectively. The short wave NIRS technique shows potential for both quantitative and qualitative analysis of wet gluten for wheat seed.

  8. The Use of Variable Q1 Isolation Windows Improves Selectivity in LC-SWATH-MS Acquisition.

    Science.gov (United States)

    Zhang, Ying; Bilbao, Aivett; Bruderer, Tobias; Luban, Jeremy; Strambio-De-Castillia, Caterina; Lisacek, Frédérique; Hopfgartner, Gérard; Varesio, Emmanuel

    2015-10-02

    As tryptic peptides and metabolites are not equally distributed along the mass range, the probability of cross fragment ion interference is higher in certain windows when fixed Q1 SWATH windows are applied. We evaluated the benefits of utilizing variable Q1 SWATH windows with regards to selectivity improvement. Variable windows based on equalizing the distribution of either the precursor ion population (PIP) or the total ion current (TIC) within each window were generated by an in-house software, swathTUNER. These two variable Q1 SWATH window strategies outperformed, with respect to quantification and identification, the basic approach using a fixed window width (FIX) for proteomic profiling of human monocyte-derived dendritic cells (MDDCs). Thus, 13.8 and 8.4% additional peptide precursors, which resulted in 13.1 and 10.0% more proteins, were confidently identified by SWATH using the strategy PIP and TIC, respectively, in the MDDC proteomic sample. On the basis of the spectral library purity score, some improvement warranted by variable Q1 windows was also observed, albeit to a lesser extent, in the metabolomic profiling of human urine. We show that the novel concept of "scheduled SWATH" proposed here, which incorporates (i) variable isolation windows and (ii) precursor retention time segmentation further improves both peptide and metabolite identifications.

  9. Oracle Efficient Variable Selection in Random and Fixed Effects Panel Data Models

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl

    This paper generalizes the results for the Bridge estimator of Huang et al. (2008) to linear random and fixed effects panel data models which are allowed to grow in both dimensions. In particular we show that the Bridge estimator is oracle efficient. It can correctly distinguish between relevant...... and irrelevant variables and the asymptotic distribution of the estimators of the coefficients of the relevant variables is the same as if only these had been included in the model, i.e. as if an oracle had revealed the true model prior to estimation. In the case of more explanatory variables than observations......, we prove that the Marginal Bridge estimator can asymptotically correctly distinguish between relevant and irrelevant explanatory variables. We do this without restricting the dependence between covariates and without assuming sub Gaussianity of the error terms thereby generalizing the results...

  10. Major histocompatibility complex harbors widespread genotypic variability of non-additive risk of rheumatoid arthritis including epistasis.

    Science.gov (United States)

    Wei, Wen-Hua; Bowes, John; Plant, Darren; Viatte, Sebastien; Yarwood, Annie; Massey, Jonathan; Worthington, Jane; Eyre, Stephen

    2016-04-25

    Genotypic variability based genome-wide association studies (vGWASs) can identify potentially interacting loci without prior knowledge of the interacting factors. We report a two-stage approach to make vGWAS applicable to diseases: firstly using a mixed model approach to partition dichotomous phenotypes into additive risk and non-additive environmental residuals on the liability scale and secondly using the Levene's (Brown-Forsythe) test to assess equality of the residual variances across genotype groups per marker. We found widespread significant (P 5e-05) vGWAS signals within the major histocompatibility complex (MHC) across all three study cohorts of rheumatoid arthritis. We further identified 10 epistatic interactions between the vGWAS signals independent of the MHC additive effects, each with a weak effect but jointly explained 1.9% of phenotypic variance. PTPN22 was also identified in the discovery cohort but replicated in only one independent cohort. Combining the three cohorts boosted power of vGWAS and additionally identified TYK2 and ANKRD55. Both PTPN22 and TYK2 had evidence of interactions reported elsewhere. We conclude that vGWAS can help discover interacting loci for complex diseases but require large samples to find additional signals.

  11. HEART RATE VARIABILITY CLASSIFICATION USING SADE-ELM CLASSIFIER WITH BAT FEATURE SELECTION

    Directory of Open Access Journals (Sweden)

    R Kavitha

    2017-07-01

    Full Text Available The electrical activity of the human heart is measured by the vital bio medical signal called ECG. This electrocardiogram is employed as a crucial source to gather the diagnostic information of a patient’s cardiopathy. The monitoring function of cardiac disease is diagnosed by documenting and handling the electrocardiogram (ECG impulses. In the recent years many research has been done and developing an enhanced method to identify the risk in the patient’s body condition by processing and analysing the ECG signal. This analysis of the signal helps to find the cardiac abnormalities, arrhythmias, and many other heart problems. ECG signal is processed to detect the variability in heart rhythm; heart rate variability is calculated based on the time interval between heart beats. Heart Rate Variability HRV is measured by the variation in the beat to beat interval. The Heart rate Variability (HRV is an essential aspect to diagnose the properties of the heart. Recent development enhances the potential with the aid of non-linear metrics in reference point with feature selection. In this paper, the fundamental elements are taken from the ECG signal for feature selection process where Bat algorithm is employed for feature selection to predict the best feature and presented to the classifier for accurate classification. The popular machine learning algorithm ELM is taken for classification, integrated with evolutionary algorithm named Self- Adaptive Differential Evolution Extreme Learning Machine SADEELM to improve the reliability of classification. It combines Effective Fuzzy Kohonen clustering network (EFKCN to be able to increase the accuracy of the effect for HRV transmission classification. Hence, it is observed that the experiment carried out unveils that the precision is improved by the SADE-ELM method and concurrently optimizes the computation time.

  12. Impact of menstruation on select hematology and clinical chemistry variables in cynomolgus macaques.

    Science.gov (United States)

    Perigard, Christopher J; Parrula, M Cecilia M; Larkin, Matthew H; Gleason, Carol R

    2016-06-01

    In preclinical studies with cynomolgus macaques, it is common to have one or more females presenting with menses. Published literature indicates that the blood lost during menses causes decreases in red blood cell mass variables (RBC, HGB, and HCT), which would be a confounding factor in the interpretation of drug-related effects on clinical pathology data, but no scientific data have been published to support this claim. This investigation was conducted to determine if the amount of blood lost during menses in cynomolgus macaques has an effect on routine hematology and serum chemistry variables. Ten female cynomolgus macaques (Macaca fascicularis), 5 to 6.5 years old, were observed daily during approximately 3 months (97 days) for the presence of menses. Hematology and serum chemistry variables were evaluated twice weekly. The results indicated that menstruation affects the erythrogram including RBC, HGB, HCT, MCHC, MCV, reticulocyte count, RDW, the leukogram including neutrophil, lymphocyte, and monocyte counts, and chemistry variables, including GGT activity, and the concentrations of total proteins, albumin, globulins, and calcium. The magnitude of the effect of menstruation on susceptible variables is dependent on the duration of the menstrual phase. Macaques with menstrual phases lasting ≥ 7 days are more likely to develop changes in variables related to chronic blood loss. In preclinical toxicology studies with cynomolgus macaques, interpretation of changes in several commonly evaluated hematology and serum chemistry variables requires adequate clinical observation and documentation concerning presence and duration of menses. There is a concern that macaques with long menstrual cycles can develop iron deficiency anemia due to chronic menstrual blood loss. © 2016 American Society for Veterinary Clinical Pathology.

  13. Large Variability in the Diversity of Physiologically Complex Surgical Procedures Exists Nationwide Among All Hospitals Including Among Large Teaching Hospitals.

    Science.gov (United States)

    Dexter, Franklin; Epstein, Richard H; Thenuwara, Kokila; Lubarsky, David A

    2017-11-22

    Multiple previous studies have shown that having a large diversity of procedures has a substantial impact on quality management of hospital surgical suites. At hospitals with substantial diversity, unless sophisticated statistical methods suitable for rare events are used, anesthesiologists working in surgical suites will have inaccurate predictions of surgical blood usage, case durations, cost accounting and price transparency, times remaining in late running cases, and use of intraoperative equipment. What is unknown is whether large diversity is a feature of only a few very unique set of hospitals nationwide (eg, the largest hospitals in each state or province). The 2013 United States Nationwide Readmissions Database was used to study heterogeneity among 1981 hospitals in their diversities of physiologically complex surgical procedures (ie, the procedure codes). The diversity of surgical procedures performed at each hospital was quantified using a summary measure, the number of different physiologically complex surgical procedures commonly performed at the hospital (ie, 1/Herfindahl). A total of 53.9% of all hospitals commonly performed 3-fold larger diversity (ie, >30 commonly performed physiologically complex procedures). Larger hospitals had greater diversity than the small- and medium-sized hospitals (P 30 procedures (lower 99% CL, 71.9% of hospitals). However, there was considerable variability among the large teaching hospitals in their diversity (interquartile range of the numbers of commonly performed physiologically complex procedures = 19.3; lower 99% CL, 12.8 procedures). The diversity of procedures represents a substantive differentiator among hospitals. Thus, the usefulness of statistical methods for operating room management should be expected to be heterogeneous among hospitals. Our results also show that "large teaching hospital" alone is an insufficient description for accurate prediction of the extent to which a hospital sustains the

  14. Selection of controlled variables in bioprocesses. Application to a SHARON-Anammox process for autotrophic nitrogen removal

    DEFF Research Database (Denmark)

    Mauricio Iglesias, Miguel; Valverde Perez, Borja; Sin, Gürkan

    Selecting the right controlled variables in a bioprocess is challenging since the objectives of the process (yields, product or substrate concentration) are difficult to relate with a given actuator. We apply here process control tools that can be used to assist in the selection of controlled var...... variables to the case of the SHARON-Anammox process for autotrophic nitrogen removal....

  15. Applicability of bioanalysis of multiple analytes in drug discovery and development: review of select case studies including assay development considerations.

    Science.gov (United States)

    Srinivas, Nuggehally R

    2006-05-01

    The development of sound bioanalytical method(s) is of paramount importance during the process of drug discovery and development culminating in a marketing approval. Although the bioanalytical procedure(s) originally developed during the discovery stage may not necessarily be fit to support the drug development scenario, they may be suitably modified and validated, as deemed necessary. Several reviews have appeared over the years describing analytical approaches including various techniques, detection systems, automation tools that are available for an effective separation, enhanced selectivity and sensitivity for quantitation of many analytes. The intention of this review is to cover various key areas where analytical method development becomes necessary during different stages of drug discovery research and development process. The key areas covered in this article with relevant case studies include: (a) simultaneous assay for parent compound and metabolites that are purported to display pharmacological activity; (b) bioanalytical procedures for determination of multiple drugs in combating a disease; (c) analytical measurement of chirality aspects in the pharmacokinetics, metabolism and biotransformation investigations; (d) drug monitoring for therapeutic benefits and/or occupational hazard; (e) analysis of drugs from complex and/or less frequently used matrices; (f) analytical determination during in vitro experiments (metabolism and permeability related) and in situ intestinal perfusion experiments; (g) determination of a major metabolite as a surrogate for the parent molecule; (h) analytical approaches for universal determination of CYP450 probe substrates and metabolites; (i) analytical applicability to prodrug evaluations-simultaneous determination of prodrug, parent and metabolites; (j) quantitative determination of parent compound and/or phase II metabolite(s) via direct or indirect approaches; (k) applicability in analysis of multiple compounds in select

  16. Variable Selection Strategies for Small-area Estimation Using FIA Plots and Remotely Sensed Data

    Science.gov (United States)

    Andrew Lister; Rachel Riemann; James Westfall; Mike Hoppus

    2005-01-01

    The USDA Forest Service's Forest Inventory and Analysis (FIA) unit maintains a network of tens of thousands of georeferenced forest inventory plots distributed across the United States. Data collected on these plots include direct measurements of tree diameter and height and other variables. We present a technique by which FIA plot data and coregistered...

  17. Variable selection for modelling effects of eutrophication on stream and river ecosystems

    NARCIS (Netherlands)

    Nijboer, R.C.; Verdonschot, P.F.M.

    2004-01-01

    Models are needed for forecasting the effects of eutrophication on stream and river ecosystems. Most of the current models do not include differences in local stream characteristics and effects on the biota. To define the most important variables that should be used in a stream eutrophication model,

  18. Model Selection and Evaluation Based on Emerging Infectious Disease Data Sets including A/H1N1 and Ebola

    Directory of Open Access Journals (Sweden)

    Wendi Liu

    2015-01-01

    Full Text Available The aim of the present study is to apply simple ODE models in the area of modeling the spread of emerging infectious diseases and show the importance of model selection in estimating parameters, the basic reproduction number, turning point, and final size. To quantify the plausibility of each model, given the data and the set of four models including Logistic, Gompertz, Rosenzweg, and Richards models, the Bayes factors are calculated and the precise estimates of the best fitted model parameters and key epidemic characteristics have been obtained. In particular, for Ebola the basic reproduction numbers are 1.3522 (95% CI (1.3506, 1.3537, 1.2101 (95% CI (1.2084, 1.2119, 3.0234 (95% CI (2.6063, 3.4881, and 1.9018 (95% CI (1.8565, 1.9478, the turning points are November 7,November 17, October 2, and November 3, 2014, and the final sizes until December 2015 are 25794 (95% CI (25630, 25958, 3916 (95% CI (3865, 3967, 9886 (95% CI (9740, 10031, and 12633 (95% CI (12515, 12750 for West Africa, Guinea, Liberia, and Sierra Leone, respectively. The main results confirm that model selection is crucial in evaluating and predicting the important quantities describing the emerging infectious diseases, and arbitrarily picking a model without any consideration of alternatives is problematic.

  19. Closed-form solutions for linear regulator-design of mechanical systems including optimal weighting matrix selection

    Science.gov (United States)

    Hanks, Brantley R.; Skelton, Robert E.

    1991-01-01

    This paper addresses the restriction of Linear Quadratic Regulator (LQR) solutions to the algebraic Riccati Equation to design spaces which can be implemented as passive structural members and/or dampers. A general closed-form solution to the optimal free-decay control problem is presented which is tailored for structural-mechanical systems. The solution includes, as subsets, special cases such as the Rayleigh Dissipation Function and total energy. Weighting matrix selection is a constrained choice among several parameters to obtain desired physical relationships. The closed-form solution is also applicable to active control design for systems where perfect, collocated actuator-sensor pairs exist. Some examples of simple spring mass systems are shown to illustrate key points.

  20. Extreme precipitation variability, forage quality and large herbivore diet selection in arid environments

    Science.gov (United States)

    Cain, James W.; Gedir, Jay V.; Marshal, Jason P.; Krausman, Paul R.; Allen, Jamison D.; Duff, Glenn C.; Jansen, Brian; Morgart, John R.

    2017-01-01

    Nutritional ecology forms the interface between environmental variability and large herbivore behaviour, life history characteristics, and population dynamics. Forage conditions in arid and semi-arid regions are driven by unpredictable spatial and temporal patterns in rainfall. Diet selection by herbivores should be directed towards overcoming the most pressing nutritional limitation (i.e. energy, protein [nitrogen, N], moisture) within the constraints imposed by temporal and spatial variability in forage conditions. We investigated the influence of precipitation-induced shifts in forage nutritional quality and subsequent large herbivore responses across widely varying precipitation conditions in an arid environment. Specifically, we assessed seasonal changes in diet breadth and forage selection of adult female desert bighorn sheep Ovis canadensis mexicana in relation to potential nutritional limitations in forage N, moisture and energy content (as proxied by dry matter digestibility, DMD). Succulents were consistently high in moisture but low in N and grasses were low in N and moisture until the wet period. Nitrogen and moisture content of shrubs and forbs varied among seasons and climatic periods, whereas trees had consistently high N and moderate moisture levels. Shrubs, trees and succulents composed most of the seasonal sheep diets but had little variation in DMD. Across all seasons during drought and during summer with average precipitation, forages selected by sheep were higher in N and moisture than that of available forage. Differences in DMD between sheep diets and available forage were minor. Diet breadth was lowest during drought and increased with precipitation, reflecting a reliance on few key forage species during drought. Overall, forage selection was more strongly associated with N and moisture content than energy content. Our study demonstrates that unlike north-temperate ungulates which are generally reported to be energy-limited, N and moisture

  1. Impact of perennial energy crops income variability on the crop selection of risk averse farmers

    International Nuclear Information System (INIS)

    Alexander, Peter; Moran, Dominic

    2013-01-01

    The UK Government policy is for the area of perennial energy crops in the UK to expand significantly. Farmers need to choose these crops in preference to conventional rotations for this to be achievable. This paper looks at the potential level and variability of perennial energy crop incomes and the relation to incomes from conventional arable crops. Assuming energy crop prices are correlated to oil prices the results suggests that incomes from them are not well correlated to conventional arable crop incomes. A farm scale mathematical programming model is then used to attempt to understand the affect on risk averse farmers crop selection. The inclusion of risk reduces the energy crop price required for the selection of these crops. However yields towards the highest of those predicted in the UK are still required to make them an optimal choice, suggesting only a small area of energy crops within the UK would be expected to be chosen to be grown. This must be regarded as a tentative conclusion, primarily due to high sensitivity found to crop yields, resulting in the proposal for further work to apply the model using spatially disaggregated data. - Highlights: ► Energy crop and conventional crop incomes suggested as uncorrelated. ► Diversification effect of energy crops investigated for a risk averse farmer. ► Energy crops indicated as optimal selection only on highest yielding UK sites. ► Large establishment grant rates to substantially alter crop selections.

  2. Soil Cd, Cr, Cu, Ni, Pb and Zn sorption and retention models using SVM: Variable selection and competitive model.

    Science.gov (United States)

    González Costa, J J; Reigosa, M J; Matías, J M; Covelo, E F

    2017-09-01

    The aim of this study was to model the sorption and retention of Cd, Cu, Ni, Pb and Zn in soils. To that extent, the sorption and retention of these metals were studied and the soil characterization was performed separately. Multiple stepwise regression was used to produce multivariate models with linear techniques and with support vector machines, all of which included 15 explanatory variables characterizing soils. When the R-squared values are represented, two different groups are noticed. Cr, Cu and Pb sorption and retention show a higher R-squared; the most explanatory variables being humified organic matter, Al oxides and, in some cases, cation-exchange capacity (CEC). The other group of metals (Cd, Ni and Zn) shows a lower R-squared, and clays are the most explanatory variables, including a percentage of vermiculite and slime. In some cases, quartz, plagioclase or hematite percentages also show some explanatory capacity. Support Vector Machine (SVM) regression shows that the different models are not as regular as in multiple regression in terms of number of variables, the regression for nickel adsorption being the one with the highest number of variables in its optimal model. On the other hand, there are cases where the most explanatory variables are the same for two metals, as it happens with Cd and Cr adsorption. A similar adsorption mechanism is thus postulated. These patterns of the introduction of variables in the model allow us to create explainability sequences. Those which are the most similar to the selectivity sequences obtained by Covelo (2005) are Mn oxides in multiple regression and change capacity in SVM. Among all the variables, the only one that is explanatory for all the metals after applying the maximum parsimony principle is the percentage of sand in the retention process. In the competitive model arising from the aforementioned sequences, the most intense competitiveness for the adsorption and retention of different metals appears between

  3. Prediction of Placental Barrier Permeability: A Model Based on Partial Least Squares Variable Selection Procedure

    Directory of Open Access Journals (Sweden)

    Yong-Hong Zhang

    2015-05-01

    Full Text Available Assessing the human placental barrier permeability of drugs is very important to guarantee drug safety during pregnancy. Quantitative structure–activity relationship (QSAR method was used as an effective assessing tool for the placental transfer study of drugs, while in vitro human placental perfusion is the most widely used method. In this study, the partial least squares (PLS variable selection and modeling procedure was used to pick out optimal descriptors from a pool of 620 descriptors of 65 compounds and to simultaneously develop a QSAR model between the descriptors and the placental barrier permeability expressed by the clearance indices (CI. The model was subjected to internal validation by cross-validation and y-randomization and to external validation by predicting CI values of 19 compounds. It was shown that the model developed is robust and has a good predictive potential (r2 = 0.9064, RMSE = 0.09, q2 = 0.7323, rp2 = 0.7656, RMSP = 0.14. The mechanistic interpretation of the final model was given by the high variable importance in projection values of descriptors. Using PLS procedure, we can rapidly and effectively select optimal descriptors and thus construct a model with good stability and predictability. This analysis can provide an effective tool for the high-throughput screening of the placental barrier permeability of drugs.

  4. Locating disease genes using Bayesian variable selection with the Haseman-Elston method

    Directory of Open Access Journals (Sweden)

    He Qimei

    2003-12-01

    Full Text Available Abstract Background We applied stochastic search variable selection (SSVS, a Bayesian model selection method, to the simulated data of Genetic Analysis Workshop 13. We used SSVS with the revisited Haseman-Elston method to find the markers linked to the loci determining change in cholesterol over time. To study gene-gene interaction (epistasis and gene-environment interaction, we adopted prior structures, which incorporate the relationship among the predictors. This allows SSVS to search in the model space more efficiently and avoid the less likely models. Results In applying SSVS, instead of looking at the posterior distribution of each of the candidate models, which is sensitive to the setting of the prior, we ranked the candidate variables (markers according to their marginal posterior probability, which was shown to be more robust to the prior. Compared with traditional methods that consider one marker at a time, our method considers all markers simultaneously and obtains more favorable results. Conclusions We showed that SSVS is a powerful method for identifying linked markers using the Haseman-Elston method, even for weak effects. SSVS is very effective because it does a smart search over the entire model space.

  5. A fast chaos-based image encryption scheme with a dynamic state variables selection mechanism

    Science.gov (United States)

    Chen, Jun-xin; Zhu, Zhi-liang; Fu, Chong; Yu, Hai; Zhang, Li-bo

    2015-03-01

    In recent years, a variety of chaos-based image cryptosystems have been investigated to meet the increasing demand for real-time secure image transmission. Most of them are based on permutation-diffusion architecture, in which permutation and diffusion are two independent procedures with fixed control parameters. This property results in two flaws. (1) At least two chaotic state variables are required for encrypting one plain pixel, in permutation and diffusion stages respectively. Chaotic state variables produced with high computation complexity are not sufficiently used. (2) The key stream solely depends on the secret key, and hence the cryptosystem is vulnerable against known/chosen-plaintext attacks. In this paper, a fast chaos-based image encryption scheme with a dynamic state variables selection mechanism is proposed to enhance the security and promote the efficiency of chaos-based image cryptosystems. Experimental simulations and extensive cryptanalysis have been carried out and the results prove the superior security and high efficiency of the scheme.

  6. Relation between sick leave and selected exposure variables among women semiconductor workers in Malaysia

    Science.gov (United States)

    Chee, H; Rampal, K

    2003-01-01

    Aims: To determine the relation between sick leave and selected exposure variables among women semiconductor workers. Methods: This was a cross sectional survey of production workers from 18 semiconductor factories. Those selected had to be women, direct production operators up to the level of line leader, and Malaysian citizens. Sick leave and exposure to physical and chemical hazards were determined by self reporting. Three sick leave variables were used; number of sick leave days taken in the past year was the variable of interest in logistic regression models where the effects of age, marital status, work task, work schedule, work section, and duration of work in factory and work section were also explored. Results: Marital status was strongly linked to the taking of sick leave. Age, work schedule, and duration of work in the factory were significant confounders only in certain cases. After adjusting for these confounders, chemical and physical exposures, with the exception of poor ventilation and smelling chemicals, showed no significant relation to the taking of sick leave within the past year. Work section was a good predictor for taking sick leave, as wafer polishing workers faced higher odds of taking sick leave for each of the three cut off points of seven days, three days, and not at all, while parts assembly workers also faced significantly higher odds of taking sick leave. Conclusion: In Malaysia, the wafer fabrication factories only carry out a limited portion of the work processes, in particular, wafer polishing and the processes immediately prior to and following it. This study, in showing higher illness rates for workers in wafer polishing compared to semiconductor assembly, has implications for the governmental policy of encouraging the setting up of wafer fabrication plants with the full range of work processes. PMID:12660374

  7. Multi-omics facilitated variable selection in Cox-regression model for cancer prognosis prediction.

    Science.gov (United States)

    Liu, Cong; Wang, Xujun; Genchev, Georgi Z; Lu, Hui

    2017-07-15

    New developments in high-throughput genomic technologies have enabled the measurement of diverse types of omics biomarkers in a cost-efficient and clinically-feasible manner. Developing computational methods and tools for analysis and translation of such genomic data into clinically-relevant information is an ongoing and active area of investigation. For example, several studies have utilized an unsupervised learning framework to cluster patients by integrating omics data. Despite such recent advances, predicting cancer prognosis using integrated omics biomarkers remains a challenge. There is also a shortage of computational tools for predicting cancer prognosis by using supervised learning methods. The current standard approach is to fit a Cox regression model by concatenating the different types of omics data in a linear manner, while penalty could be added for feature selection. A more powerful approach, however, would be to incorporate data by considering relationships among omics datatypes. Here we developed two methods: a SKI-Cox method and a wLASSO-Cox method to incorporate the association among different types of omics data. Both methods fit the Cox proportional hazards model and predict a risk score based on mRNA expression profiles. SKI-Cox borrows the information generated by these additional types of omics data to guide variable selection, while wLASSO-Cox incorporates this information as a penalty factor during model fitting. We show that SKI-Cox and wLASSO-Cox models select more true variables than a LASSO-Cox model in simulation studies. We assess the performance of SKI-Cox and wLASSO-Cox using TCGA glioblastoma multiforme and lung adenocarcinoma data. In each case, mRNA expression, methylation, and copy number variation data are integrated to predict the overall survival time of cancer patients. Our methods achieve better performance in predicting patients' survival in glioblastoma and lung adenocarcinoma. Copyright © 2017. Published by Elsevier

  8. Assessment of acute pesticide toxicity with selected biochemical variables in suicide attempting subjects

    International Nuclear Information System (INIS)

    Soomro, A.M.; Seehar, G.M.; Bhanger, M.I.

    2003-01-01

    Pesticide induced changes were assessed in thirty two subjects of attempted suicide cases. Among all, the farmers and their families were recorded as most frequently suicide attempting. The values obtained from seven biochemical variables of 29 years old (average age) hospitalized subjects were compared to the same number and age matched normal volunteers. The results revealed major differences in the mean values of the selected parameters. The mean difference calculate; alkaline phosphatase (178.7 mu/l), Bilirubin (7.5 mg/dl), GPT (59.2 mu/l) and glucose (38.6 mg/dl) were higher than the controls, which indicate the hepatotoxicity induced by the pesticides in suicide attempting individuals. Increase in serum creatinine and urea indicated renal malfunction that could be linked with pesticide induced nephrotoxicity among them. (author)

  9. VARIABILITY OF AMYLOSE AND AMYLOPECTIN IN WINTER WHEAT AND SELECTION FOR SPECIAL PURPOSES

    Directory of Open Access Journals (Sweden)

    Nikolina Weg Krstičević

    2015-06-01

    Full Text Available The aim of this study was to investigate the variability of amylose and amylopectin in 24 Croatian and six foreign winter wheat varieties and to detect the potential of these varieties for special purposes. Starch composition analysis was based on the separation of amylose and amylopectin and the determination of their amounts and ratios. Analysis of the amount of amylose and amylopectin determined statistically highly significant differences between the varieties. The tested varieties are mostly bread wheat of different quality which have the usual content of amylose and amylopectin. Some varieties were identified among them with high amylopectin and low amylose content and one variety with high amylose content. They have the potential in future breeding programs and selection for special purposes.

  10. Bayesian variable selection for post-analytic interrogation of susceptibility loci.

    Science.gov (United States)

    Chen, Siying; Nunez, Sara; Reilly, Muredach P; Foulkes, Andrea S

    2017-06-01

    Understanding the complex interplay among protein coding genes and regulatory elements requires rigorous interrogation with analytic tools designed for discerning the relative contributions of overlapping genomic regions. To this aim, we offer a novel application of Bayesian variable selection (BVS) for classifying genomic class level associations using existing large meta-analysis summary level resources. This approach is applied using the expectation maximization variable selection (EMVS) algorithm to typed and imputed SNPs across 502 protein coding genes (PCGs) and 220 long intergenic non-coding RNAs (lncRNAs) that overlap 45 known loci for coronary artery disease (CAD) using publicly available Global Lipids Gentics Consortium (GLGC) (Teslovich et al., 2010; Willer et al., 2013) meta-analysis summary statistics for low-density lipoprotein cholesterol (LDL-C). The analysis reveals 33 PCGs and three lncRNAs across 11 loci with >50% posterior probabilities for inclusion in an additive model of association. The findings are consistent with previous reports, while providing some new insight into the architecture of LDL-cholesterol to be investigated further. As genomic taxonomies continue to evolve, additional classes such as enhancer elements and splicing regions, can easily be layered into the proposed analysis framework. Moreover, application of this approach to alternative publicly available meta-analysis resources, or more generally as a post-analytic strategy to further interrogate regions that are identified through single point analysis, is straightforward. All coding examples are implemented in R version 3.2.1 and provided as supplemental material. © 2016, The International Biometric Society.

  11. INDUCED GENETIC VARIABILITY AND SELECTION FOR HIGH YIELDING MUTANTS IN BREAD WHEAT(TRITICUM AESTIVUM L.)

    International Nuclear Information System (INIS)

    SOBIEH, S.EL-S.S.

    2007-01-01

    This study was conducted during the two winter seasons of 2004/2005 and 2005/2006 at the experimental farm belonging to Plant Research Department, Nuclear Research Centre, AEA, Egypt.The aim of this study is to determine the effect of gamma rays(150, 200 and 250 Gy) on means of yield and its attributes for exotic wheat variety (vir-25) and induction of genetic variability that permits to perform visual selection through the irradiated populations, as well as to determine difference in seed protein patterns between vir-25 parent variety and some selectants in M2 generation.The results showed that the different doses of gamma rays had non-significant effect on mean value of yield/plant and significant effect on mean values of it's attributes. 0n the other hand, the considered genetic variability was generated as result of applying gamma irradiation. The highest amount of induced genetic variability was detected for number of grains/ spike, spike length and number of spikes/plant. Additionally, these three traits exhibited strong association with grain yield/plant, hence, they were used as a criterion for selection.Some variant plants were selected from radiation treatment 250 Gy, with 2-10 spikes per plant.These variant plants exhibited increasing in spike length and number of gains/spike.The results also revealed that protein electrophoresis were varied in the number and position of bands from genotype to another and various genotypes share bands with molecular weights 31.4 and 3.2 KD.Many bands were found to be specific for the genotype and the nine wheat mutants were characterized by the presence of bands of molecular weights: 151.9, 125.7, 14.1 and 5.7 KD at M-167.4, 21.7 and 8.2 at M-299.7 KD at M-3136.1, 97.6, 49.8, 27.9 and 20.6 KD at M-4 135.2, 95.3 and 28.1 KD at M-5 135.5, 67.7, 47.1, 32.3, 21.9 and 9.6 KD at M-6 126.1, 112.1, 103.3, 58.8, 20.9 and 12.1 KD at M-7 127.7, 116.6, 93.9, 55.0 and 47.4 KD at M-8 141.7, 96.1, 79.8, 68.9, 42.1, 32.7, 22.0 and 13

  12. The impact of selected organizational variables and managerial leadership on radiation therapists' organizational commitment

    International Nuclear Information System (INIS)

    Akroyd, Duane; Legg, Jeff; Jackowski, Melissa B.; Adams, Robert D.

    2009-01-01

    The purpose of this study was to examine the impact of selected organizational factors and the leadership behavior of supervisors on radiation therapists' commitment to their organizations. The population for this study consists of all full time clinical radiation therapists registered by the American Registry of Radiologic Technologists (ARRT) in the United States. A random sample of 800 radiation therapists was obtained from the ARRT for this study. Questionnaires were mailed to all participants and measured organizational variables; managerial leadership variable and three components of organizational commitment (affective, continuance and normative). It was determined that organizational support, and leadership behavior of supervisors each had a significant and positive affect on normative and affective commitment of radiation therapists and each of the models predicted over 40% of the variance in radiation therapists organizational commitment. This study examined radiation therapists' commitment to their organizations and found that affective (emotional attachment to the organization) and normative (feelings of obligation to the organization) commitments were more important than continuance commitment (awareness of the costs of leaving the organization). This study can help radiation oncology administrators and physicians to understand the values their radiation therapy employees hold that are predictive of their commitment to the organization. A crucial result of the study is the importance of the perceived support of the organization and the leadership skills of managers/supervisors on radiation therapists' commitment to the organization.

  13. The impact of selected organizational variables and managerial leadership on radiation therapists' organizational commitment

    Energy Technology Data Exchange (ETDEWEB)

    Akroyd, Duane [Department of Adult and Community College Education, College of Education, Campus Box 7801, North Carolina State University, Raleigh, NC 27695 (United States)], E-mail: duane_akroyd@ncsu.edu; Legg, Jeff [Department of Radiologic Sciences, Virginia Commonwealth University, Richmond, VA 23284 (United States); Jackowski, Melissa B. [Division of Radiologic Sciences, University of North Carolina School of Medicine 27599 (United States); Adams, Robert D. [Department of Radiation Oncology, University of North Carolina School of Medicine 27599 (United States)

    2009-05-15

    The purpose of this study was to examine the impact of selected organizational factors and the leadership behavior of supervisors on radiation therapists' commitment to their organizations. The population for this study consists of all full time clinical radiation therapists registered by the American Registry of Radiologic Technologists (ARRT) in the United States. A random sample of 800 radiation therapists was obtained from the ARRT for this study. Questionnaires were mailed to all participants and measured organizational variables; managerial leadership variable and three components of organizational commitment (affective, continuance and normative). It was determined that organizational support, and leadership behavior of supervisors each had a significant and positive affect on normative and affective commitment of radiation therapists and each of the models predicted over 40% of the variance in radiation therapists organizational commitment. This study examined radiation therapists' commitment to their organizations and found that affective (emotional attachment to the organization) and normative (feelings of obligation to the organization) commitments were more important than continuance commitment (awareness of the costs of leaving the organization). This study can help radiation oncology administrators and physicians to understand the values their radiation therapy employees hold that are predictive of their commitment to the organization. A crucial result of the study is the importance of the perceived support of the organization and the leadership skills of managers/supervisors on radiation therapists' commitment to the organization.

  14. Spatially variable natural selection and the divergence between parapatric subspecies of lodgepole pine (Pinus contorta, Pinaceae).

    Science.gov (United States)

    Eckert, Andrew J; Shahi, Hurshbir; Datwyler, Shannon L; Neale, David B

    2012-08-01

    Plant populations arrayed across sharp environmental gradients are ideal systems for identifying the genetic basis of ecologically relevant phenotypes. A series of five uplifted marine terraces along the northern coast of California represents one such system where morphologically distinct populations of lodgepole pine (Pinus contorta) are distributed across sharp soil gradients ranging from fertile soils near the coast to podzolic soils ca. 5 km inland. A total of 92 trees was sampled across four coastal marine terraces (N = 10-46 trees/terrace) located in Mendocino County, California and sequenced for a set of 24 candidate genes for growth and responses to various soil chemistry variables. Statistical analyses relying on patterns of nucleotide diversity were employed to identify genes whose diversity patterns were inconsistent with three null models. Most genes displayed patterns of nucleotide diversity that were consistent with null models (N = 19) or with the presence of paralogs (N = 3). Two genes, however, were exceptional: an aluminum responsive ABC-transporter with F(ST) = 0.664 and an inorganic phosphate transporter characterized by divergent haplotypes segregating at intermediate frequencies in most populations. Spatially variable natural selection along gradients of aluminum and phosphate ion concentrations likely accounted for both outliers. These results shed light on some of the genetic components comprising the extended phenotype of this ecosystem, as well as highlight ecotones as fruitful study systems for the detection of adaptive genetic variants.

  15. Repeat what after whom? Exploring variable selectivity in a cross-dialectal shadowing task.

    Directory of Open Access Journals (Sweden)

    Abby eWalker

    2015-05-01

    Full Text Available Twenty women from Christchurch, New Zealand and sixteen from Columbus Ohio (dialect region U.S. Midland participated in a bimodal lexical naming task where they repeated monosyllabic words after four speakers from four regional dialects: New Zealand, Australia, U.S. Inland North and U.S. Midland. The resulting utterances were acoustically analyzed, and presented to listeners on Amazon Mechanical Turk in an AXB task. Convergence is observed, but differs depending on the dialect of the speaker, the dialect of the model, the particular word class being shadowed, and the order in which dialects are presented to participants. We argue that these patterns are generally consistent with findings that convergence is promoted by a large phonetic distance between shadower and model (Babel, 2010, contra Kim, Horton & Bradlow, 2011, and greater existing variability in a vowel class (Babel, 2012. The results also suggest that more comparisons of accommodation towards different dialects are warranted, and that the investigation of the socio-indexical meaning of specific linguistic forms in context is a promising avenue for understanding variable selectivity in convergence.

  16. Comparison of Three Plot Selection Methods for Estimating Change in Temporally Variable, Spatially Clustered Populations.

    Energy Technology Data Exchange (ETDEWEB)

    Thompson, William L. [Bonneville Power Administration, Portland, OR (US). Environment, Fish and Wildlife

    2001-07-01

    Monitoring population numbers is important for assessing trends and meeting various legislative mandates. However, sampling across time introduces a temporal aspect to survey design in addition to the spatial one. For instance, a sample that is initially representative may lose this attribute if there is a shift in numbers and/or spatial distribution in the underlying population that is not reflected in later sampled plots. Plot selection methods that account for this temporal variability will produce the best trend estimates. Consequently, I used simulation to compare bias and relative precision of estimates of population change among stratified and unstratified sampling designs based on permanent, temporary, and partial replacement plots under varying levels of spatial clustering, density, and temporal shifting of populations. Permanent plots produced more precise estimates of change than temporary plots across all factors. Further, permanent plots performed better than partial replacement plots except for high density (5 and 10 individuals per plot) and 25% - 50% shifts in the population. Stratified designs always produced less precise estimates of population change for all three plot selection methods, and often produced biased change estimates and greatly inflated variance estimates under sampling with partial replacement. Hence, stratification that remains fixed across time should be avoided when monitoring populations that are likely to exhibit large changes in numbers and/or spatial distribution during the study period. Key words: bias; change estimation; monitoring; permanent plots; relative precision; sampling with partial replacement; temporary plots.

  17. Variability in dose estimates associated with the food-chain transport and ingestion of selected radionuclides

    International Nuclear Information System (INIS)

    Hoffman, F.O.; Gardner, R.H.; Eckerman, K.F.

    1982-06-01

    Dose predictions for the ingestion of 90 Sr and 137 Cs, using aquatic and terrestrial food chain transport models similar to those in the Nuclear Regulatory Commission's Regulatory Guide 1.109, are evaluated through estimating the variability of model parameters and determining the effect of this variability on model output. The variability in the predicted dose equivalent is determined using analytical and numerical procedures. In addition, a detailed discussion is included on 90 Sr dosimetry. The overall estimates of uncertainty are most relevant to conditions where site-specific data is unavailable and when model structure and parameter estimates are unbiased. Based on the comparisons performed in this report, it is concluded that the use of the generic default parameters in Regulatory Guide 1.109 will usually produce conservative dose estimates that exceed the 90th percentile of the predicted distribution of dose equivalents. An exception is the meat pathway for 137 Cs, in which use of generic default values results in a dose estimate at the 24th percentile. Among the terrestrial pathways of exposure, the non-leafy vegetable pathway is the most important for 90 Sr. For 90 Sr, the parameters for soil retention, soil-to-plant transfer, and internal dosimetry contribute most significantly to the variability in the predicted dose for the combined exposure to all terrestrial pathways. For 137 Cs, the meat transfer coefficient the mass interception factor for pasture forage, and the ingestion dose factor are the most important parameters. The freshwater finfish bioaccumulation factor is the most important parameter for the dose prediction of 90 Sr and 137 Cs transported over the water-fish-man pathway

  18. Computed ABC Analysis for Rational Selection of Most Informative Variables in Multivariate Data.

    Science.gov (United States)

    Ultsch, Alfred; Lötsch, Jörn

    2015-01-01

    Multivariate data sets often differ in several factors or derived statistical parameters, which have to be selected for a valid interpretation. Basing this selection on traditional statistical limits leads occasionally to the perception of losing information from a data set. This paper proposes a novel method for calculating precise limits for the selection of parameter sets. The algorithm is based on an ABC analysis and calculates these limits on the basis of the mathematical properties of the distribution of the analyzed items. The limits implement the aim of any ABC analysis, i.e., comparing the increase in yield to the required additional effort. In particular, the limit for set A, the "important few", is optimized in a way that both, the effort and the yield for the other sets (B and C), are minimized and the additional gain is optimized. As a typical example from biomedical research, the feasibility of the ABC analysis as an objective replacement for classical subjective limits to select highly relevant variance components of pain thresholds is presented. The proposed method improved the biological interpretation of the results and increased the fraction of valid information that was obtained from the experimental data. The method is applicable to many further biomedical problems including the creation of diagnostic complex biomarkers or short screening tests from comprehensive test batteries. Thus, the ABC analysis can be proposed as a mathematically valid replacement for traditional limits to maximize the information obtained from multivariate research data.

  19. Improved Variable Selection Algorithm Using a LASSO-Type Penalty, with an Application to Assessing Hepatitis B Infection Relevant Factors in Community Residents

    Science.gov (United States)

    Guo, Pi; Zeng, Fangfang; Hu, Xiaomin; Zhang, Dingmei; Zhu, Shuming; Deng, Yu; Hao, Yuantao

    2015-01-01

    Objectives In epidemiological studies, it is important to identify independent associations between collective exposures and a health outcome. The current stepwise selection technique ignores stochastic errors and suffers from a lack of stability. The alternative LASSO-penalized regression model can be applied to detect significant predictors from a pool of candidate variables. However, this technique is prone to false positives and tends to create excessive biases. It remains challenging to develop robust variable selection methods and enhance predictability. Material and methods Two improved algorithms denoted the two-stage hybrid and bootstrap ranking procedures, both using a LASSO-type penalty, were developed for epidemiological association analysis. The performance of the proposed procedures and other methods including conventional LASSO, Bolasso, stepwise and stability selection models were evaluated using intensive simulation. In addition, methods were compared by using an empirical analysis based on large-scale survey data of hepatitis B infection-relevant factors among Guangdong residents. Results The proposed procedures produced comparable or less biased selection results when compared to conventional variable selection models. In total, the two newly proposed procedures were stable with respect to various scenarios of simulation, demonstrating a higher power and a lower false positive rate during variable selection than the compared methods. In empirical analysis, the proposed procedures yielding a sparse set of hepatitis B infection-relevant factors gave the best predictive performance and showed that the procedures were able to select a more stringent set of factors. The individual history of hepatitis B vaccination, family and individual history of hepatitis B infection were associated with hepatitis B infection in the studied residents according to the proposed procedures. Conclusions The newly proposed procedures improve the identification of

  20. Selection of entropy-measure parameters for knowledge discovery in heart rate variability data.

    Science.gov (United States)

    Mayer, Christopher C; Bachler, Martin; Hörtenhuber, Matthias; Stocker, Christof; Holzinger, Andreas; Wassertheurer, Siegfried

    2014-01-01

    Heart rate variability is the variation of the time interval between consecutive heartbeats. Entropy is a commonly used tool to describe the regularity of data sets. Entropy functions are defined using multiple parameters, the selection of which is controversial and depends on the intended purpose. This study describes the results of tests conducted to support parameter selection, towards the goal of enabling further biomarker discovery. This study deals with approximate, sample, fuzzy, and fuzzy measure entropies. All data were obtained from PhysioNet, a free-access, on-line archive of physiological signals, and represent various medical conditions. Five tests were defined and conducted to examine the influence of: varying the threshold value r (as multiples of the sample standard deviation σ, or the entropy-maximizing rChon), the data length N, the weighting factors n for fuzzy and fuzzy measure entropies, and the thresholds rF and rL for fuzzy measure entropy. The results were tested for normality using Lilliefors' composite goodness-of-fit test. Consequently, the p-value was calculated with either a two sample t-test or a Wilcoxon rank sum test. The first test shows a cross-over of entropy values with regard to a change of r. Thus, a clear statement that a higher entropy corresponds to a high irregularity is not possible, but is rather an indicator of differences in regularity. N should be at least 200 data points for r = 0.2 σ and should even exceed a length of 1000 for r = rChon. The results for the weighting parameters n for the fuzzy membership function show different behavior when coupled with different r values, therefore the weighting parameters have been chosen independently for the different threshold values. The tests concerning rF and rL showed that there is no optimal choice, but r = rF = rL is reasonable with r = rChon or r = 0.2σ. Some of the tests showed a dependency of the test significance on the data at hand. Nevertheless, as the medical

  1. Preface to the April 2018 Issue including selected works from CIbSE 2017 and LACLO 2016

    Directory of Open Access Journals (Sweden)

    Héctor Cancela

    2018-04-01

    Full Text Available This issue of the CLEIej consists of three main parts: i a review paper on the state of the art of how contextual information extracted from a user task can help to improve searches for contents relevant to this task; ii extended and revised versions of Selected Papers (which correspond to the second and third best paper from each track presented at the XX Ibero-American Conference on Software Engineering (CIbSE 2017, which took place in Buenos Aires, Argentina, in May 2017; and, iii extended and revised versions of selected papers from LACLO 2016, the XI Latin American Conference on Learning Objects and Technology, which took place in San José, Costa Rica, in October 2016.

  2. Improving the Classification Accuracy for Near-Infrared Spectroscopy of Chinese Salvia miltiorrhiza Using Local Variable Selection

    Directory of Open Access Journals (Sweden)

    Lianqing Zhu

    2018-01-01

    Full Text Available In order to improve the classification accuracy of Chinese Salvia miltiorrhiza using near-infrared spectroscopy, a novel local variable selection strategy is thus proposed. Combining the strengths of the local algorithm and interval partial least squares, the spectra data have firstly been divided into several pairs of classes in sample direction and equidistant subintervals in variable direction. Then, a local classification model has been built, and the most proper spectral region has been selected based on the new evaluation criterion considering both classification error rate and best predictive ability under the leave-one-out cross validation scheme for each pair of classes. Finally, each observation can be assigned to belong to the class according to the statistical analysis of classification results of the local classification model built on selected variables. The performance of the proposed method was demonstrated through near-infrared spectra of cultivated or wild Salvia miltiorrhiza, which are collected from 8 geographical origins in 5 provinces of China. For comparison, soft independent modelling of class analogy and partial least squares discriminant analysis methods are, respectively, employed as the classification model. Experimental results showed that classification performance of the classification model with local variable selection was obvious better than that without variable selection.

  3. Relation of desert pupfish abundance to selected environmental variables in natural and manmade habitats in the Salton Sea basin

    Science.gov (United States)

    Martin, B.A.; Saiki, M.K.

    2005-01-01

    We assessed the relation between abundance of desert pupfish, Cyprinodon macularius, and selected biological and physicochemical variables in natural and manmade habitats within the Salton Sea Basin. Field sampling in a natural tributary, Salt Creek, and three agricultural drains captured eight species including pupfish (1.1% of the total catch), the only native species encountered. According to Bray-Curtis resemblance functions, fish species assemblages differed mostly between Salt Creek and the drains (i.e., the three drains had relatively similar species assemblages). Pupfish numbers and environmental variables varied among sites and sample periods. Canonical correlation showed that pupfish abundance was positively correlated with abundance of western mosquitofish, Gambusia affinis, and negatively correlated with abundance of porthole livebearers, Poeciliopsis gracilis, tilapias (Sarotherodon mossambica and Tilapia zillii), longjaw mudsuckers, Gillichthys mirabilis, and mollies (Poecilia latipinnaandPoecilia mexicana). In addition, pupfish abundance was positively correlated with cover, pH, and salinity, and negatively correlated with sediment factor (a measure of sediment grain size) and dissolved oxygen. Pupfish abundance was generally highest in habitats where water quality extremes (especially high pH and salinity, and low dissolved oxygen) seemingly limited the occurrence of nonnative fishes. This study also documented evidence of predation by mudsuckers on pupfish. These findings support the contention of many resource managers that pupfish populations are adversely influenced by ecological interactions with nonnative fishes. ?? Springer 2005.

  4. Selecting sagebrush seed sources for restoration in a variable climate: ecophysiological variation among genotypes

    Science.gov (United States)

    Germino, Matthew J.

    2012-01-01

    Big sagebrush (Artemisia tridentata) communities dominate a large fraction of the United States and provide critical habitat for a number of wildlife species of concern. Loss of big sagebrush due to fire followed by poor restoration success continues to reduce ecological potential of this ecosystem type, particularly in the Great Basin. Choice of appropriate seed sources for restoration efforts is currently unguided due to knowledge gaps on genetic variation and local adaptation as they relate to a changing landscape. We are assessing ecophysiological responses of big sagebrush to climate variation, comparing plants that germinated from ~20 geographically distinct populations of each of the three subspecies of big sagebrush. Seedlings were previously planted into common gardens by US Forest Service collaborators Drs. B. Richardson and N. Shaw, (USFS Rocky Mountain Research Station, Provo, Utah and Boise, Idaho) as part of the Great Basin Native Plant Selection and Increase Project. Seed sources spanned all states in the conterminous Western United States. Germination, establishment, growth and ecophysiological responses are being linked to genomics and foliar palatability. New information is being produced to aid choice of appropriate seed sources by Bureau of Land Management and USFS field offices when they are planning seed acquisitions for emergency post-fire rehabilitation projects while considering climate variability and wildlife needs.

  5. Selective attrition and intraindividual variability in response time moderate cognitive change.

    Science.gov (United States)

    Yao, Christie; Stawski, Robert S; Hultsch, David F; MacDonald, Stuart W S

    2016-01-01

    Selection of a developmental time metric is useful for understanding causal processes that underlie aging-related cognitive change and for the identification of potential moderators of cognitive decline. Building on research suggesting that time to attrition is a metric sensitive to non-normative influences of aging (e.g., subclinical health conditions), we examined reason for attrition and intraindividual variability (IIV) in reaction time as predictors of cognitive performance. Three hundred and four community dwelling older adults (64-92 years) completed annual assessments in a longitudinal study. IIV was calculated from baseline performance on reaction time tasks. Multilevel models were fit to examine patterns and predictors of cognitive change. We show that time to attrition was associated with cognitive decline. Greater IIV was associated with declines on executive functioning and episodic memory measures. Attrition due to personal health reasons was also associated with decreased executive functioning compared to that of individuals who remained in the study. These findings suggest that time to attrition is a useful metric for representing cognitive change, and reason for attrition and IIV are predictive of non-normative influences that may underlie instances of cognitive loss in older adults.

  6. Variable Selection for Nonparametric Gaussian Process Priors: Models and Computational Strategies.

    Science.gov (United States)

    Savitsky, Terrance; Vannucci, Marina; Sha, Naijun

    2011-02-01

    This paper presents a unified treatment of Gaussian process models that extends to data from the exponential dispersion family and to survival data. Our specific interest is in the analysis of data sets with predictors that have an a priori unknown form of possibly nonlinear associations to the response. The modeling approach we describe incorporates Gaussian processes in a generalized linear model framework to obtain a class of nonparametric regression models where the covariance matrix depends on the predictors. We consider, in particular, continuous, categorical and count responses. We also look into models that account for survival outcomes. We explore alternative covariance formulations for the Gaussian process prior and demonstrate the flexibility of the construction. Next, we focus on the important problem of selecting variables from the set of possible predictors and describe a general framework that employs mixture priors. We compare alternative MCMC strategies for posterior inference and achieve a computationally efficient and practical approach. We demonstrate performances on simulated and benchmark data sets.

  7. Relationship of Powder Feedstock Variability to Microstructure and Defects in Selective Laser Melted Alloy 718

    Science.gov (United States)

    Smith, T. M.; Kloesel, M. F.; Sudbrack, C. K.

    2017-01-01

    Powder-bed additive manufacturing processes use fine powders to build parts layer by layer. For selective laser melted (SLM) Alloy 718, the powders that are available off-the-shelf are in the 10-45 or 15-45 micron size range. A comprehensive investigation of sixteen powders from these typical ranges and two off-nominal-sized powders is underway to gain insight into the impact of feedstock on processing, durability and performance of 718 SLM space-flight hardware. This talk emphasizes an aspect of this work: the impact of powder variability on the microstructure and defects observed in the as-fabricated and full heated material, where lab-scale components were built using vendor recommended parameters. These typical powders exhibit variation in composition, percentage of fines, roughness, morphology and particle size distribution. How these differences relate to the melt-pool size, porosity, grain structure, precipitate distributions, and inclusion content will be presented and discussed in context of build quality and powder acceptance.

  8. r2VIM: A new variable selection method for random forests in genome-wide association studies.

    Science.gov (United States)

    Szymczak, Silke; Holzinger, Emily; Dasgupta, Abhijit; Malley, James D; Molloy, Anne M; Mills, James L; Brody, Lawrence C; Stambolian, Dwight; Bailey-Wilson, Joan E

    2016-01-01

    Machine learning methods and in particular random forests (RFs) are a promising alternative to standard single SNP analyses in genome-wide association studies (GWAS). RFs provide variable importance measures (VIMs) to rank SNPs according to their predictive power. However, in contrast to the established genome-wide significance threshold, no clear criteria exist to determine how many SNPs should be selected for downstream analyses. We propose a new variable selection approach, recurrent relative variable importance measure (r2VIM). Importance values are calculated relative to an observed minimal importance score for several runs of RF and only SNPs with large relative VIMs in all of the runs are selected as important. Evaluations on simulated GWAS data show that the new method controls the number of false-positives under the null hypothesis. Under a simple alternative hypothesis with several independent main effects it is only slightly less powerful than logistic regression. In an experimental GWAS data set, the same strong signal is identified while the approach selects none of the SNPs in an underpowered GWAS. The novel variable selection method r2VIM is a promising extension to standard RF for objectively selecting relevant SNPs in GWAS while controlling the number of false-positive results.

  9. Conflict Management Styles of Selected Managers and Their Relationship With Management and Organization Variables

    Directory of Open Access Journals (Sweden)

    Concepcion Martires

    1990-12-01

    Full Text Available This study sought to determine the relationship between the conflict management styles of managers and certain management and organization factors. A total of 462 top, middle, and lower managers from 72 companies participated in the study which utilized the Thomas-Killman Conflict Mode Instrument. To facilitate the computation of the statistical data, a microcomputer and a software package was used.The majority of the managers of the 17 types of organization included in the study use collaborative mode of managing conflict. This finding is congruent with the findings of past studies conducted on managers of commercial banks, service, manufacturing, trading advertising, appliance, investment houses, and overseas recruitment industries showing their high degree of objectivity and assertiveness of their own personal goals and of other people's concerns. The second dominant style, which is compromising, indicates their desire in sharing and searching for solutions that result in satisfaction among conflicting parties. This finding is highly consistent with the strong Filipino value of smooth interpersonal relationships (SIR as reflected and discussed in the numerous researches on Filipino values.The chi-square tests generated by the computer package in statistics showed independence between the manager's conflict management styles and each of the variables of sex, civil status, position level at work, work experience, type of corporation, and number of subordinates. This result is again congruent with those of past studies conducted in the Philippines. The past and present findings may imply that conflict management mode may be a highly personal style that is not dependent on any of these variables included in the study. However, the chi-square tests show that management style is dependent on the manager's age and educational attainment.

  10. An experiment on selecting most informative variables in socio-economic data

    Directory of Open Access Journals (Sweden)

    L. Jenkins

    2014-01-01

    Full Text Available In many studies where data are collected on several variables, there is a motivation to find if fewer variables would provide almost as much information. Variance of a variable about its mean is the common statistical measure of information content, and that is used here. We are interested whether the variability in one variable is sufficiently correlated with that in one or more of the other variables that the first variable is redundant. We wish to find one or more ‘principal variables’ that sufficiently reflect the information content in all the original variables. The paper explains the method of principal variables and reports experiments using the technique to see if just a few variables are sufficient to reflect the information in 11 socioeconomic variables on 130 countries from a World Bank (WB database. While the method of principal variables is highly successful in a statistical sense, the WB data varies greatly from year to year, demonstrating that fewer variables wo uld be inadequate for this data.

  11. Genetic and Psychosocial Predictors of Aggression: Variable Selection and Model Building With Component-Wise Gradient Boosting

    Directory of Open Access Journals (Sweden)

    Robert Suchting

    2018-05-01

    Full Text Available Rationale: Given datasets with a large or diverse set of predictors of aggression, machine learning (ML provides efficient tools for identifying the most salient variables and building a parsimonious statistical model. ML techniques permit efficient exploration of data, have not been widely used in aggression research, and may have utility for those seeking prediction of aggressive behavior.Objectives: The present study examined predictors of aggression and constructed an optimized model using ML techniques. Predictors were derived from a dataset that included demographic, psychometric and genetic predictors, specifically FK506 binding protein 5 (FKBP5 polymorphisms, which have been shown to alter response to threatening stimuli, but have not been tested as predictors of aggressive behavior in adults.Methods: The data analysis approach utilized component-wise gradient boosting and model reduction via backward elimination to: (a select variables from an initial set of 20 to build a model of trait aggression; and then (b reduce that model to maximize parsimony and generalizability.Results: From a dataset of N = 47 participants, component-wise gradient boosting selected 8 of 20 possible predictors to model Buss-Perry Aggression Questionnaire (BPAQ total score, with R2 = 0.66. This model was simplified using backward elimination, retaining six predictors: smoking status, psychopathy (interpersonal manipulation and callous affect, childhood trauma (physical abuse and neglect, and the FKBP5_13 gene (rs1360780. The six-factor model approximated the initial eight-factor model at 99.4% of R2.Conclusions: Using an inductive data science approach, the gradient boosting model identified predictors consistent with previous experimental work in aggression; specifically psychopathy and trauma exposure. Additionally, allelic variants in FKBP5 were identified for the first time, but the relatively small sample size limits generality of results and calls for

  12. Genetic and Psychosocial Predictors of Aggression: Variable Selection and Model Building With Component-Wise Gradient Boosting.

    Science.gov (United States)

    Suchting, Robert; Gowin, Joshua L; Green, Charles E; Walss-Bass, Consuelo; Lane, Scott D

    2018-01-01

    Rationale : Given datasets with a large or diverse set of predictors of aggression, machine learning (ML) provides efficient tools for identifying the most salient variables and building a parsimonious statistical model. ML techniques permit efficient exploration of data, have not been widely used in aggression research, and may have utility for those seeking prediction of aggressive behavior. Objectives : The present study examined predictors of aggression and constructed an optimized model using ML techniques. Predictors were derived from a dataset that included demographic, psychometric and genetic predictors, specifically FK506 binding protein 5 (FKBP5) polymorphisms, which have been shown to alter response to threatening stimuli, but have not been tested as predictors of aggressive behavior in adults. Methods : The data analysis approach utilized component-wise gradient boosting and model reduction via backward elimination to: (a) select variables from an initial set of 20 to build a model of trait aggression; and then (b) reduce that model to maximize parsimony and generalizability. Results : From a dataset of N = 47 participants, component-wise gradient boosting selected 8 of 20 possible predictors to model Buss-Perry Aggression Questionnaire (BPAQ) total score, with R 2 = 0.66. This model was simplified using backward elimination, retaining six predictors: smoking status, psychopathy (interpersonal manipulation and callous affect), childhood trauma (physical abuse and neglect), and the FKBP5_13 gene (rs1360780). The six-factor model approximated the initial eight-factor model at 99.4% of R 2 . Conclusions : Using an inductive data science approach, the gradient boosting model identified predictors consistent with previous experimental work in aggression; specifically psychopathy and trauma exposure. Additionally, allelic variants in FKBP5 were identified for the first time, but the relatively small sample size limits generality of results and calls for

  13. Managing anthelmintic resistance-Variability in the dose of drug reaching the target worms influences selection for resistance?

    Science.gov (United States)

    Leathwick, Dave M; Luo, Dongwen

    2017-08-30

    The concentration profile of anthelmintic reaching the target worms in the host can vary between animals even when administered doses are tailored to individual liveweight at the manufacturer's recommended rate. Factors contributing to variation in drug concentration include weather, breed of animal, formulation and the route by which drugs are administered. The implications of this variability for the development of anthelmintic resistance was investigated using Monte-Carlo simulation. A model framework was established where 100 animals each received a single drug treatment. The 'dose' of drug allocated to each animal (i.e. the concentration-time profile of drug reaching the target worms) was sampled at random from a distribution of doses with mean m and standard deviation s. For each animal the dose of drug was used in conjunction with pre-determined dose-response relationships, representing single and poly-genetic inheritance, to calculate efficacy against susceptible and resistant genotypes. These data were then used to calculate the overall change in resistance gene frequency for the worm population as a result of the treatment. Values for m and s were varied to reflect differences in both mean dose and the variability in dose, and for each combination of these 100,000 simulations were run. The resistance gene frequency in the population after treatment increased as m decreased and as s increased. This occurred for both single and poly-gene models and for different levels of dominance (survival under treatment) of the heterozygote genotype(s). The results indicate that factors which result in lower and/or more variable concentrations of active reaching the target worms are more likely to select for resistance. The potential of different routes of anthelmintic administration to play a role in the development of anthelmintic resistance is discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. A selective review of the first 20 years of instrumental variables models in health-services research and medicine.

    Science.gov (United States)

    Cawley, John

    2015-01-01

    The method of instrumental variables (IV) is useful for estimating causal effects. Intuitively, it exploits exogenous variation in the treatment, sometimes called natural experiments or instruments. This study reviews the literature in health-services research and medical research that applies the method of instrumental variables, documents trends in its use, and offers examples of various types of instruments. A literature search of the PubMed and EconLit research databases for English-language journal articles published after 1990 yielded a total of 522 original research articles. Citations counts for each article were derived from the Web of Science. A selective review was conducted, with articles prioritized based on number of citations, validity and power of the instrument, and type of instrument. The average annual number of papers in health services research and medical research that apply the method of instrumental variables rose from 1.2 in 1991-1995 to 41.8 in 2006-2010. Commonly-used instruments (natural experiments) in health and medicine are relative distance to a medical care provider offering the treatment and the medical care provider's historic tendency to administer the treatment. Less common but still noteworthy instruments include randomization of treatment for reasons other than research, randomized encouragement to undertake the treatment, day of week of admission as an instrument for waiting time for surgery, and genes as an instrument for whether the respondent has a heritable condition. The use of the method of IV has increased dramatically in the past 20 years, and a wide range of instruments have been used. Applications of the method of IV have in several cases upended conventional wisdom that was based on correlations and led to important insights about health and healthcare. Future research should pursue new applications of existing instruments and search for new instruments that are powerful and valid.

  15. ASSESSMENT OF THE CHANGES IN BLOOD PRESSURE CIRCADIAN PROFILE AND VARIABILITY IN PATIENTS WITH CHRONIC HEART FAILURE AND ARTERIAL HYPERTENSION DURING COMBINED THERAPY INCLUDING IVABRADINE

    Directory of Open Access Journals (Sweden)

    M. V. Surovtseva

    2012-01-01

    Full Text Available Aim. To assess the changes in blood pressure (BP circadian profile and variability in patients with chronic heart failure (CHF of ischemic etiology and arterial hypertension (HT due to the complex therapy including ivabradine. Material and methods. Patients (n=90 with CHF class II–III NYHA associated with stable angina II-III class and HT were examined. The patients were randomized into 3 groups depending on received drugs: perindopril and ivabradine - group 1; perindopril, bisoprolol and ivabradine - group 2; perindopril and bisoprolol - group 3. The duration of therapy was 6 months. Ambulatory BP monitoring (ABPM was assessed at baseline and after treatment. Results. More significant reduction in average 24-hours systolic BP was found in groups 1 and 2 compared to group 3 (Δ%: -19.4±0,4; -21.1±0.4 and -11.8±0.6, respectively as well as diastolic BP (Δ%: -10.6±0.6; -12.9±0.4 and -4,3±0.3, respectively and other ABPM indicators. Improvement of BP circadian rhythm was found due to increase in the number of «Dipper» patients (p=0.016. More significant reduction in average daily and night systolic and diastolic BP (p=0.001, as well as daily and night BP variability (p=0.001 was also found in patients of group 2 compared to these of group 1. Conclusion. Moderate antihypertensive effect (in respect of both diastolic and systolic BP was shown when ivabradine was included into the complex therapy of patients with ischemic CHF and HT. The effect was more pronounced when ivabradine was combined with perindopril and bisoprolol. This was accompanied by reduction in high BP daily variability and improvement of the BP circadian rhythm. 

  16. ASSESSMENT OF THE CHANGES IN BLOOD PRESSURE CIRCADIAN PROFILE AND VARIABILITY IN PATIENTS WITH CHRONIC HEART FAILURE AND ARTERIAL HYPERTENSION DURING COMBINED THERAPY INCLUDING IVABRADINE

    Directory of Open Access Journals (Sweden)

    M. V. Surovtseva

    2015-12-01

    Full Text Available Aim. To assess the changes in blood pressure (BP circadian profile and variability in patients with chronic heart failure (CHF of ischemic etiology and arterial hypertension (HT due to the complex therapy including ivabradine. Material and methods. Patients (n=90 with CHF class II–III NYHA associated with stable angina II-III class and HT were examined. The patients were randomized into 3 groups depending on received drugs: perindopril and ivabradine - group 1; perindopril, bisoprolol and ivabradine - group 2; perindopril and bisoprolol - group 3. The duration of therapy was 6 months. Ambulatory BP monitoring (ABPM was assessed at baseline and after treatment. Results. More significant reduction in average 24-hours systolic BP was found in groups 1 and 2 compared to group 3 (Δ%: -19.4±0,4; -21.1±0.4 and -11.8±0.6, respectively as well as diastolic BP (Δ%: -10.6±0.6; -12.9±0.4 and -4,3±0.3, respectively and other ABPM indicators. Improvement of BP circadian rhythm was found due to increase in the number of «Dipper» patients (p=0.016. More significant reduction in average daily and night systolic and diastolic BP (p=0.001, as well as daily and night BP variability (p=0.001 was also found in patients of group 2 compared to these of group 1. Conclusion. Moderate antihypertensive effect (in respect of both diastolic and systolic BP was shown when ivabradine was included into the complex therapy of patients with ischemic CHF and HT. The effect was more pronounced when ivabradine was combined with perindopril and bisoprolol. This was accompanied by reduction in high BP daily variability and improvement of the BP circadian rhythm. 

  17. Dynamic variable selection in SNP genotype autocalling from APEX microarray data

    Directory of Open Access Journals (Sweden)

    Zamar Ruben H

    2006-11-01

    Full Text Available Abstract Background Single nucleotide polymorphisms (SNPs are DNA sequence variations, occurring when a single nucleotide – adenine (A, thymine (T, cytosine (C or guanine (G – is altered. Arguably, SNPs account for more than 90% of human genetic variation. Our laboratory has developed a highly redundant SNP genotyping assay consisting of multiple probes with signals from multiple channels for a single SNP, based on arrayed primer extension (APEX. This mini-sequencing method is a powerful combination of a highly parallel microarray with distinctive Sanger-based dideoxy terminator sequencing chemistry. Using this microarray platform, our current genotype calling system (known as SNP Chart is capable of calling single SNP genotypes by manual inspection of the APEX data, which is time-consuming and exposed to user subjectivity bias. Results Using a set of 32 Coriell DNA samples plus three negative PCR controls as a training data set, we have developed a fully-automated genotyping algorithm based on simple linear discriminant analysis (LDA using dynamic variable selection. The algorithm combines separate analyses based on the multiple probe sets to give a final posterior probability for each candidate genotype. We have tested our algorithm on a completely independent data set of 270 DNA samples, with validated genotypes, from patients admitted to the intensive care unit (ICU of St. Paul's Hospital (plus one negative PCR control sample. Our method achieves a concordance rate of 98.9% with a 99.6% call rate for a set of 96 SNPs. By adjusting the threshold value for the final posterior probability of the called genotype, the call rate reduces to 94.9% with a higher concordance rate of 99.6%. We also reversed the two independent data sets in their training and testing roles, achieving a concordance rate up to 99.8%. Conclusion The strength of this APEX chemistry-based platform is its unique redundancy having multiple probes for a single SNP. Our

  18. Network-based group variable selection for detecting expression quantitative trait loci (eQTL

    Directory of Open Access Journals (Sweden)

    Zhang Xuegong

    2011-06-01

    Full Text Available Abstract Background Analysis of expression quantitative trait loci (eQTL aims to identify the genetic loci associated with the expression level of genes. Penalized regression with a proper penalty is suitable for the high-dimensional biological data. Its performance should be enhanced when we incorporate biological knowledge of gene expression network and linkage disequilibrium (LD structure between loci in high-noise background. Results We propose a network-based group variable selection (NGVS method for QTL detection. Our method simultaneously maps highly correlated expression traits sharing the same biological function to marker sets formed by LD. By grouping markers, complex joint activity of multiple SNPs can be considered and the dimensionality of eQTL problem is reduced dramatically. In order to demonstrate the power and flexibility of our method, we used it to analyze two simulations and a mouse obesity and diabetes dataset. We considered the gene co-expression network, grouped markers into marker sets and treated the additive and dominant effect of each locus as a group: as a consequence, we were able to replicate results previously obtained on the mouse linkage dataset. Furthermore, we observed several possible sex-dependent loci and interactions of multiple SNPs. Conclusions The proposed NGVS method is appropriate for problems with high-dimensional data and high-noise background. On eQTL problem it outperforms the classical Lasso method, which does not consider biological knowledge. Introduction of proper gene expression and loci correlation information makes detecting causal markers more accurate. With reasonable model settings, NGVS can lead to novel biological findings.

  19. Bayesian nonparametric variable selection as an exploratory tool for discovering differentially expressed genes.

    Science.gov (United States)

    Shahbaba, Babak; Johnson, Wesley O

    2013-05-30

    High-throughput scientific studies involving no clear a priori hypothesis are common. For example, a large-scale genomic study of a disease may examine thousands of genes without hypothesizing that any specific gene is responsible for the disease. In these studies, the objective is to explore a large number of possible factors (e.g., genes) in order to identify a small number that will be considered in follow-up studies that tend to be more thorough and on smaller scales. A simple, hierarchical, linear regression model with random coefficients is assumed for case-control data that correspond to each gene. The specific model used will be seen to be related to a standard Bayesian variable selection model. Relatively large regression coefficients correspond to potential differences in responses for cases versus controls and thus to genes that might 'matter'. For large-scale studies, and using a Dirichlet process mixture model for the regression coefficients, we are able to find clusters of regression effects of genes with increasing potential effect or 'relevance', in relation to the outcome of interest. One cluster will always correspond to genes whose coefficients are in a neighborhood that is relatively close to zero and will be deemed least relevant. Other clusters will correspond to increasing magnitudes of the random/latent regression coefficients. Using simulated data, we demonstrate that our approach could be quite effective in finding relevant genes compared with several alternative methods. We apply our model to two large-scale studies. The first study involves transcriptome analysis of infection by human cytomegalovirus. The second study's objective is to identify differentially expressed genes between two types of leukemia. Copyright © 2012 John Wiley & Sons, Ltd.

  20. Influence of probiotics, included in peanut butter, on the fate of selected Salmonella and Listeria strains under simulated gastrointestinal conditions.

    Science.gov (United States)

    Klu, Y A K; Chen, J

    2016-04-01

    This study observed the behaviour of probiotics and selected bacterial pathogens co-inoculated into peanut butter during gastrointestinal simulation. Peanut butter homogenates co-inoculated with Salmonella/Listeria strains (5 log CFU ml(-1) ) and lyophilized or cultured probiotics (9 log CFU ml(-1) ) were exposed to simulated gastrointestinal conditions for 24 h at 37°C. Sample pH, titratable acidity and pathogen populations were determined. Agar diffusion assay was performed to assess the inhibitory effect of probiotic culture supernatants with either natural (3·80 (Lactobacillus), 3·78 (Bifidobacteirum) and 5·17 (Streptococcus/Lactococcus)) or neutralized (6·0) pH. Antibacterial effect of crude bacteriocin extracts were also evaluated against the pathogens. After 24 h, samples with probiotics had lower pH and higher titratable acidity than those without probiotics. The presence of probiotics caused a significant reduction (P Probiotics in 'peanut butter' survived simulated gastrointestinal conditions and inhibited the growth of Salmonella/Listeria. Peanut butter is a plausible carrier to deliver probiotics to improve the gastrointestinal health of children in developing countries. © 2016 The Society for Applied Microbiology.

  1. A SEARCH FOR L/T TRANSITION DWARFS WITH Pan-STARRS1 AND WISE: DISCOVERY OF SEVEN NEARBY OBJECTS INCLUDING TWO CANDIDATE SPECTROSCOPIC VARIABLES

    International Nuclear Information System (INIS)

    Best, William M. J.; Liu, Michael C.; Magnier, Eugene A.; Aller, Kimberly M.; Burgett, W. S.; Chambers, K. C.; Hodapp, K. W.; Kaiser, N.; Kudritzki, R.-P.; Morgan, J. S.; Tonry, J. L.; Wainscoat, R. J.; Deacon, Niall R.; Dupuy, Trent J.; Redstone, Joshua; Price, P. A.

    2013-01-01

    We present initial results from a wide-field (30,000 deg 2 ) search for L/T transition brown dwarfs within 25 pc using the Pan-STARRS1 and Wide-field Infrared Survey Explorer (WISE) surveys. Previous large-area searches have been incomplete for L/T transition dwarfs, because these objects are faint in optical bands and have near-infrared (near-IR) colors that are difficult to distinguish from background stars. To overcome these obstacles, we have cross-matched the Pan-STARRS1 (optical) and WISE (mid-IR) catalogs to produce a unique multi-wavelength database for finding ultracool dwarfs. As part of our initial discoveries, we have identified seven brown dwarfs in the L/T transition within 9-15 pc of the Sun. The L9.5 dwarf PSO J140.2308+45.6487 and the T1.5 dwarf PSO J307.6784+07.8263 (both independently discovered by Mace et al.) show possible spectroscopic variability at the Y and J bands. Two more objects in our sample show evidence of photometric J-band variability, and two others are candidate unresolved binaries based on their spectra. We expect our full search to yield a well-defined, volume-limited sample of L/T transition dwarfs that will include many new targets for study of this complex regime. PSO J307.6784+07.8263 in particular may be an excellent candidate for in-depth study of variability, given its brightness (J = 14.2 mag) and proximity (11 pc)

  2. A SEARCH FOR L/T TRANSITION DWARFS WITH Pan-STARRS1 AND WISE: DISCOVERY OF SEVEN NEARBY OBJECTS INCLUDING TWO CANDIDATE SPECTROSCOPIC VARIABLES

    Energy Technology Data Exchange (ETDEWEB)

    Best, William M. J.; Liu, Michael C.; Magnier, Eugene A.; Aller, Kimberly M.; Burgett, W. S.; Chambers, K. C.; Hodapp, K. W.; Kaiser, N.; Kudritzki, R.-P.; Morgan, J. S.; Tonry, J. L.; Wainscoat, R. J. [Institute for Astronomy, University of Hawaii at Manoa, Honolulu, HI 96822 (United States); Deacon, Niall R. [Max Planck Institute for Astronomy, Koenigstuhl 17, D-69117 Heidelberg (Germany); Dupuy, Trent J. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Redstone, Joshua [Facebook, 335 Madison Ave, New York, NY 10017-4677 (United States); Price, P. A., E-mail: wbest@ifa.hawaii.edu [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States)

    2013-11-10

    We present initial results from a wide-field (30,000 deg{sup 2}) search for L/T transition brown dwarfs within 25 pc using the Pan-STARRS1 and Wide-field Infrared Survey Explorer (WISE) surveys. Previous large-area searches have been incomplete for L/T transition dwarfs, because these objects are faint in optical bands and have near-infrared (near-IR) colors that are difficult to distinguish from background stars. To overcome these obstacles, we have cross-matched the Pan-STARRS1 (optical) and WISE (mid-IR) catalogs to produce a unique multi-wavelength database for finding ultracool dwarfs. As part of our initial discoveries, we have identified seven brown dwarfs in the L/T transition within 9-15 pc of the Sun. The L9.5 dwarf PSO J140.2308+45.6487 and the T1.5 dwarf PSO J307.6784+07.8263 (both independently discovered by Mace et al.) show possible spectroscopic variability at the Y and J bands. Two more objects in our sample show evidence of photometric J-band variability, and two others are candidate unresolved binaries based on their spectra. We expect our full search to yield a well-defined, volume-limited sample of L/T transition dwarfs that will include many new targets for study of this complex regime. PSO J307.6784+07.8263 in particular may be an excellent candidate for in-depth study of variability, given its brightness (J = 14.2 mag) and proximity (11 pc)

  3. On the selection of significant variables in a model for the deteriorating process of facades

    Science.gov (United States)

    Serrat, C.; Gibert, V.; Casas, J. R.; Rapinski, J.

    2017-10-01

    In previous works the authors of this paper have introduced a predictive system that uses survival analysis techniques for the study of time-to-failure in the facades of a building stock. The approach is population based, in order to obtain information on the evolution of the stock across time, and to help the manager in the decision making process on global maintenance strategies. For the decision making it is crutial to determine those covariates -like materials, morphology and characteristics of the facade, orientation or environmental conditions- that play a significative role in the progression of different failures. The proposed platform also incorporates an open source GIS plugin that includes survival and test moduli that allow the investigator to model the time until a lesion taking into account the variables collected during the inspection process. The aim of this paper is double: a) to shortly introduce the predictive system, as well as the inspection and the analysis methodologies and b) to introduce and illustrate the modeling strategy for the deteriorating process of an urban front. The illustration will be focused on the city of L’Hospitalet de Llobregat (Barcelona, Spain) in which more than 14,000 facades have been inspected and analyzed.

  4. Bayesian inference for the genetic control of water deficit tolerance in spring wheat by stochastic search variable selection.

    Science.gov (United States)

    Safari, Parviz; Danyali, Syyedeh Fatemeh; Rahimi, Mehdi

    2018-06-02

    Drought is the main abiotic stress seriously influencing wheat production. Information about the inheritance of drought tolerance is necessary to determine the most appropriate strategy to develop tolerant cultivars and populations. In this study, generation means analysis to identify the genetic effects controlling grain yield inheritance in water deficit and normal conditions was considered as a model selection problem in a Bayesian framework. Stochastic search variable selection (SSVS) was applied to identify the most important genetic effects and the best fitted models using different generations obtained from two crosses applying two water regimes in two growing seasons. The SSVS is used to evaluate the effect of each variable on the dependent variable via posterior variable inclusion probabilities. The model with the highest posterior probability is selected as the best model. In this study, the grain yield was controlled by the main effects (additive and non-additive effects) and epistatic. The results demonstrate that breeding methods such as recurrent selection and subsequent pedigree method and hybrid production can be useful to improve grain yield.

  5. Angular scanning and variable wavelength surface plasmon resonance allowing free sensor surface selection for optimum material- and bio-sensing

    NARCIS (Netherlands)

    Lakayan, Dina; Tuppurainen, Jussipekka; Albers, Martin; van Lint, Matthijs J.; van Iperen, Dick J.; Weda, Jelmer J.A.; Kuncova-Kallio, Johana; Somsen, Govert W.; Kool, Jeroen

    2018-01-01

    A variable-wavelength Kretschmann configuration surface plasmon resonance (SPR) apparatus with angle scanning is presented. The setup provides the possibility of selecting the optimum wavelength with respect to the properties of the metal layer of the sensorchip, sample matrix, and biomolecular

  6. NUMBER OF SUCCESSIVE CYCLES NECESSARY TO ACHIEVE STABILITY OF SELECTED GROUND REACTION FORCE VARIABLES DURING CONTINUOUS JUMPING

    Directory of Open Access Journals (Sweden)

    Jasmes M.W. Brownjohn

    2009-12-01

    Full Text Available Because of inherent variability in all human cyclical movements, such as walking, running and jumping, data collected across a single cycle might be atypical and potentially unable to represent an individual's generalized performance. The study described here was designed to determine the number of successive cycles due to continuous, repetitive countermovement jumping which a test subject should perform in a single experimental session to achieve stability of the mean of the corresponding continuously measured ground reaction force (GRF variables. Seven vertical GRF variables (period of jumping cycle, duration of contact phase, peak force amplitude and its timing, average rate of force development, average rate of force relaxation and impulse were extracted on the cycle-by-cycle basis from vertical jumping force time histories generated by twelve participants who were jumping in response to regular electronic metronome beats in the range 2-2.8 Hz. Stability of the selected GRF variables across successive jumping cycles was examined for three jumping rates (2, 2.4 and 2.8 Hz using two statistical methods: intra-class correlation (ICC analysis and segmental averaging technique (SAT. Results of the ICC analysis indicated that an average of four successive cycles (mean 4.5 ± 2.7 for 2 Hz; 3.9 ± 2.6 for 2.4 Hz; 3.3 ± 2.7 for 2.8 Hz were necessary to achieve maximum ICC values. Except for jumping period, maximum ICC values took values from 0.592 to 0.991 and all were significantly (p < 0.05 different from zero. Results of the SAT revealed that an average of ten successive cycles (mean 10.5 ± 3.5 for 2 Hz; 9.2 ± 3.8 for 2.4 Hz; 9.0 ± 3.9 for 2.8 Hz were necessary to achieve stability of the selected parameters using criteria previously reported in the literature. Using 10 reference trials, the SAT required standard deviation criterion values of 0.49, 0.41 and 0.55 for 2 Hz, 2.4 Hz and 2.8 Hz jumping rates, respectively, in order to approximate

  7. Multivariate modeling of complications with data driven variable selection: Guarding against overfitting and effects of data set size

    International Nuclear Information System (INIS)

    Schaaf, Arjen van der; Xu Chengjian; Luijk, Peter van; Veld, Aart A. van’t; Langendijk, Johannes A.; Schilstra, Cornelis

    2012-01-01

    Purpose: Multivariate modeling of complications after radiotherapy is frequently used in conjunction with data driven variable selection. This study quantifies the risk of overfitting in a data driven modeling method using bootstrapping for data with typical clinical characteristics, and estimates the minimum amount of data needed to obtain models with relatively high predictive power. Materials and methods: To facilitate repeated modeling and cross-validation with independent datasets for the assessment of true predictive power, a method was developed to generate simulated data with statistical properties similar to real clinical data sets. Characteristics of three clinical data sets from radiotherapy treatment of head and neck cancer patients were used to simulate data with set sizes between 50 and 1000 patients. A logistic regression method using bootstrapping and forward variable selection was used for complication modeling, resulting for each simulated data set in a selected number of variables and an estimated predictive power. The true optimal number of variables and true predictive power were calculated using cross-validation with very large independent data sets. Results: For all simulated data set sizes the number of variables selected by the bootstrapping method was on average close to the true optimal number of variables, but showed considerable spread. Bootstrapping is more accurate in selecting the optimal number of variables than the AIC and BIC alternatives, but this did not translate into a significant difference of the true predictive power. The true predictive power asymptotically converged toward a maximum predictive power for large data sets, and the estimated predictive power converged toward the true predictive power. More than half of the potential predictive power is gained after approximately 200 samples. Our simulations demonstrated severe overfitting (a predicative power lower than that of predicting 50% probability) in a number of small

  8. Selective cesium and strontium removal for TRU-liquid waste including fission products and concentrated nitric acids

    International Nuclear Information System (INIS)

    Mimori, T.; Miyajima, K.; Kozeki, M.; Kubota, T.; Tusa, E.; Keskinen, A.

    1996-01-01

    A nuclide removal system was designed for treatment of liquid radioactive waste at the Japan Atomic Energy Research Institute (JAERI) Tokai site. Total system will include removal of plutonium, cesium and strontium. Removal of plutonium will be carried out by a method developed by JAERI. Removal of cesium and strontium will be carried out by the methods developed in Finland. The whole project will be implemented for JAERI in cooperation between Mitsui Engineering and Shipbuilding and IVO International. This project has been carried out under the Science and Technology Agency (STA) of Japan. The liquid to be treated includes 7.4x10 9 Bq/L of cesium and 7.4x10 9 Bq/L of strontium. The amount of alpha nuclides is 3.7x10 6 Bq/L. Nitric acid concentration is 1.74 mol/L. The volume of 11,000 liters had to be treated in 200 batches of operation. Removal of cesium and strontium is based on the use of new ion exchange materials developed in Finland. These inorganic ion exchange materials have extremely good properties to separate cesium and strontium from even very difficult liquids. Ion exchange material will be used in columns, where there are materials both for cesium and strontium. According to column tests with simulated waste, one 2 liter column will effectively reach the required DF during 10 batches of operation. Purified liquid can be led to further liquid treatment at the site. After treatment of liquids, both used particle filters and used ion exchange columns will be drained and stored to wait for final treatment and disposal. The designed treatment system has a special beneficial feature as it does not produce secondary waste. Final waste is in the form of particle filters or ion exchange columns with material. Used ion exchange columns and filters will be replaced with new ones by means of remote handling. Construction of the treatment system will be scheduled to commence in FY1995 and assemblying at the site in FY1996. (J.P.N.)

  9. The Salience of Selected Variables on Choice for Movie Attendance among High School Students.

    Science.gov (United States)

    Austin, Bruce A.

    A questionnaire was designed for a study assessing both the importance of 28 variables in movie attendance and the importance of movie-going as a leisure-time activity. Respondents were 130 ninth and twelfth grade students. The 28 variables were broadly organized into eight categories: movie production personnel, production elements, advertising,…

  10. Nonrandomized studies are not always found even when selection criteria for health systems intervention reviews include them: a methodological study.

    Science.gov (United States)

    Glenton, Claire; Lewin, Simon; Mayhew, Alain; Scheel, Inger; Odgaard-Jensen, Jan

    2013-04-01

    Systematic reviews within the Cochrane Effective Practice and Organisation of Care Group (EPOC) can include both randomized and nonrandomized study designs. We explored how many EPOC reviews consider and identify nonrandomized studies, and whether the proportion of nonrandomized studies identified is linked to the review topic. We recorded the study designs considered in 65 EPOC reviews. For reviews that considered nonrandomized studies, we calculated the proportion of identified studies that were nonrandomized and explored whether there were differences in the proportion of nonrandomized studies according to the review topic. Fifty-one (78.5%) reviews considered nonrandomized studies. Forty-six of these reviews found nonrandomized studies, but the proportion varied a great deal (median, 33%; interquartile range, 25--50%). Reviews of health care delivery interventions had lower proportions of nonrandomized studies than those of financial and governance interventions. Most EPOC reviews consider nonrandomized studies, but the degree to which they find them varies. As nonrandomized studies are believed to be at higher risk of bias and their inclusion entails a considerable effort, review authors should consider whether the benefits justify the inclusion of these designs. Research should explore whether it is more useful to consider nonrandomized studies in reviews of some intervention types than others. Copyright © 2013 Elsevier Inc. All rights reserved.

  11. PLS-based and regularization-based methods for the selection of relevant variables in non-targeted metabolomics data

    Directory of Open Access Journals (Sweden)

    Renata Bujak

    2016-07-01

    Full Text Available Non-targeted metabolomics constitutes a part of systems biology and aims to determine many metabolites in complex biological samples. Datasets obtained in non-targeted metabolomics studies are multivariate and high-dimensional due to the sensitivity of mass spectrometry-based detection methods as well as complexity of biological matrices. Proper selection of variables which contribute into group classification is a crucial step, especially in metabolomics studies which are focused on searching for disease biomarker candidates. In the present study, three different statistical approaches were tested using two metabolomics datasets (RH and PH study. Orthogonal projections to latent structures-discriminant analysis (OPLS-DA without and with multiple testing correction as well as least absolute shrinkage and selection operator (LASSO were tested and compared. For the RH study, OPLS-DA model built without multiple testing correction, selected 46 and 218 variables based on VIP criteria using Pareto and UV scaling, respectively. In the case of the PH study, 217 and 320 variables were selected based on VIP criteria using Pareto and UV scaling, respectively. In the RH study, OPLS-DA model built with multiple testing correction, selected 4 and 19 variables as statistically significant in terms of Pareto and UV scaling, respectively. For PH study, 14 and 18 variables were selected based on VIP criteria in terms of Pareto and UV scaling, respectively. Additionally, the concept and fundaments of the least absolute shrinkage and selection operator (LASSO with bootstrap procedure evaluating reproducibility of results, was demonstrated. In the RH and PH study, the LASSO selected 14 and 4 variables with reproducibility between 99.3% and 100%. However, apart from the popularity of PLS-DA and OPLS-DA methods in metabolomics, it should be highlighted that they do not control type I or type II error, but only arbitrarily establish a cut-off value for PLS-DA loadings

  12. The role of protozoa-driven selection in shaping human genetic variability.

    Science.gov (United States)

    Pozzoli, Uberto; Fumagalli, Matteo; Cagliani, Rachele; Comi, Giacomo P; Bresolin, Nereo; Clerici, Mario; Sironi, Manuela

    2010-03-01

    Protozoa exert a strong selective pressure in humans. The selection signatures left by these pathogens can be exploited to identify genetic modulators of infection susceptibility. We show that protozoa diversity in different geographic locations is a good measure of protozoa-driven selective pressure; protozoa diversity captured selection signatures at known malaria resistance loci and identified several selected single nucleotide polymorphisms in immune and hemolytic anemia genes. A genome-wide search enabled us to identify 5180 variants mapping to 1145 genes that are subjected to protozoa-driven selective pressure. We provide a genome-wide estimate of protozoa-driven selective pressure and identify candidate susceptibility genes for protozoa-borne diseases. Copyright 2010 Elsevier Ltd. All rights reserved.

  13. Variable selection for confounder control, flexible modeling and Collaborative Targeted Minimum Loss-based Estimation in causal inference

    Science.gov (United States)

    Schnitzer, Mireille E.; Lok, Judith J.; Gruber, Susan

    2015-01-01

    This paper investigates the appropriateness of the integration of flexible propensity score modeling (nonparametric or machine learning approaches) in semiparametric models for the estimation of a causal quantity, such as the mean outcome under treatment. We begin with an overview of some of the issues involved in knowledge-based and statistical variable selection in causal inference and the potential pitfalls of automated selection based on the fit of the propensity score. Using a simple example, we directly show the consequences of adjusting for pure causes of the exposure when using inverse probability of treatment weighting (IPTW). Such variables are likely to be selected when using a naive approach to model selection for the propensity score. We describe how the method of Collaborative Targeted minimum loss-based estimation (C-TMLE; van der Laan and Gruber, 2010) capitalizes on the collaborative double robustness property of semiparametric efficient estimators to select covariates for the propensity score based on the error in the conditional outcome model. Finally, we compare several approaches to automated variable selection in low-and high-dimensional settings through a simulation study. From this simulation study, we conclude that using IPTW with flexible prediction for the propensity score can result in inferior estimation, while Targeted minimum loss-based estimation and C-TMLE may benefit from flexible prediction and remain robust to the presence of variables that are highly correlated with treatment. However, in our study, standard influence function-based methods for the variance underestimated the standard errors, resulting in poor coverage under certain data-generating scenarios. PMID:26226129

  14. A flow system for generation of concentration perturbation in two-dimensional correlation near-infrared spectroscopy: application to variable selection in multivariate calibration.

    Science.gov (United States)

    Pereira, Claudete Fernandes; Pasquini, Celio

    2010-05-01

    A flow system is proposed to produce a concentration perturbation in liquid samples, aiming at the generation of two-dimensional correlation near-infrared spectra. The system presents advantages in relation to batch systems employed for the same purpose: the experiments are accomplished in a closed system; application of perturbation is rapid and easy; and the experiments can be carried out with micro-scale volumes. The perturbation system has been evaluated in the investigation and selection of relevant variables for multivariate calibration models for the determination of quality parameters of gasoline, including ethanol content, MON (motor octane number), and RON (research octane number). The main advantage of this variable selection approach is the direct association between spectral features and chemical composition, allowing easy interpretation of the regression models.

  15. Estimation of Genetic Variance Components Including Mutation and Epistasis using Bayesian Approach in a Selection Experiment on Body Weight in Mice

    DEFF Research Database (Denmark)

    Widyas, Nuzul; Jensen, Just; Nielsen, Vivi Hunnicke

    Selection experiment was performed for weight gain in 13 generations of outbred mice. A total of 18 lines were included in the experiment. Nine lines were allotted to each of the two treatment diets (19.3 and 5.1 % protein). Within each diet three lines were selected upwards, three lines were...... selected downwards and three lines were kept as controls. Bayesian statistical methods are used to estimate the genetic variance components. Mixed model analysis is modified including mutation effect following the methods by Wray (1990). DIC was used to compare the model. Models including mutation effect...... have better fit compared to the model with only additive effect. Mutation as direct effect contributes 3.18% of the total phenotypic variance. While in the model with interactions between additive and mutation, it contributes 1.43% as direct effect and 1.36% as interaction effect of the total variance...

  16. The selection of a mode of urban transportation: Integrating psychological variables to discrete choice models

    International Nuclear Information System (INIS)

    Cordoba Maquilon, Jorge E; Gonzalez Calderon, Carlos A; Posada Henao, John J

    2011-01-01

    A study using revealed preference surveys and psychological tests was conducted. Key psychological variables of behavior involved in the choice of transportation mode in a population sample of the Metropolitan Area of the Valle de Aburra were detected. The experiment used the random utility theory for discrete choice models and reasoned action in order to assess beliefs. This was used as a tool for analysis of the psychological variables using the sixteen personality factor questionnaire (16PF test). In addition to the revealed preference surveys, two other surveys were carried out: one with socio-economic characteristics and the other with latent indicators. This methodology allows for an integration of discrete choice models and latent variables. The integration makes the model operational and quantifies the unobservable psychological variables. The most relevant result obtained was that anxiety affects the choice of urban transportation mode and shows that physiological alterations, as well as problems in perception and beliefs, can affect the decision-making process.

  17. Diagnostic Value of Selected Echocardiographic Variables to Identify Pulmonary Hypertension in Dogs with Myxomatous Mitral Valve Disease.

    Science.gov (United States)

    Tidholm, A; Höglund, K; Häggström, J; Ljungvall, I

    2015-01-01

    Pulmonary hypertension (PH) is commonly associated with myxomatous mitral valve disease (MMVD). Because dogs with PH present without measureable tricuspid regurgitation (TR), it would be useful to investigate echocardiographic variables that can identify PH. To investigate associations between estimated systolic TR pressure gradient (TRPG) and dog characteristics and selected echocardiographic variables. 156 privately owned dogs. Prospective observational study comparing the estimations of TRPG with dog characteristics and selected echocardiographic variables in dogs with MMVD and measureable TR. Tricuspid regurgitation pressure gradient was significantly (P modeled as linear variables LA/Ao (P modeled as second order polynomial variables: AT/DT (P = .0039) and LVIDDn (P value for the final model was 0.45 and receiver operating characteristic curve analysis suggested the model's performance to predict PH, defined as 36, 45, and 55 mmHg as fair (area under the curve [AUC] = 0.80), good (AUC = 0.86), and excellent (AUC = 0.92), respectively. In dogs with MMVD, the presence of PH might be suspected with the combination of decreased PA AT/DT, increased RVIDDn and LA/Ao, and a small or great LVIDDn. Copyright © 2015 The Authors Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.

  18. Determination of main fruits in adulterated nectars by ATR-FTIR spectroscopy combined with multivariate calibration and variable selection methods.

    Science.gov (United States)

    Miaw, Carolina Sheng Whei; Assis, Camila; Silva, Alessandro Rangel Carolino Sales; Cunha, Maria Luísa; Sena, Marcelo Martins; de Souza, Scheilla Vitorino Carvalho

    2018-07-15

    Grape, orange, peach and passion fruit nectars were formulated and adulterated by dilution with syrup, apple and cashew juices at 10 levels for each adulterant. Attenuated total reflectance Fourier transform mid infrared (ATR-FTIR) spectra were obtained. Partial least squares (PLS) multivariate calibration models allied to different variable selection methods, such as interval partial least squares (iPLS), ordered predictors selection (OPS) and genetic algorithm (GA), were used to quantify the main fruits. PLS improved by iPLS-OPS variable selection showed the highest predictive capacity to quantify the main fruit contents. The selected variables in the final models varied from 72 to 100; the root mean square errors of prediction were estimated from 0.5 to 2.6%; the correlation coefficients of prediction ranged from 0.948 to 0.990; and, the mean relative errors of prediction varied from 3.0 to 6.7%. All of the developed models were validated. Copyright © 2018 Elsevier Ltd. All rights reserved.

  19. Genotype-by-environment interactions leads to variable selection on life-history strategy in Common Evening Primrose (Oenothera biennis).

    Science.gov (United States)

    Johnson, M T J

    2007-01-01

    Monocarpic plant species, where reproduction is fatal, frequently exhibit variation in the length of their prereproductive period prior to flowering. If this life-history variation in flowering strategy has a genetic basis, genotype-by-environment interactions (G x E) may maintain phenotypic diversity in flowering strategy. The native monocarpic plant Common Evening Primrose (Oenothera biennis L., Onagraceae) exhibits phenotypic variation for annual vs. biennial flowering strategies. I tested whether there was a genetic basis to variation in flowering strategy in O. biennis, and whether environmental variation causes G x E that imposes variable selection on flowering strategy. In a field experiment, I randomized more than 900 plants from 14 clonal families (genotypes) into five distinct habitats that represented a natural productivity gradient. G x E strongly affected the lifetime fruit production of O. biennis, with the rank-order in relative fitness of genotypes changing substantially between habitats. I detected genetic variation in annual vs. biennial strategies in most habitats, as well as a G x E effect on flowering strategy. This variation in flowering strategy was correlated with genetic variation in relative fitness, and phenotypic and genotypic selection analyses revealed that environmental variation resulted in variable directional selection on annual vs. biennial strategies. Specifically, a biennial strategy was favoured in moderately productive environments, whereas an annual strategy was favoured in low-productivity environments. These results highlight the importance of variable selection for the maintenance of genetic variation in the life-history strategy of a monocarpic plant.

  20. A volatolomic approach for studying plant variability: the case of selected Helichrysum species (Asteraceae).

    Science.gov (United States)

    Giuliani, Claudia; Lazzaro, Lorenzo; Calamassi, Roberto; Calamai, Luca; Romoli, Riccardo; Fico, Gelsomina; Foggi, Bruno; Mariotti Lippi, Marta

    2016-10-01

    The species of Helichrysum sect. Stoechadina (Asteraceae) are well-known for their secondary metabolite content and the characteristic aromatic bouquets. In the wild, populations exhibit a wide phenotypic plasticity which makes critical the circumscription of species and infraspecific ranks. Previous investigations on Helichrysum italicum complex focused on a possible phytochemical typification based on hydrodistilled essential oils. Aims of this paper are three-fold: (i) characterizing the volatile profiles of different populations, testing (ii) how these profiles vary across populations and (iii) how the phytochemical diversity may contribute in solving taxonomic problems. Nine selected Helichrysum populations, included within the H. italicum complex, Helichrysum litoreum and Helichrysum stoechas, were investigated. H. stoechas was chosen as outgroup for validating the method. After collection in the wild, plants were cultivated in standard growing conditions for over one year. Annual leafy shoots were screened in the post-blooming period for the emissions of volatile organic compounds (VOCs) by means of headspace solid phase microextraction coupled with gas-chromatography and mass spectrometry (HS-SPME-GC/MS). The VOC composition analysis revealed the production of overall 386 different compounds, with terpenes being the most represented compound class. Statistical data processing allowed the identification of the indicator compounds that differentiate the single populations, revealing the influence of the geographical provenance area in determining the volatile profiles. These results suggested the potential use of VOCs as valuable diacritical characters in discriminating the Helichrysum populations. In addition, the cross-validation analysis hinted the potentiality of this volatolomic study in the discrimination of the Helichrysum species and subspecies, highlighting a general congruence with the current taxonomic treatment of the genus. The consistency

  1. Using Variable Dwell Time to Accelerate Gaze-based Web Browsing with Two-step Selection

    OpenAIRE

    Chen, Zhaokang; Shi, Bertram E.

    2017-01-01

    In order to avoid the "Midas Touch" problem, gaze-based interfaces for selection often introduce a dwell time: a fixed amount of time the user must fixate upon an object before it is selected. Past interfaces have used a uniform dwell time across all objects. Here, we propose an algorithm for adjusting the dwell times of different objects based on the inferred probability that the user intends to select them. In particular, we introduce a probabilistic model of natural gaze behavior while sur...

  2. FIRE: an SPSS program for variable selection in multiple linear regression analysis via the relative importance of predictors.

    Science.gov (United States)

    Lorenzo-Seva, Urbano; Ferrando, Pere J

    2011-03-01

    We provide an SPSS program that implements currently recommended techniques and recent developments for selecting variables in multiple linear regression analysis via the relative importance of predictors. The approach consists of: (1) optimally splitting the data for cross-validation, (2) selecting the final set of predictors to be retained in the equation regression, and (3) assessing the behavior of the chosen model using standard indices and procedures. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.

  3. Genetic gain and economic values of selection strategies including semen traits in three- and four-way crossbreeding systems for swine production.

    Science.gov (United States)

    González-Peña, D; Knox, R V; MacNeil, M D; Rodriguez-Zas, S L

    2015-03-01

    Four semen traits: volume (VOL), concentration (CON), progressive motility of spermatozoa (MOT), and abnormal spermatozoa (ABN) provide complementary information on boar fertility. Assessment of the impact of selection for semen traits is hindered by limited information on economic parameters. Objectives of this study were to estimate economic values for semen traits and to evaluate the genetic gain when these traits are incorporated into traditional selection strategies in a 3-tier system of swine production. Three-way (maternal nucleus lines A and B and paternal nucleus line C) and 4-way (additional paternal nucleus line D) crossbreeding schemes were compared. A novel population structure that accommodated selection for semen traits was developed. Three selection strategies were simulated. Selection Strategy I (baseline) encompassed selection for maternal traits: number of pigs born alive (NBA), litter birth weight (LBW), adjusted 21-d litter weight (A21), and number of pigs at 21 d (N21); and paternal traits: number of days to 113.5 kg (D113), backfat (BF), ADG, feed efficiency (FE), and carcass lean % (LEAN). Selection Strategy II included Strategy I and the number of usable semen doses per collection (DOSES), a function of the 4 semen traits. Selection Strategy III included Strategy I and the 4 semen traits individually. The estimated economic values of VOL, CON, MOT, ABN, and DOSES for 7 to 1 collections/wk ranged from $0.21 to $1.44/mL, $0.12 to $0.83/10 spermatozoa/mm, $0.61 to $12.66/%, -$0.53 to -$10.88/%, and $2.01 to $41.43/%, respectively. The decrease in the relative economic values of semen traits and DOSES with higher number of collections per wk was sharper between 1 and 2.33 collections/wk than between 2.33 and 7 collections/wk. The higher economic value of MOT and ABN relative to VOL and CON could be linked to the genetic variances and covariances of these traits. Average genetic gains for the maternal traits were comparable across strategies

  4. Firefly as a novel swarm intelligence variable selection method in spectroscopy.

    Science.gov (United States)

    Goodarzi, Mohammad; dos Santos Coelho, Leandro

    2014-12-10

    A critical step in multivariate calibration is wavelength selection, which is used to build models with better prediction performance when applied to spectral data. Up to now, many feature selection techniques have been developed. Among all different types of feature selection techniques, those based on swarm intelligence optimization methodologies are more interesting since they are usually simulated based on animal and insect life behavior to, e.g., find the shortest path between a food source and their nests. This decision is made by a crowd, leading to a more robust model with less falling in local minima during the optimization cycle. This paper represents a novel feature selection approach to the selection of spectroscopic data, leading to more robust calibration models. The performance of the firefly algorithm, a swarm intelligence paradigm, was evaluated and compared with genetic algorithm and particle swarm optimization. All three techniques were coupled with partial least squares (PLS) and applied to three spectroscopic data sets. They demonstrate improved prediction results in comparison to when only a PLS model was built using all wavelengths. Results show that firefly algorithm as a novel swarm paradigm leads to a lower number of selected wavelengths while the prediction performance of built PLS stays the same. Copyright © 2014. Published by Elsevier B.V.

  5. AVC: Selecting discriminative features on basis of AUC by maximizing variable complementarity.

    Science.gov (United States)

    Sun, Lei; Wang, Jun; Wei, Jinmao

    2017-03-14

    The Receiver Operator Characteristic (ROC) curve is well-known in evaluating classification performance in biomedical field. Owing to its superiority in dealing with imbalanced and cost-sensitive data, the ROC curve has been exploited as a popular metric to evaluate and find out disease-related genes (features). The existing ROC-based feature selection approaches are simple and effective in evaluating individual features. However, these approaches may fail to find real target feature subset due to their lack of effective means to reduce the redundancy between features, which is essential in machine learning. In this paper, we propose to assess feature complementarity by a trick of measuring the distances between the misclassified instances and their nearest misses on the dimensions of pairwise features. If a misclassified instance and its nearest miss on one feature dimension are far apart on another feature dimension, the two features are regarded as complementary to each other. Subsequently, we propose a novel filter feature selection approach on the basis of the ROC analysis. The new approach employs an efficient heuristic search strategy to select optimal features with highest complementarities. The experimental results on a broad range of microarray data sets validate that the classifiers built on the feature subset selected by our approach can get the minimal balanced error rate with a small amount of significant features. Compared with other ROC-based feature selection approaches, our new approach can select fewer features and effectively improve the classification performance.

  6. An Investigation of Selected Variables Related to Student Algebra I Performance in Mississippi

    Science.gov (United States)

    Scott, Undray

    2016-01-01

    This research study attempted to determine if specific variables were related to student performance on the Algebra I subject-area test. This study also sought to determine in which of grades 8, 9, or 10 students performed better on the Algebra I Subject Area Test. This study also investigated the different criteria that are used to schedule…

  7. Cortical Response Variability as a Developmental Index of Selective Auditory Attention

    Science.gov (United States)

    Strait, Dana L.; Slater, Jessica; Abecassis, Victor; Kraus, Nina

    2014-01-01

    Attention induces synchronicity in neuronal firing for the encoding of a given stimulus at the exclusion of others. Recently, we reported decreased variability in scalp-recorded cortical evoked potentials to attended compared with ignored speech in adults. Here we aimed to determine the developmental time course for this neural index of auditory…

  8. SPATIAL AND TEMPORAL VARIABILITY IN ACROLEIN AND SELECT VOLATILE ORGANIC COMPOUNDS IN DETROIT, MICHIGAN

    Science.gov (United States)

    The variability in outdoor concentrations of acrolein, benzene, toluene, ethylbenzene and xylenes (BTEX), and 1,3-butadiene was examined for data measured during summer 2004 of the Detroit Exposure and Aerosol Research Study (DEARS). Results for acrolein indicated no significant...

  9. Temporal variability of selected chemical and physical propertires of topsoil of three soil types

    Czech Academy of Sciences Publication Activity Database

    Jirků, V.; Kodešová, R.; Nikodem, A.; Mühlhanselová, M.; Žigová, Anna

    2013-01-01

    Roč. 15, - (2013) ISSN 1607-7962. [EGU General Assembly /10./. 07.04.2013-12.04.2013, Vienna] R&D Projects: GA ČR GA526/08/0434 Institutional support: RVO:67985831 Keywords : soil properties * soil types * temporal variability Subject RIV: DF - Soil Science http://meetingorganizer.copernicus.org/EGU2013/EGU2013-7650-1.pdf

  10. Total sulfur determination in residues of crude oil distillation using FT-IR/ATR and variable selection methods

    Science.gov (United States)

    Müller, Aline Lima Hermes; Picoloto, Rochele Sogari; Mello, Paola de Azevedo; Ferrão, Marco Flores; dos Santos, Maria de Fátima Pereira; Guimarães, Regina Célia Lourenço; Müller, Edson Irineu; Flores, Erico Marlon Moraes

    2012-04-01

    Total sulfur concentration was determined in atmospheric residue (AR) and vacuum residue (VR) samples obtained from petroleum distillation process by Fourier transform infrared spectroscopy with attenuated total reflectance (FT-IR/ATR) in association with chemometric methods. Calibration and prediction set consisted of 40 and 20 samples, respectively. Calibration models were developed using two variable selection models: interval partial least squares (iPLS) and synergy interval partial least squares (siPLS). Different treatments and pre-processing steps were also evaluated for the development of models. The pre-treatment based on multiplicative scatter correction (MSC) and the mean centered data were selected for models construction. The use of siPLS as variable selection method provided a model with root mean square error of prediction (RMSEP) values significantly better than those obtained by PLS model using all variables. The best model was obtained using siPLS algorithm with spectra divided in 20 intervals and combinations of 3 intervals (911-824, 823-736 and 737-650 cm-1). This model produced a RMSECV of 400 mg kg-1 S and RMSEP of 420 mg kg-1 S, showing a correlation coefficient of 0.990.

  11. A variational conformational dynamics approach to the selection of collective variables in metadynamics

    Science.gov (United States)

    McCarty, James; Parrinello, Michele

    2017-11-01

    In this paper, we combine two powerful computational techniques, well-tempered metadynamics and time-lagged independent component analysis. The aim is to develop a new tool for studying rare events and exploring complex free energy landscapes. Metadynamics is a well-established and widely used enhanced sampling method whose efficiency depends on an appropriate choice of collective variables. Often the initial choice is not optimal leading to slow convergence. However by analyzing the dynamics generated in one such run with a time-lagged independent component analysis and the techniques recently developed in the area of conformational dynamics, we obtain much more efficient collective variables that are also better capable of illuminating the physics of the system. We demonstrate the power of this approach in two paradigmatic examples.

  12. Identifying market segments in consumer markets: variable selection and data interpretation

    OpenAIRE

    Tonks, D G

    2004-01-01

    Market segmentation is often articulated as being a process which displays the recognised features of classical rationalism but in part; convention, convenience, prior experience and the overarching impact of rhetoric will influence if not determine the outcomes of a segmentation exercise. Particular examples of this process are addressed critically in this paper which concentrates on the issues of variable choice for multivariate approaches to market segmentation and also the methods used fo...

  13. Ultrahigh Dimensional Variable Selection for Interpolation of Point Referenced Spatial Data: A Digital Soil Mapping Case Study

    Science.gov (United States)

    Lamb, David W.; Mengersen, Kerrie

    2016-01-01

    Modern soil mapping is characterised by the need to interpolate point referenced (geostatistical) observations and the availability of large numbers of environmental characteristics for consideration as covariates to aid this interpolation. Modelling tasks of this nature also occur in other fields such as biogeography and environmental science. This analysis employs the Least Angle Regression (LAR) algorithm for fitting Least Absolute Shrinkage and Selection Operator (LASSO) penalized Multiple Linear Regressions models. This analysis demonstrates the efficiency of the LAR algorithm at selecting covariates to aid the interpolation of geostatistical soil carbon observations. Where an exhaustive search of the models that could be constructed from 800 potential covariate terms and 60 observations would be prohibitively demanding, LASSO variable selection is accomplished with trivial computational investment. PMID:27603135

  14. Empirically Driven Variable Selection for the Estimation of Causal Effects with Observational Data

    Science.gov (United States)

    Keller, Bryan; Chen, Jianshen

    2016-01-01

    Observational studies are common in educational research, where subjects self-select or are otherwise non-randomly assigned to different interventions (e.g., educational programs, grade retention, special education). Unbiased estimation of a causal effect with observational data depends crucially on the assumption of ignorability, which specifies…

  15. The study of variability and strain selection in Streptomyces atroolivaceus. III

    International Nuclear Information System (INIS)

    Blumauerova, M.; Lipavska, H.; Stajner, K.; Vanek, Z.

    1976-01-01

    Mutants of Streptomyces atroolivaceus blocked in the biosynthesis of mithramycin were isolated both by natural selection and after treatment with mutagenic factors (UV and gamma rays, nitrous acid). Both physical factors were more effective than nitrous acid. The selection was complicated by the high instability of isolates, out of which 20 to 80%=. (depending on their origin) reversed spontaneously to the parent type. Primary screening (selection of morphological variants and determination of their activity using the method of agar blocks) made it possible to detect only potentially non-productive strains; however, the final selection always had to be made under submerged conditions. Fifty-four stable non-productive mutants were divided, according to results of the chromatographic analysis, into five groups differing in the production of the six biologically inactive metabolites. The mutants did not accumulate chromomycinone, chromocyclomycin and chromocyclin. On mixed cultivation none of the pairs of mutants was capable of the cosynthesis of mithramycin or of new compounds differing from standard metabolites. Possible causes of the above results are discussed. (author)

  16. COPD phenotypes on computed tomography and its correlation with selected lung function variables in severe patients

    Directory of Open Access Journals (Sweden)

    da Silva SMD

    2016-03-01

    Full Text Available Silvia Maria Doria da Silva, Ilma Aparecida Paschoal, Eduardo Mello De Capitani, Marcos Mello Moreira, Luciana Campanatti Palhares, Mônica Corso PereiraPneumology Service, Department of Internal Medicine, School of Medical Sciences, State University of Campinas (UNICAMP, Campinas, São Paulo, BrazilBackground: Computed tomography (CT phenotypic characterization helps in understanding the clinical diversity of chronic obstructive pulmonary disease (COPD patients, but its clinical relevance and its relationship with functional features are not clarified. Volumetric capnography (VC uses the principle of gas washout and analyzes the pattern of CO2 elimination as a function of expired volume. The main variables analyzed were end-tidal concentration of carbon dioxide (ETCO2, Slope of phase 2 (Slp2, and Slope of phase 3 (Slp3 of capnogram, the curve which represents the total amount of CO2 eliminated by the lungs during each breath.Objective: To investigate, in a group of patients with severe COPD, if the phenotypic analysis by CT could identify different subsets of patients, and if there was an association of CT findings and functional variables.Subjects and methods: Sixty-five patients with COPD Gold III–IV were admitted for clinical evaluation, high-resolution CT, and functional evaluation (spirometry, 6-minute walk test [6MWT], and VC. The presence and profusion of tomography findings were evaluated, and later, the patients were identified as having emphysema (EMP or airway disease (AWD phenotype. EMP and AWD groups were compared; tomography findings scores were evaluated versus spirometric, 6MWT, and VC variables.Results: Bronchiectasis was found in 33.8% and peribronchial thickening in 69.2% of the 65 patients. Structural findings of airways had no significant correlation with spirometric variables. Air trapping and EMP were strongly correlated with VC variables, but in opposite directions. There was some overlap between the EMP and AWD

  17. Characterization of Machine Variability and Progressive Heat Treatment in Selective Laser Melting of Inconel 718

    Science.gov (United States)

    Prater, Tracie; Tilson, Will; Jones, Zack

    2015-01-01

    The absence of an economy of scale in spaceflight hardware makes additive manufacturing an immensely attractive option for propulsion components. As additive manufacturing techniques are increasingly adopted by government and industry to produce propulsion hardware in human-rated systems, significant development efforts are needed to establish these methods as reliable alternatives to conventional subtractive manufacturing. One of the critical challenges facing powder bed fusion techniques in this application is variability between machines used to perform builds. Even with implementation of robust process controls, it is possible for two machines operating at identical parameters with equivalent base materials to produce specimens with slightly different material properties. The machine variability study presented here evaluates 60 specimens of identical geometry built using the same parameters. 30 samples were produced on machine 1 (M1) and the other 30 samples were built on machine 2 (M2). Each of the 30-sample sets were further subdivided into three subsets (with 10 specimens in each subset) to assess the effect of progressive heat treatment on machine variability. The three categories for post-processing were: stress relief, stress relief followed by hot isostatic press (HIP), and stress relief followed by HIP followed by heat treatment per AMS 5664. Each specimen (a round, smooth tensile) was mechanically tested per ASTM E8. Two formal statistical techniques, hypothesis testing for equivalency of means and one-way analysis of variance (ANOVA), were applied to characterize the impact of machine variability and heat treatment on six material properties: tensile stress, yield stress, modulus of elasticity, fracture elongation, and reduction of area. This work represents the type of development effort that is critical as NASA, academia, and the industrial base work collaboratively to establish a path to certification for additively manufactured parts. For future

  18. Some compositional and health indicators of milk quality of dairy cows with higher milk yield at including of selected corn species into feeding ration

    Directory of Open Access Journals (Sweden)

    Jan Pozdíšek

    2008-01-01

    Full Text Available Because of economical reasons the substitution of maize by feed corn as wheat (Sulamit and triticale (Kitaro was revolved in concentrate part of dairy cow feeding rations. The design of mentioned replacement in feeding rations was carried out according to results of previous research (Pozdíšek and Vaculová, 2008 for nutrition experiment. The aim of this paper was to evaluate the possible effects of corn replacement in cow feeding rations on milk composition and properties. The expressively different variants of corn were selected for experiment in comparison to maize (reference. Dairy cows were fed by total mixed ration on the basis of maize and clover silage and hay. Otherwise the identical day feeding rations among cow groups differed only in concentrate portions ((K, control group maize 1.5 kg, wheat (P1 2.0 kg and triticale (P2 2.0 kg (experimental groups. Group feeding rations 1 (K, 2 (P1 and 3 (P2 had: NEL/kg dry (DM matter (6.524, 6.512 and 6.491; NL % in DM (17.9, 18.2 and 17.9; fibre % in DM (15.96, 15.74 and 15.72; PDIN/PDIE (1.189, 1.189 and 1.191. The experiment took six weeks, there were included 8, 9 and 9 cows (n = 26 of Czech Fleckvieh breed. Feed groups were well balanced in terms of milk yield, days in milk and number of lactation. The tie stable and pipeline milking equipment were used in experiment. Animals were milked twice a day and sampled at morning milking in intervals about seven days approximately. Cows were relatively healthy in terms of occurrence of milk secretion disorders. Within groups the individual milk samples (in total 182 in experiment were aggregated into bulk samples (n = 21 = 3 groups × 7 sampling periods, which were analysed on 45 milk indicators, 18 of them were evaluated in this paper. The differences in milk yield were significantly advantageous for K group (15.32 > 14.07 (wheat or 13.86 kg (triticale at morning milking, while fat (3.27 < 3.47 or 3.44 % was lower (P < 0.05. Lactose was not

  19. The relationship between selected variables and customer loyalty within an optometric practice environment

    Directory of Open Access Journals (Sweden)

    T. Van Vuuren

    2012-12-01

    Full Text Available Purpose: The purpose of the research that informed this article was to examine the relationship between customer satisfaction, trust, supplier image, commitment and customer loyalty within an optometric practice environment. Problem investigated: Optometric businesses need to adopt their strategies to enhance loyalty, as customer satisfaction is not enough to ensure loyalty and customer retention. An understanding of the variables influencing loyalty could help businesses within the optometric service environment to retain their customers and become more profitable. Methodology: The methodological approach followed was exploratory and quantitative in nature. The sample consisted of 357 customers who visited the practice twice or more over the previous six years. A structured questionnaire, with a five-point Likert scale, was fielded to gather the data. The descriptive and multiple regression analysis approach was used to analyse the results. Collinearity statistics and Pearson's correlation coefficient were also calculated to determine which independent variable has the largest influence on customer loyalty. Findings and implications: The main finding is that customer satisfaction had the highest correlation with customer loyalty. The other independent variables, however, also appear to significantly influence customer loyalty within an optometric practice environment. The implication is that optometric practices need to focus on customer satisfaction, trust, supplier image and commitment when addressing the improvement of customer loyalty. Originality and value of the research: The article contributes to the improvement of customer loyalty within a service business environment that could assist in facilitating larger market share, higher customer retention and greater profitability for the business over the long term.

  20. Select injury-related variables are affected by stride length and foot strike style during running.

    Science.gov (United States)

    Boyer, Elizabeth R; Derrick, Timothy R

    2015-09-01

    Some frontal plane and transverse plane variables have been associated with running injury, but it is not known if they differ with foot strike style or as stride length is shortened. To identify if step width, iliotibial band strain and strain rate, positive and negative free moment, pelvic drop, hip adduction, knee internal rotation, and rearfoot eversion differ between habitual rearfoot and habitual mid-/forefoot strikers when running with both a rearfoot strike (RFS) and a mid-/forefoot strike (FFS) at 3 stride lengths. Controlled laboratory study. A total of 42 healthy runners (21 habitual rearfoot, 21 habitual mid-/forefoot) ran overground at 3.35 m/s with both a RFS and a FFS at their preferred stride lengths and 5% and 10% shorter. Variables did not differ between habitual groups. Step width was 1.5 cm narrower for FFS, widening to 0.8 cm as stride length shortened. Iliotibial band strain and strain rate did not differ between foot strikes but decreased as stride length shortened (0.3% and 1.8%/s, respectively). Pelvic drop was reduced 0.7° for FFS compared with RFS, and both pelvic drop and hip adduction decreased as stride length shortened (0.8° and 1.5°, respectively). Peak knee internal rotation was not affected by foot strike or stride length. Peak rearfoot eversion was not different between foot strikes but decreased 0.6° as stride length shortened. Peak positive free moment (normalized to body weight [BW] and height [h]) was not affected by foot strike or stride length. Peak negative free moment was -0.0038 BW·m/h greater for FFS and decreased -0.0004 BW·m/h as stride length shortened. The small decreases in most variables as stride length shortened were likely associated with the concomitant wider step width. RFS had slightly greater pelvic drop, while FFS had slightly narrower step width and greater negative free moment. Shortening one's stride length may decrease or at least not increase propensity for running injuries based on the variables

  1. Effect of Integrated Yoga Module on Selected Psychological Variables among Women with Anxiety Problem.

    Science.gov (United States)

    Parthasarathy, S; Jaiganesh, K; Duraisamy

    2014-01-01

    The implementation of yogic practices has proven benefits in both organic and psychological diseases. Forty-five women with anxiety selected by a random sampling method were divided into three groups. Experimental group I was subjected to asanas, relaxation and pranayama while Experimental group II was subjected to an integrated yoga module. The control group did not receive any intervention. Anxiety was measured by Taylor's Manifest Anxiety Scale before and after treatment. Frustration was measured through Reaction to Frustration Scale. All data were spread in an Excel sheet to be analysed with SPSS 16 software using analysis of covariance (ANCOVA). Selected yoga and asanas decreased anxiety and frustration scores but treatment with an integrated yoga module resulted in significant reduction of anxiety and frustration. To conclude, the practice of asanas and yoga decreased anxiety in women, and yoga as an integrated module significantly improved anxiety scores in young women with proven anxiety without any ill effects.

  2. Induction and selection of superior genetic variables of oil seed rape (brassica napus L.)

    International Nuclear Information System (INIS)

    Shah, S.S.; Ali, I.; Rehman, K.

    1990-01-01

    Dry and uniform seeds of two rape seed varieties, Ganyou-5 and Tower, were subjected to different doses of gamma rays. Genetic variation in yield and yield components generated in M1 was studied in M2 and 30 useful variants were isolated from a large magnetized population. The selected mutants were progeny tested for stability of the characters in M3. Only five out of 30 progenies were identified to be uniform and stable. Further selection was made in the segregating m3 progenies. Results on some of the promising mutants are reported. The effect of irradiation treatment was highly pronounced on pod length, seeds per pod and 1000-seed weight. The genetic changes thus induced would help to evolve high yielding versions of different rape seed varieties under local environmental conditions. (author)

  3. Travelling green : Variables influencing students’ intention to select a green hotel

    OpenAIRE

    Lindqvist, Julia; Andersson, Mikaela

    2015-01-01

    Problematization: Tourism has a major impact on the environment. However, there is a conflict of interest making it difficult for the hotel business to decrease this impact. On the one hand, there is a pressure for environmentally friendly behaviour from society. On the other hand, the customers want to be pampered during their hotel stay. This makes it necessary to further investigate what influences customers’ intention to select a green hotel. Therefore this thesis examines students’ inten...

  4. Models of simulation and prediction of the behavior of dengue in four Colombian cities, including climate like modulating variable of the disease

    International Nuclear Information System (INIS)

    Garcia Giraldo, Jairo A; Boshell, Jose Francisco

    2004-01-01

    ARIMA-type models are proposed to simulate the behavior of dengue and to make apparent the relations with the climatic variability in four localities of Colombia. The climatic variable was introduced into the models as an index that modulates the behavior of the disease. It was obtained by means of a multivariate analysis of principal components. The investigation was carried out with information corresponding to the epidemiological weeks from January 1997 to December 2000, for both the number of disease cases and the data corresponding to the meteorological variables. The study shows that the variations of the climate between the previous 9 to 14 weeks have influence on the appearance of new cases of dengue. In particular, the precipitation in these weeks was seen to be greater when in later periods the disease presented epidemic characteristics than the precipitation in those weeks preceded the disease within endemic limits

  5. The effect of aquatic plyometric training with and without resistance on selected physical fitness variables among volleyball players

    Directory of Open Access Journals (Sweden)

    K. KAMALAKKANNAN

    2011-06-01

    Full Text Available The purpose of this study is to analyze the effect of aquatic plyometric training with and without the use ofweights on selected physical fitness variables among volleyball players. To achieve the purpose of these study 36physically active undergraduate volleyball players between 18 and 20 years of age volunteered as participants.The participants were randomly categorized into three groups of 12 each: a control group (CG, an aquaticPlyometric training with weight group (APTWG, and an aquatic Plyometric training without weight group(APTWOG. The subjects of the control group were not exposed to any training. Both experimental groupsunderwent their respective experimental treatment for 12 weeks, 3 days per week and a single session on eachday. Speed, endurance, and explosive power were measured as the dependent variables for this study. 36 days ofexperimental treatment was conducted for all the groups and pre and post data was collected. The collected datawere analyzed using an analysis of covariance (ANCOVA and followed by a Scheffé’s post hoc test. The resultsrevealed significant differences between groups on all the selected dependent variables. This study demonstratedthat aquatic plyometric training can be one effective means for improving speed, endurance, and explosivepower in volley ball players

  6. Neuronal Intra-Individual Variability Masks Response Selection Differences between ADHD Subtypes—A Need to Change Perspectives

    Directory of Open Access Journals (Sweden)

    Annet Bluschke

    2017-06-01

    Full Text Available Due to the high intra-individual variability in attention deficit/hyperactivity disorder (ADHD, there may be considerable bias in knowledge about altered neurophysiological processes underlying executive dysfunctions in patients with different ADHD subtypes. When aiming to establish dimensional cognitive-neurophysiological constructs representing symptoms of ADHD as suggested by the initiative for Research Domain Criteria, it is crucial to consider such processes independent of variability. We examined patients with the predominantly inattentive subtype (attention deficit disorder, ADD and the combined subtype of ADHD (ADHD-C in a flanker task measuring conflict control. Groups were matched for task performance. Besides using classic event-related potential (ERP techniques and source localization, neurophysiological data was also analyzed using residue iteration decomposition (RIDE to statistically account for intra-individual variability and S-LORETA to estimate the sources of the activations. The analysis of classic ERPs related to conflict monitoring revealed no differences between patients with ADD and ADHD-C. When individual variability was accounted for, clear differences became apparent in the RIDE C-cluster (analog to the P3 ERP-component. While patients with ADD distinguished between compatible and incompatible flanker trials early on, patients with ADHD-C seemed to employ more cognitive resources overall. These differences are reflected in inferior parietal areas. The study demonstrates differences in neuronal mechanisms related to response selection processes between ADD and ADHD-C which, according to source localization, arise from the inferior parietal cortex. Importantly, these differences could only be detected when accounting for intra-individual variability. The results imply that it is very likely that differences in neurophysiological processes between ADHD subtypes are underestimated and have not been recognized because intra

  7. Variability and accuracy of coronary CT angiography including use of iterative reconstruction algorithms for plaque burden assessment as compared with intravascular ultrasound - an ex vivo study

    Energy Technology Data Exchange (ETDEWEB)

    Stolzmann, Paul [Massachusetts General Hospital and Harvard Medical School, Cardiac MR PET CT Program, Boston, MA (United States); University Hospital Zurich, Institute of Diagnostic and Interventional Radiology, Zurich (Switzerland); Schlett, Christopher L.; Maurovich-Horvat, Pal; Scheffel, Hans; Engel, Leif-Christopher; Karolyi, Mihaly; Hoffmann, Udo [Massachusetts General Hospital and Harvard Medical School, Cardiac MR PET CT Program, Boston, MA (United States); Maehara, Akiko; Ma, Shixin; Mintz, Gary S. [Columbia University Medical Center, Cardiovascular Research Foundation, New York, NY (United States)

    2012-10-15

    To systematically assess inter-technique and inter-/intra-reader variability of coronary CT angiography (CTA) to measure plaque burden compared with intravascular ultrasound (IVUS) and to determine whether iterative reconstruction algorithms affect variability. IVUS and CTA data were acquired from nine human coronary arteries ex vivo. CT images were reconstructed using filtered back projection (FBPR) and iterative reconstruction algorithms: adaptive-statistical (ASIR) and model-based (MBIR). After co-registration of 284 cross-sections between IVUS and CTA, two readers manually delineated the cross-sectional plaque area in all images presented in random order. Average plaque burden by IVUS was 63.7 {+-} 10.7% and correlated significantly with all CTA measurements (r = 0.45-0.52; P < 0.001), while CTA overestimated the burden by 10 {+-} 10%. There were no significant differences among FBPR, ASIR and MBIR (P > 0.05). Increased overestimation was associated with smaller plaques, eccentricity and calcification (P < 0.001). Reproducibility of plaque burden by CTA and IVUS datasets was excellent with a low mean intra-/inter-reader variability of <1/<4% for CTA and <0.5/<1% for IVUS respectively (P < 0.05) with no significant difference between CT reconstruction algorithms (P > 0.05). In ex vivo coronary arteries, plaque burden by coronary CTA had extremely low inter-/intra-reader variability and correlated significantly with IVUS measurements. Accuracy as well as reader reliability were independent of CT image reconstruction algorithm. (orig.)

  8. Is DAS28-CRP with three and four variables interchangeable in individual patients selected for biological treatment in daily clinical practice?

    DEFF Research Database (Denmark)

    Madsen, Ole Rintek

    2011-01-01

    DAS28 is a widely used composite score for the assessment of disease activity in patients with rheumatoid arthritis (RA) and is often used as a treatment decision tool in the daily clinic. Different versions of DAS28 are available. DAS28-CRP(3) is calculated based on three variables: swollen...... and tender joint counts and CRP. DAS28-CRP(4) also includes patient global assessment. Thresholds for low and high disease activity are the same for the two scores. Based on the Bland-Altman method, the interchangeability between DAS28-CRP with three and four variables was examined in 319 RA patients...... selected for initiating biological treatment. Data were extracted from the Danish registry for biological treatment in rheumatology (DANBIO). Multiple regression analysis was used to assess the predictability of the DAS28 scores by several measures of disease activity. The overall mean DAS28-CRP was 4...

  9. Robust portfolio selection based on asymmetric measures of variability of stock returns

    Science.gov (United States)

    Chen, Wei; Tan, Shaohua

    2009-10-01

    This paper addresses a new uncertainty set--interval random uncertainty set for robust optimization. The form of interval random uncertainty set makes it suitable for capturing the downside and upside deviations of real-world data. These deviation measures capture distributional asymmetry and lead to better optimization results. We also apply our interval random chance-constrained programming to robust mean-variance portfolio selection under interval random uncertainty sets in the elements of mean vector and covariance matrix. Numerical experiments with real market data indicate that our approach results in better portfolio performance.

  10. Joint High-Dimensional Bayesian Variable and Covariance Selection with an Application to eQTL Analysis

    KAUST Repository

    Bhadra, Anindya

    2013-04-22

    We describe a Bayesian technique to (a) perform a sparse joint selection of significant predictor variables and significant inverse covariance matrix elements of the response variables in a high-dimensional linear Gaussian sparse seemingly unrelated regression (SSUR) setting and (b) perform an association analysis between the high-dimensional sets of predictors and responses in such a setting. To search the high-dimensional model space, where both the number of predictors and the number of possibly correlated responses can be larger than the sample size, we demonstrate that a marginalization-based collapsed Gibbs sampler, in combination with spike and slab type of priors, offers a computationally feasible and efficient solution. As an example, we apply our method to an expression quantitative trait loci (eQTL) analysis on publicly available single nucleotide polymorphism (SNP) and gene expression data for humans where the primary interest lies in finding the significant associations between the sets of SNPs and possibly correlated genetic transcripts. Our method also allows for inference on the sparse interaction network of the transcripts (response variables) after accounting for the effect of the SNPs (predictor variables). We exploit properties of Gaussian graphical models to make statements concerning conditional independence of the responses. Our method compares favorably to existing Bayesian approaches developed for this purpose. © 2013, The International Biometric Society.

  11. SEASONAL VARIABILITY OF SELECTED NUTRIENTS IN THE WATERS OF LAKES NIEPRUSZEWSKIE, PAMIATKOWSKIE AND STRYKOWSKIE

    Directory of Open Access Journals (Sweden)

    Anna Zbierska

    2016-09-01

    Full Text Available The paper presents the evaluation of seasonal and long-term changes in selected nutrients of three lakes of the Poznań Lakeland. The lakes were selected due to the high risk of pollution from agricultural and residential areas. Water samples were taken in 6 control points in the spring, summer and autumn, from 2004 to 2014. Trophic status of the lakes was evaluated based on the concentration of nutrients (nitrates, nitrites, ammonium, nitrogen and phosphorus and indicators of eutrophication. Studies have shown that the concentration of nutrients varied greatly both in individual years and seasons of the analyzed decades, especially in Lakes Niepruszewskie and Pamiątkowskie. The main problem is the high concentration of nitrates. In general, it showed an upward trend until 2013, especially in the spring. This may indicate that actions restricting runoff pollution from agricultural sources have not been fully effective. On the other hand, a marked downward trend in the concentrations of NH4 over the years from 2004 to 2014, especially after 2007, indicates a gradual improvement of wastewater management. Moreover, seasonal variation in NH4 concentrations differed from those of NO3 and NO2. The highest values were reported in the autumn season, the lowest in the summer. Concentrations of nutrients and eutrophication indexes reached high values in all analysed lakes, indicating a eutrophic or hypertrophic state of the lakes. The high value of the N:P ratio indicates that the lakes had a huge surplus of nitrogen, and phosphorus is a productivity limiting factor.

  12. 12 YEARS OF X-RAY VARIABILITY IN M31 GLOBULAR CLUSTERS, INCLUDING 8 BLACK HOLE CANDIDATES, AS SEEN BY CHANDRA

    International Nuclear Information System (INIS)

    Barnard, R.; Garcia, M.; Murray, S. S.

    2012-01-01

    We examined 134 Chandra observations of the population of X-ray sources associated with globular clusters (GCs) in the central region of M31. These are expected to be X-ray binary systems (XBs), consisting of a neutron star or black hole accreting material from a close companion. We created long-term light curves for these sources, correcting for background, interstellar absorption, and instrumental effects. We tested for variability by examining the goodness of fit for the best-fit constant intensity. We also created structure functions (SFs) for every object in our sample, the first time this technique has been applied to XBs. We found significant variability in 28 out of 34 GCs and GC candidates; the other 6 sources had 0.3-10 keV luminosities fainter than ∼2 × 10 36 erg s –1 , limiting our ability to detect similar variability. The SFs of XBs with 0.3-10 keV luminosities ∼2-50 × 10 36 erg s –1 generally showed considerably more variability than the published ensemble SF of active galactic nuclei (AGNs). Our brightest XBs were mostly consistent with the AGN SF; however, their 2-10 keV fluxes could be matched by <1 AGN per square degree. These encouraging results suggest that examining the long-term light curves of other X-ray sources in the field may provide an important distinction between X-ray binaries and background galaxies, as the X-ray emission spectra from these two classes of X-ray sources are similar. Additionally, we identify 3 new black hole candidates (BHCs) using additional XMM-Newton data, bringing the total number of M31 GC BHCs to 9, with 8 covered in this survey.

  13. A Variable Service Broker Routing Policy for data center selection in cloud analyst

    Directory of Open Access Journals (Sweden)

    Ahmad M. Manasrah

    2017-07-01

    Full Text Available Cloud computing depends on sharing distributed computing resources to handle different services such as servers, storage and applications. The applications and infrastructures are provided as pay per use services through data center to the end user. The data centers are located at different geographic locations. However, these data centers can get overloaded with the increase number of client applications being serviced at the same time and location; this will degrade the overall QoS of the distributed services. Since different user applications may require different configuration and requirements, measuring the user applications performance of various resources is challenging. The service provider cannot make decisions for the right level of resources. Therefore, we propose a Variable Service Broker Routing Policy – VSBRP, which is a heuristic-based technique that aims to achieve minimum response time through considering the communication channel bandwidth, latency and the size of the job. The proposed service broker policy will also reduce the overloading of the data centers by redirecting the user requests to the next data center that yields better response and processing time. The simulation shows promising results in terms of response and processing time compared to other known broker policies from the literature.

  14. Bias and Stability of Single Variable Classifiers for Feature Ranking and Selection.

    Science.gov (United States)

    Fakhraei, Shobeir; Soltanian-Zadeh, Hamid; Fotouhi, Farshad

    2014-11-01

    Feature rankings are often used for supervised dimension reduction especially when discriminating power of each feature is of interest, dimensionality of dataset is extremely high, or computational power is limited to perform more complicated methods. In practice, it is recommended to start dimension reduction via simple methods such as feature rankings before applying more complex approaches. Single Variable Classifier (SVC) ranking is a feature ranking based on the predictive performance of a classifier built using only a single feature. While benefiting from capabilities of classifiers, this ranking method is not as computationally intensive as wrappers. In this paper, we report the results of an extensive study on the bias and stability of such feature ranking method. We study whether the classifiers influence the SVC rankings or the discriminative power of features themselves has a dominant impact on the final rankings. We show the common intuition of using the same classifier for feature ranking and final classification does not always result in the best prediction performance. We then study if heterogeneous classifiers ensemble approaches provide more unbiased rankings and if they improve final classification performance. Furthermore, we calculate an empirical prediction performance loss for using the same classifier in SVC feature ranking and final classification from the optimal choices.

  15. Impact of oil price shocks on selected macroeconomic variables in Nigeria

    International Nuclear Information System (INIS)

    Iwayemi, Akin; Fowowe, Babajide

    2011-01-01

    The impact of oil price shocks on the macroeconomy has received a great deal of attention since the 1970 s. Initially, many empirical studies found a significant negative effect between oil price shocks and GDP but more recently, empirical studies have reported an insignificant relationship between oil shocks and the macroeconomy. A key feature of existing research is that it applies predominantly to advanced, oil-importing countries. For oil-exporting countries, different conclusions are expected but this can only be ascertained empirically. This study conducts an empirical analysis of the effects of oil price shocks on a developing country oil-exporter - Nigeria. Our findings showed that oil price shocks do not have a major impact on most macroeconomic variables in Nigeria. The results of the Granger-causality tests, impulse response functions, and variance decomposition analysis all showed that different measures of linear and positive oil shocks have not caused output, government expenditure, inflation, and the real exchange rate. The tests support the existence of asymmetric effects of oil price shocks because we find that negative oil shocks significantly cause output and the real exchange rate. (author)

  16. Effect of Selected Variables on Regular School Teachers Attitude towards Inclusive Education

    Science.gov (United States)

    Priyadarshini, S. Saradha; Thangarajathi, S.

    2017-01-01

    Inclusive education is a means of creating effective classrooms where educational needs of all children including children with special needs are addressed. The concept of inclusion is still emerging as far as India is concerned. In the recent years, there is a growing awareness about inclusive education among educators. Government of India had…

  17. Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra

    Science.gov (United States)

    Shan, Jiajia; Wang, Xue; Zhou, Hao; Han, Shuqing; Riza, Dimas Firmanda Al; Kondo, Naoshi

    2018-04-01

    Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models’ performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.

  18. Selective nature and inherent variability of interrill erosion across prolonged rainfall simulation

    Science.gov (United States)

    Hu, Y.; Kuhn, N. J.; Fister, W.

    2012-04-01

    Sediment of interrill erosion has been generally recognized to be selectively enriched with soil organic carbon (SOC) and fine fractions (clay/silt-sized particles or aggregates) in comparison to source area soil. Limited kinetic energy and lack of concentrated runoff are the dominant factors causing selective detachment and transportation. Although enrichment ratios of SOC (ERsoc) in eroded sediment were generally reported > 1, the values varied widely. Causal factors to variation, such as initial soil properties, rainfall properties and experimental conditions, have been extensively discussed. But less attention was directed to the potential influence of prolonged rainfall time onto the temporal pattern of ERsoc. Conservation of mass dictates that ERsoc must be balanced by a decline in the source material which should also lead to a reduced or even negative ERsoc in sediment over time. Besides, the stabilizing effects of structural crust on reducing erosional variation, and the unavoidable variations of erosional response induced by the inherent complexity of interrill erosion, have scarcely been integrated. Moreover, during a prolonged rainfall event surface roughness evolves and affects the movement of eroded aggregates and mineral particles. In this study, two silt loams from Möhlin, Switzerland, organically (OS) and conventionally farmed (CS), were exposed to simulated rainfall of 30 mm h-1 for up to 6 hours. Round donut-flumes with a confined eroding area (1845 cm2) and limited transporting distance (20 cm) were used. Sediments, runoff and subsurface flow were collected in intervals of 30 min. Loose aggregates left on the eroded soil surface, crusts and the soil underneath the crusts were collected after the experiment. All the samples were analyzed for total organic carbon (TOC) content, and texture. Laser scanning of soil surface was applied before and after the rainfall event. The whole experiment was repeated for 10 times. Results from this study showed

  19. The influence of selected socio-demographic variables on symptoms occurring during the menopause

    Directory of Open Access Journals (Sweden)

    Marta Makara-Studzińska

    2015-02-01

    Full Text Available Introduction: It is considered that the lifestyle conditioned by socio-demographic or socio-economic factors determines the health condition of people to the greatest extent. The aim of this study is to evaluate the influence of selected socio-demographic factors on the kinds of symptoms occurring during menopause. Material and methods : The study group consisted of 210 women aged 45 to 65, not using hormone replacement therapy, staying at healthcare centers for rehabilitation treatment. The study was carried out in 2013-2014 in the Silesian, Podlaskie and Lesser Poland voivodeships. The set of tools consisted of the authors’ own survey questionnaire and the Menopause Rating Scale (MRS. Results : The most commonly occurring symptom in the group of studied women was a depressive mood, from the group of psychological symptoms, followed by physical and mental fatigue, and discomfort connected with muscle and joint pain. The greatest intensity of symptoms was observed in the group of women with the lowest level of education, reporting an average or bad material situation, and unemployed women. Conclusions : An alarmingly high number of reported psychological symptoms in the group of menopausal women was observed, and in particular among the group of low socio-economic status. Career seems to be a factor reducing the risk of occurrence of psychological symptoms. There is an urgent need for health promotion and prophylaxis in the group of menopausal women, and in many cases for implementation of specialist psychological assistance.

  20. Characterization of SiO2/SiC interface states and channel mobility from MOSFET characteristics including variable-range hopping at cryogenic temperature

    Directory of Open Access Journals (Sweden)

    Hironori Yoshioka

    2018-04-01

    Full Text Available The characteristics of SiC MOSFETs (drain current vs. gate voltage were measured at 0.14−350 K and analyzed considering variable-range hopping conduction through interface states. The total interface state density was determined to be 5.4×1012 cm−2 from the additional shift in the threshold gate voltage with a temperature change. The wave-function size of interface states was determined from the temperature dependence of the measured hopping current and was comparable to the theoretical value. The channel mobility was approximately 100 cm2V−1s−1 and was almost independent of temperature.

  1. Characterization of SiO2/SiC interface states and channel mobility from MOSFET characteristics including variable-range hopping at cryogenic temperature

    Science.gov (United States)

    Yoshioka, Hironori; Hirata, Kazuto

    2018-04-01

    The characteristics of SiC MOSFETs (drain current vs. gate voltage) were measured at 0.14-350 K and analyzed considering variable-range hopping conduction through interface states. The total interface state density was determined to be 5.4×1012 cm-2 from the additional shift in the threshold gate voltage with a temperature change. The wave-function size of interface states was determined from the temperature dependence of the measured hopping current and was comparable to the theoretical value. The channel mobility was approximately 100 cm2V-1s-1 and was almost independent of temperature.

  2. Detecting temporal changes in acoustic scenes: The variable benefit of selective attention.

    Science.gov (United States)

    Demany, Laurent; Bayle, Yann; Puginier, Emilie; Semal, Catherine

    2017-09-01

    Four experiments investigated change detection in acoustic scenes consisting of a sum of five amplitude-modulated pure tones. As the tones were about 0.7 octave apart and were amplitude-modulated with different frequencies (in the range 2-32 Hz), they were perceived as separate streams. Listeners had to detect a change in the frequency (experiments 1 and 2) or the shape (experiments 3 and 4) of the modulation of one of the five tones, in the presence of an informative cue orienting selective attention either before the scene (pre-cue) or after it (post-cue). The changes left intensity unchanged and were not detectable in the spectral (tonotopic) domain. Performance was much better with pre-cues than with post-cues. Thus, change deafness was manifest in the absence of an appropriate focusing of attention when the change occurred, even though the streams and the changes to be detected were acoustically very simple (in contrast to the conditions used in previous demonstrations of change deafness). In one case, the results were consistent with a model based on the assumption that change detection was possible if and only if attention was endogenously focused on a single tone. However, it was also found that changes resulting in a steepening of amplitude rises were to some extent able to draw attention exogenously. Change detection was not markedly facilitated when the change produced a discontinuity in the modulation domain, contrary to what could be expected from the perspective of predictive coding. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Clinical variability of Waardenburg-Shah syndrome in patients with proximal 13q deletion syndrome including the endothelin-B receptor locus.

    Science.gov (United States)

    Tüysüz, Beyhan; Collin, Anna; Arapoğlu, Müjde; Suyugül, Nezir

    2009-10-01

    Waardenburg-Shah syndrome (Waardenburg syndrome type IV-WS4) is an auditory-pigmentary disorder that combines clinical features of pigmentary abnormalities of the skin, hair and irides, sensorineural hearing loss, and Hirschsprung disease (HSCR). Mutations in the endothelin-B receptor (EDNRB) gene on 13q22 have been found to cause this syndrome. Mutations in both alleles cause the full phenotype, while heterozygous mutations cause isolated HSCR or HSCR with minor pigmentary anomalies and/or sensorineural deafness. We investigated the status of the EDNRB gene, by FISH analysis, in three patients with de novo proximal 13q deletions detected at cytogenetic analysis and examined the clinical variability of WS4 among these patients. Chromosome 13q was screened with locus specific FISH probes and breakpoints were determined at 13q22.1q31.3 in Patients 1 and 3, and at 13q21.1q31.3 in Patient 2. An EDNRB specific FISH probe was deleted in all three patients. All patients had common facial features seen in proximal 13q deletion syndrome and mild mental retardation. However, findings related to WS4 were variable; Patient 1 had hypopigmentation of the irides and HSCR, Patient 2 had prominent bicolored irides and mild bilateral hearing loss, and Patient 3 had only mild unilateral hearing loss. These data contribute new insights into the pathogenesis of WS4.

  4. Habitat Heterogeneity Variably Influences Habitat Selection by Wild Herbivores in a Semi-Arid Tropical Savanna Ecosystem.

    Directory of Open Access Journals (Sweden)

    Victor K Muposhi

    Full Text Available An understanding of the habitat selection patterns by wild herbivores is critical for adaptive management, particularly towards ecosystem management and wildlife conservation in semi arid savanna ecosystems. We tested the following predictions: (i surface water availability, habitat quality and human presence have a strong influence on the spatial distribution of wild herbivores in the dry season, (ii habitat suitability for large herbivores would be higher compared to medium-sized herbivores in the dry season, and (iii spatial extent of suitable habitats for wild herbivores will be different between years, i.e., 2006 and 2010, in Matetsi Safari Area, Zimbabwe. MaxEnt modeling was done to determine the habitat suitability of large herbivores and medium-sized herbivores. MaxEnt modeling of habitat suitability for large herbivores using the environmental variables was successful for the selected species in 2006 and 2010, except for elephant (Loxodonta africana for the year 2010. Overall, large herbivores probability of occurrence was mostly influenced by distance from rivers. Distance from roads influenced much of the variability in the probability of occurrence of medium-sized herbivores. The overall predicted area for large and medium-sized herbivores was not different. Large herbivores may not necessarily utilize larger habitat patches over medium-sized herbivores due to the habitat homogenizing effect of water provisioning. Effect of surface water availability, proximity to riverine ecosystems and roads on habitat suitability of large and medium-sized herbivores in the dry season was highly variable thus could change from one year to another. We recommend adaptive management initiatives aimed at ensuring dynamic water supply in protected areas through temporal closure and or opening of water points to promote heterogeneity of wildlife habitats.

  5. Selecting statistical models and variable combinations for optimal classification using otolith microchemistry.

    Science.gov (United States)

    Mercier, Lény; Darnaude, Audrey M; Bruguier, Olivier; Vasconcelos, Rita P; Cabral, Henrique N; Costa, Maria J; Lara, Monica; Jones, David L; Mouillot, David

    2011-06-01

    Reliable assessment of fish origin is of critical importance for exploited species, since nursery areas must be identified and protected to maintain recruitment to the adult stock. During the last two decades, otolith chemical signatures (or "fingerprints") have been increasingly used as tools to discriminate between coastal habitats. However, correct assessment of fish origin from otolith fingerprints depends on various environmental and methodological parameters, including the choice of the statistical method used to assign fish to unknown origin. Among the available methods of classification, Linear Discriminant Analysis (LDA) is the most frequently used, although it assumes data are multivariate normal with homogeneous within-group dispersions, conditions that are not always met by otolith chemical data, even after transformation. Other less constrained classification methods are available, but there is a current lack of comparative analysis in applications to otolith microchemistry. Here, we assessed stock identification accuracy for four classification methods (LDA, Quadratic Discriminant Analysis [QDA], Random Forests [RF], and Artificial Neural Networks [ANN]), through the use of three distinct data sets. In each case, all possible combinations of chemical elements were examined to identify the elements to be used for optimal accuracy in fish assignment to their actual origin. Our study shows that accuracy differs according to the model and the number of elements considered. Best combinations did not include all the elements measured, and it was not possible to define an ad hoc multielement combination for accurate site discrimination. Among all the models tested, RF and ANN performed best, especially for complex data sets (e.g., with numerous fish species and/or chemical elements involved). However, for these data, RF was less time-consuming and more interpretable than ANN, and far more efficient and less demanding in terms of assumptions than LDA or QDA

  6. Including climate variability in determination of the optimum rate of N fertilizer application using a crop model: A case study for rainfed corn in eastern Canada

    Science.gov (United States)

    Mesbah, M.; Pattey, E.; Jégo, G.; Geng, X.; Tremblay, N.; Didier, A.

    2017-12-01

    Identifying optimum nitrogen (N) application rate is essential for increasing agricultural production while limiting potential environmental contaminations caused by release of reactive N, especially for high demand N crops such as corn. The central question of N management is then how the optimum N rate is affected by climate variability for given soil. The experimental determination of optimum N rates involve the analyses of variance on the mean value of crop yield response to various N application rates used by factorial plot based experiments for a few years in several regions. This traditional approach has limitations to capture 1) the non-linear response of yield to N application rates due to large incremental N rates (often more than 40 kg N ha-1) and 2) the ecophysiological response of the crop to climate variability because of limited numbers of growing seasons considered. Modeling on the other hand, does not have such limitations and hence we use a crop model and propose a model-based methodology called Finding NEMO (N Ecophysiologically Modelled Optimum) to identify the optimum N rates for variable agro-climatic conditions and given soil properties. The performance of the methodology is illustrated using the STICS crop model adapted for rainfed corn in the Mixedwood Plains ecozone of eastern Canada (42.3oN 83oW-46.8oN 71oW) where more than 90% of Canadian corn is produced. The simulations were performed using small increment of preplant N application rate (10 kg N ha -1), long time series of daily climatic data (48 to 61 years) for 5 regions along the ecozone, and three contrasting soils per region. The results show that N recommendations should be region and soil specific. Soils with lower available water capacity required more N compared to soil with higher available water capacity. When N rates were at their ecophysiologically optimum level, 10 to 17 kg increase in dry yield could be achieved by adding 1 kg N. Expected yield also affected the optimum

  7. A 1D constitutive model for shape memory alloy using strain and temperature as control variables and including martensite reorientation and asymmetric behaviors

    International Nuclear Information System (INIS)

    Jaber, M Ben; Mehrez, S; Ghazouani, O

    2014-01-01

    In this paper, a new 1D constitutive model for shape memory alloy using strain and temperature as control variables is presented. The new formulation is restricted to the 1D stress case and takes into account the martensite reorientation and the asymmetry of the SMA behavior in tension and compression. Numerical implementation of the new model in a finite element code was conducted. The numerical results for superelastic behavior in tension and compression tests are presented and were compared to experimental data taken from the literature. Other numerical tests are presented, showing the model’s ability to reproduce the main aspects of SMA behavior such as the shape memory effect and the martensite reorientation under cyclic loading. Finally, to demonstrate the utility of the new constitutive model, a dynamic test of a bi-clamped SMA bending beam under forced oscillation is described. (paper)

  8. Internal state variable plasticity-damage modeling of AISI 4140 steel including microstructure-property relations: temperature and strain rate effects

    Science.gov (United States)

    Nacif el Alaoui, Reda

    Mechanical structure-property relations have been quantified for AISI 4140 steel. under different strain rates and temperatures. The structure-property relations were used. to calibrate a microstructure-based internal state variable plasticity-damage model for. monotonic tension, compression and torsion plasticity, as well as damage evolution. Strong stress state and temperature dependences were observed for the AISI 4140 steel. Tension tests on three different notched Bridgman specimens were undertaken to study. the damage-triaxiality dependence for model validation purposes. Fracture surface. analysis was performed using Scanning Electron Microscopy (SEM) to quantify the void. nucleation and void sizes in the different specimens. The stress-strain behavior exhibited. a fairly large applied stress state (tension, compression dependence, and torsion), a. moderate temperature dependence, and a relatively small strain rate dependence.

  9. An adaptive technique for multiscale approximate entropy (MAEbin) threshold (r) selection: application to heart rate variability (HRV) and systolic blood pressure variability (SBPV) under postural stress.

    Science.gov (United States)

    Singh, Amritpal; Saini, Barjinder Singh; Singh, Dilbag

    2016-06-01

    Multiscale approximate entropy (MAE) is used to quantify the complexity of a time series as a function of time scale τ. Approximate entropy (ApEn) tolerance threshold selection 'r' is based on either: (1) arbitrary selection in the recommended range (0.1-0.25) times standard deviation of time series (2) or finding maximum ApEn (ApEnmax) i.e., the point where self-matches start to prevail over other matches and choosing the corresponding 'r' (rmax) as threshold (3) or computing rchon by empirically finding the relation between rmax, SD1/SD2 ratio and N using curve fitting, where, SD1 and SD2 are short-term and long-term variability of a time series respectively. None of these methods is gold standard for selection of 'r'. In our previous study [1], an adaptive procedure for selection of 'r' is proposed for approximate entropy (ApEn). In this paper, this is extended to multiple time scales using MAEbin and multiscale cross-MAEbin (XMAEbin). We applied this to simulations i.e. 50 realizations (n = 50) of random number series, fractional Brownian motion (fBm) and MIX (P) [1] series of data length of N = 300 and short term recordings of HRV and SBPV performed under postural stress from supine to standing. MAEbin and XMAEbin analysis was performed on laboratory recorded data of 50 healthy young subjects experiencing postural stress from supine to upright. The study showed that (i) ApEnbin of HRV is more than SBPV in supine position but is lower than SBPV in upright position (ii) ApEnbin of HRV decreases from supine i.e. 1.7324 ± 0.112 (mean ± SD) to upright 1.4916 ± 0.108 due to vagal inhibition (iii) ApEnbin of SBPV increases from supine i.e. 1.5535 ± 0.098 to upright i.e. 1.6241 ± 0.101 due sympathetic activation (iv) individual and cross complexities of RRi and systolic blood pressure (SBP) series depend on time scale under consideration (v) XMAEbin calculated using ApEnmax is correlated with cross-MAE calculated using ApEn (0.1-0.26) in steps of 0

  10. Model selection for semiparametric marginal mean regression accounting for within-cluster subsampling variability and informative cluster size.

    Science.gov (United States)

    Shen, Chung-Wei; Chen, Yi-Hau

    2018-03-13

    We propose a model selection criterion for semiparametric marginal mean regression based on generalized estimating equations. The work is motivated by a longitudinal study on the physical frailty outcome in the elderly, where the cluster size, that is, the number of the observed outcomes in each subject, is "informative" in the sense that it is related to the frailty outcome itself. The new proposal, called Resampling Cluster Information Criterion (RCIC), is based on the resampling idea utilized in the within-cluster resampling method (Hoffman, Sen, and Weinberg, 2001, Biometrika 88, 1121-1134) and accommodates informative cluster size. The implementation of RCIC, however, is free of performing actual resampling of the data and hence is computationally convenient. Compared with the existing model selection methods for marginal mean regression, the RCIC method incorporates an additional component accounting for variability of the model over within-cluster subsampling, and leads to remarkable improvements in selecting the correct model, regardless of whether the cluster size is informative or not. Applying the RCIC method to the longitudinal frailty study, we identify being female, old age, low income and life satisfaction, and chronic health conditions as significant risk factors for physical frailty in the elderly. © 2018, The International Biometric Society.

  11. In Vitro Tumor Models: Advantages, Disadvantages, Variables, and Selecting the Right Platform.

    Science.gov (United States)

    Katt, Moriah E; Placone, Amanda L; Wong, Andrew D; Xu, Zinnia S; Searson, Peter C

    2016-01-01

    In vitro tumor models have provided important tools for cancer research and serve as low-cost screening platforms for drug therapies; however, cancer recurrence remains largely unchecked due to metastasis, which is the cause of the majority of cancer-related deaths. The need for an improved understanding of the progression and treatment of cancer has pushed for increased accuracy and physiological relevance of in vitro tumor models. As a result, in vitro tumor models have concurrently increased in complexity and their output parameters further diversified, since these models have progressed beyond simple proliferation, invasion, and cytotoxicity screens and have begun recapitulating critical steps in the metastatic cascade, such as intravasation, extravasation, angiogenesis, matrix remodeling, and tumor cell dormancy. Advances in tumor cell biology, 3D cell culture, tissue engineering, biomaterials, microfabrication, and microfluidics have enabled rapid development of new in vitro tumor models that often incorporate multiple cell types, extracellular matrix materials, and spatial and temporal introduction of soluble factors. Other innovations include the incorporation of perfusable microvessels to simulate the tumor vasculature and model intravasation and extravasation. The drive toward precision medicine has increased interest in adapting in vitro tumor models for patient-specific therapies, clinical management, and assessment of metastatic potential. Here, we review the wide range of current in vitro tumor models and summarize their advantages, disadvantages, and suitability in modeling specific aspects of the metastatic cascade and drug treatment.

  12. Variable selection in near infrared spectroscopy for quantitative models of homologous analogs of cephalosporins

    Directory of Open Access Journals (Sweden)

    Yan-Chun Feng

    2014-07-01

    Full Text Available Two universal spectral ranges (4550–4100 cm-1 and 6190–5510 cm-1 for construction of quantitative models of homologous analogs of cephalosporins were proposed by evaluating the performance of five spectral ranges and their combinations, using three data sets of cephalosporins for injection, i.e., cefuroxime sodium, ceftriaxone sodium and cefoperazone sodium. Subsequently, the proposed ranges were validated by using eight calibration sets of other homologous analogs of cephalosporins for injection, namely cefmenoxime hydrochloride, ceftezole sodium, cefmetazole, cefoxitin sodium, cefotaxime sodium, cefradine, cephazolin sodium and ceftizoxime sodium. All the constructed quantitative models for the eight kinds of cephalosporins using these universal ranges could fulfill the requirements for quick quantification. After that, competitive adaptive reweighted sampling (CARS algorithm and infrared (IR–near infrared (NIR two-dimensional (2D correlation spectral analysis were used to determine the scientific basis of these two spectral ranges as the universal regions for the construction of quantitative models of cephalosporins. The CARS algorithm demonstrated that the ranges of 4550–4100 cm-1 and 6190–5510 cm-1 included some key wavenumbers which could be attributed to content changes of cephalosporins. The IR–NIR 2D spectral analysis showed that certain wavenumbers in these two regions have strong correlations to the structures of those cephalosporins that were easy to degrade.

  13. Petroleomics by electrospray ionization FT-ICR mass spectrometry coupled to partial least squares with variable selection methods: prediction of the total acid number of crude oils.

    Science.gov (United States)

    Terra, Luciana A; Filgueiras, Paulo R; Tose, Lílian V; Romão, Wanderson; de Souza, Douglas D; de Castro, Eustáquio V R; de Oliveira, Mirela S L; Dias, Júlio C M; Poppi, Ronei J

    2014-10-07

    Negative-ion mode electrospray ionization, ESI(-), with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was coupled to a Partial Least Squares (PLS) regression and variable selection methods to estimate the total acid number (TAN) of Brazilian crude oil samples. Generally, ESI(-)-FT-ICR mass spectra present a power of resolution of ca. 500,000 and a mass accuracy less than 1 ppm, producing a data matrix containing over 5700 variables per sample. These variables correspond to heteroatom-containing species detected as deprotonated molecules, [M - H](-) ions, which are identified primarily as naphthenic acids, phenols and carbazole analog species. The TAN values for all samples ranged from 0.06 to 3.61 mg of KOH g(-1). To facilitate the spectral interpretation, three methods of variable selection were studied: variable importance in the projection (VIP), interval partial least squares (iPLS) and elimination of uninformative variables (UVE). The UVE method seems to be more appropriate for selecting important variables, reducing the dimension of the variables to 183 and producing a root mean square error of prediction of 0.32 mg of KOH g(-1). By reducing the size of the data, it was possible to relate the selected variables with their corresponding molecular formulas, thus identifying the main chemical species responsible for the TAN values.

  14. Effects of selected water chemistry variables on copper pitting propagation in potable water

    International Nuclear Information System (INIS)

    Ha Hung; Taxen, Claes; Williams, Keith; Scully, John

    2011-01-01

    Highlights: → The effects of water composition on pit propagation kinetics on Cu were separated from pit initiation and stabilization using the artificial pit method in a range of dilute HCO 3 - , SO 4 2- and Cl - -containing waters. → The effective polarization and Ohmic resistance of pits were lower in SO4 2- -containing solutions and greater in Cl - -containing solutions. → Relationship between the solution composition and the corrosion product identity and morphology were found. → These, in turn controlled the corrosion product Ohmic resistance and subsequently the pit growth rate. - Abstract: The pit propagation behavior of copper (UNS C11000) was investigated from an electrochemical perspective using the artificial pit method. Pit growth was studied systematically in a range of HCO 3 - , SO 4 2- and Cl - containing-waters at various concentrations. Pit propagation was mediated by the nature of the corrosion products formed both inside and over the pit mouth (i.e., cap). Certain water chemistry concentrations such as those high in sulfate were found to promote fast pitting that could be sustained over long times at a fixed applied potential but gradually stifled in all but the lowest concentration solutions. In contrast, Cl - containing waters without sulfate ions resulted in slower pit growth and eventual repassivation. These observations were interpreted through understanding of the identity, amount and porosity of corrosion products formed inside and over pits. These factors controlled their resistive nature as characterized using electrochemical impedance spectroscopy. A finite element model (FEM) was developed which included copper oxidation kinetics, transport by migration and diffusion, Cu(I) and Cu(II) solid corrosion product formation and porosity governed by equilibrium thermodynamics and a saturation index, as well as pit current and depth of penetration. The findings of the modeling were in good agreement with artificial pit experiments

  15. The influence of some selected variables from accounting system on profit or loss of agricultural companies in the Slovak republic

    Directory of Open Access Journals (Sweden)

    Alexandra Ferenczi Vaňová

    2017-01-01

    Full Text Available 1024x768 The article presents the influence assessment of significance of some selected variables from the entrepreneurs' accounting system on the achieved profit or loss of the agricultural companies in the Slovak Republic. Accounting information serves as an active tool for internal users for operational as well as strategic company management, and for external users the information is determined as legally binding output information which is a subject to disclosure. Individual financial statements of assessed agricultural companies are considered to be the relevant source of information. Agricultural companies are represented by commercial companies and agricultural cooperatives. Profit or loss after income tax presents the final complex effect of economic company's performance. The existence and development of companies is conditioned by assets which amount and structure depend on focus and the range of subject activity but as well as on specific factors set by the production process in the agricultural primary production. The increase in liabilities is notable by the influence of unsufficient amount of own company funding sources, mainly the increase in trade payables. The continuance of company reproduction process is secured by a bank loan drawdown. The income situation of companies of agricultural primary production is favourably influenced by the subsidies of non-investment character. During the observed period of years 2004 - 2014 the examined variables were assessed by means of statistical methods. The obtained results of rate determination of statistical correlation between selected variables by means of classical canonical analysis and non-parametric correlation analysis secured that in the assessed group of companies all analysed variables influenced statistically significantly profit or loss after income tax, mainly the total value of assets and non-investment subsidies, except for years 2010, 2012 a 2013, when the statistically

  16. Characterization of Genotoxic Response to 15 Multiwalled Carbon Nanotubes with Variable Physicochemical Properties Including Surface Functionalizations in the FE1-Muta(TM) Mouse Lung Epithelial Cell Line

    DEFF Research Database (Denmark)

    Jackson, Petra; Kling, Kirsten; Jensen, Keld Alstrup

    2015-01-01

    Carbon nanotubes vary greatly in physicochemical properties. We compared cytotoxic and genotoxic response to 15 multiwalled carbon nanotubes (MWCNT) with varying physicochemical properties to identify drivers of toxic responses. The studied MWCNT included OECD Working Party on Manufactured...... Nanomaterials (WPMN) (NM-401, NM-402, and NM-403), materials (NRCWE-026 and MWCNT-XNRI-7), and three sets of surface-modified MWCNT grouped by physical characteristics (thin, thick, and short I-III, respectively). Each Groups I-III included pristine, hydroxylated and carboxylated MWCNT. Group III also included...... an amino-functionalized MWCNT. The level of surface functionalization of the MWCNT was low. The level and type of elemental impurities of the MWCNT varied by...

  17. ZP Domain Proteins in the Abalone Egg Coat Include a Paralog of VERL under Positive Selection That Binds Lysin and 18-kDa Sperm Proteins

    Science.gov (United States)

    Aagaard, Jan E.; Vacquier, Victor D.; MacCoss, Michael J.; Swanson, Willie J.

    2010-01-01

    Identifying fertilization molecules is key to our understanding of reproductive biology, yet only a few examples of interacting sperm and egg proteins are known. One of the best characterized comes from the invertebrate archeogastropod abalone (Haliotis spp.), where sperm lysin mediates passage through the protective egg vitelline envelope (VE) by binding to the VE protein vitelline envelope receptor for lysin (VERL). Rapid adaptive divergence of abalone lysin and VERL are an example of positive selection on interacting fertilization proteins contributing to reproductive isolation. Previously, we characterized a subset of the abalone VE proteins that share a structural feature, the zona pellucida (ZP) domain, which is common to VERL and the egg envelopes of vertebrates. Here, we use additional expressed sequence tag sequencing and shotgun proteomics to characterize this family of proteins in the abalone egg VE. We expand 3-fold the number of known ZP domain proteins present within the VE (now 30 in total) and identify a paralog of VERL (vitelline envelope zona pellucida domain protein [VEZP] 14) that contains a putative lysin-binding motif. We find that, like VERL, the divergence of VEZP14 among abalone species is driven by positive selection on the lysin-binding motif alone and that these paralogous egg VE proteins bind a similar set of sperm proteins including a rapidly evolving 18-kDa paralog of lysin, which may mediate sperm–egg fusion. This work identifies an egg coat paralog of VERL under positive selection and the candidate sperm proteins with which it may interact during abalone fertilization. PMID:19767347

  18. Genetic variability and natural selection at the ligand domain of the Duffy binding protein in brazilian Plasmodium vivax populations

    Directory of Open Access Journals (Sweden)

    Gil Luiz HS

    2010-11-01

    Full Text Available Abstract Background Plasmodium vivax malaria is a major public health challenge in Latin America, Asia and Oceania, with 130-435 million clinical cases per year worldwide. Invasion of host blood cells by P. vivax mainly depends on a type I membrane protein called Duffy binding protein (PvDBP. The erythrocyte-binding motif of PvDBP is a 170 amino-acid stretch located in its cysteine-rich region II (PvDBPII, which is the most variable segment of the protein. Methods To test whether diversifying natural selection has shaped the nucleotide diversity of PvDBPII in Brazilian populations, this region was sequenced in 122 isolates from six different geographic areas. A Bayesian method was applied to test for the action of natural selection under a population genetic model that incorporates recombination. The analysis was integrated with a structural model of PvDBPII, and T- and B-cell epitopes were localized on the 3-D structure. Results The results suggest that: (i recombination plays an important role in determining the haplotype structure of PvDBPII, and (ii PvDBPII appears to contain neutrally evolving codons as well as codons evolving under natural selection. Diversifying selection preferentially acts on sites identified as epitopes, particularly on amino acid residues 417, 419, and 424, which show strong linkage disequilibrium. Conclusions This study shows that some polymorphisms of PvDBPII are present near the erythrocyte-binding domain and might serve to elude antibodies that inhibit cell invasion. Therefore, these polymorphisms should be taken into account when designing vaccines aimed at eliciting antibodies to inhibit erythrocyte invasion.

  19. Synthesis, Characterization, and Variable-Temperature NMR Studies of Silver(I) Complexes for Selective Nitrene Transfer.

    Science.gov (United States)

    Huang, Minxue; Corbin, Joshua R; Dolan, Nicholas S; Fry, Charles G; Vinokur, Anastasiya I; Guzei, Ilia A; Schomaker, Jennifer M

    2017-06-05

    An array of silver complexes supported by nitrogen-donor ligands catalyze the transformation of C═C and C-H bonds to valuable C-N bonds via nitrene transfer. The ability to achieve high chemoselectivity and site selectivity in an amination event requires an understanding of both the solid- and solution-state behavior of these catalysts. X-ray structural characterizations were helpful in determining ligand features that promote the formation of monomeric versus dimeric complexes. Variable-temperature 1 H and DOSY NMR experiments were especially useful for understanding how the ligand identity influences the nuclearity, coordination number, and fluxional behavior of silver(I) complexes in solution. These insights are valuable for developing improved ligand designs.

  20. Mercury Concentrations in Fish and Sediment within Streams are Influenced by Watershed and Landscape Variables including Historical Gold Mining in the Sierra Nevada, California

    Science.gov (United States)

    Alpers, C. N.; Yee, J. L.; Ackerman, J. T.; Orlando, J. L.; Slotton, D. G.; Marvin-DiPasquale, M. C.

    2015-12-01

    We compiled available data on total mercury (THg) and methylmercury (MeHg) concentrations in fish tissue and streambed sediment from stream sites in the Sierra Nevada, California, to assess whether spatial data, including information on historical mining, can be used to make robust predictions of fish fillet tissue THg concentrations. A total of 1,271 fish from five species collected at 103 sites during 1980-2012 were used for the modeling effort: 210 brown trout, 710 rainbow trout, 79 Sacramento pikeminnow, 93 Sacramento sucker, and 179 smallmouth bass. Sediment data were used from 73 sites, including 106 analyses of THg and 77 analyses of MeHg. The dataset included 391 fish (mostly rainbow trout) and 28 sediment samples collected explicitly for this study during 2011-12. Spatial data on historical mining included the USGS Mineral Resources Data System and publicly available maps and satellite photos showing the areas of hydraulic mine pits and other placer mines. Modeling was done using multivariate linear regression and multi-model inference using Akaike Information Criteria. Results indicate that fish THg, accounting for species and length, can be predicted using geospatial data on mining history together with other landscape characteristics including land use/land cover. A model requiring only geospatial data, with an R2 value of 0.61, predicted fish THg correctly with respect to over-or-under 0.2 μg/g wet weight (a California regulatory threshold) for 108 of 121 (89 %) size-species combinations tested. Data for THg in streambed sediment did not improve the geospatial-only model. However, data for sediment MeHg, loss on ignition (organic content), and percent of sediment less than 0.063 mm resulted in a slightly improved model, with an R2 value of 0.63. It is anticipated that these models will be useful to the State of California and others to predict areas where mercury concentrations in fish are likely to exceed regulatory criteria.

  1. THE HOST GALAXY PROPERTIES OF VARIABILITY SELECTED AGN IN THE PAN-STARRS1 MEDIUM DEEP SURVEY

    Energy Technology Data Exchange (ETDEWEB)

    Heinis, S.; Gezari, S.; Kumar, S. [Department of Astronomy, University of Maryland, College Park, MD (United States); Burgett, W. S.; Flewelling, H.; Huber, M. E.; Kaiser, N.; Wainscoat, R. J.; Waters, C. [Institute for Astronomy, University of Hawaii at Manoa, Honolulu, HI 96822 (United States)

    2016-07-20

    We study the properties of 975 active galactic nuclei (AGNs) selected by variability in the Pan-STARRS1 Medium deep Survey. Using complementary multi-wavelength data from the ultraviolet to the far-infrared, we use spectral energy distribution fitting to determine the AGN and host properties at z < 1 and compare to a well-matched control sample. We confirm the trend previously observed: that the variability amplitude decreases with AGN luminosity, but we also observe that the slope of this relation steepens with wavelength, resulting in a “redder when brighter” trend at low luminosities. Our results show that AGNs are hosted by more massive hosts than control sample galaxies, while the rest frame dust-corrected NUV r color distribution of AGN hosts is similar to control galaxies. We find a positive correlation between the AGN luminosity and star formation rate (SFR), independent of redshift. AGN hosts populate the entire range of SFRs within and outside of the Main Sequence of star-forming galaxies. Comparing the distribution of AGN hosts and control galaxies, we show that AGN hosts are less likely to be hosted by quiescent galaxies and more likely to be hosted by Main Sequence or starburst galaxies.

  2. Genetic variability, partial regression, Co-heritability studies and their implication in selection of high yielding potato gen

    International Nuclear Information System (INIS)

    Iqbal, Z.M.; Khan, S.A.

    2003-01-01

    Partial regression coefficient, genotypic and phenotypic variabilities, heritability co-heritability and genetic advance were studied in 15 Potato varieties of exotic and local origin. Both genotypic and phenotypic coefficients of variations were high for scab and rhizoctonia incidence percentage. Significant partial regression coefficient for emergence percentage indicated its relative importance in tuber yield. High heritability (broadsense) estimates coupled with high genetic advance for plant height, number of stems per plant and scab percentage revealed substantial contribution of additive genetic variance in the expression of these traits. Hence, the selection based on these characters could play a significant role in their improvement the dominance and epistatic variance was more important for character expression of yield ha/sup -1/, emergence and rhizoctonia percentage. This phenomenon is mainly due to the accumulative effects of low heritability and low to moderate genetic advance. The high co-heritability coupled with negative genotypic and phenotypic covariance revealed that selection of varieties having low scab and rhizoctonia percentage resulted in more potato yield. (author)

  3. Risk estimates for hip fracture from clinical and densitometric variables and impact of database selection in Lebanese subjects.

    Science.gov (United States)

    Badra, Mohammad; Mehio-Sibai, Abla; Zeki Al-Hazzouri, Adina; Abou Naja, Hala; Baliki, Ghassan; Salamoun, Mariana; Afeiche, Nadim; Baddoura, Omar; Bulos, Suhayl; Haidar, Rachid; Lakkis, Suhayl; Musharrafieh, Ramzi; Nsouli, Afif; Taha, Assaad; Tayim, Ahmad; El-Hajj Fuleihan, Ghada

    2009-01-01

    Bone mineral density (BMD) and fracture incidence vary greatly worldwide. The data, if any, on clinical and densitometric characteristics of patients with hip fractures from the Middle East are scarce. The objective of the study was to define risk estimates from clinical and densitometric variables and the impact of database selection on such estimates. Clinical and densitometric information were obtained in 60 hip fracture patients and 90 controls. Hip fracture subjects were 74 yr (9.4) old, were significantly taller, lighter, and more likely to be taking anxiolytics and sleeping pills than controls. National Health and Nutrition Examination Survey (NHANES) database selection resulted in a higher sensitivity and almost equal specificity in identifying patients with a hip fracture compared with the Lebanese database. The odds ratio (OR) and its confidence interval (CI) for hip fracture per standard deviation (SD) decrease in total hip BMD was 2.1 (1.45-3.05) with the NHANES database, and 2.11 (1.36-2.37) when adjusted for age and body mass index (BMI). Risk estimates were higher in male compared with female subjects. In Lebanese subjects, BMD- and BMI-derived hip fracture risk estimates are comparable to western standards. The study validates the universal use of the NHANES database, and the applicability of BMD- and BMI-derived risk fracture estimates in the World Health Organization (WHO) global fracture risk model, to the Lebanese.

  4. Variable mechanical ventilation.

    Science.gov (United States)

    Fontela, Paula Caitano; Prestes, Renata Bernardy; Forgiarini, Luiz Alberto; Friedman, Gilberto

    2017-01-01

    To review the literature on the use of variable mechanical ventilation and the main outcomes of this technique. Search, selection, and analysis of all original articles on variable ventilation, without restriction on the period of publication and language, available in the electronic databases LILACS, MEDLINE®, and PubMed, by searching the terms "variable ventilation" OR "noisy ventilation" OR "biologically variable ventilation". A total of 36 studies were selected. Of these, 24 were original studies, including 21 experimental studies and three clinical studies. Several experimental studies reported the beneficial effects of distinct variable ventilation strategies on lung function using different models of lung injury and healthy lungs. Variable ventilation seems to be a viable strategy for improving gas exchange and respiratory mechanics and preventing lung injury associated with mechanical ventilation. However, further clinical studies are necessary to assess the potential of variable ventilation strategies for the clinical improvement of patients undergoing mechanical ventilation.

  5. Estimating relations between temperature, relative humidity as independed variables and selected water quality parameters in Lake Manzala, Egypt

    Directory of Open Access Journals (Sweden)

    Gehan A.H. Sallam

    2018-03-01

    Full Text Available In Egypt, Lake Manzala is the largest and the most productive lake of northern coastal lakes. In this study, the continuous measurements data of the Real Time Water Quality Monitoring stations in Lake Manzala were statistically analyzed to measure the regional and seasonal variations of the selected water quality parameters in relation to the change of air temperature and relative humidity. Simple formulas are elaborated using the DataFit software to predict the selected water quality parameters of the Lake including pH, Dissolved Oxygen (DO, Electrical Conductivity (EC, Total Dissolved Solids (TDS, Turbidity, and Chlorophyll as a function of air temperature, relative humidity and quantities and qualities of the drainage water that discharge into the lake. An empirical positive relation was found between air temperature and the relative humidity and pH, EC and TDS and negative relation with DO. There is no significant effect on the other two parameters of turbidity and chlorophyll.

  6. Selective dopamine D3 receptor antagonism by SB-277011A attenuates cocaine reinforcement as assessed by progressive-ratio and variable-cost–variable-payoff fixed-ratio cocaine self-administration in rats

    OpenAIRE

    Xi, Zheng-Xiong; Gilbert, Jeremy G.; Pak, Arlene C.; Ashby, Charles R.; Heidbreder, Christian A.; Gardner, Eliot L.

    2005-01-01

    In rats, acute administration of SB-277011A, a highly selective dopamine (DA) D3 receptor antagonist, blocks cocaine-enhanced brain stimulation reward, cocaine-seeking behaviour and reinstatement of cocaine-seeking behaviour. Here, we investigated whether SB-277011A attenuates cocaine reinforcement as assessed by cocaine self-administration under variable-cost–variable-payoff fixed-ratio (FR) and progressive-ratio (PR) reinforcement schedules. Acute i.p. administration of SB-277011A (3–24 mg/...

  7. A spatio-temporal nonparametric Bayesian variable selection model of fMRI data for clustering correlated time courses.

    Science.gov (United States)

    Zhang, Linlin; Guindani, Michele; Versace, Francesco; Vannucci, Marina

    2014-07-15

    In this paper we present a novel wavelet-based Bayesian nonparametric regression model for the analysis of functional magnetic resonance imaging (fMRI) data. Our goal is to provide a joint analytical framework that allows to detect regions of the brain which exhibit neuronal activity in response to a stimulus and, simultaneously, infer the association, or clustering, of spatially remote voxels that exhibit fMRI time series with similar characteristics. We start by modeling the data with a hemodynamic response function (HRF) with a voxel-dependent shape parameter. We detect regions of the brain activated in response to a given stimulus by using mixture priors with a spike at zero on the coefficients of the regression model. We account for the complex spatial correlation structure of the brain by using a Markov random field (MRF) prior on the parameters guiding the selection of the activated voxels, therefore capturing correlation among nearby voxels. In order to infer association of the voxel time courses, we assume correlated errors, in particular long memory, and exploit the whitening properties of discrete wavelet transforms. Furthermore, we achieve clustering of the voxels by imposing a Dirichlet process (DP) prior on the parameters of the long memory process. For inference, we use Markov Chain Monte Carlo (MCMC) sampling techniques that combine Metropolis-Hastings schemes employed in Bayesian variable selection with sampling algorithms for nonparametric DP models. We explore the performance of the proposed model on simulated data, with both block- and event-related design, and on real fMRI data. Copyright © 2014 Elsevier Inc. All rights reserved.

  8. 30 min of treadmill walking at self-selected speed does not increase gait variability in independent elderly.

    Science.gov (United States)

    Da Rocha, Emmanuel S; Kunzler, Marcos R; Bobbert, Maarten F; Duysens, Jacques; Carpes, Felipe P

    2018-06-01

    Walking is one of the preferred exercises among elderly, but could a prolonged walking increase gait variability, a risk factor for a fall in the elderly? Here we determine whether 30 min of treadmill walking increases coefficient of variation of gait in elderly. Because gait responses to exercise depend on fitness level, we included 15 sedentary and 15 active elderly. Sedentary participants preferred a lower gait speed and made smaller steps than the actives. Step length coefficient of variation decreased ~16.9% by the end of the exercise in both the groups. Stride length coefficient of variation decreased ~9% after 10 minutes of walking, and sedentary elderly showed a slightly larger step width coefficient of variation (~2%) at 10 min than active elderly. Active elderly showed higher walk ratio (step length/cadence) than sedentary in all times of walking, but the times did not differ in both the groups. In conclusion, treadmill gait kinematics differ between sedentary and active elderly, but changes over time are similar in sedentary and active elderly. As a practical implication, 30 min of walking might be a good strategy of exercise for elderly, independently of the fitness level, because it did not increase variability in step and stride kinematics, which is considered a risk of fall in this population.

  9. Using Variable Precision Rough Set for Selection and Classification of Biological Knowledge Integrated in DNA Gene Expression

    Directory of Open Access Journals (Sweden)

    Calvo-Dmgz D.

    2012-12-01

    Full Text Available DNA microarrays have contributed to the exponential growth of genomic and experimental data in the last decade. This large amount of gene expression data has been used by researchers seeking diagnosis of diseases like cancer using machine learning methods. In turn, explicit biological knowledge about gene functions has also grown tremendously over the last decade. This work integrates explicit biological knowledge, provided as gene sets, into the classication process by means of Variable Precision Rough Set Theory (VPRS. The proposed model is able to highlight which part of the provided biological knowledge has been important for classification. This paper presents a novel model for microarray data classification which is able to incorporate prior biological knowledge in the form of gene sets. Based on this knowledge, we transform the input microarray data into supergenes, and then we apply rough set theory to select the most promising supergenes and to derive a set of easy interpretable classification rules. The proposed model is evaluated over three breast cancer microarrays datasets obtaining successful results compared to classical classification techniques. The experimental results shows that there are not significat differences between our model and classical techniques but it is able to provide a biological-interpretable explanation of how it classifies new samples.

  10. The TAL effector PthA4 interacts with nuclear factors involved in RNA-dependent processes including a HMG protein that selectively binds poly(U RNA.

    Directory of Open Access Journals (Sweden)

    Tiago Antonio de Souza

    Full Text Available Plant pathogenic bacteria utilize an array of effector proteins to cause disease. Among them, transcriptional activator-like (TAL effectors are unusual in the sense that they modulate transcription in the host. Although target genes and DNA specificity of TAL effectors have been elucidated, how TAL proteins control host transcription is poorly understood. Previously, we showed that the Xanthomonas citri TAL effectors, PthAs 2 and 3, preferentially targeted a citrus protein complex associated with transcription control and DNA repair. To extend our knowledge on the mode of action of PthAs, we have identified new protein targets of the PthA4 variant, required to elicit canker on citrus. Here we show that all the PthA4-interacting proteins are DNA and/or RNA-binding factors implicated in chromatin remodeling and repair, gene regulation and mRNA stabilization/modification. The majority of these proteins, including a structural maintenance of chromosomes protein (CsSMC, a translin-associated factor X (CsTRAX, a VirE2-interacting protein (CsVIP2, a high mobility group (CsHMG and two poly(A-binding proteins (CsPABP1 and 2, interacted with each other, suggesting that they assemble into a multiprotein complex. CsHMG was shown to bind DNA and to interact with the invariable leucine-rich repeat region of PthAs. Surprisingly, both CsHMG and PthA4 interacted with PABP1 and 2 and showed selective binding to poly(U RNA, a property that is novel among HMGs and TAL effectors. Given that homologs of CsHMG, CsPABP1, CsPABP2, CsSMC and CsTRAX in other organisms assemble into protein complexes to regulate mRNA stability and translation, we suggest a novel role of TAL effectors in mRNA processing and translational control.

  11. Variable Selection in Heterogeneous Datasets: A Truncated-rank Sparse Linear Mixed Model with Applications to Genome-wide Association Studies.

    Science.gov (United States)

    Wang, Haohan; Aragam, Bryon; Xing, Eric P

    2018-04-26

    A fundamental and important challenge in modern datasets of ever increasing dimensionality is variable selection, which has taken on renewed interest recently due to the growth of biological and medical datasets with complex, non-i.i.d. structures. Naïvely applying classical variable selection methods such as the Lasso to such datasets may lead to a large number of false discoveries. Motivated by genome-wide association studies in genetics, we study the problem of variable selection for datasets arising from multiple subpopulations, when this underlying population structure is unknown to the researcher. We propose a unified framework for sparse variable selection that adaptively corrects for population structure via a low-rank linear mixed model. Most importantly, the proposed method does not require prior knowledge of sample structure in the data and adaptively selects a covariance structure of the correct complexity. Through extensive experiments, we illustrate the effectiveness of this framework over existing methods. Further, we test our method on three different genomic datasets from plants, mice, and human, and discuss the knowledge we discover with our method. Copyright © 2018. Published by Elsevier Inc.

  12. Impact of strong selection for the PrP major gene on genetic variability of four French sheep breeds (Open Access publication

    Directory of Open Access Journals (Sweden)

    Pantano Thais

    2008-11-01

    Full Text Available Abstract Effective selection on the PrP gene has been implemented since October 2001 in all French sheep breeds. After four years, the ARR "resistant" allele frequency increased by about 35% in young males. The aim of this study was to evaluate the impact of this strong selection on genetic variability. It is focussed on four French sheep breeds and based on the comparison of two groups of 94 animals within each breed: the first group of animals was born before the selection began, and the second, 3–4 years later. Genetic variability was assessed using genealogical and molecular data (29 microsatellite markers. The expected loss of genetic variability on the PrP gene was confirmed. Moreover, among the five markers located in the PrP region, only the three closest ones were affected. The evolution of the number of alleles, heterozygote deficiency within population, expected heterozygosity and the Reynolds distances agreed with the criteria from pedigree and pointed out that neutral genetic variability was not much affected. This trend depended on breed, i.e. on their initial states (population size, PrP frequencies and on the selection strategies for improving scrapie resistance while carrying out selection for production traits.

  13. A composite model including visfatin, tissue polypeptide-specific antigen, hyaluronic acid, and hematological variables for the diagnosis of moderate-to-severe fibrosis in nonalcoholic fatty liver disease: a preliminary study.

    Science.gov (United States)

    Chwist, Alina; Hartleb, Marek; Lekstan, Andrzej; Kukla, Michał; Gutkowski, Krzysztof; Kajor, Maciej

    2014-01-01

    Histopathological risk factors for end-stage liver failure in patients with nonalcoholic fatty liver disease (NAFLD) include nonalcoholic steatohepatitis (NASH) and advanced liver fibrosis. There is a need for noninvasive diagnostic methods for these 2 conditions. The aim of this study was to investigate new laboratory variables with a predictive potential to detect advanced fibrosis (stages 2 and 3) in NAFLD. The study involved 70 patients with histologically proven NAFLD of varied severity. Additional laboratory variables included zonulin, haptoglobin, visfatin, adiponectin, leptin, tissue polypeptide-specific antigen (TPSA), hyaluronic acid, and interleukin 6. Patients with NASH (NAFLD activity score of ≥5) had significantly higher HOMA-IR values and serum levels of visfatin, haptoglobin, and zonulin as compared with those without NASH on histological examination. Advanced fibrosis was found in 16 patients (22.9%) and the risk factors associated with its prevalence were age, the ratio of erythrocyte count to red blood cell distribution width, platelet count, and serum levels of visfatin and TPSA. Based on these variables, we constructed a scoring system that differentiated between NAFLD patients with and without advanced fibrosis with a sensitivity of 75% and specificity of 100% (area under the receiver operating characteristic curve, 0.93). The scoring system based on the above variables allows to predict advanced fibrosis with high sensitivity and specificity. However, its clinical utility should be verified in further studies involving a larger number of patients.

  14. Analysis of the waste selective collection at drop-off systems: Case study including the income level and the seasonal variation.

    Science.gov (United States)

    Gallardo, A; Carlos, M; Colomer, F J; Edo-Alcón, N

    2018-01-01

    There are several factors which have an influence in the selective collection of the municipal waste. To define a selective collection system, the waste generation pattern should be firstly determined and these factors should be analyzed in depth. This paper tries to analyze the economic income level and the seasonal variation on the collection and the purity of light-packaging waste to determine actions to improve the waste management plan of a town. In the first stage of the work, waste samples of the light-packaging containers were collected in two zones of the town with different economic characteristics in different seasons during one year. In the second stage, the samples were characterized to analyze the composition and purity of the waste. They were firstly separated into four fractions: metals; plastic; beverage cartons; and misplaced materials. The misplaced fraction was in its turn separated into cardboard, rubber and leather, inert waste, organic matter, paper, hazardous waste, clothes and shoes, glass and others. The plastic fraction was separated into five types of plastics and the metal fraction into three. In the third stage, the data have been analyzed and conclusions have been extracted. The main result is that the quality of the light-packaging fraction collected in these zones during both seasons were similar. This methodology can be extrapolated to towns with similar characteristics. It will be useful when implementing a system to collect the waste selectively and to develop actions to achieve a good participation in the selective collection of the waste.

  15. Online Monitoring of Copper Damascene Electroplating Bath by Voltammetry: Selection of Variables for Multiblock and Hierarchical Chemometric Analysis of Voltammetric Data

    Directory of Open Access Journals (Sweden)

    Aleksander Jaworski

    2017-01-01

    Full Text Available The Real Time Analyzer (RTA utilizing DC- and AC-voltammetric techniques is an in situ, online monitoring system that provides a complete chemical analysis of different electrochemical deposition solutions. The RTA employs multivariate calibration when predicting concentration parameters from a multivariate data set. Although the hierarchical and multiblock Principal Component Regression- (PCR- and Partial Least Squares- (PLS- based methods can handle data sets even when the number of variables significantly exceeds the number of samples, it can be advantageous to reduce the number of variables to obtain improvement of the model predictions and better interpretation. This presentation focuses on the introduction of a multistep, rigorous method of data-selection-based Least Squares Regression, Simple Modeling of Class Analogy modeling power, and, as a novel application in electroanalysis, Uninformative Variable Elimination by PLS and by PCR, Variable Importance in the Projection coupled with PLS, Interval PLS, Interval PCR, and Moving Window PLS. Selection criteria of the optimum decomposition technique for the specific data are also demonstrated. The chief goal of this paper is to introduce to the community of electroanalytical chemists numerous variable selection methods which are well established in spectroscopy and can be successfully applied to voltammetric data analysis.

  16. Energy-efficient relay selection and optimal power allocation for performance-constrained dual-hop variable-gain AF relaying

    KAUST Repository

    Zafar, Ammar; Radaydeh, Redha Mahmoud Mesleh; Chen, Yunfei; Alouini, Mohamed-Slim

    2013-01-01

    This paper investigates the energy-efficiency enhancement of a variable-gain dual-hop amplify-and-forward (AF) relay network utilizing selective relaying. The objective is to minimize the total consumed power while keeping the end-to-end signal

  17. Classification and quantitation of milk powder by near-infrared spectroscopy and mutual information-based variable selection and partial least squares

    Science.gov (United States)

    Chen, Hui; Tan, Chao; Lin, Zan; Wu, Tong

    2018-01-01

    Milk is among the most popular nutrient source worldwide, which is of great interest due to its beneficial medicinal properties. The feasibility of the classification of milk powder samples with respect to their brands and the determination of protein concentration is investigated by NIR spectroscopy along with chemometrics. Two datasets were prepared for experiment. One contains 179 samples of four brands for classification and the other contains 30 samples for quantitative analysis. Principal component analysis (PCA) was used for exploratory analysis. Based on an effective model-independent variable selection method, i.e., minimal-redundancy maximal-relevance (MRMR), only 18 variables were selected to construct a partial least-square discriminant analysis (PLS-DA) model. On the test set, the PLS-DA model based on the selected variable set was compared with the full-spectrum PLS-DA model, both of which achieved 100% accuracy. In quantitative analysis, the partial least-square regression (PLSR) model constructed by the selected subset of 260 variables outperforms significantly the full-spectrum model. It seems that the combination of NIR spectroscopy, MRMR and PLS-DA or PLSR is a powerful tool for classifying different brands of milk and determining the protein content.

  18. The Use of Asymptotic Functions for Determining Empirical Values of CN Parameter in Selected Catchments of Variable Land Cover

    Science.gov (United States)

    Wałęga, Andrzej; Młyński, Dariusz; Wachulec, Katarzyna

    2017-12-01

    The aim of the study was to assess the applicability of asymptotic functions for determining the value of CN parameter as a function of precipitation depth in mountain and upland catchments. The analyses were carried out in two catchments: the Rudawa, left tributary of the Vistula, and the Kamienica, right tributary of the Dunajec. The input material included data on precipitation and flows for a multi-year period 1980-2012, obtained from IMGW PIB in Warsaw. Two models were used to determine empirical values of CNobs parameter as a function of precipitation depth: standard Hawkins model and 2-CN model allowing for a heterogeneous nature of a catchment area. The study analyses confirmed that asymptotic functions properly described P-CNobs relationship for the entire range of precipitation variability. In the case of high rainfalls, CNobs remained above or below the commonly accepted average antecedent moisture conditions AMCII. The study calculations indicated that the runoff amount calculated according to the original SCS-CN method might be underestimated, and this could adversely affect the values of design flows required for the design of hydraulic engineering projects. In catchments with heterogeneous land cover, the results of CNobs were more accurate when 2-CN model was used instead of the standard Hawkins model. 2-CN model is more precise in accounting for differences in runoff formation depending on retention capacity of the substrate. It was also demonstrated that the commonly accepted initial abstraction coefficient λ = 0.20 yielded too big initial loss of precipitation in the analyzed catchments and, therefore, the computed direct runoff was underestimated. The best results were obtained for λ = 0.05.

  19. Control of Variability in the Performance of Selective Laser Melting (SLM) Parts through Microstructure Control and Design

    Data.gov (United States)

    National Aeronautics and Space Administration — The high variability and low repeatability of metal parts produced using Additive Manufacturing (AM) represent a major barrier in getting AM into the mainstream....

  20. Selected nutrient contents, fatty acid composition, including conjugated linoleic acid, and retention values in separable lean from lamb rib loins as affected by external fat and cooking method.

    Science.gov (United States)

    Badiani, Anna; Montellato, Lara; Bochicchio, Davide; Anfossi, Paola; Zanardi, Emanuela; Maranesi, Magda

    2004-08-11

    Proximate composition and fatty acid profile, conjugated linoleic acid (CLA) isomers included, were determined in separable lean of raw and cooked lamb rib loins. The cooking methods compared, which were also investigated for cooking yields and true nutrient retention values, were dry heating of fat-on cuts and moist heating of fat-off cuts; the latter method was tested as a sort of dietetic approach against the more traditional former type. With significantly (P cooking losses, dry heating of fat-on rib-loins produced slightly (although only rarely significantly) higher retention values for all of the nutrients considered, including CLA isomers. On the basis of the retention values obtained, both techniques led to a minimum migration of lipids into the separable lean, which was higher (P cooking of the class of CLA isomers (including that of the nutritionally most important isomer cis-9,trans-11) was more similar to that of the monounsaturated than the polyunsaturated fatty acids.

  1. Water-quality characteristics for selected sites on the Cape Fear River, North Carolina, 1955-80; variability, loads, and trends of selected constituents

    Science.gov (United States)

    Crawford, J. Kent

    1983-01-01

    Water-quality data for selected sites in the Cape Fear River basin collected by the U.S. Geological Survey, the North Carolina Department of Natural Resources and Community Development and the University of North Carolina at Chapel Hill are analyzed and interpreted in this report. Emphasis is given to the Cape Fear River at Lock 1 near Kelly, where data are most complete. Other data included in the report were collected from the Cape Fear River at Lillington, the Haw River near the Jordan Dam, and the Deep River at Moncure. Available data indicate that concentrations of dissolved oxygen at study sites are almost always within U.S. Environmental Protection Agency criteria; however, on two sampling dates, the concentration of dissolved oxygen in the Cape Fear at Lock 1 fell slightly below the 5.0 mg/L recommended for fish populations. Measurements of pH from all stations were frequently below the lower limit of 6.5 pH units recommended for protection of freshwater aquatic life. Major dissolved ions detected are sodium and bicarbonate. Sodium concentration averages 8.6 mg/L and bicarbonate averages 17.5 mg/L at Lock 1. Concentrations of dissolved substances and suspended sediment decrease in the downstream direction, presumably because the more heavily populated part of the basin is near the headwaters of the system. Heavy metals, with the exceptions of cadmium and mercury, rarely exceed Environmental Protection Agency criteria for the protection of aquatic life. Concentrations of mercury in the Haw River, which exceed the recommended 0.20 mg/L needed to protect aquatic life, have frequently been reported by other authors. Several of the most toxic metals, arsenic, cadmium, and cobalt, are about five times more concentrated in water from the Haw River site than from other study sites in the basin. Iron and manganese frequently exceed North Carolina water-quality standards. Available nitrogen averages 1.21 mg/L and available phosphorus averages 0.21 mg/L at Lock 1

  2. Detecting correlation between allele frequencies and environmental variables as a signature of selection. A fast computational approach for genome-wide studies

    DEFF Research Database (Denmark)

    Guillot, Gilles; Vitalis, Renaud; Rouzic, Arnaud le

    2014-01-01

    to disentangle the potential effect of environmental variables from the confounding effect of population history. For the routine analysis of genome-wide datasets, one also needs fast inference and model selection algorithms. We propose a method based on an explicit spatial model which is an instance of spatial...... for the most common types of genetic markers, obtained either at the individual or at the population level. Analyzing the simulated data produced under a geostatistical model then under an explicit model of selection, we show that the method is efficient. We also re-analyze a dataset relative to nineteen pine...

  3. An Analysis of the Effectiveness of Supplemental Instruction: The Problem of Selection Bias and Limited Dependent Variables

    Science.gov (United States)

    Bowles, Tyler J.; Jones, Jason

    2004-01-01

    Single equation regression models have been used rather extensively to test the effectiveness of Supplemental Instruction (SI). This approach, however, fails to account for the possibility that SI attendance and the outcome of SI attendance are jointly determined endogenous variables. Moreover, the standard approach fails to account for the fact…

  4. An Application of Supervised Learning Methods to Search for Variable Stars in a Selected Field of the VVV Survey

    Science.gov (United States)

    Rodríguez-Feliciano, B.; García-Varela, A.; Pérez-Ortiz, M. F.; Sabogal, B. E.; Minniti, D.

    2017-07-01

    We characterize properties of time series of variable stars in the B278 field of the VVV survey, using robust statistics. Using random forest and support vector machines classifiers we propose 47 candidates to RR Lyraae, and 12 candidates to WU Ursae Majoris eclipsing binaries.

  5. Clonal variability for water use efficiency and carbon isotope discrimination ( 13C) in selected clones of a few Eucalyptus species

    CSIR Research Space (South Africa)

    Mohan Raju, B

    2011-11-01

    Full Text Available and develop high water use efficient clones to cultivate under water limited environments. The major objective was to assess the eucalyptus clones for variability in WUE and to determine the relationship between WUE and carbon isotope discrimination ( 13C...

  6. Microbiological quality of selected ready-to-eat leaf vegetables, sprouts and non-pasteurized fresh fruit-vegetable juices including the presence of Cronobacter spp.

    Science.gov (United States)

    Berthold-Pluta, Anna; Garbowska, Monika; Stefańska, Ilona; Pluta, Antoni

    2017-08-01

    Bacteria of the genus Cronobacter are emerging food-borne pathogens. Foods contaminated with Cronobacter spp. may pose a risk to infants or adults with suppressed immunity. This study was aimed at determining the microbiological quality of ready-to-eat (RTE) plant-origin food products available on the Polish market with special emphasis on the prevalence of Cronobacter genus bacteria. Analyses were carried out on 60 samples of commercial RTE type plant-origin food products, including: leaf vegetables (20 samples), sprouts (20 samples) and non-pasteurized vegetable, fruit and fruit-vegetable juices (20 samples). All samples were determined for the total count of aerobic mesophilic bacteria (TAMB) and for the presence of Cronobacter spp. The isolates of Cronobacter spp. were subjected to genetic identification and differentiation by 16S rDNA sequencing, PCR-RFLP analysis and RAPD-PCR and evaluation of antibiotic susceptibility by the disk diffusion assay. The TAMB count in samples of lettuces, sprouts and non-pasteurized fruit, vegetable and fruit-vegetable juices was in the range of 5.6-7.6, 6.7-8.4 and 2.9-7.7 log CFU g -1 , respectively. The presence of Cronobacter spp. was detected in 21 (35%) samples of the products, including in 6 (30%) samples of leaf vegetables (rucola, lamb's lettuce, endive escarola and leaf vegetables mix) and in 15 (75%) samples of sprouts (alfalfa, broccoli, small radish, lentil, sunflower, leek and sprout mix). No presence of Cronobacter spp. was detected in the analyzed samples of non-pasteurized fruit, vegetable and fruit-vegetable juices. The 21 strains of Cronobacter spp. isolated from leaf vegetable and sprouts included: 13 strains of C. sakazakii, 4 strains of C. muytjensii, 2 strains of C. turicensis, one strain of C. malonaticus and one strain of C. condimenti. All isolated C. sakazakii, C. muytjensii, C. turicensis and C. malonaticus strains were sensitive to ampicillin, cefepime, chloramphenicol, gentamycin

  7. Positive selection in the chromosome 16 VKORC1 genomic region has contributed to the variability of anticoagulant response in humans.

    Directory of Open Access Journals (Sweden)

    Blandine Patillon

    Full Text Available VKORC1 (vitamin K epoxide reductase complex subunit 1, 16p11.2 is the main genetic determinant of human response to oral anticoagulants of antivitamin K type (AVK. This gene was recently suggested to be a putative target of positive selection in East Asian populations. In this study, we genotyped the HGDP-CEPH Panel for six VKORC1 SNPs and downloaded chromosome 16 genotypes from the HGDP-CEPH database in order to characterize the geographic distribution of footprints of positive selection within and around this locus. A unique VKORC1 haplotype carrying the promoter mutation associated with AVK sensitivity showed especially high frequencies in all the 17 HGDP-CEPH East Asian population samples. VKORC1 and 24 neighboring genes were found to lie in a 505 kb region of strong linkage disequilibrium in these populations. Patterns of allele frequency differentiation and haplotype structure suggest that this genomic region has been submitted to a near complete selective sweep in all East Asian populations and only in this geographic area. The most extreme scores of the different selection tests are found within a smaller 45 kb region that contains VKORC1 and three other genes (BCKDK, MYST1 (KAT8, and PRSS8 with different functions. Because of the strong linkage disequilibrium, it is not possible to determine if VKORC1 or one of the three other genes is the target of this strong positive selection that could explain present-day differences among human populations in AVK dose requirement. Our results show that the extended region surrounding a presumable single target of positive selection should be analyzed for genetic variation in a wide range of genetically diverse populations in order to account for other neighboring and confounding selective events and the hitchhiking effect.

  8. Investigation of pyrrolizidine alkaloids including their respective N-oxides in selected food products available in Hong Kong by liquid chromatography electrospray ionisation mass spectrometry.

    Science.gov (United States)

    Chung, Stephen W C; Lam, Aaron C H

    2017-07-01

    This study determined the levels of pyrrolizidine alkaloids (PAs), including their respective N-oxides, in foodstuffs available in Hong Kong by liquid chromatography-electrospray ionisation tandem mass spectrometry. A total of 234 samples (48 food items) were collected randomly from a local market and analysed. About 50% of samples were found to contain detectable amount of PAs. Amongst the 48 food items, PAs were not detected in 11 food items, including barley flour, beef, cattle liver, pork, pig liver, chicken meat, chicken liver, milk, non-fermented tea, Melissa tea and linden tea. For those found to contain detectable PAs, the summed PA content ranged up to 11,000 µg kg -1 . The highest sum of PA content among the 37 food items calculated with lower bound was cumin seed, then followed by oregano, tarragon and herbs de Provence with ranges of 2.5-11,000, 1.5-5100, 8.0-3300 and 18-1300 µg kg -1 respectively. Among the samples, the highest sum of PA content was detected in a cumin seed sample (11,000 µg kg -1 ), followed by an oregano (5100 µg kg -1 ), a tarragon (3300 µg kg -1 ) and a herbs de Provence (1300 µg kg -1 ). In general, the results of this study agreed well with other published results in peer-reviewed journals, except that the total PAs in honey and specific tea infusion in this study were comparatively lower.

  9. Swift Observations of Mrk 421 in Selected Epochs. II. An Extreme Spectral Flux Variability in 2009–2012

    Science.gov (United States)

    Kapanadze, B.; Vercellone, S.; Romano, P.; Hughes, P.; Aller, M.; Aller, H.; Kharshiladze, O.; Tabagari, L.

    2018-05-01

    We present the results from a detailed spectral and timing study of Mrk 421 based on the rich archival Swift data obtained during 2009–2012. Best fits of the 0.3–10 keV spectra were mostly obtained using the log-parabolic model showing the relatively low spectral curvature that is expected in the case of efficient stochastic acceleration of particles. The position of the synchrotron spectral energy density peak E p of 173 spectra is found at energies higher than 2 keV. The photon index at 1 keV exhibited a very broad range of values a = 1.51–3.02, and very hard spectra with a historical state and that corresponding to a rate higher than 100 cts s‑1. Moreover, 113 instances of intraday variability were revealed, exhibiting shortest flux-doubling/halving times of about 1.2 hr, as well as brightenings by 7%–24% in 180–720 s and declines by 68%–22% in 180–900 s. The X-ray and very high-energy fluxes generally showed a correlated variability, although one incidence of a more complicated variability was also detected, indicating that the multifrequency emission of Mrk 421 could not be generated in a single zone.

  10. Energy-efficient relay selection and optimal power allocation for performance-constrained dual-hop variable-gain AF relaying

    KAUST Repository

    Zafar, Ammar

    2013-12-01

    This paper investigates the energy-efficiency enhancement of a variable-gain dual-hop amplify-and-forward (AF) relay network utilizing selective relaying. The objective is to minimize the total consumed power while keeping the end-to-end signal-to-noise-ratio (SNR) above a certain peak value and satisfying the peak power constraints at the source and relay nodes. To achieve this objective, an optimal relay selection and power allocation strategy is derived by solving the power minimization problem. Numerical results show that the derived optimal strategy enhances the energy-efficiency as compared to a benchmark scheme in which both the source and the selected relay transmit at peak power. © 2013 IEEE.

  11. Do birds of a feather flock together? The variable bases for African American, Asian American, and European American adolescents' selection of similar friends.

    Science.gov (United States)

    Hamm, J V

    2000-03-01

    Variability in adolescent-friend similarity is documented in a diverse sample of African American, Asian American, and European American adolescents. Similarity was greatest for substance use, modest for academic orientations, and low for ethnic identity. Compared with Asian American and European American adolescents, African American adolescents chose friends who were less similar with respect to academic orientation or substance use but more similar with respect to ethnic identity. For all three ethnic groups, personal endorsement of the dimension in question and selection of cross-ethnic-group friends heightened similarity. Similarity was a relative rather than an absolute selection criterion: Adolescents did not choose friends with identical orientations. These findings call for a comprehensive theory of friendship selection sensitive to diversity in adolescents' experiences. Implications for peer influence and self-development are discussed.

  12. A comparison of small-area estimation techniques to estimate selected stand attributes using LiDAR-derived auxiliary variables

    Science.gov (United States)

    Michael E. Goerndt; Vicente J. Monleon; Hailemariam. Temesgen

    2011-01-01

    One of the challenges often faced in forestry is the estimation of forest attributes for smaller areas of interest within a larger population. Small-area estimation (SAE) is a set of techniques well suited to estimation of forest attributes for small areas in which the existing sample size is small and auxiliary information is available. Selected SAE methods were...

  13. Optimal Selective Harmonic Mitigation Technique on Variable DC Link Cascaded H-Bridge Converter to Meet Power Quality Standards

    DEFF Research Database (Denmark)

    Najjar, Mohammad; Moeini, Amirhossein; Dowlatabadi, Mohammadkazem Bakhshizadeh

    2016-01-01

    In this paper, the power quality standards such as IEC 61000-3-6, IEC 61000-2-12, EN 50160, and CIGRE WG 36-05 are fulfilled for single- and three-phase medium voltage applications by using Selective Harmonic Mitigation-PWM (SHM-PWM) in a Cascaded H-Bridge (CHB) converter. Furthermore, the ER G5/...

  14. Variability in a three-generation family with Pierre Robin sequence, acampomelic campomelic dysplasia, and intellectual disability due to a novel ∼1 Mb deletion upstream of SOX9, and including KCNJ2 and KCNJ16.

    Science.gov (United States)

    Castori, Marco; Bottillo, Irene; Morlino, Silvia; Barone, Chiara; Cascone, Piero; Grammatico, Paola; Laino, Luigi

    2016-01-01

    Campomelic dysplasia and acampomelic campomelic dysplasia (ACD) are allelic disorders due to heterozygous mutations in or around SOX9. Translocations and deletions involving the SOX9 5' regulatory region are rare causes of these disorders, as well as Pierre Robin sequence (PRS) and 46,XY gonadal dysgenesis. Genotype-phenotype correlations are not straightforward due to the complex epigenetic regulation of SOX9 expression during development. We report a three-generation pedigree with a novel ∼1 Mb deletion upstream of SOX9 and including KCNJ2 and KCNJ16, and ascertained for dominant transmission of PRS. Further characterization of the family identified subtle appendicular anomalies and a variable constellation of axial skeletal features evocative of ACD in several members. Affected males showed learning disability. The identified deletion was smaller than all other chromosome rearrangements associated with ACD. Comparison with other reported translocations and deletions involving this region allowed further refining of genotype-phenotype correlations and an update of the smallest regions of overlap associated with the different phenotypes. Intrafamilial variability in this pedigree suggests a phenotypic continuity between ACD and PRS in patients carrying mutations in the SOX9 5' regulatory region. © 2015 Wiley Periodicals, Inc.

  15. Emergency department documentation templates: variability in template selection and association with physical examination and test ordering in dizziness presentations

    Directory of Open Access Journals (Sweden)

    Meurer William J

    2011-03-01

    Full Text Available Abstract Background Clinical documentation systems, such as templates, have been associated with process utilization. The T-System emergency department (ED templates are widely used but lacking are analyses of the templates association with processes. This system is also unique because of the many different template options available, and thus the selection of the template may also be important. We aimed to describe the selection of templates in ED dizziness presentations and to investigate the association between items on templates and process utilization. Methods Dizziness visits were captured from a population-based study of EDs that use documentation templates. Two relevant process outcomes were assessed: head computerized tomography (CT scan and nystagmus examination. Multivariable logistic regression was used to estimate the probability of each outcome for patients who did or did not receive a relevant-item template. Propensity scores were also used to adjust for selection effects. Results The final cohort was 1,485 visits. Thirty-one different templates were used. Use of a template with a head CT item was associated with an increase in the adjusted probability of head CT utilization from 12.2% (95% CI, 8.9%-16.6% to 29.3% (95% CI, 26.0%-32.9%. The adjusted probability of documentation of a nystagmus assessment increased from 12.0% (95%CI, 8.8%-16.2% when a nystagmus-item template was not used to 95.0% (95% CI, 92.8%-96.6% when a nystagmus-item template was used. The associations remained significant after propensity score adjustments. Conclusions Providers use many different templates in dizziness presentations. Important differences exist in the various templates and the template that is used likely impacts process utilization, even though selection may be arbitrary. The optimal design and selection of templates may offer a feasible and effective opportunity to improve care delivery.

  16. Input Selection for Return Temperature Estimation in Mixing Loops using Partial Mutual Information with Flow Variable Delay

    DEFF Research Database (Denmark)

    Overgaard, Anders; Kallesøe, Carsten Skovmose; Bendtsen, Jan Dimon

    2017-01-01

    adgang til data, er ønsker at skabe en datadreven model til kontrol. Grundet den store mængde tilgængelig data anvendes der en metode til valg af inputs kaldet "Partial Mutual Information" (PMI). Denne artikel introducerer en metode til at inkluderer flow variable forsinkelser i PMI. Data fra en...... kontorbygning i Bjerringbro anvendes til analyse. Det vises at "Mutual Information" og et "Generalized Regression Neural Network" begge forbedres ved at anvende flow variabelt forsinkelse i forhold til at anvende konstante delay....

  17. Estimation of genetic variability and selection response for clutch length in dwarf brown-egg layers carrying or not the naked neck gene

    Directory of Open Access Journals (Sweden)

    Tixier-Boichard Michèle

    2003-03-01

    Full Text Available Abstract In order to investigate the possibility of using the dwarf gene for egg production, two dwarf brown-egg laying lines were selected for 16 generations on average clutch length; one line (L1 was normally feathered and the other (L2 was homozygous for the naked neck gene NA. A control line from the same base population, dwarf and segregating for the NA gene, was maintained during the selection experiment under random mating. The average clutch length was normalized using a Box-Cox transformation. Genetic variability and selection response were estimated either with the mixed model methodology, or with the classical methods for calculating genetic gain, as the deviation from the control line, and the realized heritability, as the ratio of the selection response on cumulative selection differentials. Heritability of average clutch length was estimated to be 0.42 ± 0.02, with a multiple trait animal model, whereas the estimates of the realized heritability were lower, being 0.28 and 0.22 in lines L1 and L2, respectively. REML estimates of heritability were found to decline with generations of selection, suggesting a departure from the infinitesimal model, either because a limited number of genes was involved, or their frequencies were changed. The yearly genetic gains in average clutch length, after normalization, were estimated to be 0.37 ± 0.02 and 0.33 ± 0.04 with the classical methods, 0.46 ± 0.02 and 0.43 ± 0.01 with animal model methodology, for lines L1 and L2 respectively, which represented about 30% of the genetic standard deviation on the transformed scale. Selection response appeared to be faster in line L2, homozygous for the NA gene, but the final cumulated selection response for clutch length was not different between the L1 and L2 lines at generation 16.

  18. Interval ridge regression (iRR) as a fast and robust method for quantitative prediction and variable selection applied to edible oil adulteration.

    Science.gov (United States)

    Jović, Ozren; Smrečki, Neven; Popović, Zora

    2016-04-01

    A novel quantitative prediction and variable selection method called interval ridge regression (iRR) is studied in this work. The method is performed on six data sets of FTIR, two data sets of UV-vis and one data set of DSC. The obtained results show that models built with ridge regression on optimal variables selected with iRR significantly outperfom models built with ridge regression on all variables in both calibration (6 out of 9 cases) and validation (2 out of 9 cases). In this study, iRR is also compared with interval partial least squares regression (iPLS). iRR outperfomed iPLS in validation (insignificantly in 6 out of 9 cases and significantly in one out of 9 cases for poil, a well known health beneficial nutrient, is studied in this work by mixing it with cheap and widely used oils such as soybean (So) oil, rapeseed (R) oil and sunflower (Su) oil. Binary mixture sets of hempseed oil with these three oils (HSo, HR and HSu) and a ternary mixture set of H oil, R oil and Su oil (HRSu) were considered. The obtained accuracy indicates that using iRR on FTIR and UV-vis data, each particular oil can be very successfully quantified (in all 8 cases RMSEPoil (R(2)>0.99). Copyright © 2015 Elsevier B.V. All rights reserved.

  19. Evaluation of Phenolic Content Variability along with Antioxidant, Antimicrobial, and Cytotoxic Potential of Selected Traditional Medicinal Plants from India.

    Science.gov (United States)

    Singh, Garima; Passsari, Ajit K; Leo, Vincent V; Mishra, Vineet K; Subbarayan, Sarathbabu; Singh, Bhim P; Kumar, Brijesh; Kumar, Sunil; Gupta, Vijai K; Lalhlenmawia, Hauzel; Nachimuthu, Senthil K

    2016-01-01

    Plants have been used since ancient times as an important source of biologically active substances. The aim of the present study was to investigate the phytochemical constituents (flavonoids and phenolics), antioxidant potential, cytotoxicity against HepG2 (human hepato carcinoma) cancer cell lines, and the antimicrobial activity of the methanol extract of selected traditional medicinal plants collected from Mizoram, India. A number of phenolic compounds were detected using HPLC-DAD-ESI-TOF-MS, mainly Luteolin, Kaempferol, Myricetin, Gallic Acid, Quercetin and Rutin, some of which have been described for the first time in the selected plants. The total phenolic and flavonoid contents showed high variation ranging from 4.44 to 181.91 μg of Gallic Acid equivalent per milligram DW (GAE/mg DW) and 3.17 to 102.2 μg of Quercetin/mg, respectively. The antioxidant capacity was determined by DPPH (IC50 values ranges from 34.22 to 131.4 μg/mL), ABTS (IC50 values ranges from 24.08 to 513.4 μg/mL), and reducing power assays. Antimicrobial activity was assayed against gram positive (Staphylococcus aureus), gram negative (Escherichia coli, Pseudomonas aeruginosa), and yeast (Candida albicans) demonstrating that the methanol extracts of some plants were efficacious antimicrobial agents. Additionally, cytotoxicity was assessed on human hepato carcinoma (HepG2) cancer cell lines and found that the extracts of Albizia lebbeck, Dillenia indica, and Bombax ceiba significantly decreased the cell viability at low concentrations with IC50 values of 24.03, 25.09, and 29.66 μg/mL, respectively. This is the first report of detection of phenolic compounds along with antimicrobial, antioxidant and cytotoxic potential of selected medicinal plants from India, which indicates that these plants might be valuable source for human and animal health.

  20. Evaluation of phenolic content variability, antioxidant, antimicrobial and cytotoxic potential of selected traditional medicinal plants from India

    Directory of Open Access Journals (Sweden)

    Garima eSingh

    2016-03-01

    Full Text Available Plants have been used since ancient times as an important source of biologically active substances. The aim of the present study was to investigate the phytochemical constituents (flavonoids and phenolics, antioxidant potential, cytotoxicity against HepG2 (human hepato carcinoma cancer cell lines and the antimicrobial activity of the methanol extract of selected traditional medicinal plants collected from Mizoram, India. A number of phenolic compounds were detected using HPLC-DAD-ESI-TOF-MS, mainly Luteolin, Kaempferol, Myricetin, Gallic Acid, Quercetin and Rutin, some of which have been described for the first time in the selected plants. The total phenolic and flavonoid contents showed high variation ranging from 4.44 to 181.91 µg of Gallic Acid equivalent per milligram DW (GAE/mg DW and 3.17 to 102.2 µg of Quercetin/mg, respectively. The antioxidant capacity was determined by DPPH (IC50 values ranges from 34.22 to 131.4 µg/mL, ABTS (IC50 values ranges from 24.08 to 513.4 µg/mL and reducing power assays. Antimicrobial activity was assayed against gram positive (Staphylococcus aureus, gram negative (Escherichia coli, Pseudomonas aeruginosa and yeast (Candida albicans demonstrating that the methanol extracts of some plants were efficacious antimicrobial agents. Additionally, cytotoxicity was assessed on human hepato carcinoma (HepG2 cancer cell lines and found that the extracts of Albizia lebbeck, Dillenia indica and Bombax ceiba significantly decreased the cell viability at low concentrations with IC50 values of 24.03, 25.09 and 29.66 µg/mL, respectively. This is the first report of detection of phenolic compounds along with antimicrobial, antioxidant and cytotoxic potential of selected medicinal plants from India, which indicates that these plants might be valuable source for human and animal health.

  1. The Criteria and Variables Affecting the Selection of Quality Book Ideally Suited for Translation: The Perspectives of King Saud University Staff

    Directory of Open Access Journals (Sweden)

    Abdulaziz Abdulrahman Abanomey

    2015-04-01

    Full Text Available This study investigated the ideal definition of QB, that is Quality Book- one that is ideally suited for translation- and the variables affecting its selection criteria among 136 members of King Saud University (KSU academic staff. A workshop was held to elicit the ideal definition of QB to answer the first question, and a 19-item electronic questionnaire with four domains was designed to help collect the data necessary to answer the other two questions of the study. The results revealed that all four domains came low; “Authorship and Publication” came the highest with a mean score of 2.28 and “Titling and Contents” came the lowest with a mean score of 1.76. 5-way ANOVA (without interaction was applied in accordance with the variables of the study at α≤ 0.05 among the mean scores. The analysis revealed significance of the variables of gender, those who translated a book or more before, and those who participated in a conference devoted for translation whereas the variables of qualification and revising a translated book did not reveal any statistical significance. Key words: Quality Book, KSU, Authorship, Translation, Titling

  2. Developing a NIR multispectral imaging for prediction and visualization of peanut protein content using variable selection algorithms

    Science.gov (United States)

    Cheng, Jun-Hu; Jin, Huali; Liu, Zhiwei

    2018-01-01

    The feasibility of developing a multispectral imaging method using important wavelengths from hyperspectral images selected by genetic algorithm (GA), successive projection algorithm (SPA) and regression coefficient (RC) methods for modeling and predicting protein content in peanut kernel was investigated for the first time. Partial least squares regression (PLSR) calibration model was established between the spectral data from the selected optimal wavelengths and the reference measured protein content ranged from 23.46% to 28.43%. The RC-PLSR model established using eight key wavelengths (1153, 1567, 1972, 2143, 2288, 2339, 2389 and 2446 nm) showed the best predictive results with the coefficient of determination of prediction (R2P) of 0.901, and root mean square error of prediction (RMSEP) of 0.108 and residual predictive deviation (RPD) of 2.32. Based on the obtained best model and image processing algorithms, the distribution maps of protein content were generated. The overall results of this study indicated that developing a rapid and online multispectral imaging system using the feature wavelengths and PLSR analysis is potential and feasible for determination of the protein content in peanut kernels.

  3. Occurrence and temporal variability of methyl tert-butyl ether (MTBE) and other volatile organic compounds in select sources of drinking water : results of the focused survey

    Science.gov (United States)

    Delzer, Gregory C.; Ivahnenko, Tamara

    2003-01-01

    The large-scale use of the gasoline oxygenate methyl tert-butyl ether (MTBE), and its high solubility, low soil adsorption, and low biodegradability, has resulted in its detection in ground water and surface water in many places throughout the United States. Studies by numerous researchers, as well as many State and local environmental agencies, have discovered high levels of MTBE in soils and ground water at leaking underground gasoline-storage-tank sites and frequent occurrence of low to intermediate levels of MTBE in reservoirs used for both public water supply and recreational boating.In response to these findings, the American Water Works Association Research Foundation sponsored an investigation of MTBE and other volatile organic compounds (VOCs) in the Nation's sources of drinking water. The goal of the investigation was to provide additional information on the frequency of occurrence, concentration, and temporal variability of MTBE and other VOCs in source water used by community water systems (CWSs). The investigation was completed in two stages: (1) reviews of available literature and (2) the collection of new data. Two surveys were associated with the collection of new data. The first, termed the Random Survey, employed a statistically stratified design for sampling source water from 954 randomly selected CWSs. The second, which is the focus of this report, is termed the Focused Survey, which included samples collected from 134 CWS source waters, including ground water, reservoirs, lakes, rivers, and streams, that were suspected or known to contain MTBE. The general intent of the Focused Survey was to compare results with the Random Survey and provide an improved understanding of the occurrence, concentration, temporal variability, and anthropogenic factors associated with frequently detected VOCs. Each sample collected was analyzed for 66 VOCs, including MTBE and three other ether gasoline oxygenates (hereafter termed gasoline oxygenates). As part of

  4. Selective interaction of heparin with the variable region 3 within surface glycoprotein of laboratory-adapted feline immunodeficiency virus.

    Directory of Open Access Journals (Sweden)

    Qiong-Ying Hu

    Full Text Available Heparan sulfate proteoglycans (HSPG can act as binding receptors for certain laboratory-adapted (TCA strains of feline immunodeficiency virus (FIV and human immunodeficiency virus (HIV. Heparin, a soluble heparin sulfate (HS, can inhibit TCA HIV and FIV entry mediated by HSPG interaction in vitro. In the present study, we further determined the selective interaction of heparin with the V3 loop of TCA of FIV. Our current results indicate that heparin selectively inhibits infection by TCA strains, but not for field isolates (FS. Heparin also specifically interferes with TCA surface glycoprotein (SU binding to CXCR4, by interactions with HSPG binding sites on the V3 loop of the FIV envelope protein. Peptides representing either the N- or C-terminal side of the V3 loop and containing HSPG binding sites were able to compete away the heparin block of TCA SU binding to CXCR4. Heparin does not interfere with the interaction of SU with anti-V3 antibodies that target the CXCR4 binding region or with the interaction between FS FIV and anti-V3 antibodies since FS SU has no HSPG binding sites within the HSPG binding region. Our data show that heparin blocks TCA FIV infection or entry not only through its competition of HSPG on the cell surface interaction with SU, but also by its interference with CXCR4 binding to SU. These studies aid in the design and development of heparin derivatives or analogues that can inhibit steps in virus infection and are informative regarding the HSPG/SU interaction.

  5. Impact of selected personal factors on seasonal variability of recreationist weather perceptions and preferences in Warsaw (Poland)

    Science.gov (United States)

    Lindner-Cendrowska, Katarzyna; Błażejczyk, Krzysztof

    2018-01-01

    Weather and climate are important natural resources for tourism and recreation, although sometimes they can make outdoor leisure activities less satisfying or even impossible. The aim of this work was to determine weather perception seasonal variability of people staying outdoors in urban environment for tourism and recreation, as well as to determine if personal factors influence estimation of recreationist actual biometeorological conditions and personal expectations towards weather elements. To investigate how human thermal sensations vary upon meteorological conditions typical for temperate climate, weather perception field researches were conducted in Warsaw (Poland) in all seasons. Urban recreationists' preference for slightly warm thermal conditions, sunny, windless and cloudless weather, were identified as well as PET values considered to be optimal for sightseeing were defined between 27.3 and 31.7 °C. The results confirmed existence of phenomena called alliesthesia, which manifested in divergent thermal perception of comparable biometeorological conditions in transitional seasons. The results suggest that recreationist thermal sensations differed from other interviewees' responses and were affected not only by physiological processes but they were also conditioned by psychological factors (i.e. attitude, expectations). Significant impact of respondents' place of origin and its climate on creating thermal sensations and preferences was observed. Sex and age influence thermal preferences, whereas state of acclimatization is related with thermal sensations to some point.

  6. Area-Selective ZnO Thin Film Deposition on Variable Microgap Electrodes and Their Impact on UV Sensing

    Directory of Open Access Journals (Sweden)

    Q. Humayun

    2013-01-01

    Full Text Available ZnO thin films were deposited on patterned gold electrodes using the sol-gel spin coating technique. Conventional photolithography process was used to obtain the variable microgaps of 30 and 43 μm in butterfly topology by using zero-gap chrome mask. The structural, morphological, and electrical properties of the deposited thin films were characterized by X-ray diffraction (XRD, scanning electron microscope (SEM, and Keithley SourceMeter, respectively. The current-voltage (I-V characterization was performed to investigate the effect of UV light on the fabricated devices. The ZnO fabricated sensors showed a photo to dark current (Iph/Id ratios of 6.26 for 30 μm and 5.28 for 43 μm gap electrodes spacing, respectively. Dynamic responses of both fabricated sensors were observed till 1V with good reproducibility. At the applied voltage of 1 V, the response time was observed to be 4.817 s and 3.704 s while the recovery time was observed to be 0.3738 s and 0.2891 s for 30 and 43 μm gaps, respectively. The signal detection at low operating voltages suggested that the fabricated sensors could be used for miniaturized devices with low power consumption.

  7. Non-targeted detection of chemical contamination in carbonated soft drinks using NMR spectroscopy, variable selection and chemometrics

    Energy Technology Data Exchange (ETDEWEB)

    Charlton, Adrian J. [Department for Environment, Food and Rural Affairs, Central Science Laboratory, Sand Hutton, York YO41 1LZ (United Kingdom)], E-mail: adrian.charlton@csl.gov.uk; Robb, Paul; Donarski, James A.; Godward, John [Department for Environment, Food and Rural Affairs, Central Science Laboratory, Sand Hutton, York YO41 1LZ (United Kingdom)

    2008-06-23

    An efficient method for detecting malicious and accidental contamination of foods has been developed using a combined {sup 1}H nuclear magnetic resonance (NMR) and chemometrics approach. The method has been demonstrated using a commercially available carbonated soft drink, as being capable of identifying atypical products and to identify contaminant resonances. Soft-independent modelling of class analogy (SIMCA) was used to compare {sup 1}H NMR profiles of genuine products (obtained from the manufacturer) against retail products spiked in the laboratory with impurities. The benefits of using feature selection for extracting contaminant NMR frequencies were also assessed. Using example impurities (paraquat, p-cresol and glyphosate) NMR spectra were analysed using multivariate methods resulting in detection limits of approximately 0.075, 0.2, and 0.06 mM for p-cresol, paraquat and glyphosate, respectively. These detection limits are shown to be approximately 100-fold lower than the minimum lethal dose for paraquat. The methodology presented here is used to assess the composition of complex matrices for the presence of contaminating molecules without a priori knowledge of the nature of potential contaminants. The ability to detect if a sample does not fit into the expected profile without recourse to multiple targeted analyses is a valuable tool for incident detection and forensic applications.

  8. Non-targeted detection of chemical contamination in carbonated soft drinks using NMR spectroscopy, variable selection and chemometrics

    International Nuclear Information System (INIS)

    Charlton, Adrian J.; Robb, Paul; Donarski, James A.; Godward, John

    2008-01-01

    An efficient method for detecting malicious and accidental contamination of foods has been developed using a combined 1 H nuclear magnetic resonance (NMR) and chemometrics approach. The method has been demonstrated using a commercially available carbonated soft drink, as being capable of identifying atypical products and to identify contaminant resonances. Soft-independent modelling of class analogy (SIMCA) was used to compare 1 H NMR profiles of genuine products (obtained from the manufacturer) against retail products spiked in the laboratory with impurities. The benefits of using feature selection for extracting contaminant NMR frequencies were also assessed. Using example impurities (paraquat, p-cresol and glyphosate) NMR spectra were analysed using multivariate methods resulting in detection limits of approximately 0.075, 0.2, and 0.06 mM for p-cresol, paraquat and glyphosate, respectively. These detection limits are shown to be approximately 100-fold lower than the minimum lethal dose for paraquat. The methodology presented here is used to assess the composition of complex matrices for the presence of contaminating molecules without a priori knowledge of the nature of potential contaminants. The ability to detect if a sample does not fit into the expected profile without recourse to multiple targeted analyses is a valuable tool for incident detection and forensic applications

  9. Variability and changes in selected climate elements in Madrid and Alicante in the period 2000-2014

    Directory of Open Access Journals (Sweden)

    Cielecka Katarzyna

    2015-10-01

    Full Text Available The aim of this study is to compare climatic conditions between the interior of the Iberian Peninsula and the southeastern coast of Spain. The article analyzes selected elements of climate over the last 15 years (2000-2014. Synoptic data from airport meteorological stations in Madrid Barajas and Alicante Elche were used. Attention was focused on annual air temperature, relative humidity and precipitation. The mean climatic conditions over the period 2000-2014 were compared with those over the 1961-1990 period which is recommended by WMO as climate normal and with data for the 1971-2000 coming from ‘Climate Atlas’ of Spanish meteorologists group AEMET. Two of climate elements discussed were characterized by significant changes. The annual air temperature was higher by about 0.2°C in Alicante and 0.9°C in Madrid in the period 2000-2014 compared to the 1961-1990. The current winters were colder than in years 1961-1990 at both stations. Gradual decrease in annual precipitation totals was observed at both stations. In 1961-1990 the annual average precipitation in Madrid amounted to 414 mm, while in Alicante it was 356 mm. However, in the recent years of 2000-2014 these totals were lower compared to 1961-1990 reaching 364.1 mm in the central part of Spain and 245.7 mm on the south-western coast.

  10. Genetic variability, local selection and demographic history: genomic evidence of evolving towards allopatric speciation in Asian seabass.

    Science.gov (United States)

    Wang, Le; Wan, Zi Yi; Lim, Huan Sein; Yue, Gen Hua

    2016-08-01

    Genomewide analysis of genetic divergence is critically important in understanding the genetic processes of allopatric speciation. We sequenced RAD tags of 131 Asian seabass individuals of six populations from South-East Asia and Australia/Papua New Guinea. Using 32 433 SNPs, we examined the genetic diversity and patterns of population differentiation across all the populations. We found significant evidence of genetic heterogeneity between South-East Asian and Australian/Papua New Guinean populations. The Australian/Papua New Guinean populations showed a rather lower level of genetic diversity. FST and principal components analysis revealed striking divergence between South-East Asian and Australian/Papua New Guinean populations. Interestingly, no evidence of contemporary gene flow was observed. The demographic history was further tested based on the folded joint site frequency spectrum. The scenario of ancient migration with historical population size changes was suggested to be the best fit model to explain the genetic divergence of Asian seabass between South-East Asia and Australia/Papua New Guinea. This scenario also revealed that Australian/Papua New Guinean populations were founded by ancestors from South-East Asia during mid-Pleistocene and were completely isolated from the ancestral population after the last glacial retreat. We also detected footprints of local selection, which might be related to differential ecological adaptation. The ancient gene flow was examined and deemed likely insufficient to counteract the genetic differentiation caused by genetic drift. The observed genomic pattern of divergence conflicted with the 'genomic islands' scenario. Altogether, Asian seabass have likely been evolving towards allopatric speciation since the split from the ancestral population during mid-Pleistocene. © 2016 John Wiley & Sons Ltd.

  11. Macroinvertebrate Prey Availability and Fish Diet Selectivity in Relation to Environmental Variables in Natural and Restoring North San Francisco Bay Tidal Marsh Channels

    Directory of Open Access Journals (Sweden)

    Emily R. Howe

    2014-03-01

    Full Text Available Tidal marsh wetlands provide important foraging habitat for a variety of estuarine fishes. Prey organisms include benthic–epibenthic macroinvertebrates, neustonic arthropods, and zooplankton. Little is known about the abundance and distribution of interior marsh macroinvertebrate communities in the San Francisco Estuary (estuary. We describe seasonal, regional, and site variation in the composition and abundance of neuston and benthic–epibenthic macroinvertebrates that inhabit tidal marsh channels, and relate these patterns to environmental conditions. We also describe spatial and temporal variation in diets of marsh-associated inland silverside, yellowfin goby, and western mosquitofish. Fish and invertebrates were sampled quarterly from October 2003 to June 2005 at six marsh sites located in three river systems of the northern estuary: Petaluma River, Napa River, and  the west Delta. Benthic/epibenthic macroinvertebrates and neuston responded to environmental variables related to seasonal changes (i.e., temperature, salinity, as well as those related to marsh structure (i.e., vegetation, channel edge. The greatest variation in abundance occurred seasonally for neuston and spatially for benthic–epibenthic organisms, suggesting that each community responds to different environmental drivers. Benthic/epibenthic invertebrate abundance and diversity was lowest in the west Delta, and increased with increasing salinity. Insect abundance increased during the spring and summer, while Collembolan (springtail abundance increased during the winter. Benthic/epibenthic macroinvertebrates dominated fish diets, supplemented by insects, with zooplankton playing a minor role. Diet compositions of the three fish species overlapped considerably, with strong selection indicated for epibenthic crustaceans—a surprising result given the typical classification of Menidia beryllina as a planktivore, Acanthogobius flavimanus as a benthic predator, and Gambusia

  12. The relationship of document and quantitative literacy with learning styles and selected personal variables for aerospace technology students at Indiana State University

    Science.gov (United States)

    Martin, Royce Ann

    The purpose of this study was to determine the extent that student scores on a researcher-constructed quantitative and document literacy test, the Aviation Documents Delineator (ADD), were associated with (a) learning styles (imaginative, analytic, common sense, dynamic, and undetermined), as identified by the Learning Type Measure, (b) program curriculum (aerospace administration, professional pilot, both aerospace administration and professional pilot, other, or undeclared), (c) overall cumulative grade point average at Indiana State University, and (d) year in school (freshman, sophomore, junior, or senior). The Aviation Documents Delineator (ADD) was a three-part, 35 question survey that required students to interpret graphs, tables, and maps. Tasks assessed in the ADD included (a) locating, interpreting, and describing specific data displayed in the document, (b) determining data for a specified point on the table through interpolation, (c) comparing data for a string of variables representing one aspect of aircraft performance to another string of variables representing a different aspect of aircraft performance, (d) interpreting the documents to make decisions regarding emergency situations, and (e) performing single and/or sequential mathematical operations on a specified set of data. The Learning Type Measure (LTM) was a 15 item self-report survey developed by Bernice McCarthy (1995) to profile an individual's processing and perception tendencies in order to reveal different individual approaches to learning. The sample used in this study included 143 students enrolled in Aerospace Technology Department courses at Indiana State University in the fall of 1996. The ADD and the LTM were administered to each subject. Data collected in this investigation were analyzed using a stepwise multiple regression analysis technique. Results of the study revealed that the variables, year in school and GPA, were significant predictors of the criterion variables, document

  13. The Use of Asymptotic Functions for Determining Empirical Values of CN Parameter in Selected Catchments of Variable Land Cover

    Directory of Open Access Journals (Sweden)

    Wałęga Andrzej

    2017-12-01

    Full Text Available The aim of the study was to assess the applicability of asymptotic functions for determining the value of CN parameter as a function of precipitation depth in mountain and upland catchments. The analyses were carried out in two catchments: the Rudawa, left tributary of the Vistula, and the Kamienica, right tributary of the Dunajec. The input material included data on precipitation and flows for a multi-year period 1980–2012, obtained from IMGW PIB in Warsaw. Two models were used to determine empirical values of CNobs parameter as a function of precipitation depth: standard Hawkins model and 2-CN model allowing for a heterogeneous nature of a catchment area.

  14. The effect of selected preparation variables on the radiochemical purity of 99mTc-EDDA-HYNIC-TOC

    International Nuclear Information System (INIS)

    Betuel Tasdelen

    2011-01-01

    [ 99m Tc-EDDA-HYNIC-D-Phe 1 , Tyr 3 ]-Ocreotide ( 99m Tc-EDDA-HYNIC-TOC) increasingly emerges to be an alternative tool for somatostatin receptor (SSTR) scintigraphy of neuroendocrine tumours. The high quality of this radiopharmaceutical and its uniformity are very important facts for application of this preparation in clinical practice. Various factors may influence the radiochemical purity (RCP) of certain reagent kits. Some of these include the amount of activity added to the reagent kit, heating time and the age of the formulated kit. The effect of these factors on RCP of 99m Tc-EDDA-HYNIC-TOC has been investigated using high performance liquid chromatography (HPLC) and instant thin layer chromatography (ITLC). (author)

  15. Area- and depth- weighted averages of selected SSURGO variables for the conterminous United States and District of Columbia

    Science.gov (United States)

    Wieczorek, Michael

    2014-01-01

    This digital data release consists of seven data files of soil attributes for the United States and the District of Columbia. The files are derived from National Resources Conservations Service’s (NRCS) Soil Survey Geographic database (SSURGO). The data files can be linked to the raster datasets of soil mapping unit identifiers (MUKEY) available through the NRCS’s Gridded Soil Survey Geographic (gSSURGO) database (http://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/geo/?cid=nrcs142p2_053628). The associated files, named DRAINAGECLASS, HYDRATING, HYDGRP, HYDRICCONDITION, LAYER, TEXT, and WTDEP are area- and depth-weighted average values for selected soil characteristics from the SSURGO database for the conterminous United States and the District of Columbia. The SSURGO tables were acquired from the NRCS on March 5, 2014. The soil characteristics in the DRAINAGE table are drainage class (DRNCLASS), which identifies the natural drainage conditions of the soil and refers to the frequency and duration of wet periods. The soil characteristics in the HYDRATING table are hydric rating (HYDRATE), a yes/no field that indicates whether or not a map unit component is classified as a "hydric soil". The soil characteristics in the HYDGRP table are the percentages for each hydrologic group per MUKEY. The soil characteristics in the HYDRICCONDITION table are hydric condition (HYDCON), which describes the natural condition of the soil component. The soil characteristics in the LAYER table are available water capacity (AVG_AWC), bulk density (AVG_BD), saturated hydraulic conductivity (AVG_KSAT), vertical saturated hydraulic conductivity (AVG_KV), soil erodibility factor (AVG_KFACT), porosity (AVG_POR), field capacity (AVG_FC), the soil fraction passing a number 4 sieve (AVG_NO4), the soil fraction passing a number 10 sieve (AVG_NO10), the soil fraction passing a number 200 sieve (AVG_NO200), and organic matter (AVG_OM). The soil characteristics in the TEXT table are

  16. The Impact of Variability of Selected Geological and Mining Parameters on the Value and Risks of Projects in the Hard Coal Mining Industry

    Science.gov (United States)

    Kopacz, Michał

    2017-09-01

    The paper attempts to assess the impact of variability of selected geological (deposit) parameters on the value and risks of projects in the hard coal mining industry. The study was based on simulated discounted cash flow analysis, while the results were verified for three existing bituminous coal seams. The Monte Carlo simulation was based on nonparametric bootstrap method, while correlations between individual deposit parameters were replicated with use of an empirical copula. The calculations take into account the uncertainty towards the parameters of empirical distributions of the deposit variables. The Net Present Value (NPV) and the Internal Rate of Return (IRR) were selected as the main measures of value and risk, respectively. The impact of volatility and correlation of deposit parameters were analyzed in two aspects, by identifying the overall effect of the correlated variability of the parameters and the indywidual impact of the correlation on the NPV and IRR. For this purpose, a differential approach, allowing determining the value of the possible errors in calculation of these measures in numerical terms, has been used. Based on the study it can be concluded that the mean value of the overall effect of the variability does not exceed 11.8% of NPV and 2.4 percentage points of IRR. Neglecting the correlations results in overestimating the NPV and the IRR by up to 4.4%, and 0.4 percentage point respectively. It should be noted, however, that the differences in NPV and IRR values can vary significantly, while their interpretation depends on the likelihood of implementation. Generalizing the obtained results, based on the average values, the maximum value of the risk premium in the given calculation conditions of the "X" deposit, and the correspondingly large datasets (greater than 2500), should not be higher than 2.4 percentage points. The impact of the analyzed geological parameters on the NPV and IRR depends primarily on their co-existence, which can be

  17. Genetic variability in arbuscular mycorrhizal fungi compatibility supports the selection of durum wheat genotypes for enhancing soil ecological services and cropping systems in Canada.

    Science.gov (United States)

    Singh, A K; Hamel, C; Depauw, R M; Knox, R E

    2012-03-01

    Crop nutrient- and water-use efficiency could be improved by using crop varieties highly compatible with arbuscular mycorrhizal fungi (AMF). Two greenhouse experiments demonstrated the presence of genetic variability for this trait in modern durum wheat ( Triticum turgidum L. var. durum Desf.) germplasm. Among the five cultivars tested, 'AC Morse' had consistently low levels of AM root colonization and DT710 had consistently high levels of AM root colonization, whereas 'Commander', which had the highest colonization levels under low soil fertility conditions, developed poor colonization levels under medium fertility level. The presence of genetic variability in durum wheat compatibility with AMF was further evidenced by significant genotype × inoculation interaction effects in grain and straw biomass production; grain P, straw P, and straw K concentrations under medium soil fertility level; and straw K and grain Fe concentrations at low soil fertility. Mycorrhizal dependency was an undesirable trait of 'Mongibello', which showed poor growth and nutrient balance in the absence of AMF. An AMF-mediated reduction in grain Cd under low soil fertility indicated that breeding durum wheat for compatibility with AMF could help reduce grain Cd concentration in durum wheat. Durum wheat genotypes should be selected for compatibility with AMF rather than for mycorrhizal dependency.

  18. Selective dopamine D3 receptor antagonism by SB-277011A attenuates cocaine reinforcement as assessed by progressive-ratio and variable-cost–variable-payoff fixed-ratio cocaine self-administration in rats

    Science.gov (United States)

    Xi, Zheng-Xiong; Gilbert, Jeremy G.; Pak, Arlene C.; Ashby, Charles R.; Heidbreder, Christian A.; Gardner, Eliot L.

    2013-01-01

    In rats, acute administration of SB-277011A, a highly selective dopamine (DA) D3 receptor antagonist, blocks cocaine-enhanced brain stimulation reward, cocaine-seeking behaviour and reinstatement of cocaine-seeking behaviour. Here, we investigated whether SB-277011A attenuates cocaine reinforcement as assessed by cocaine self-administration under variable-cost–variable-payoff fixed-ratio (FR) and progressive-ratio (PR) reinforcement schedules. Acute i.p. administration of SB-277011A (3–24 mg/kg) did not significantly alter cocaine (0.75 mg/kg/infusion) self-administration reinforced under FR1 (one lever press for one cocaine infusion) conditions. However, acute administration of SB-277011A (24 mg/kg, i.p.) progressively attenuated cocaine self-administration when: (a) the unit dose of self-administered cocaine was lowered from 0.75 to 0.125–0.5 mg/kg, and (b) the work demand for cocaine reinforcement was increased from FR1 to FR10. Under PR (increasing number of lever presses for each successive cocaine infusion) cocaine reinforcement, acute administration of SB-277011A (6–24 mg/kg i.p.) lowered the PR break point for cocaine self-administration in a dose-dependent manner. The reduction in the cocaine (0.25–1.0 mg/kg) dose–response break-point curve produced by 24 mg/kg SB-277011A is consistent with a reduction in cocaine’s reinforcing efficacy. When substituted for cocaine, SB-277011A alone did not sustain self-administration behaviour. In contrast with the mixed DA D2/D3 receptor antagonist haloperidol (1 mg/kg), SB-277011A (3, 12 or 24 mg/kg) failed to impede locomotor activity, failed to impair rearing behaviour, failed to produce catalepsy and failed to impair rotarod performance. These results show that SB-277011A significantly inhibits acute cocaine-induced reinforcement except at high cocaine doses and low work requirement for cocaine. If these results extrapolate to humans, SB-277011A or similar selective DA D3 receptor antagonists may be

  19. Genetic variability in G2 and F2 region between biological clones of human respiratory syncytial virus with or without host immune selection pressure

    Directory of Open Access Journals (Sweden)

    Claudia Trigo Pedroso Moraes

    2015-02-01

    Full Text Available Human respiratory syncytial virus (HRSV is an important respiratory pathogens among children between zero-five years old. Host immunity and viral genetic variability are important factors that can make vaccine production difficult. In this work, differences between biological clones of HRSV were detected in clinical samples in the absence and presence of serum collected from children in the convalescent phase of the illness and from their biological mothers. Viral clones were selected by plaque assay in the absence and presence of serum and nucleotide sequences of the G2 and F2 genes of HRSV biological clones were compared. One non-synonymous mutation was found in the F gene (Ile5Asn in one clone of an HRSV-B sample and one non-synonymous mutation was found in the G gene (Ser291Pro in four clones of the same HRSV-B sample. Only one of these clones was obtained after treatment with the child's serum. In addition, some synonymous mutations were determined in two clones of the HRSV-A samples. In conclusion, it is possible that minor sequences could be selected by host antibodies contributing to the HRSV evolutionary process, hampering the development of an effective vaccine, since we verify the same codon alteration in absence and presence of human sera in individual clones of BR-85 sample.

  20. Genetic variability in G2 and F2 region between biological clones of human respiratory syncytial virus with or without host immune selection pressure.

    Science.gov (United States)

    Moraes, Claudia Trigo Pedroso; Oliveira, Danielle Bruna Leal; Campos, Angelica Cristine Almeida; Bosso, Patricia Alves; Lima, Hildener Nogueira; Stewien, Klaus Eberhard; Gilio, Alfredo Elias; Vieira, Sandra Elisabete; Botosso, Viviane Fongaro; Durigon, Edison Luiz

    2015-02-01

    Human respiratory syncytial virus (HRSV) is an important respiratory pathogens among children between zero-five years old. Host immunity and viral genetic variability are important factors that can make vaccine production difficult. In this work, differences between biological clones of HRSV were detected in clinical samples in the absence and presence of serum collected from children in the convalescent phase of the illness and from their biological mothers. Viral clones were selected by plaque assay in the absence and presence of serum and nucleotide sequences of the G2 and F2 genes of HRSV biological clones were compared. One non-synonymous mutation was found in the F gene (Ile5Asn) in one clone of an HRSV-B sample and one non-synonymous mutation was found in the G gene (Ser291Pro) in four clones of the same HRSV-B sample. Only one of these clones was obtained after treatment with the child's serum. In addition, some synonymous mutations were determined in two clones of the HRSV-A samples. In conclusion, it is possible that minor sequences could be selected by host antibodies contributing to the HRSV evolutionary process, hampering the development of an effective vaccine, since we verify the same codon alteration in absence and presence of human sera in individual clones of BR-85 sample.

  1. AEP's selection of GE Energy's variable frequency transformer (VFT) for their grid interconnection project between the United States and Mexico

    Energy Technology Data Exchange (ETDEWEB)

    Spurlock, M.; O' Keefe, R. [American Electric Power, Gahanna, OH (United States); Kidd, D. [American Electric Power, Tulsa, OK (United States); Larsen, E. [GE Energy, Schenectady, NY (United States); Roedel, J. [GE Energy, Denver, CO (United States); Bodo, R. [GE Energy, Carrolton, TX (United States); Marken, P. [GE Energy, Columbia City, IN (United States)

    2006-07-01

    Variable frequency transformers (VFTs) are controllable, bi-directional transmission devices capable of allowing power transfer between asynchronous networks. The VFT uses a rotary transformer with 3-phase windings on both the rotor and the stator. A motor and drive system is also used to manipulate the rotational position of the rotor in order to control the magnitude and direction of the power flow. The VFT was recently selected by American Electric Power (AEP) for its new asynchronous transmission link between the United States and Mexico. This paper provided details of the feasibility studies conducted to select the technology. Three categories of asynchronous interconnection devices were evaluated: (1) a VFT; (2) a voltage source converter; and (3) a conventional high voltage direct current (HVDC) back-to-back system. Stability performance system studies were conducted for all options. The overall reliability benefits of the options were reviewed, as well as their ability to meet steady-state system requirements. Dynamic models were used to conduct the comparative evaluation. Results of the feasibility study indicated that both the VFT and the voltage source converter performed better than the HVDC system. However, the VFT was more stable than the voltage source converter. 5 refs., 3 figs.

  2. SELECTION OF BURST-LIKE TRANSIENTS AND STOCHASTIC VARIABLES USING MULTI-BAND IMAGE DIFFERENCING IN THE PAN-STARRS1 MEDIUM-DEEP SURVEY

    International Nuclear Information System (INIS)

    Kumar, S.; Gezari, S.; Heinis, S.; Chornock, R.; Berger, E.; Soderberg, A.; Stubbs, C. W.; Kirshner, R. P.; Rest, A.; Huber, M. E.; Narayan, G.; Marion, G. H.; Burgett, W. S.; Foley, R. J.; Scolnic, D.; Riess, A. G.; Lawrence, A.; Smartt, S. J.; Smith, K.; Wood-Vasey, W. M.

    2015-01-01

    We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands g P1 , r P1 , i P1 , and z P1 . We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to

  3. SELECTION OF BURST-LIKE TRANSIENTS AND STOCHASTIC VARIABLES USING MULTI-BAND IMAGE DIFFERENCING IN THE PAN-STARRS1 MEDIUM-DEEP SURVEY

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, S.; Gezari, S.; Heinis, S. [Department of Astronomy, University of Maryland, Stadium Drive, College Park, MD 21224 (United States); Chornock, R.; Berger, E.; Soderberg, A.; Stubbs, C. W.; Kirshner, R. P. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Rest, A. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Huber, M. E.; Narayan, G.; Marion, G. H.; Burgett, W. S. [Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822 (United States); Foley, R. J. [Astronomy Department, University of Illinois at Urbana-Champaign, 1002 West Green Street, Urbana, IL 61801 (United States); Scolnic, D.; Riess, A. G. [Department of Physics and Astronomy, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218 (United States); Lawrence, A. [Institute for Astronomy, University of Edinburgh Scottish Universities Physics Alliance, Royal Observatory, Blackford Hill, Edinburgh EH9 3HJ (United Kingdom); Smartt, S. J.; Smith, K. [Astrophysics Research Centre, School of Mathematics and Physics, Queen' s University Belfast, Belfast BT7 1NN (United Kingdom); Wood-Vasey, W. M. [Pittsburgh Particle Physics, Astrophysics, and Cosmology Center, Department of Physics and Astronomy, University of Pittsburgh, 3941 O' Hara Street, Pittsburgh, PA 15260 (United States); and others

    2015-03-20

    We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands g {sub P1}, r {sub P1}, i {sub P1}, and z {sub P1}. We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host

  4. Improved intact soil-core carbon determination applying regression shrinkage and variable selection techniques to complete spectrum laser-induced breakdown spectroscopy (LIBS).

    Science.gov (United States)

    Bricklemyer, Ross S; Brown, David J; Turk, Philip J; Clegg, Sam M

    2013-10-01

    Laser-induced breakdown spectroscopy (LIBS) provides a potential method for rapid, in situ soil C measurement. In previous research on the application of LIBS to intact soil cores, we hypothesized that ultraviolet (UV) spectrum LIBS (200-300 nm) might not provide sufficient elemental information to reliably discriminate between soil organic C (SOC) and inorganic C (IC). In this study, using a custom complete spectrum (245-925 nm) core-scanning LIBS instrument, we analyzed 60 intact soil cores from six wheat fields. Predictive multi-response partial least squares (PLS2) models using full and reduced spectrum LIBS were compared for directly determining soil total C (TC), IC, and SOC. Two regression shrinkage and variable selection approaches, the least absolute shrinkage and selection operator (LASSO) and sparse multivariate regression with covariance estimation (MRCE), were tested for soil C predictions and the identification of wavelengths important for soil C prediction. Using complete spectrum LIBS for PLS2 modeling reduced the calibration standard error of prediction (SEP) 15 and 19% for TC and IC, respectively, compared to UV spectrum LIBS. The LASSO and MRCE approaches provided significantly improved calibration accuracy and reduced SEP 32-55% over UV spectrum PLS2 models. We conclude that (1) complete spectrum LIBS is superior to UV spectrum LIBS for predicting soil C for intact soil cores without pretreatment; (2) LASSO and MRCE approaches provide improved calibration prediction accuracy over PLS2 but require additional testing with increased soil and target analyte diversity; and (3) measurement errors associated with analyzing intact cores (e.g., sample density and surface roughness) require further study and quantification.

  5. Sperm variables as predictors of fertility in Black Castellana roosters; use in the selection of sperm donors for genome resource banking purposes

    Energy Technology Data Exchange (ETDEWEB)

    Santiago Moreno, J.; Lopez Sebastian, A.; Castano, C.; Coloma, M. A.; Gomez Brunet, A.; Toledano Diaz, A.; Prieto, M. T.; Campo, J. L.

    2009-07-01

    Semen was collected from 10 Black Castellana roosters and the classic sperm variables (ejaculate volume, sperm concentration and sperm motility) examined. In addition, the hypo-osmotic swelling test was used to investigate sperm cell membrane integrity, and acidic aniline blue staining used to screen for morphological abnormalities (including acrosome integrity) and to examine the condensation status of the chromatin. The latter was also examined by Gram staining. Large and small semen volumes were associated high and low sperm concentrations respectively (R2=0.04, P<0.05). The percentage of motile spermatozoa correlated strongly with the percentage of sperm cells showing an intact acrosome (R2=0.13, P<0.001) and with the percentage of morphologically normal spermatozoa (R2=0.04, P<0.05). The percentage of Gram positive spermatozoa was positively correlated with semen appearance (R2=0.12, P<0.05), sperm cell concentration (R2=0.13, P<0.05), and with the sperm motility variables studied (R2=0.14, P<0.05 for percentage mobility, and R2=0.12, P<0.05 for quality of movement). Only three of the 10 roosters, all with fertilisation potentials of 80-90%, were considered potential sperm donors for genome resource banking purposes. The remaining birds were all of low fertility (. 50%); in fact, some produced semen volumes too small to perform fertility tests. Semen volume and membrane integrity were found to be the best variables for predicting the fertilisation potential of rooster ejaculates. (Author) 37 refs.

  6. Bayesian variable selection for multistate Markov models with interval-censored data in an ecological momentary assessment study of smoking cessation.

    Science.gov (United States)

    Koslovsky, Matthew D; Swartz, Michael D; Chan, Wenyaw; Leon-Novelo, Luis; Wilkinson, Anna V; Kendzor, Darla E; Businelle, Michael S

    2017-10-11

    The application of sophisticated analytical methods to intensive longitudinal data, collected with ecological momentary assessments (EMA), has helped researchers better understand smoking behaviors after a quit attempt. Unfortunately, the wealth of information captured with EMAs is typically underutilized in practice. Thus, novel methods are needed to extract this information in exploratory research studies. One of the main objectives of intensive longitudinal data analysis is identifying relations between risk factors and outcomes of interest. Our goal is to develop and apply expectation maximization variable selection for Bayesian multistate Markov models with interval-censored data to generate new insights into the relation between potential risk factors and transitions between smoking states. Through simulation, we demonstrate the effectiveness of our method in identifying associated risk factors and its ability to outperform the LASSO in a special case. Additionally, we use the expectation conditional-maximization algorithm to simplify estimation, a deterministic annealing variant to reduce the algorithm's dependence on starting values, and Louis's method to estimate unknown parameter uncertainty. We then apply our method to intensive longitudinal data collected with EMA to identify risk factors associated with transitions between smoking states after a quit attempt in a cohort of socioeconomically disadvantaged smokers who were interested in quitting. © 2017, The International Biometric Society.

  7. Diagnostic screening identifies a wide range of mutations involving the SHOX gene, including a common 47.5 kb deletion 160 kb downstream with a variable phenotypic effect.

    Science.gov (United States)

    Bunyan, David J; Baker, Kevin R; Harvey, John F; Thomas, N Simon

    2013-06-01

    Léri-Weill dyschondrosteosis (LWD) results from heterozygous mutations of the SHOX gene, with homozygosity or compound heterozygosity resulting in the more severe form, Langer mesomelic dysplasia (LMD). These mutations typically take the form of whole or partial gene deletions, point mutations within the coding sequence, or large (>100 kb) 3' deletions of downstream regulatory elements. We have analyzed the coding sequence of the SHOX gene and its downstream regulatory regions in a cohort of 377 individuals referred with symptoms of LWD, LMD or short stature. A causative mutation was identified in 68% of the probands with LWD or LMD (91/134). In addition, a 47.5 kb deletion was found 160 kb downstream of the SHOX gene in 17 of the 377 patients (12% of the LWD referrals, 4.5% of all referrals). In 14 of these 17 patients, this was the only potentially causative abnormality detected (13 had symptoms consistent with LWD and one had short stature only), but the other three 47.5 kb deletions were found in patients with an additional causative SHOX mutation (with symptoms of LWD rather than LMD). Parental samples were available on 14/17 of these families, and analysis of these showed a more variable phenotype ranging from apparently unaffected to LWD. Breakpoint sequence analysis has shown that the 47.5 kb deletion is identical in all 17 patients, most likely due to an ancient founder mutation rather than recurrence. This deletion was not seen in 471 normal controls (P<0.0001), providing further evidence for a phenotypic effect, albeit one with variable penetration. Copyright © 2013 Wiley Periodicals, Inc.

  8. HLA-A and -B alleles and haplotypes in 240 index patients with common variable immunodeficiency and selective IgG subclass deficiency in central Alabama

    Directory of Open Access Journals (Sweden)

    Barton James C

    2003-06-01

    Full Text Available Abstract Background We wanted to quantify HLA-A and -B phenotype and haplotype frequencies in Alabama index patients with common variable immunodeficiency (CVID and selective IgG subclass deficiency (IgGSD, and in control subjects. Methods Phenotypes were detected using DNA-based typing (index cases and microlymphocytotoxicity typing (controls. Results A and B phenotypes were determined in 240 index cases (114 CVID, 126 IgGSD and 1,321 controls and haplotypes in 195 index cases and 751 controls. Phenotyping revealed that the "uncorrected" frequencies of A*24, B*14, B*15, B*35, B*40, B*49, and B*50 were significantly greater in index cases, and frequencies of B*35, B*58, B*62 were significantly lower in index cases. After Bonferroni corrections, the frequencies of phenotypes A*24, B*14, and B*40 were significantly greater in index cases, and the frequency of B*62 was significantly lower in index cases. The most common haplotypes in index cases were A*02-B*44 (frequency 0.1385, A*01-B*08 (frequency 0.1308, and A*03-B*07 (frequency 0.1000, and the frequency of each was significantly greater in index cases than in control subjects ("uncorrected" values of p p p = 0.0166. Most phenotype and haplotype frequencies in CVID and IgGSD were similar. 26.7% of index patients were HLA-haploidentical with one or more other index patients. We diagnosed CVID or IgGSD in first-degree or other relatives of 26 of 195 index patients for whom HLA-A and -B haplotypes had been ascertained; A*01-B*08, A*02-B*44, and A*29-B*44 were most frequently associated with CVID or IgGSD in these families. We conservatively estimated the combined population frequency of CVID and IgGSD to be 0.0092 in adults, based on the occurrence of CVID and IgGSD in spouses of the index cases. Conclusions CVID and IgGSD in adults are significantly associated with several HLA haplotypes, many of which are also common in the Alabama Caucasian population. Immunoglobulin phenotype variability

  9. Evaluation of Diversity Based on Morphological Variabilities and ISSR Molecular Markers in Iranian Cynodon dactylon (L.) Pers. Accessions to Select and Introduce Cold-Tolerant Genotypes.

    Science.gov (United States)

    Akbari, M; Salehi, H; Niazi, A

    2018-04-01

    The main goals of the present study were to screen Iranian common bermudagrasses to find cold-tolerant accessions and evaluate their genetic and morphological variabilities. In this study, 49 accessions were collected from 18 provinces of Iran. One foreign cultivar of common bermudagrass was used as control. Morphological variation was evaluated based on 14 morphological traits to give information about taxonomic position of Iranian common bermudagrass. Data from morphological traits were evaluated to categorize all accessions as either cold sensitive or tolerant using hierarchical clustering with Ward's method in SPSS software. Inter-Simple Sequence Repeat (ISSR) primers were employed to evaluate genetic variability of accessions. The results of our taxonomic investigation support the existence of two varieties of Cynodon dactylon in Iran: var. dactylon (hairless plant) and var. villosous (plant with hairs at leaf underside and/or upper side surfaces or exterior surfaces of sheath). All 15 primers amplified and gave clear and highly reproducible DNA fragments. In total, 152 fragments were produced, of which 144 (94.73%) being polymorphic. The polymorphic information content (PIC) values ranged from 0.700 to 0.928. The average PIC value obtained with 15 ISSR primers was 0.800, which shows that all primers were informative. Probability identity (PI) and discriminating power between all primers ranged from 0.029 to 0.185 and 0.815 to 0.971, respectively. Genetic data were converted into a binary data matrix. NTSYS software was used for data analysis. Clustering was done by the unweighted pair-group method with arithmetic averages and principle coordinate analysis, separated the accessions into six main clusters. According to both morphological and genetic diversity investigations of accessions, they can be clustered into three groups: cold sensitive, cold semi-tolerant, and cold tolerant. The most cold-tolerant accessions were: Taft, Malayear, Gorgan, Safashahr

  10. Age-related change in renal corticomedullary differentiation: evaluation with noncontrast-enhanced steady-state free precession (SSFP) MRI with spatially selective inversion pulse using variable inversion time.

    Science.gov (United States)

    Noda, Yasufumi; Kanki, Akihiko; Yamamoto, Akira; Higashi, Hiroki; Tanimoto, Daigo; Sato, Tomohiro; Higaki, Atsushi; Tamada, Tsutomu; Ito, Katsuyoshi

    2014-07-01

    To evaluate age-related change in renal corticomedullary differentiation and renal cortical thickness by means of noncontrast-enhanced steady-state free precession (SSFP) magnetic resonance imaging (MRI) with spatially selective inversion recovery (IR) pulse. The Institutional Review Board of our hospital approved this retrospective study and patient informed consent was waived. This study included 48 patients without renal diseases who underwent noncontrast-enhanced SSFP MRI with spatially selective IR pulse using variable inversion times (TIs) (700-1500 msec). The signal intensity of renal cortex and medulla were measured to calculate renal corticomedullary contrast ratio. Additionally, renal cortical thickness was measured. The renal corticomedullary junction was clearly depicted in all patients. The mean cortical thickness was 3.9 ± 0.83 mm. The mean corticomedullary contrast ratio was 4.7 ± 1.4. There was a negative correlation between optimal TI for the best visualization of renal corticomedullary differentiation and age (r = -0.378; P = 0.001). However, there was no significant correlation between renal corticomedullary contrast ratio and age (r = 0.187; P = 0.20). Similarly, no significant correlation was observed between renal cortical thickness and age (r = 0.054; P = 0.712). In the normal kidney, noncontrast-enhanced SSFP MRI with spatially selective IR pulse can be used to assess renal corticomedullary differentiation and cortical thickness without the influence of aging, although optimal TI values for the best visualization of renal corticomedullary junction were shortened with aging. © 2013 Wiley Periodicals, Inc.

  11. Does basal metabolic rate contain a useful signal? Mammalian BMR allometry and correlations with a selection of physiological, ecological, and life-history variables.

    Science.gov (United States)

    White, Craig R; Seymour, Roger S

    2004-01-01

    Basal metabolic rate (BMR, mL O2 h(-1)) is a useful measurement only if standard conditions are realised. We present an analysis of the relationship between mammalian body mass (M, g) and BMR that accounts for variation associated with body temperature, digestive state, and phylogeny. In contrast to the established paradigm that BMR proportional to M3/4, data from 619 species, representing 19 mammalian orders and encompassing five orders of magnitude variation in M, show that BMR proportional to M2/3. If variation associated with body temperature and digestive state are removed, the BMRs of eutherians, marsupials, and birds do not differ, and no significant allometric exponent heterogeneity remains between orders. The usefulness of BMR as a general measurement is supported by the observation that after the removal of body mass effects, the residuals of BMR are significantly correlated with the residuals for a variety of physiological and ecological variables, including maximum metabolic rate, field metabolic rate, resting heart rate, life span, litter size, and population density.

  12. Survival time and effect of selected predictor variables on survival in owned pet cats seropositive for feline immunodeficiency and leukemia virus attending a referral clinic in northern Italy.

    Science.gov (United States)

    Spada, Eva; Perego, Roberta; Sgamma, Elena Assunta; Proverbio, Daniela

    2018-02-01

    Feline immunodeficiency virus (FIV) and feline leukemia virus (FeLV) are among the most important feline infectious diseases worldwide. This retrospective study investigated survival times and effects of selected predictor factors on survival time in a population of owned pet cats in Northern Italy testing positive for the presence of FIV antibodies and FeLV antigen. One hundred and three retrovirus-seropositive cats, 53 FIV-seropositive cats, 40 FeLV-seropositive cats, and 10 FIV+FeLV-seropositive cats were included in the study. A population of 103 retrovirus-seronegative age and sex-matched cats was selected. Survival time was calculated and compared between retrovirus-seronegative, FIV, FeLV and FIV+FeLV-seropositive cats using Kaplan-Meier survival analysis. Cox proportional-hazards regression analysis was used to study the effect of selected predictor factors (male gender, peripheral blood cytopenia as reduced red blood cells - RBC- count, leukopenia, neutropenia and lymphopenia, hypercreatininemia and reduced albumin to globulin ratio) on survival time in retrovirus-seropositive populations. Median survival times for seronegative cats, FIV, FeLV and FIV+FeLV-seropositive cats were 3960, 2040, 714 and 77days, respectively. Compared to retrovirus-seronegative cats median survival time was significantly lower (P<0.000) in FeLV and FIV+FeLV-seropositive cats. Median survival time in FeLV and FIV+FeLV-seropositive cats was also significant lower (P<0.000) when compared to FIV-seropositive cats. Hazard ratio of death in FeLV and FIV+FeLV-seropositive cats being respectively 3.4 and 7.4 times higher, in comparison to seronegative cats and 2.3 and 4.8 times higher in FeLV and FIV+FeLV-seropositive cats as compared to FIV-seropositive cats. A Cox proportional-hazards regression analysis showed that FIV and FeLV-seropositive cats with reduced RBC counts at time of diagnosis of seropositivity had significantly shorter survival times when compared to FIV and Fe

  13. Quantification of glutathione transverse relaxation time T2 using echo time extension with variable refocusing selectivity and symmetry in the human brain at 7 Tesla

    Science.gov (United States)

    Swanberg, Kelley M.; Prinsen, Hetty; Coman, Daniel; de Graaf, Robin A.; Juchem, Christoph

    2018-05-01

    Glutathione (GSH) is an endogenous antioxidant implicated in numerous biological processes, including those associated with multiple sclerosis, aging, and cancer. Spectral editing techniques have greatly facilitated the acquisition of glutathione signal in living humans via proton magnetic resonance spectroscopy, but signal quantification at 7 Tesla is still hampered by uncertainty about the glutathione transverse decay rate T2 relative to those of commonly employed quantitative references like N-acetyl aspartate (NAA), total creatine, or water. While the T2 of uncoupled singlets can be derived in a straightforward manner from exponential signal decay as a function of echo time, similar estimation of signal decay in GSH is complicated by a spin system that involves both weak and strong J-couplings as well as resonances that overlap those of several other metabolites and macromolecules. Here, we extend a previously published method for quantifying the T2 of GABA, a weakly coupled system, to quantify T2 of the strongly coupled spin system glutathione in the human brain at 7 Tesla. Using full density matrix simulation of glutathione signal behavior, we selected an array of eight optimized echo times between 72 and 322 ms for glutathione signal acquisition by J-difference editing (JDE). We varied the selectivity and symmetry parameters of the inversion pulses used for echo time extension to further optimize the intensity, simplicity, and distinctiveness of glutathione signals at chosen echo times. Pairs of selective adiabatic inversion pulses replaced nonselective pulses at three extended echo times, and symmetry of the time intervals between the two extension pulses was adjusted at one extended echo time to compensate for J-modulation, thereby resulting in appreciable signal-to-noise ratio and quantifiable signal shapes at all measured points. Glutathione signal across all echo times fit smooth monoexponential curves over ten scans of occipital cortex voxels in nine

  14. Quantifying human disturbance in watersheds: Variable selection and performance of a GIS-based disturbance index for predicting the biological condition of perennial streams

    Science.gov (United States)

    Falcone, James A.; Carlisle, Daren M.; Weber, Lisa C.

    2010-01-01

    Characterizing the relative severity of human disturbance in watersheds is often part of stream assessments and is frequently done with the aid of Geographic Information System (GIS)-derived data. However, the choice of variables and how they are used to quantify disturbance are often subjective. In this study, we developed a number of disturbance indices by testing sets of variables, scoring methods, and weightings of 33 potential disturbance factors derived from readily available GIS data. The indices were calibrated using 770 watersheds located in the western United States for which the severity of disturbance had previously been classified from detailed local data by the United States Environmental Protection Agency (USEPA) Environmental Monitoring and Assessment Program (EMAP). The indices were calibrated by determining which variable or variable combinations and aggregation method best differentiated between least- and most-disturbed sites. Indices composed of several variables performed better than any individual variable, and best results came from a threshold method of scoring using six uncorrelated variables: housing unit density, road density, pesticide application, dam storage, land cover along a mainstem buffer, and distance to nearest canal/pipeline. The final index was validated with 192 withheld watersheds and correctly classified about two-thirds (68%) of least- and most-disturbed sites. These results provide information about the potential for using a disturbance index as a screening tool for a priori ranking of watersheds at a regional/national scale, and which landscape variables and methods of combination may be most helpful in doing so.

  15. Response rates and selection problems, with emphasis on mental health variables and DNA sampling, in large population-based, cross-sectional and longitudinal studies of adolescents in Norway

    Directory of Open Access Journals (Sweden)

    Lien Lars

    2010-10-01

    Full Text Available Abstract Background Selection bias is a threat to the internal validity of epidemiological studies. In light of a growing number of studies which aim to provide DNA, as well as a considerable number of invitees who declined to participate, we discuss response rates, predictors of lost to follow-up and failure to provide DNA, and the presence of possible selection bias, based on five samples of adolescents. Methods We included nearly 7,000 adolescents from two longitudinal studies of 18/19 year olds with two corresponding cross-sectional baseline studies at age 15/16 (10th graders, and one cross-sectional study of 13th graders (18/19 years old. DNA was sampled from the cheek mucosa of 18/19 year olds. Predictors of lost to follow-up and failure to provide DNA were studied by Poisson regression. Selection bias in the follow-up at age 18/19 was estimated through investigation of prevalence ratios (PRs between selected exposures (physical activity, smoking and outcome variables (general health, mental distress, externalizing problems measured at baseline. Results Out of 5,750 who participated at age 15/16, we lost 42% at follow-up at age 18/19. The percentage of participants who gave their consent to DNA provision was as high as the percentage that consented to a linkage of data with other health registers and surveys, approximately 90%. Significant predictors of lost to follow-up and failure to provide DNA samples in the present genetic epidemiological study were: male gender; non-western ethnicity; postal survey compared with school-based; low educational plans; low education and income of father; low perceived family economy; unmarried parents; poor self-reported health; externalized symptoms and smoking, with some differences in subgroups of ethnicity and gender. The association measures (PRs were quite similar among participants and all invitees, with some minor discrepancies in subgroups of non-western boys and girls. Conclusions Lost to

  16. Response rates and selection problems, with emphasis on mental health variables and DNA sampling, in large population-based, cross-sectional and longitudinal studies of adolescents in Norway.

    Science.gov (United States)

    Bjertness, Espen; Sagatun, Ase; Green, Kristian; Lien, Lars; Søgaard, Anne Johanne; Selmer, Randi

    2010-10-12

    Selection bias is a threat to the internal validity of epidemiological studies. In light of a growing number of studies which aim to provide DNA, as well as a considerable number of invitees who declined to participate, we discuss response rates, predictors of lost to follow-up and failure to provide DNA, and the presence of possible selection bias, based on five samples of adolescents. We included nearly 7,000 adolescents from two longitudinal studies of 18/19 year olds with two corresponding cross-sectional baseline studies at age 15/16 (10th graders), and one cross-sectional study of 13th graders (18/19 years old). DNA was sampled from the cheek mucosa of 18/19 year olds. Predictors of lost to follow-up and failure to provide DNA were studied by Poisson regression. Selection bias in the follow-up at age 18/19 was estimated through investigation of prevalence ratios (PRs) between selected exposures (physical activity, smoking) and outcome variables (general health, mental distress, externalizing problems) measured at baseline. Out of 5,750 who participated at age 15/16, we lost 42% at follow-up at age 18/19. The percentage of participants who gave their consent to DNA provision was as high as the percentage that consented to a linkage of data with other health registers and surveys, approximately 90%. Significant predictors of lost to follow-up and failure to provide DNA samples in the present genetic epidemiological study were: male gender; non-western ethnicity; postal survey compared with school-based; low educational plans; low education and income of father; low perceived family economy; unmarried parents; poor self-reported health; externalized symptoms and smoking, with some differences in subgroups of ethnicity and gender. The association measures (PRs) were quite similar among participants and all invitees, with some minor discrepancies in subgroups of non-western boys and girls. Lost to follow-up had marginal impact on the estimated prevalence ratios

  17. Variability of wind stress and currents at selected locations over the north Indian Ocean during 1977 and 1979 summer monsoon seasons

    Digital Repository Service at National Institute of Oceanography (India)

    Gopalakrishna, V.V.; Sadhuram, Y.; RameshBabu, V.; Rao, M.V.

    Intra-seasonal variability of wind stress, wind stress curl and currents at different locations over the northern Indian Ocean during two contrasting monsoon seasons has been investigated making use of the time series data collected during MONSOON...

  18. Variable Cycle Intake for Reverse Core Engine

    Science.gov (United States)

    Suciu, Gabriel L (Inventor); Chandler, Jesse M (Inventor); Staubach, Joseph B (Inventor)

    2016-01-01

    A gas generator for a reverse core engine propulsion system has a variable cycle intake for the gas generator, which variable cycle intake includes a duct system. The duct system is configured for being selectively disposed in a first position and a second position, wherein free stream air is fed to the gas generator when in the first position, and fan stream air is fed to the gas generator when in the second position.

  19. Trends of ozone and O{sub x} in Switzerland from 1992 to 2007: observations at selected stations of the NABEL, OASI (Ticino) and ANU (Graubuenden) networks corrected for meteorological variability. Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Keller, J.; Prevot, A. [Paul Scherrer Institut (PSI), Laboratory of Atmospheric Chemistry (LAC), Villigen (Switzerland); Beguin, A.F. [Swiss Federal Institute of Technology, Institute for Atmospheric and Climate Science (IAC), Zuerich (Switzerland); Jutzi, V. [Vincent Jutzi, Lausanne (Switzerland); Ordonez, C. [Met Office, Exeter EX1 3PB (United Kingdom)

    2008-11-15

    Long-term changes of ozone concentrations are influenced by a variety of quantities, in particular meteorological variables and emissions. In order to evaluate the contributions of regional emissions and of the background concentration to changes in observed ozone levels, the variability due to meteorology has to be removed. Ordonez et al. (2005) investigated the temporal evolution of tropospheric ozone over the Swiss Plateau using meteorological and air quality measurements taken at stations of the Swiss air quality networks NABEL and OSTLUFT. Time period was 1992 to 2002 including a discussion of the heat wave in summer 2003. The air quality measurements were corrected for meteorological influences on the basis of a multi-linear model approach. Despite the emission abatement measures of the last decades no significant decrease in ozone levels was observed. Air quality stations south of the Alps, which often act as a barrier for air mass exchange between south and north, were not included in the investigation. This study (a) includes all NABEL stations, (b) considers also southern air quality stations of the cantons Ticino (OASI) and Graubuenden (ANU), and (c) extends the time frame until 2007. The methodology of correcting ozone and O{sub x} = O{sub 3} + NO{sub 2} for meteorological variability is based on the ANalysis of COVAriance (ANCOVA). This approach assumes that the mixing ratios of O{sub 3} and O{sub x} are multi-linear functions of selected meteorological quantities. The analysis is performed using the statistics package R, which supports the dependence on continuous variables (e.g. air temperature) as well as on discrete quantities (e.g. wind direction expressed in terms of discrete wind direction sectors). The following daily values of each station are considered in the analysis (examples): (i) Meteorological variables (averages): afternoon temperature, morning global irradiance, afternoon wind speed, etc. If no co-located meteorological data are

  20. Trends of ozone and Ox in Switzerland from 1992 to 2007: observations at selected stations of the NABEL, OASI (Ticino) and ANU (Graubuenden) networks corrected for meteorological variability. Final Report

    International Nuclear Information System (INIS)

    Keller, J.; Prevot, A.; Beguin, A.F.; Jutzi, V.; Ordonez, C.

    2008-11-01

    Long-term changes of ozone concentrations are influenced by a variety of quantities, in particular meteorological variables and emissions. In order to evaluate the contributions of regional emissions and of the background concentration to changes in observed ozone levels, the variability due to meteorology has to be removed. Ordonez et al. (2005) investigated the temporal evolution of tropospheric ozone over the Swiss Plateau using meteorological and air quality measurements taken at stations of the Swiss air quality networks NABEL and OSTLUFT. Time period was 1992 to 2002 including a discussion of the heat wave in summer 2003. The air quality measurements were corrected for meteorological influences on the basis of a multi-linear model approach. Despite the emission abatement measures of the last decades no significant decrease in ozone levels was observed. Air quality stations south of the Alps, which often act as a barrier for air mass exchange between south and north, were not included in the investigation. This study (a) includes all NABEL stations, (b) considers also southern air quality stations of the cantons Ticino (OASI) and Graubuenden (ANU), and (c) extends the time frame until 2007. The methodology of correcting ozone and O x = O 3 + NO 2 for meteorological variability is based on the ANalysis of COVAriance (ANCOVA). This approach assumes that the mixing ratios of O 3 and O x are multi-linear functions of selected meteorological quantities. The analysis is performed using the statistics package R, which supports the dependence on continuous variables (e.g. air temperature) as well as on discrete quantities (e.g. wind direction expressed in terms of discrete wind direction sectors). The following daily values of each station are considered in the analysis (examples): (i) Meteorological variables (averages): afternoon temperature, morning global irradiance, afternoon wind speed, etc. If no co-located meteorological data are available, data of the closest

  1. QSRR modeling for the chromatographic retention behavior of some β-lactam antibiotics using forward and firefly variable selection algorithms coupled with multiple linear regression.

    Science.gov (United States)

    Fouad, Marwa A; Tolba, Enas H; El-Shal, Manal A; El Kerdawy, Ahmed M

    2018-05-11

    The justified continuous emerging of new β-lactam antibiotics provokes the need for developing suitable analytical methods that accelerate and facilitate their analysis. A face central composite experimental design was adopted using different levels of phosphate buffer pH, acetonitrile percentage at zero time and after 15 min in a gradient program to obtain the optimum chromatographic conditions for the elution of 31 β-lactam antibiotics. Retention factors were used as the target property to build two QSRR models utilizing the conventional forward selection and the advanced nature-inspired firefly algorithm for descriptor selection, coupled with multiple linear regression. The obtained models showed high performance in both internal and external validation indicating their robustness and predictive ability. Williams-Hotelling test and student's t-test showed that there is no statistical significant difference between the models' results. Y-randomization validation showed that the obtained models are due to significant correlation between the selected molecular descriptors and the analytes' chromatographic retention. These results indicate that the generated FS-MLR and FFA-MLR models are showing comparable quality on both the training and validation levels. They also gave comparable information about the molecular features that influence the retention behavior of β-lactams under the current chromatographic conditions. We can conclude that in some cases simple conventional feature selection algorithm can be used to generate robust and predictive models comparable to that are generated using advanced ones. Copyright © 2018 Elsevier B.V. All rights reserved.

  2. IRAS variables as galactic structure tracers - Classification of the bright variables

    Science.gov (United States)

    Allen, L. E.; Kleinmann, S. G.; Weinberg, M. D.

    1993-01-01

    The characteristics of the 'bright infrared variables' (BIRVs), a sample consisting of the 300 brightest stars in the IRAS Point Source Catalog with IRAS variability index VAR of 98 or greater, are investigated with the purpose of establishing which of IRAS variables are AGB stars (e.g., oxygen-rich Miras and carbon stars, as was assumed by Weinberg (1992)). Results of the analysis of optical, infrared, and microwave spectroscopy of these stars indicate that, out of 88 stars in the BIRV sample identified with cataloged variables, 86 can be classified as Miras. Results of a similar analysis performed for a color-selected sample of stars, using the color limits employed by Habing (1988) to select AGB stars, showed that, out of 52 percent of classified stars, 38 percent are non-AGB stars, including H II regions, planetary nebulae, supergiants, and young stellar objects, indicating that studies using color-selected samples are subject to misinterpretation.

  3. A Flow System for Generation of Concentration Perturbation in Two-Dimensional Correlation Near-Infrared Spectroscopy: Application to Variable Selection in Multivariate Calibration

    OpenAIRE

    Pereira, CF; Pasquini, C

    2010-01-01

    A flow system is proposed to produce a concentration perturbation in liquid samples, aiming at the generation of two-dimensional correlation near-infrared spectra. The system presents advantages in relation to batch systems employed for the same purpose: the experiments are accomplished in a closed system; application of perturbation is rapid and easy; and the experiments can be carried out with micro-scale volumes. The perturbation system has been evaluated in the investigation and selection...

  4. Variations in selected water quality variables and metal concentrations in the sediment of the lower Olifants and Selati rivers, South Africa

    Directory of Open Access Journals (Sweden)

    T. Seymore

    1994-08-01

    Full Text Available A survey of the water and sediment quality of the lower Olifants River and lower Selati River was carried out. Metal concentrations (Cr, Cu, Fe, Mn, Ni, Pb, Sr and Zn in the water and sediment, as well as the physical and chemical characteristics of the water were determined over a two-year period (April 1990 - February 1992. The water quality of the lower Selati River, which flows through the Phalaborwa area, was found to be influenced by the mining and industrial activities in the area. It was also the case with the lower Olifants River after the Selati-Olifants confluence, although the concentrations of most variables did decrease from the western side of the Kruger National Park to the eastern side due to dilution of the water by tributaries of the Olifants River. Variables of special concern were sodium, fluoride. chloride, sulphate, potassium, the total dissolved salts and the metal concentrations (except strontium. The water quality of the Selati River in the study area is a great cause of concern and a further degradation thereof cannot be afforded.

  5. Determination of the effects of fine-grained sediment and other limiting variables on trout habitat for selected streams in Wisconsin

    Science.gov (United States)

    Scudder, Barbara C.; Selbig, J.W.; Waschbusch, R.J.

    2000-01-01

    Two Habitat Suitability Index (HSI) models, developed by the U.S. Fish and Wildlife Service, were used to evaluate the effects of fine-grained (less than 2 millimeters) sediment on brook trout (Salvelinusfontinalis, Mitchill) and brown trout (Salmo trutta, Linnaeus) in 11 streams in west-central and southwestern Wisconsin. Our results indicated that fine-grained sediment limited brook trout habitat in 8 of 11 streams and brown trout habitat in only one stream. Lack of winter and escape cover for fry was the primary limiting variable for brown trout at 61 percent of the sites, and this factor also limited brook trout at several stations. Pool area or quality, in stream cover, streambank vegetation for erosion control, minimum flow, thalweg depth maximum, water temperature, spawning substrate, riffle dominant substrate, and dissolved oxygen also were limiting to trout in the study streams. Brook trout appeared to be more sensitive to the effects of fine-grained sediment than brown trout. The models for brook trout and brown trout appeared to be useful and objective screening tools for identifying variables limiting trout habitat in these streams. The models predicted that reduction in the amount of fine-grained sediment would improve brook trout habitat. These models may be valuable for establishing instream sediment-reduction goals; however, the decrease in sediment delivery needed to meet these goals cannot be estimated without quantitative data on land use practices and their effects on sediment delivery and retention by streams.

  6. VARIABILITY OF LENGTH OF STEM OF DETERMINATE AND INDETERMINATE CULTIVARS OF COMMON VETCH (VICIA SATIVA L. SSP. SATIVA AND ITS IMPACT ON SELECTED CROPPING FEATURES

    Directory of Open Access Journals (Sweden)

    Jadwiga ANDRZEJEWSKA

    2006-12-01

    Full Text Available In the years 2001 and 2002, the study was conducted in six experiments in order to examine the conditioning of the length of stem variability and its impact on cropping features of determinate and indeterminate cultivars of common vetch. Rainfall in June and July as well as during the whole growing season was positively correlated with length of stem, but negatively correlated with seed yield, to a larger extent in the group of indeterminate cultivars than in the determinate one. Duration of blooming stage, length of stem, and seed yield showed the largest variability in both groups. Increase in length of stem of plants of indeterminate cultivars led to the delay in maturation, to less even maturation, and to the decrease in the thousand seed weight and seed yield. Increase in length of stem of plants of determinate cultivars delayed reaching the phase of technical maturation and decreased evenness of plant maturation. Determinate growth of common vetch did not lead to the reduction of lodging.

  7. Evaluation of the impact of explanatory variables on the accuracy of prediction of daily inflow to the sewage treatment plant by selected models nonlinear

    Directory of Open Access Journals (Sweden)

    Szeląg Bartosz

    2017-09-01

    Full Text Available The aim of the study was to evaluate the possibility of applying different methods of data mining to model the inflow of sewage into the municipal sewage treatment plant. Prediction models were elaborated using methods of support vector machines (SVM, random forests (RF, k-nearest neighbour (k-NN and of Kernel regression (K. Data consisted of the time series of daily rainfalls, water level measurements in the clarified sewage recipient and the wastewater inflow into the Rzeszow city plant. Results indicate that the best models with one input delayed by 1 day were obtained using the k-NN method while the worst with the K method. For the models with two input variables and one explanatory one the smallest errors were obtained if model inputs were sewage inflow and rainfall data delayed by 1 day and the best fit is provided using RF method while the worst with the K method. In the case of models with three inputs and two explanatory variables, the best results were reported for the SVM and the worst for the K method. In the most of the modelling runs the smallest prediction errors are obtained using the SVM method and the biggest ones with the K method. In the case of the simplest model with one input delayed by 1 day the best results are provided using k-NN method and by the models with two inputs in two modelling runs the RF method appeared as the best.

  8. Geostatistical interpolation model selection based on ArcGIS and spatio-temporal variability analysis of groundwater level in piedmont plains, northwest China.

    Science.gov (United States)

    Xiao, Yong; Gu, Xiaomin; Yin, Shiyang; Shao, Jingli; Cui, Yali; Zhang, Qiulan; Niu, Yong

    2016-01-01

    Based on the geo-statistical theory and ArcGIS geo-statistical module, datas of 30 groundwater level observation wells were used to estimate the decline of groundwater level in Beijing piedmont. Seven different interpolation methods (inverse distance weighted interpolation, global polynomial interpolation, local polynomial interpolation, tension spline interpolation, ordinary Kriging interpolation, simple Kriging interpolation and universal Kriging interpolation) were used for interpolating groundwater level between 2001 and 2013. Cross-validation, absolute error and coefficient of determination (R(2)) was applied to evaluate the accuracy of different methods. The result shows that simple Kriging method gave the best fit. The analysis of spatial and temporal variability suggest that the nugget effects from 2001 to 2013 were increasing, which means the spatial correlation weakened gradually under the influence of human activities. The spatial variability in the middle areas of the alluvial-proluvial fan is relatively higher than area in top and bottom. Since the changes of the land use, groundwater level also has a temporal variation, the average decline rate of groundwater level between 2007 and 2013 increases compared with 2001-2006. Urban development and population growth cause over-exploitation of residential and industrial areas. The decline rate of the groundwater level in residential, industrial and river areas is relatively high, while the decreasing of farmland area and development of water-saving irrigation reduce the quantity of water using by agriculture and decline rate of groundwater level in agricultural area is not significant.

  9. New seismograph includes filters

    Energy Technology Data Exchange (ETDEWEB)

    1979-11-02

    The new Nimbus ES-1210 multichannel signal enhancement seismograph from EG and G geometrics has recently been redesigned to include multimode signal fillers on each amplifier. The ES-1210F is a shallow exploration seismograph for near subsurface exploration such as in depth-to-bedrock, geological hazard location, mineral exploration, and landslide investigations.

  10. The selective treatment of clinical mastitis based on on-farm culture results: II. Effects on lactation performance, including clinical mastitis recurrence, somatic cell count, milk production, and cow survival.

    Science.gov (United States)

    Lago, A; Godden, S M; Bey, R; Ruegg, P L; Leslie, K

    2011-09-01

    The objective of this multi-state, multi-herd clinical trial was to report on the efficacy of using an on-farm culture system to guide strategic treatment decisions in cows with clinical mastitis. The study was conducted in 8 commercial dairy farms ranging in size from 144 to 1,795 cows from Minnesota, Wisconsin, and Ontario, Canada. A total of 422 cows affected with mild or moderate clinical mastitis in 449 quarters were randomly assigned to either (1) a positive-control treatment program or (2) an on-farm culture-based treatment program. Quarter cases assigned to the positive-control group received immediate on-label intramammary treatment with cephapirin sodium. Quarters assigned to the culture-based treatment program were not treated until the results of on-farm culture were determined after 18 to 24h of incubation. Quarters in the culture-based treatment program that had gram-positive growth or a mixed infection were treated according to label instruction using intramammary cephapirin sodium. Quarters assigned to the culture-based treatment program that had gram-negative or no-growth did not receive intramammary therapy. It was already reported in a companion paper that the selective treatment of clinical mastitis based on on-farm culture results decreases antibiotic use by half and tends to decrease milk withholding time without affecting short-term clinical and bacteriological outcomes. The present article reports on long-term outcomes of the aforementioned study. No statistically significant differences existed between cases assigned to the positive-control program and cases assigned to the culture-based treatment program in risk and days for recurrence of clinical mastitis in the same quarter (35% and 78 d vs. 43% and 82 d), linear somatic cell count (4.2 vs. 4.4), daily milk production (30.0 vs. 30.7 kg), and risk and days for culling or death events (28% and 160 d vs. 32% and 137 d) for the rest of the lactation after enrollment of the clinical mastitis

  11. Variable cycle engine

    Energy Technology Data Exchange (ETDEWEB)

    Adamson, A.P.; Sprunger, E.V.

    1980-09-16

    A variable cycle turboshaft engine includes a remote fan system and respective high and low pressure systems for selectively driving the fan system in such a manner as to provide VTOL takeoff capability and minimum specific fuel consumption (SFC) at cruise and loiter conditions. For takeoff the fan system is primarily driven by the relatively large low pressure system whose combustor receives the motive fluid from a core bypass duct and, for cruise and loiter conditions, the fan system is driven by both a relatively small high pressure core and the low pressure system with its combustor inoperative. A mixer is disposed downstream of the high pressure system for mixing the relatively cold air from the bypass duct and the relatively hot air from the core prior to its flow to the low pressure turbine.

  12. Variability Bugs:

    DEFF Research Database (Denmark)

    Melo, Jean

    . Although many researchers suggest that preprocessor-based variability amplifies maintenance problems, there is little to no hard evidence on how actually variability affects programs and programmers. Specifically, how does variability affect programmers during maintenance tasks (bug finding in particular......)? How much harder is it to debug a program as variability increases? How do developers debug programs with variability? In what ways does variability affect bugs? In this Ph.D. thesis, I set off to address such issues through different perspectives using empirical research (based on controlled...... experiments) in order to understand quantitatively and qualitatively the impact of variability on programmers at bug finding and on buggy programs. From the program (and bug) perspective, the results show that variability is ubiquitous. There appears to be no specific nature of variability bugs that could...

  13. Analytic device including nanostructures

    KAUST Repository

    Di Fabrizio, Enzo M.; Fratalocchi, Andrea; Totero Gongora, Juan Sebastian; Coluccio, Maria Laura; Candeloro, Patrizio; Cuda, Gianni

    2015-01-01

    A device for detecting an analyte in a sample comprising: an array including a plurality of pixels, each pixel including a nanochain comprising: a first nanostructure, a second nanostructure, and a third nanostructure, wherein size of the first nanostructure is larger than that of the second nanostructure, and size of the second nanostructure is larger than that of the third nanostructure, and wherein the first nanostructure, the second nanostructure, and the third nanostructure are positioned on a substrate such that when the nanochain is excited by an energy, an optical field between the second nanostructure and the third nanostructure is stronger than an optical field between the first nanostructure and the second nanostructure, wherein the array is configured to receive a sample; and a detector arranged to collect spectral data from a plurality of pixels of the array.

  14. Saskatchewan resources. [including uranium

    Energy Technology Data Exchange (ETDEWEB)

    1979-09-01

    The production of chemicals and minerals for the chemical industry in Saskatchewan are featured, with some discussion of resource taxation. The commodities mentioned include potash, fatty amines, uranium, heavy oil, sodium sulfate, chlorine, sodium hydroxide, sodium chlorate and bentonite. Following the successful outcome of the Cluff Lake inquiry, the uranium industry is booming. Some developments and production figures for Gulf Minerals, Amok, Cenex and Eldorado are mentioned.

  15. Development of mathematical models to elaborate strategies, select alternatives and development of plans for adaptation of communities to climate change in different geographical areas including costs to implement it

    Science.gov (United States)

    Anton, J. M.; Grau, J. B.; Tarquis, A. M.; Andina, D.; Cisneros, J. M.

    2012-04-01

    There is evidence that the climate changes and that now, the change is influenced and accelerated by the CO2 augmentation in atmosphere due to combustion by humans. Such "Climate change" is on the policy agenda at the global level, with the aim of understanding and reducing its causes and to mitigate its consequences. In most countries and international organisms UNO (e.g. Rio de Janeiro 1992), OECD, EC, etc … the efforts and debates have been directed to know the possible causes, to predict the future evolution of some variable conditioners, and trying to make studies to fight against the effects or to delay the negative evolution of such. The Protocol of Kyoto 1997 set international efforts about CO2 emissions, but it was partial and not followed e.g. by USA and China …, and in Durban 2011 the ineffectiveness of humanity on such global real challenges was set as evident. Among all that, the elaboration of a global model was not boarded that can help to choose the best alternative between the feasible ones, to elaborate the strategies and to evaluate the costs, and the authors propose to enter in that frame for study. As in all natural, technological and social changes, the best-prepared countries will have the best bear and the more rapid recover. In all the geographic areas the alternative will not be the same one, but the model must help us to make the appropriated decision. It is essential to know those areas that are more sensitive to the negative effects of climate change, the parameters to take into account for its evaluation, and comprehensive plans to deal with it. The objective of this paper is to elaborate a mathematical model support of decisions, which will allow to develop and to evaluate alternatives of adaptation to the climatic change of different communities in Europe and Latin-America, mainly in especially vulnerable areas to the climatic change, considering in them all the intervening factors. The models will consider criteria of physical

  16. Genetic algorithm as a variable selection procedure for the simulation of 13C nuclear magnetic resonance spectra of flavonoid derivatives using multiple linear regression.

    Science.gov (United States)

    Ghavami, Raoof; Najafi, Amir; Sajadi, Mohammad; Djannaty, Farhad

    2008-09-01

    In order to accurately simulate (13)C NMR spectra of hydroxy, polyhydroxy and methoxy substituted flavonoid a quantitative structure-property relationship (QSPR) model, relating atom-based calculated descriptors to (13)C NMR chemical shifts (ppm, TMS=0), is developed. A dataset consisting of 50 flavonoid derivatives was employed for the present analysis. A set of 417 topological, geometrical, and electronic descriptors representing various structural characteristics was calculated and separate multilinear QSPR models were developed between each carbon atom of flavonoid and the calculated descriptors. Genetic algorithm (GA) and multiple linear regression analysis (MLRA) were used to select the descriptors and to generate the correlation models. Analysis of the results revealed a correlation coefficient and root mean square error (RMSE) of 0.994 and 2.53ppm, respectively, for the prediction set.

  17. The study of the laser parameters and environment variables effect on mechanical properties of high compact parts elaborated by selective laser melting 316L powder

    International Nuclear Information System (INIS)

    Zhang, Baicheng; Dembinski, Lucas; Coddet, Christian

    2013-01-01

    In this work, a systematic analysis of the main parameters for the selective laser melting (SLM) of a commercial stainless steel 316L powder was conducted to improve the mechanical properties and dimensional accuracy of the fabricated parts. First, the effects of the processing parameters, such as the laser beam scanning velocity, laser power, substrate condition and thickness of the powder layer, on the formation of single tracks for achieving a continuous melting and densification of the material were analysed. Then, the influence of the environmental conditions (gas nature) and of the preheating temperature on the density and dimensional accuracy of the parts was considered. The microstructural features of the SLM SS 316L parts were carefully observed to elucidate the melting-solidification mechanism and the thermal history, which are the basis of the manufacturing process. Finally, the mechanical properties of the corresponding material were also determined

  18. Being Included and Excluded

    DEFF Research Database (Denmark)

    Korzenevica, Marina

    2016-01-01

    Following the civil war of 1996–2006, there was a dramatic increase in the labor mobility of young men and the inclusion of young women in formal education, which led to the transformation of the political landscape of rural Nepal. Mobility and schooling represent a level of prestige that rural...... politics. It analyzes how formal education and mobility either challenge or reinforce traditional gendered norms which dictate a lowly position for young married women in the household and their absence from community politics. The article concludes that women are simultaneously excluded and included from...... community politics. On the one hand, their mobility and decision-making powers decrease with the increase in the labor mobility of men and their newly gained education is politically devalued when compared to the informal education that men gain through mobility, but on the other hand, schooling strengthens...

  19. Bias in random forest variable importance measures: Illustrations, sources and a solution

    Directory of Open Access Journals (Sweden)

    Hothorn Torsten

    2007-01-01

    Full Text Available Abstract Background Variable importance measures for random forests have been receiving increased attention as a means of variable selection in many classification tasks in bioinformatics and related scientific fields, for instance to select a subset of genetic markers relevant for the prediction of a certain disease. We show that random forest variable importance measures are a sensible means for variable selection in many applications, but are not reliable in situations where potential predictor variables vary in their scale of measurement or their number of categories. This is particularly important in genomics and computational biology, where predictors often include variables of different types, for example when predictors include both sequence data and continuous variables such as folding energy, or when amino acid sequence data show different numbers of categories. Results Simulation studies are presented illustrating that, when random forest variable importance measures are used with data of varying types, the results are misleading because suboptimal predictor variables may be artificially preferred in variable selection. The two mechanisms underlying this deficiency are biased variable selection in the individual classification trees used to build the random forest on one hand, and effects induced by bootstrap sampling with replacement on the other hand. Conclusion We propose to employ an alternative implementation of random forests, that provides unbiased variable selection in the individual classification trees. When this method is applied using subsampling without replacement, the resulting variable importance measures can be used reliably for variable selection even in situations where the potential predictor variables vary in their scale of measurement or their number of categories. The usage of both random forest algorithms and their variable importance measures in the R system for statistical computing is illustrated and

  20. STRATEGIC PLANNING DIMENSIONS IN SMALL AND MEDIUM ENTERPRISES (SMEs IN SOUTH AFRICA: THEIR RELATIVE IMPORTANCE AND VARIATIONS IN SELECTED DEMOGRAPHIC VARIABLES.

    Directory of Open Access Journals (Sweden)

    MAXWELL SANDADA

    2015-02-01

    Full Text Available The purpose of the study was to evaluate the strategic dimensions of SMEs and how each dimension is rated by owners and managers of SMEs. The other objective of the study was to ascertain if differences in strategic planning practices existed with respect to demographic variables namely gender, age and position in the organization. It was found that the main dimensions of strategic planning are mission and vision, environmental scanning, employee participation in the strategic planning process, time horizon of strategic planning, implementation incentives, evaluation and control, formality of strategic planning and source of information about the environment. It was also found that mission and vision, formality of strategic planning and evaluation and control were the most valued factors. No significant statistical difference existed among owners and managers of different age, gender and positions in strategic planning practices. The value of the study is that it offers various dimensions of strategic planning that SMEs can implement to be competitive and sustainable.

  1. Genotypic variability and relationships between mite infestation levels, mite damage, grooming intensity, and removal of Varroa destructor mites in selected strains of worker honey bees (Apis mellifera L.).

    Science.gov (United States)

    Guzman-Novoa, Ernesto; Emsen, Berna; Unger, Peter; Espinosa-Montaño, Laura G; Petukhova, Tatiana

    2012-07-01

    The objective of this study was to demonstrate genotypic variability and analyze the relationships between the infestation levels of the parasitic mite Varroa destructor in honey bee (Apis mellifera) colonies, the rate of damage of fallen mites, and the intensity with which bees of different genotypes groom themselves to remove mites from their bodies. Sets of paired genotypes that are presumably susceptible and resistant to the varroa mite were compared at the colony level for number of mites falling on sticky papers and for proportion of damaged mites. They were also compared at the individual level for intensity of grooming and mite removal success. Bees from the "resistant" colonies had lower mite population rates (up to 15 fold) and higher percentages of damaged mites (up to 9 fold) than bees from the "susceptible" genotypes. At the individual level, bees from the "resistant" genotypes performed significantly more instances of intense grooming (up to 4 fold), and a significantly higher number of mites were dislodged from the bees' bodies by intense grooming than by light grooming (up to 7 fold) in all genotypes. The odds of mite removal were high and significant for all "resistant" genotypes when compared with the "susceptible" genotypes. The results of this study strongly suggest that grooming behavior and the intensity with which bees perform it, is an important component in the resistance of some honey bee genotypes to the growth of varroa mite populations. The implications of these results are discussed. Copyright © 2012 Elsevier Inc. All rights reserved.

  2. Selective oxidation

    International Nuclear Information System (INIS)

    Cortes Henao, Luis F.; Castro F, Carlos A.

    2000-01-01

    It is presented a revision and discussion about the characteristics and factors that relate activity and selectivity in the catalytic and not catalytic partial oxidation of methane and the effect of variables as the temperature, pressure and others in the methane conversion to methanol. It thinks about the zeolites use modified for the catalytic oxidation of natural gas

  3. Evaluation of the phenotype variability and early selection to rust of the sugar cane (Puccinia melanocephala H. & P. Syd in plants generated from irradiated callus from the variaty of sugar cane ´SP 70-1284´.

    Directory of Open Access Journals (Sweden)

    Apolonio Valdez Balero

    2004-10-01

    Full Text Available It was evaluated the variability fenotípic in early phases of selection from plants regenerated of the mutagenic treatment with dose of 30 Gy of radiations Gamma (source 60Co applicated to calluses in growth of the donating ´SP 70-1284´ tolerant to the rust disease of the sugarcane Puccinia melanocephala. The main changes the plants obtained in vitro, consinted in the height, the color, habit of growth, length and width of the leaf, as well as in the affectation for the rust disease. 14.28% of the changes all fenotipic was observed in plantín, and in the shoot the plants presented 10.99% of changes all fenotipic. In the vegetative multiplication one (MV1 three possible mutants were selected with smaller affectation in front rust disease of the sugarcan, resistance character to the rust disease efficiency of the tissue culture and the mutations induction with the dose of 30 Gy were of a mutant for each 1 525 plants evaluated in early phase of selection. Key words: variation fenotipic, selection early, mutagenesis

  4. The Effect of Acepromazine Alone or in Combination with Methadone, Morphine, or Tramadol on Sedation and Selected Cardiopulmonary Variables in Sheep

    Directory of Open Access Journals (Sweden)

    Lilian Toshiko Nishimura

    2017-01-01

    Full Text Available The sedative and selected cardiopulmonary effects of acepromazine alone or in combination with methadone, morphine, or tramadol were compared in sheep. Six ewes were randomly assigned to treatments: A (0.05 mg/kg acepromazine, AM (A plus 0.5 mg/kg methadone, AMO (A plus 0.5 mg/kg morphine, and AT (A plus 5 mg/kg tramadol. Parameters were assessed before sedative drug administration (baseline and every 15 minutes thereafter, for two hours. Treatments A and AM were associated with increases in sedation score for 60 minutes and treatments AMO and AT for 30 minutes; however, there were no significant differences between treatments. There was a decrease in mean arterial pressure compared to baseline values in treatment A at 15, 45, 60, and 90 minutes, in treatment AM at 15 minutes, and in treatment AT from 45 to 120 minutes. Arterial blood carbon dioxide pressure increased at all time points in all treatments. Arterial oxygen pressure decreased in treatment AMO at 15, 30, and 120 minutes and in treatment AT at 15–45, 105, and 120 minutes, compared to baseline. Acepromazine alone causes a level of sedation similar to that observed when it is coadministered with opioids methadone, morphine, and tramadol. These combinations did not cause clinical cardiopulmonary changes.

  5. Macroinvertebrate Prey Availability and Fish Diet Selectivity in Relation to Environmental Variables in Natural and Restoring North San Francisco Bay Tidal Marsh Channels

    OpenAIRE

    Emily R. Howe; Charles A. Simenstad; Jason D. Toft; Jeffrey R. Cordell; Stephen M. Bollens

    2014-01-01

    Tidal marsh wetlands provide important foraging habitat for a variety of estuarine fishes. Prey organisms include benthic–epibenthic macroinvertebrates, neustonic arthropods, and zooplankton. Little is known about the abundance and distribution of interior marsh macroinvertebrate communities in the San Francisco Estuary (estuary). We describe seasonal, regional, and site variation in the composition and abundance of neuston and benthic–epibenthic macroinvertebrates that inhabit tidal marsh ch...

  6. Seasonal variability in soil-surface CO{sub 2} efflux in selected young tree plantations in semi-arid eco-climate of Madurai

    Energy Technology Data Exchange (ETDEWEB)

    Saraswathi, S.G.; Lalrammawia, C.; Paliwal, K. [Madurai Kamaraj Univ., Madurai (India). Dept. of Plant Sciences

    2008-07-10

    Atmospheric CO{sub 2} concentrations have been increasing in response to the disruption of the global carbon cycle by anthropogenic activities such as deforestation, agricultural practices and burning of fossil fuels. This has resulted in large shifts among carbon pools. The efflux of CO{sub 2} from soil results from the combined rates of autotrophic (root) and heterotrophic (microbial and soil fauna) respiration. It is often called soil respiration. The response of soil respiration (SR) to varying soil temperature and soil moisture was studied in three year-old plantation sites of Dalbergia sissoo, Dalbergia latifolia, Albizia lebbeck, Hardwickia binata and Cassia siamea during 2005--06. Significant seasonal differences in SR rates were observed in each site (P {<=} 0.001). The highest rates of soil CO{sub 2} efflux were generally found during the rainy season and the lowest during summer in all the study sites. Highest SR rates were found in D. sissoo, 9.89 {+-} 0.78 {mu}mol m{sup -2} s{sup -1} in November and December, followed by H. binata, 9.68 {+-} 0.45 {mu}mol m{sup -2} s{sup -1} in September and October 2005, A. lebbeck, 8.84 {+-} 0.43 {mu}mol m{sup -2} s{sup -1} between November 2005 and January 2006, D. latifolia, 7.6 {+-} 0.12 {mu}mol m{sup -2} s{sup -1} in November and December 2005 and C. siamea, 7.3 {mu}mol m{sup -2} s{sup -1} in December 2005. There was a positive and significant (P {<=} 0.001) relationship between SR rates and soil moisture in all the sites (r{sup 2} above 0.60), except C. siamea (r{sup 2} = 0.30). A poor relationship was observed between SR and soil temperature in all the sites (r{sup 2} below 0.2). Examination of the seasonal pattern of SR rates suggests that much of the variability could be attributed to variations in soil moisture. There was a strong indication suggesting that the soil-water deficits served to reduce SR rates during summer and after subsequent rain events. Overall sensitivity of SR rate to soil moisture seems to

  7. Variable collimator

    International Nuclear Information System (INIS)

    Richey, J.B.; McBride, T.R.; Covic, J.

    1979-01-01

    This invention describes an automatic variable collimator which controls the width and thickness of X-ray beams in X-ray diagnostic medical equipment, and which is particularly adapted for use with computerized axial tomographic scanners. A two-part collimator is provided which shapes an X-ray beam both prior to its entering an object subject to radiographic analysis and after the attenuated beam has passed through the object. Interposed between a source of radiation and the object subject to radiographic analysis is a first or source collimator. The source collimator causes the X-ray beam emitted by the source of radiation to be split into a plurality of generally rectangular shaped beams. Disposed within the source collimator is a movable aperture plate which may be used to selectively vary the thickness of the plurality of generally rectangular shaped beams transmitted through the source collimator. A second or receiver collimator is interposed between the object subject to radiographic analysis and a series of radiation detectors. The receiver collimator is disposed to receive the attenuated X-ray beams passing through the object subject to radiographic analysis. Located within the receiver collimator are a plurality of movable aperture plates adapted to be displaced relative to a plurality of fixed aperture plates for the purpose of varying the width and thickness of the attenuated X-ray beams transmitted through the object subject to radiographic analysis. The movable aperture plates of the source and receiver collimators are automatically controlled by circuitry which is provided to allow remote operation of the movable aperture plates

  8. [Selective mutism].

    Science.gov (United States)

    Ytzhak, A; Doron, Y; Lahat, E; Livne, A

    2012-10-01

    Selective mutism is an uncommon disorder in young children, in which they selectively don't speak in certain social situations, while being capable of speaking easily in other social situations. Many etiologies were proposed for selective mutism including psychodynamic, behavioral and familial etc. A developmental etiology that includes insights from all the above is gaining support. Accordingly, mild language impairment in a child with an anxiety trait may be at the root of developing selective mutism. The behavior will be reinforced by an avoidant pattern in the family. Early treatment and followup for children with selective mutism is important. The treatment includes non-pharmacological therapy (psychodynamic, behavioral and familial) and pharmacologic therapy--mainly selective serotonin reuptake inhibitors (SSRI).

  9. HadISD: a quality-controlled global synoptic report database for selected variables at long-term stations from 1973–2011

    Directory of Open Access Journals (Sweden)

    D. E. Parker

    2012-10-01

    Full Text Available This paper describes the creation of HadISD: an automatically quality-controlled synoptic resolution dataset of temperature, dewpoint temperature, sea-level pressure, wind speed, wind direction and cloud cover from global weather stations for 1973–2011. The full dataset consists of over 6000 stations, with 3427 long-term stations deemed to have sufficient sampling and quality for climate applications requiring sub-daily resolution. As with other surface datasets, coverage is heavily skewed towards Northern Hemisphere mid-latitudes. The dataset is constructed from a large pre-existing ASCII flatfile data bank that represents over a decade of substantial effort at data retrieval, reformatting and provision. These raw data have had varying levels of quality control applied to them by individual data providers. The work proceeded in several steps: merging stations with multiple reporting identifiers; reformatting to netCDF; quality control; and then filtering to form a final dataset. Particular attention has been paid to maintaining true extreme values where possible within an automated, objective process. Detailed validation has been performed on a subset of global stations and also on UK data using known extreme events to help finalise the QC tests. Further validation was performed on a selection of extreme events world-wide (Hurricane Katrina in 2005, the cold snap in Alaska in 1989 and heat waves in SE Australia in 2009. Some very initial analyses are performed to illustrate some of the types of problems to which the final data could be applied. Although the filtering has removed the poorest station records, no attempt has been made to homogenise the data thus far, due to the complexity of retaining the true distribution of high-resolution data when applying adjustments. Hence non-climatic, time-varying errors may still exist in many of the individual station records and care is needed in inferring long-term trends from these data. This

  10. Pulsating variables

    International Nuclear Information System (INIS)

    1989-01-01

    The study of stellar pulsations is a major route to the understanding of stellar structure and evolution. At the South African Astronomical Observatory (SAAO) the following stellar pulsation studies were undertaken: rapidly oscillating Ap stars; solar-like oscillations in stars; 8-Scuti type variability in a classical Am star; Beta Cephei variables; a pulsating white dwarf and its companion; RR Lyrae variables and galactic Cepheids. 4 figs

  11. Variable frequency microwave heating apparatus

    Energy Technology Data Exchange (ETDEWEB)

    Bible, D.W.; Lauf, R.J.; Johnson, A.C.; Thigpen, L.T.

    1999-10-05

    A variable frequency microwave heating apparatus (10) designed to allow modulation of the frequency of the microwaves introduced into a multi-mode microwave cavity (34) for testing or other selected applications. The variable frequency microwave heating apparatus (10) includes a microwave signal generator (12) and a high-power microwave amplifier (20) or a high-power microwave oscillator (14). A power supply (22) is provided for operation of the high-power microwave oscillator (14) or microwave amplifier (20). A directional coupler (24) is provided for detecting the direction and amplitude of signals incident upon and reflected from the microwave cavity (34). A first power meter (30) is provided for measuring the power delivered to the microwave furnace (32). A second power meter (26) detects the magnitude of reflected power. Reflected power is dissipated in the reflected power load (28).

  12. Variability in copepod trophic levels and feeding selectivity based on stable isotope analysis in Gwangyang Bay of the southern coast of the Korean Peninsula

    Science.gov (United States)

    Chen, Mianrun; Kim, Dongyoung; Liu, Hongbin; Kang, Chang-Keun

    2018-04-01

    Trophic preference (i.e., food resources and trophic levels) of different copepod groups was assessed along a salinity gradient in the temperate estuarine Gwangyang Bay of Korea, based on seasonal investigation of taxonomic results in 2015 and stable isotope analysis incorporating multiple linear regression models. The δ13C and δ15N values of copepods in the bay displayed significant spatial heterogeneity as well as seasonal variations, which were indicated by their significant relationships with salinity and temperature, respectively. Both spatial and temporal variations reflected those in isotopic values of food sources. The major calanoid groups (marine calanoids and brackish water calanoids) had a mean trophic level of 2.2 relative to nanoplankton as the basal food source, similar to the bulk copepod assemblage; however, they had dissimilar food sources based on the different δ13C values. Calanoid isotopic values indicated a mixture of different genera including species with high δ15N values (e.g., Labidocera, Sinocalanus, and Tortanus), moderate values (Calanus sinicus, Centropages, Paracalanus, and Acartia), and relatively low δ15N values (Eurytemora pacifica and Pseudodiaptomus). Feeding preferences of different copepods probably explain these seasonal and spatial patterns of the community trophic niche. Bayesian mixing model calculations based on source materials of two size fractions of particulate organic matter (nanoplankton at simple energy flow of the planktonic food web of Gwangyang Bay: from primary producers (nanoplankton) and a mixture of primary producers and herbivores (microplankton) through omnivores (Acartia, Calanus, Centropages, and Paracalanus) and detritivores (Pseudodiaptomus, Eurytemora, and harpacticoids) to carnivores (Corycaeus, Tortanus, Labidocera, and Sinocalanus).

  13. Cognitive Variability

    Science.gov (United States)

    Siegler, Robert S.

    2007-01-01

    Children's thinking is highly variable at every level of analysis, from neural and associative levels to the level of strategies, theories, and other aspects of high-level cognition. This variability exists within people as well as between them; individual children often rely on different strategies or representations on closely related problems…

  14. The Performance of Variable Annuities

    OpenAIRE

    Michael J. McNamara; Henry R. Oppenheimer

    1991-01-01

    Variable annuities have become increasingly important in retirement plans. This paper provides an examination of the investment performance of variable annuities for the period year-end 1973 to year-end 1988. Returns, risk, and selectivity measures are analyzed for the sample of annuities, for individual variable annuities, and for subsamples of annuities with similar portfolio size and turnover. While the investment returns of variable annuities were greater than inflation over the period, t...

  15. Variable volume combustor

    Science.gov (United States)

    Ostebee, Heath Michael; Ziminsky, Willy Steve; Johnson, Thomas Edward; Keener, Christopher Paul

    2017-01-17

    The present application provides a variable volume combustor for use with a gas turbine engine. The variable volume combustor may include a liner, a number of micro-mixer fuel nozzles positioned within the liner, and a linear actuator so as to maneuver the micro-mixer fuel nozzles axially along the liner.

  16. The nebular variables

    CERN Document Server

    Glasby, John S

    1974-01-01

    The Nebular Variables focuses on the nebular variables and their characteristics. Discussions are organized by type of nebular variable, namely, RW Aurigae stars, T Orionis stars, T Tauri stars, and peculiar nebular objects. Topics range from light variations of the stars to their spectroscopic and physical characteristics, spatial distribution, interaction with nebulosity, and evolutionary features. This volume is divided into four sections and consists of 25 chapters, the first of which provides general information on nebular variables, including their stellar associations and their classifi

  17. Several complex variables

    International Nuclear Information System (INIS)

    Field, M.J.

    1976-01-01

    Topics discussed include the elementary of holomorphic functions of several complex variables; the Weierstrass preparation theorem; meromorphic functions, holomorphic line bundles and divisors; elliptic operators on compact manifolds; hermitian connections; the Hodge decomposition theorem. ( author)

  18. Selective amplification of T-cell receptor variable region species is demonstrable but not essential in early lesions of psoriasis vulgaris: analysis by anchored polymerase chain reaction and hypervariable region size spectratyping.

    Science.gov (United States)

    Vekony, M A; Holder, J E; Lee, A J; Horrocks, C; Eperon, I C; Camp, R D

    1997-07-01

    Several groups have investigated the role of T cells in the pathogenesis of psoriasis by determination of T-cell receptor (TCR) B-chain variable (V) region usage, both in chronic plaque (psoriasis vulgaris) and guttate forms, with various results. Because there are no data on TCR expression in early psoriasis vulgaris, when specific cellular immune events may be expected to be most pronounced, we have analyzed early lesions (less than 3 wk old) of ten patients, with highly reproducible results. We have developed a highly controlled anchored polymerase chain reaction (PCR) method in which TCR beta chain species are all amplified with the same primer pair and products are quantified by dot blot hybridization with BV family-specific oligonucleotide probes. Overexpression of certain TCR BV genes was observed in the majority of lesional biopsies, but in samples in which the expanded BV family formed more than 10% of total lesional BV (half of the samples analyzed), BV2 and BV6 predominated. The consistency of overexpression of these BV species between patients was much less than in previous studies of TCRBV usage in established chronic plaque psoriasis lesions. Complementarity-determining region 3 (CDR3) size spectratyping demonstrated evidence for selective clonal T cell accumulation in less than half of the lesional samples showing BV expansion. These results indicate that selective amplification of TCRBV species occurs in early psoriasis vulgaris but is not essential to the pathogenic process and may be more important in the maintenance or expansion of chronic lesions.

  19. THE CHANDRA VARIABLE GUIDE STAR CATALOG

    International Nuclear Information System (INIS)

    Nichols, Joy S.; Lauer, Jennifer L.; Morgan, Douglas L.; Sundheim, Beth A.; Henden, Arne A.; Huenemoerder, David P.; Martin, Eric

    2010-01-01

    Variable stars have been identified among the optical-wavelength light curves of guide stars used for pointing control of the Chandra X-ray Observatory. We present a catalog of these variable stars along with their light curves and ancillary data. Variability was detected to a lower limit of 0.02 mag amplitude in the 4000-10000 A range using the photometrically stable Aspect Camera on board the Chandra spacecraft. The Chandra Variable Guide Star Catalog (VGUIDE) contains 827 stars, of which 586 are classified as definitely variable and 241 are identified as possibly variable. Of the 586 definite variable stars, we believe 319 are new variable star identifications. Types of variables in the catalog include eclipsing binaries, pulsating stars, and rotating stars. The variability was detected during the course of normal verification of each Chandra pointing and results from analysis of over 75,000 guide star light curves from the Chandra mission. The VGUIDE catalog represents data from only about 9 years of the Chandra mission. Future releases of VGUIDE will include newly identified variable guide stars as the mission proceeds. An important advantage of the use of space data to identify and analyze variable stars is the relatively long observations that are available. The Chandra orbit allows for observations up to 2 days in length. Also, guide stars were often used multiple times for Chandra observations, so many of the stars in the VGUIDE catalog have multiple light curves available from various times in the mission. The catalog is presented as both online data associated with this paper and as a public Web interface. Light curves with data at the instrumental time resolution of about 2 s, overplotted with the data binned at 1 ks, can be viewed on the public Web interface and downloaded for further analysis. VGUIDE is a unique project using data collected during the mission that would otherwise be ignored. The stars available for use as Chandra guide stars are

  20. SEEPAGE MODEL FOR PA INCLUDING DRIFT COLLAPSE

    International Nuclear Information System (INIS)

    C. Tsang

    2004-01-01

    The purpose of this report is to document the predictions and analyses performed using the seepage model for performance assessment (SMPA) for both the Topopah Spring middle nonlithophysal (Tptpmn) and lower lithophysal (Tptpll) lithostratigraphic units at Yucca Mountain, Nevada. Look-up tables of seepage flow rates into a drift (and their uncertainty) are generated by performing numerical simulations with the seepage model for many combinations of the three most important seepage-relevant parameters: the fracture permeability, the capillary-strength parameter 1/a, and the percolation flux. The percolation flux values chosen take into account flow focusing effects, which are evaluated based on a flow-focusing model. Moreover, multiple realizations of the underlying stochastic permeability field are conducted. Selected sensitivity studies are performed, including the effects of an alternative drift geometry representing a partially collapsed drift from an independent drift-degradation analysis (BSC 2004 [DIRS 166107]). The intended purpose of the seepage model is to provide results of drift-scale seepage rates under a series of parameters and scenarios in support of the Total System Performance Assessment for License Application (TSPA-LA). The SMPA is intended for the evaluation of drift-scale seepage rates under the full range of parameter values for three parameters found to be key (fracture permeability, the van Genuchten 1/a parameter, and percolation flux) and drift degradation shape scenarios in support of the TSPA-LA during the period of compliance for postclosure performance [Technical Work Plan for: Performance Assessment Unsaturated Zone (BSC 2002 [DIRS 160819], Section I-4-2-1)]. The flow-focusing model in the Topopah Spring welded (TSw) unit is intended to provide an estimate of flow focusing factors (FFFs) that (1) bridge the gap between the mountain-scale and drift-scale models, and (2) account for variability in local percolation flux due to

  1. Complex variables

    CERN Document Server

    Fisher, Stephen D

    1999-01-01

    The most important topics in the theory and application of complex variables receive a thorough, coherent treatment in this introductory text. Intended for undergraduates or graduate students in science, mathematics, and engineering, this volume features hundreds of solved examples, exercises, and applications designed to foster a complete understanding of complex variables as well as an appreciation of their mathematical beauty and elegance. Prerequisites are minimal; a three-semester course in calculus will suffice to prepare students for discussions of these topics: the complex plane, basic

  2. Internet interventions for chronic pain including headache: A systematic review

    Directory of Open Access Journals (Sweden)

    Monica Buhrman

    2016-05-01

    Full Text Available Chronic pain is a major health problem and behavioral based treatments have been shown to be effective. However, the availability of these kinds of treatments is scarce and internet-based treatments have been shown to be promising in this area. The objective of the present systematic review is to evaluate internet-based interventions for persons with chronic pain. The specific aims are to do an updated review with a broad inclusion of different chronic pain diagnoses and to assess disability and pain and also measures of catastrophizing, depression and anxiety. A systematic search identified 891 studies and 22 trials were selected as eligible for review. Two of the selected trials included children/youth and five included individuals with chronic headache and/or migraine. The most frequently measured domain reflected in the primary outcomes was interference/disability, followed by catastrophizing. Result across the studies showed a number of beneficial effects. Twelve trials reported significant effects on disability/interference outcomes and pain intensity. Positive effects were also found on psychological variable such as catastrophizing, depression and anxiety. Several studies (n = 12 were assessed to have an unclear level of risk bias. The attrition levels ranged from 4% to 54% where the headache trials had the highest drop-out levels. However, findings suggest that internet-based treatments based on cognitive behavioural therapy (CBT are efficacious measured with different outcome variables. Results are in line with trials in clinical settings. Meta-analytic statistics were calculated for interference/disability, pain intensity, catastrophizing and mood ratings. Results showed that the effect size for interference/disability was Hedge's g = −0.39, for pain intensity Hedge's g = −0.33, for catastrophizing Hedge's g = −0.49 and for mood variables (depression Hedge's g = −0.26.

  3. Including investment risk in large-scale power market models

    DEFF Research Database (Denmark)

    Lemming, Jørgen Kjærgaard; Meibom, P.

    2003-01-01

    Long-term energy market models can be used to examine investments in production technologies, however, with market liberalisation it is crucial that such models include investment risks and investor behaviour. This paper analyses how the effect of investment risk on production technology selection...... can be included in large-scale partial equilibrium models of the power market. The analyses are divided into a part about risk measures appropriate for power market investors and a more technical part about the combination of a risk-adjustment model and a partial-equilibrium model. To illustrate...... the analyses quantitatively, a framework based on an iterative interaction between the equilibrium model and a separate risk-adjustment module was constructed. To illustrate the features of the proposed modelling approach we examined how uncertainty in demand and variable costs affects the optimal choice...

  4. Design and Synthesis of a Series of L-trans-4-Substituted Prolines as Selective Antagonists for the Ionotropic Glutamate Receptors Including Functional and X-ray Crystallographic Studies of New Subtype Selective Kainic Acid Receptor Subtype 1 (GluK1) Antagonist (2S,4R)-4-(2-Carboxyphenoxy)pyrrolidine

    DEFF Research Database (Denmark)

    Krogsgaard-Larsen, Niels; Delgar, Claudia; Koch, Karina

    2017-01-01

    Ionotropic glutamate receptor antagonists are valuable tool compounds for studies of neurological pathways in the central nervous system. On the basis of rational ligand design, a new class of selective antagonists, represented by (2S,4R)-4-(2-carboxy-phenoxy)pyrrolidine-2-carboxylic acid (1b...... to the structure with glutamate, consistent with 1b being an antagonist. A structure-activity relationship study showed that the chemical nature of the tethering atom (C,O, or S) linking the pyrrolidine ring and the phenyl ring plays a key role in the receptor selectivity profile and that substituents......), for cloned homomeric kainic acid receptor subtype 1 (GluK1) was attained (Ki = 4 µM). In a functional assay, 1b displayed full antagonist activity with IC50 = 6 ± 2 µM. A crystal structure was obtained of 1b when bound in the ligand binding domain of GluK1. A domain opening of 13-14° was seen compared...

  5. Variable stars

    International Nuclear Information System (INIS)

    Feast, M.W.; Wenzel, W.; Fernie, J.D.; Percy, J.R.; Smak, J.; Gascoigne, S.C.B.; Grindley, J.E.; Lovell, B.; Sawyer Hogg, H.B.; Baker, N.; Fitch, W.S.; Rosino, L.; Gursky, H.

    1976-01-01

    A critical review of variable stars is presented. A fairly complete summary of major developments and discoveries during the period 1973-1975 is given. The broad developments and new trends are outlined. Essential problems for future research are identified. (B.R.H. )

  6. Modeling soil organic matter (SOM) from satellite data using VISNIR-SWIR spectroscopy and PLS regression with step-down variable selection algorithm: case study of Campos Amazonicos National Park savanna enclave, Brazil

    Science.gov (United States)

    Rosero-Vlasova, O.; Borini Alves, D.; Vlassova, L.; Perez-Cabello, F.; Montorio Lloveria, R.

    2017-10-01

    Deforestation in Amazon basin due, among other factors, to frequent wildfires demands continuous post-fire monitoring of soil and vegetation. Thus, the study posed two objectives: (1) evaluate the capacity of Visible - Near InfraRed - ShortWave InfraRed (VIS-NIR-SWIR) spectroscopy to estimate soil organic matter (SOM) in fire-affected soils, and (2) assess the feasibility of SOM mapping from satellite images. For this purpose, 30 soil samples (surface layer) were collected in 2016 in areas of grass and riparian vegetation of Campos Amazonicos National Park, Brazil, repeatedly affected by wildfires. Standard laboratory procedures were applied to determine SOM. Reflectance spectra of soils were obtained in controlled laboratory conditions using Fieldspec4 spectroradiometer (spectral range 350nm- 2500nm). Measured spectra were resampled to simulate reflectances for Landsat-8, Sentinel-2 and EnMap spectral bands, used as predictors in SOM models developed using Partial Least Squares regression and step-down variable selection algorithm (PLSR-SD). The best fit was achieved with models based on reflectances simulated for EnMap bands (R2=0.93; R2cv=0.82 and NMSE=0.07; NMSEcv=0.19). The model uses only 8 out of 244 predictors (bands) chosen by the step-down variable selection algorithm. The least reliable estimates (R2=0.55 and R2cv=0.40 and NMSE=0.43; NMSEcv=0.60) resulted from Landsat model, while Sentinel-2 model showed R2=0.68 and R2cv=0.63; NMSE=0.31 and NMSEcv=0.38. The results confirm high potential of VIS-NIR-SWIR spectroscopy for SOM estimation. Application of step-down produces sparser and better-fit models. Finally, SOM can be estimated with an acceptable accuracy (NMSE 0.35) from EnMap and Sentinel-2 data enabling mapping and analysis of impacts of repeated wildfires on soils in the study area.

  7. Spatial and temporal variability of winds in the Northern European Seas

    DEFF Research Database (Denmark)

    Karagali, Ioanna; Badger, Merete; Hahmann, Andrea N.

    2013-01-01

    the spatial and temporal variability of the near-surface wind field, including the inter- and intra-annual variability for resource assessment purposes. This study demonstrates the applicability of satellite observations as the means to provide information useful for selecting areas to perform higher...

  8. Calculus of one variable

    CERN Document Server

    Grossman, Stanley I

    1986-01-01

    Calculus of One Variable, Second Edition presents the essential topics in the study of the techniques and theorems of calculus.The book provides a comprehensive introduction to calculus. It contains examples, exercises, the history and development of calculus, and various applications. Some of the topics discussed in the text include the concept of limits, one-variable theory, the derivatives of all six trigonometric functions, exponential and logarithmic functions, and infinite series.This textbook is intended for use by college students.

  9. Statistical variability of hydro-meteorological variables as indicators ...

    African Journals Online (AJOL)

    Statistical variability of hydro-meteorological variables as indicators of climate change in north-east Sokoto-Rima basin, Nigeria. ... water resources development including water supply project, agriculture and tourism in the study area. Key word: Climate change, Climatic variability, Actual evapotranspiration, Global warming ...

  10. Complex variables

    CERN Document Server

    Flanigan, Francis J

    2010-01-01

    A caution to mathematics professors: Complex Variables does not follow conventional outlines of course material. One reviewer noting its originality wrote: ""A standard text is often preferred [to a superior text like this] because the professor knows the order of topics and the problems, and doesn't really have to pay attention to the text. He can go to class without preparation."" Not so here-Dr. Flanigan treats this most important field of contemporary mathematics in a most unusual way. While all the material for an advanced undergraduate or first-year graduate course is covered, discussion

  11. Selective mutism.

    Science.gov (United States)

    Hua, Alexandra; Major, Nili

    2016-02-01

    Selective mutism is a disorder in which an individual fails to speak in certain social situations though speaks normally in other settings. Most commonly, this disorder initially manifests when children fail to speak in school. Selective mutism results in significant social and academic impairment in those affected by it. This review will summarize the current understanding of selective mutism with regard to diagnosis, epidemiology, cause, prognosis, and treatment. Studies over the past 20 years have consistently demonstrated a strong relationship between selective mutism and anxiety, most notably social phobia. These findings have led to the recent reclassification of selective mutism as an anxiety disorder in the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition. In addition to anxiety, several other factors have been implicated in the development of selective mutism, including communication delays and immigration/bilingualism, adding to the complexity of the disorder. In the past few years, several randomized studies have supported the efficacy of psychosocial interventions based on a graduated exposure to situations requiring verbal communication. Less data are available regarding the use of pharmacologic treatment, though there are some studies that suggest a potential benefit. Selective mutism is a disorder that typically emerges in early childhood and is currently conceptualized as an anxiety disorder. The development of selective mutism appears to result from the interplay of a variety of genetic, temperamental, environmental, and developmental factors. Although little has been published about selective mutism in the general pediatric literature, pediatric clinicians are in a position to play an important role in the early diagnosis and treatment of this debilitating condition.

  12. A Bayesian random effects discrete-choice model for resource selection: Population-level selection inference

    Science.gov (United States)

    Thomas, D.L.; Johnson, D.; Griffith, B.

    2006-01-01

    Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a

  13. A comparison of the hourly output between the Ambu® Smart-Infuser™ Pain Pump and the On-Q Pump® with Select-A-Flow™ Variable Rate Controller with standard and overfill volumes.

    Science.gov (United States)

    Iliev, Peter; Bhalla, Tarun; Tobias, Joseph D

    2016-04-01

    The Ambu Smart-Infuser Pain Pump and the On-Q Pump with Select-a-Flow Variable Rate Controller are elastomeric devices with a flow regulator that controls the rate of infusion of a local anesthetic agent through a peripheral catheter. As a safety evaluation, we evaluated the infusion characteristics of these two devices when filled with manufacturer recommended standard volumes and when overfilled with a volume 50% in excess of that which is recommended. Nineteen disposable devices from the two manufacturers were used in this study. Nine were filled with 0.9% normal saline according to the respective manufacturers' recommendations (four Ambu pumps were filled with 650 ml and five On-Q pumps were filled with 550 ml) and 10 devices were 150% overfilled (five Ambu pumps were filled with 975 ml and five On-Q pumps were filled with 825 ml). All of the devices were set to infuse at 10 ml · h(-1) at room temperature (21°C) for 12 h. The fluid delivered during each 2-h period was measured using a graduated column. The On-Q pump (in the settings of normal fill and 150% overfill) delivered a significantly higher output per hour than the set rate during the first 8 h, while the Ambu pump delivered a value close to the set rate of 10 ml · h(-1). No significant difference in the hourly delivered output was noted for either device when comparing the normal fill to the 150% overfill groups. This investigation demonstrates that no change in the hourly output occurs with overfilling of these home infusion devices. However, as noted previously, the hourly output from the On-Q device is significantly higher than the set rate during the initial 8 h of infusion which could have potential clinical implications. © 2016 John Wiley & Sons Ltd.

  14. Statistical model selection with “Big Data”

    Directory of Open Access Journals (Sweden)

    Jurgen A. Doornik

    2015-12-01

    Full Text Available Big Data offer potential benefits for statistical modelling, but confront problems including an excess of false positives, mistaking correlations for causes, ignoring sampling biases and selecting by inappropriate methods. We consider the many important requirements when searching for a data-based relationship using Big Data, and the possible role of Autometrics in that context. Paramount considerations include embedding relationships in general initial models, possibly restricting the number of variables to be selected over by non-statistical criteria (the formulation problem, using good quality data on all variables, analyzed with tight significance levels by a powerful selection procedure, retaining available theory insights (the selection problem while testing for relationships being well specified and invariant to shifts in explanatory variables (the evaluation problem, using a viable approach that resolves the computational problem of immense numbers of possible models.

  15. A Permutation Approach for Selecting the Penalty Parameter in Penalized Model Selection

    Science.gov (United States)

    Sabourin, Jeremy A; Valdar, William; Nobel, Andrew B

    2015-01-01

    Summary We describe a simple, computationally effcient, permutation-based procedure for selecting the penalty parameter in LASSO penalized regression. The procedure, permutation selection, is intended for applications where variable selection is the primary focus, and can be applied in a variety of structural settings, including that of generalized linear models. We briefly discuss connections between permutation selection and existing theory for the LASSO. In addition, we present a simulation study and an analysis of real biomedical data sets in which permutation selection is compared with selection based on the following: cross-validation (CV), the Bayesian information criterion (BIC), Scaled Sparse Linear Regression, and a selection method based on recently developed testing procedures for the LASSO. PMID:26243050

  16. Gaia DR1 documentation Chapter 6: Variability

    Science.gov (United States)

    Eyer, L.; Rimoldini, L.; Guy, L.; Holl, B.; Clementini, G.; Cuypers, J.; Mowlavi, N.; Lecoeur-Taïbi, I.; De Ridder, J.; Charnas, J.; Nienartowicz, K.

    2017-12-01

    This chapter describes the photometric variability processing of the Gaia DR1 data. Coordination Unit 7 is responsible for the variability analysis of over a billion celestial sources. In particular the definition, design, development, validation and provision of a software package for the data processing of photometrically variable objects. Data Processing Centre Geneva (DPCG) responsibilities cover all issues related to the computational part of the CU7 analysis. These span: hardware provisioning, including selection, deployment and optimisation of suitable hardware, choosing and developing software architecture, defining data and scientific workflows as well as operational activities such as configuration management, data import, time series reconstruction, storage and processing handling, visualisation and data export. CU7/DPCG is also responsible for interaction with other DPCs and CUs, software and programming training for the CU7 members, scientific software quality control and management of software and data lifecycle. Details about the specific data treatment steps of the Gaia DR1 data products are found in Eyer et al. (2017) and are not repeated here. The variability content of the Gaia DR1 focusses on a subsample of Cepheids and RR Lyrae stars around the South ecliptic pole, showcasing the performance of the Gaia photometry with respect to variable objects.

  17. Technological Capability's Predictor Variables

    Directory of Open Access Journals (Sweden)

    Fernanda Maciel Reichert

    2011-03-01

    Full Text Available The aim of this study was to identify the factors that influence in configuration of the technological capability of companies in sectors with medium-low technological intensity. To achieve the goal proposed in this article a survey was carried out. Based on the framework developed by Lall (1992 which classifies firms in basic, intermediate and advanced level of technological capability; it was found that the predominant technological capability is intermediate, with 83.7% of respondent companies (plastics companies in Brazil. It is believed that the main contribution of this study is the finding that the dependent variable named “Technological Capability” can be explained at a rate of 65% by six variables: development of new processes; selection of the best equipment supplier; sales of internally developed new technology to third parties; design and manufacture of equipment; study of the work methods and perform inventory control; and improvement of product quality.

  18. Internal variables in thermoelasticity

    CERN Document Server

    Berezovski, Arkadi

    2017-01-01

    This book describes an effective method for modeling advanced materials like polymers, composite materials and biomaterials, which are, as a rule, inhomogeneous. The thermoelastic theory with internal variables presented here provides a general framework for predicting a material’s reaction to external loading. The basic physical principles provide the primary theoretical information, including the evolution equations of the internal variables. The cornerstones of this framework are the material representation of continuum mechanics, a weak nonlocality, a non-zero extra entropy flux, and a consecutive employment of the dissipation inequality. Examples of thermoelastic phenomena are provided, accompanied by detailed procedures demonstrating how to simulate them.

  19. The Relationship between Macroeconomic Variables and ISE Industry Index

    Directory of Open Access Journals (Sweden)

    Ahmet Ozcan

    2012-01-01

    Full Text Available In this study, the relationship between macroeconomic variables and Istanbul Stock Exchange (ISE industry index is examined. Over the past years, numerous studies have analyzed these relationships and the different results obtained from these studies have motivated further research. The relationship between stock exchange index and macroeconomic variables has been well documented for the developed markets. However, there are few studies regarding the relationship between macroeconomic variables and stock exchange index for the developing markets. Thus, this paper seeks to address the question of whether macroeconomic variables have a significant relationship with ISE industry index using monthly data for the period from 2003 to 2010. The selected macroeconomic variables for the study include interest rates, consumer price index, money supply, exchange rate, gold prices, oil prices, current account deficit and export volume. The Johansen’s cointegration test is utilized to determine the impact of selected macroeconomic variables on ISE industry index. The result of the Johansen’s cointegration shows that macroeconomic variables exhibit a long run equilibrium relationship with the ISE industry index.

  20. GGVS. Ordinance on road transport of hazardous materials, including the European agreement on international road transport of hazardous materials (ADR), in their wording. Annexes A and B. Ordinances regarding exceptions from GGVS and from the ordinance on rail transport of hazardous materials, GGVE. Reasons. Selected guidelines. List of materials. 6. rev. and enlarged ed.

    International Nuclear Information System (INIS)

    Ridder, K.

    1990-01-01

    The brochure contains the following texts: (1) Ordinance on road transport of hazardous materials (GGVS), including the European agreement on international road transport of hazardous materials (ADR), as of 1990: Skeleton ordinance, annexes A and B, reasons given for the first version, and for the first amendment in 1988, execution guidelines - RS 002 (guidelines for executing the ordinance on road transport of hazardous materials, with catalogue of penalties), guidelines for drawing up written instructions for the event of accidents - RS 006, guiding principles for the training of vehicle conductors; (2) ordinance regarding exceptions from the ordinance on road transport of hazardous materials; (3) ordinance regarding exceptions from the ordinance on rail transport of hazardous materials; (4) selected guidelines: Technical guidelines TR IBC K 001, TRS 003, TRS 004, TRS 005, TRS 006; (5) listing of materials and objects governed by the ordinance on hazardous materials transport; (6) catalogue of penalties relative to road transport of hazardous materials. (orig./HP) [de

  1. NASA/DOD Aerospace Knowledge Diffusion Research Project. Report 6: The relationship between the use of US government technical reports by US aerospace engineers and scientists and selected institutional and sociometric variables. Ph.D. Thesis - Indiana Univ., Nov. 1990 No. 6

    Science.gov (United States)

    Pinelli, Thomas E.

    1991-01-01

    The relationship between the use of U.S. government technical reports by U.S. aerospace engineers and scientists and selected institutional and sociometric variables was investigated. The methodology used for this study was survey research. Data were collected by means of a self-administered mail questionnaire. The approximately 34,000 members of the American Institute of Aeronautics and Astronauts (AIAA) served as the study population. The response rate for the survey was 70 percent. A dependent relationship was found to exist between the use of U.S. government technical reports and three of the institutional variables (academic preparation, years of professional aerospace work experience, and technical discipline). The use of U.S. government technical reports was found to be independent of all of the sociometric variables. The institutional variables best explain the use of U.S. government technical reports by U.S. aerospace engineers and scientists.

  2. Diagnostic for two-mode variable valve activation device

    Science.gov (United States)

    Fedewa, Andrew M

    2014-01-07

    A method is provided for diagnosing a multi-mode valve train device which selectively provides high lift and low lift to a combustion valve of an internal combustion engine having a camshaft phaser actuated by an electric motor. The method includes applying a variable electric current to the electric motor to achieve a desired camshaft phaser operational mode and commanding the multi-mode valve train device to a desired valve train device operational mode selected from a high lift mode and a low lift mode. The method also includes monitoring the variable electric current and calculating a first characteristic of the parameter. The method also includes comparing the calculated first characteristic against a predetermined value of the first characteristic measured when the multi-mode valve train device is known to be in the desired valve train device operational mode.

  3. Climate variability from isotope records in precipitation

    International Nuclear Information System (INIS)

    Grassl, H.; Latif, M.; Schotterer, U.; Gourcy, L.

    2002-01-01

    Selected time series from the Global Network for Isotopes in Precipitation (GNIP) revealed a close relationship to climate variability phenomena like El Nino - Southern Oscillation (ENSO) or the North Atlantic Oscillation (NAO) although the precipitation anomaly in the case studies of Manaus (Brazil) and Groningen (The Netherlands) is rather weak. For a sound understanding of this relationship especially in the case of Manaus, the data should include major events like the 1997/98 El Nino, however, the time series are interrupted frequently or important stations are even closed. Improvements are only possible if existing key stations and new ones (placed at 'hot spots' derived from model experiments) are supported continuously. A close link of GNIP to important scientific programmes like CLIVAR, the Climate Variability and Predictability Programme seems to be indispensable for a successful continuation. (author)

  4. (including travel dates) Proposed itinerary

    Indian Academy of Sciences (India)

    Ashok

    31 July to 22 August 2012 (including travel dates). Proposed itinerary: Arrival in Bangalore on 1 August. 1-5 August: Bangalore, Karnataka. Suggested institutions: Indian Institute of Science, Bangalore. St Johns Medical College & Hospital, Bangalore. Jawaharlal Nehru Centre, Bangalore. 6-8 August: Chennai, TN.

  5. Theory including future not excluded

    DEFF Research Database (Denmark)

    Nagao, K.; Nielsen, H.B.

    2013-01-01

    We study a complex action theory (CAT) whose path runs over not only past but also future. We show that, if we regard a matrix element defined in terms of the future state at time T and the past state at time TA as an expectation value in the CAT, then we are allowed to have the Heisenberg equation......, Ehrenfest's theorem, and the conserved probability current density. In addition,we showthat the expectation value at the present time t of a future-included theory for large T - t and large t - T corresponds to that of a future-not-included theory with a proper inner product for large t - T. Hence, the CAT...

  6. Soil variability in mountain areas

    OpenAIRE

    Zanini, E.; Freppaz, M.; Stanchi, S.; Bonifacio, E.; Egli, M.

    2015-01-01

    The high spatial variability of soils is a relevant issue at local and global scales, and determines the complexity of soil ecosystem functions and services. This variability derives from strong dependencies of soil ecosystems on parent materials, climate, relief and biosphere, including human impact. Although present in all environments, the interactions of soils with these forming factors are particularly striking in mountain areas.

  7. Variability in human body size

    Science.gov (United States)

    Annis, J. F.

    1978-01-01

    The range of variability found among homogeneous groups is described and illustrated. Those trends that show significantly marked differences between sexes and among a number of racial/ethnic groups are also presented. Causes of human-body size variability discussed include genetic endowment, aging, nutrition, protective garments, and occupation. The information is presented to aid design engineers of space flight hardware and equipment.

  8. A COMPARISON OF IN SITU AND MODELLED ESTIMATES OF SELECTED APPARENT OPTICAL PROPERTIES IN RESPONSE TO CHL A AND CDOM VARIABILITY IN THE COASTAL WATERS OF SOUTHERN NEW ENGLAND DURING SUMMER 1999

    Science.gov (United States)

    Chlorophyll a concentrations, colored dissolved organic matter (CDOM) absorption coefficients, and selected apparent optical properties (AOPs) of waters along the Western Passage of Narragansett Bay and adjoining Rhode Island Sound were determined from May -August 1999. Water sam...

  9. An evaluation of FIA's stand age variable

    Science.gov (United States)

    John D. Shaw

    2015-01-01

    The Forest Inventory and Analysis Database (FIADB) includes a large number of measured and computed variables. The definitions of measured variables are usually well-documented in FIA field and database manuals. Some computed variables, such as live basal area of the condition, are equally straightforward. Other computed variables, such as individual tree volume,...

  10. Device including a contact detector

    DEFF Research Database (Denmark)

    2011-01-01

    arms (12) may extend from the supporting body in co-planar relationship with the first surface. The plurality of cantilever arms (12) may extend substantially parallel to each other and each of the plurality of cantilever arms (12) may include an electrical conductive tip for contacting the area......The present invention relates to a probe for determining an electrical property of an area of a surface of a test sample, the probe is intended to be in a specific orientation relative to the test sample. The probe may comprise a supporting body defining a first surface. A plurality of cantilever...... of the test sample by movement of the probe relative to the surface of the test sample into the specific orientation.; The probe may further comprise a contact detector (14) extending from the supporting body arranged so as to contact the surface of the test sample prior to any one of the plurality...

  11. Neoclassical transport including collisional nonlinearity.

    Science.gov (United States)

    Candy, J; Belli, E A

    2011-06-10

    In the standard δf theory of neoclassical transport, the zeroth-order (Maxwellian) solution is obtained analytically via the solution of a nonlinear equation. The first-order correction δf is subsequently computed as the solution of a linear, inhomogeneous equation that includes the linearized Fokker-Planck collision operator. This equation admits analytic solutions only in extreme asymptotic limits (banana, plateau, Pfirsch-Schlüter), and so must be solved numerically for realistic plasma parameters. Recently, numerical codes have appeared which attempt to compute the total distribution f more accurately than in the standard ordering by retaining some nonlinear terms related to finite-orbit width, while simultaneously reusing some form of the linearized collision operator. In this work we show that higher-order corrections to the distribution function may be unphysical if collisional nonlinearities are ignored.

  12. Choice of the thermodynamic variables

    International Nuclear Information System (INIS)

    Balian, R.

    1985-09-01

    Some basic ideas of thermodynamics and statistical mechanics, both at equilibrium and off equilibrium, are recalled. In particular, the selection of relevant variables which underlies any macroscopic description is discussed, together with the meaning of the various thermodynamic quantities, in order to set the thermodynamic approaches used in nuclear physics in a general prospect [fr

  13. Several real variables

    CERN Document Server

    Kantorovitz, Shmuel

    2016-01-01

    This undergraduate textbook is based on lectures given by the author on the differential and integral calculus of functions of several real variables. The book has a modern approach and includes topics such as: •The p-norms on vector space and their equivalence •The Weierstrass and Stone-Weierstrass approximation theorems •The differential as a linear functional; Jacobians, Hessians, and Taylor's theorem in several variables •The Implicit Function Theorem for a system of equations, proved via Banach’s Fixed Point Theorem •Applications to Ordinary Differential Equations •Line integrals and an introduction to surface integrals This book features numerous examples, detailed proofs, as well as exercises at the end of sections. Many of the exercises have detailed solutions, making the book suitable for self-study. Several Real Variables will be useful for undergraduate students in mathematics who have completed first courses in linear algebra and analysis of one real variable.

  14. MOS modeling hierarchy including radiation effects

    International Nuclear Information System (INIS)

    Alexander, D.R.; Turfler, R.M.

    1975-01-01

    A hierarchy of modeling procedures has been developed for MOS transistors, circuit blocks, and integrated circuits which include the effects of total dose radiation and photocurrent response. The models were developed for use with the SCEPTRE circuit analysis program, but the techniques are suitable for other modern computer aided analysis programs. The modeling hierarchy permits the designer or analyst to select the level of modeling complexity consistent with circuit size, parametric information, and accuracy requirements. Improvements have been made in the implementation of important second order effects in the transistor MOS model, in the definition of MOS building block models, and in the development of composite terminal models for MOS integrated circuits

  15. Impact of Psychological Variables on Playing Ability of University Level Soccer Players

    Directory of Open Access Journals (Sweden)

    Ertan Tufekcioglu

    2014-10-01

    Full Text Available The purpose of the study was to find out the relationship between psychological variables and soccer playing ability among the university level male players. 42 soccer players representing different universities who participated in inter university competitions were selected as the subjects of the study. The dependent variable was soccer playing ability and independent variables were the selected psychological variables. Soccer playing ability was determined through a 10 point scale at the time of competitions. Psychological variables included achievement motivation, anxiety, self-concept and aggression. The data was statistically analyzed using Karl Pearson’s correlation coefficient and multiple regression analysis using SPSS. It was concluded that soccer playing ability has a positive correlation with achievement motivation and self-concept whereas anxiety and aggression have a negative correlation with soccer playing ability.

  16. Manipulating continuous variable photonic entanglement

    International Nuclear Information System (INIS)

    Plenio, M.B.

    2005-01-01

    I will review our work on photonic entanglement in the continuous variable regime including both Gaussian and non-Gaussian states. The feasibility and efficiency of various entanglement purification protocols are discussed this context. (author)

  17. Photoactive devices including porphyrinoids with coordinating additives

    Science.gov (United States)

    Forrest, Stephen R; Zimmerman, Jeramy; Yu, Eric K; Thompson, Mark E; Trinh, Cong; Whited, Matthew; Diev, Vlacheslav

    2015-05-12

    Coordinating additives are included in porphyrinoid-based materials to promote intermolecular organization and improve one or more photoelectric characteristics of the materials. The coordinating additives are selected from fullerene compounds and organic compounds having free electron pairs. Combinations of different coordinating additives can be used to tailor the characteristic properties of such porphyrinoid-based materials, including porphyrin oligomers. Bidentate ligands are one type of coordinating additive that can form coordination bonds with a central metal ion of two different porphyrinoid compounds to promote porphyrinoid alignment and/or pi-stacking. The coordinating additives can shift the absorption spectrum of a photoactive material toward higher wavelengths, increase the external quantum efficiency of the material, or both.

  18. Biological Sampling Variability Study

    Energy Technology Data Exchange (ETDEWEB)

    Amidan, Brett G. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hutchison, Janine R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2016-11-08

    There are many sources of variability that exist in the sample collection and analysis process. This paper addresses many, but not all, sources of variability. The main focus of this paper was to better understand and estimate variability due to differences between samplers. Variability between days was also studied, as well as random variability within each sampler. Experiments were performed using multiple surface materials (ceramic and stainless steel), multiple contaminant concentrations (10 spores and 100 spores), and with and without the presence of interfering material. All testing was done with sponge sticks using 10-inch by 10-inch coupons. Bacillus atrophaeus was used as the BA surrogate. Spores were deposited using wet deposition. Grime was coated on the coupons which were planned to include the interfering material (Section 3.3). Samples were prepared and analyzed at PNNL using CDC protocol (Section 3.4) and then cultured and counted. Five samplers were trained so that samples were taken using the same protocol. Each sampler randomly sampled eight coupons each day, four coupons with 10 spores deposited and four coupons with 100 spores deposited. Each day consisted of one material being tested. The clean samples (no interfering materials) were run first, followed by the dirty samples (coated with interfering material). There was a significant difference in recovery efficiency between the coupons with 10 spores deposited (mean of 48.9%) and those with 100 spores deposited (mean of 59.8%). There was no general significant difference between the clean and dirty (containing interfering material) coupons or between the two surface materials; however, there was a significant interaction between concentration amount and presence of interfering material. The recovery efficiency was close to the same for coupons with 10 spores deposited, but for the coupons with 100 spores deposited, the recovery efficiency for the dirty samples was significantly larger (65

  19. Variably insulating portable heater/cooler

    Science.gov (United States)

    Potter, T.F.

    1998-09-29

    A compact vacuum insulation panel is described comprising a chamber enclosed by two sheets of metal, glass-like spaces disposed in the chamber between the sidewalls, and a high-grade vacuum in the chamber includes apparatus and methods for enabling and disabling, or turning ``on`` and ``off`` the thermal insulating capability of the panel. One type of enabling and disabling apparatus and method includes a metal hydride for releasing hydrogen gas into the chamber in response to heat, and a hydrogen grate between the metal hydride and the chamber for selectively preventing and allowing return of the hydrogen gas to the metal hydride. Another type of enabling and disabling apparatus and method includes a variable emissivity coating on the sheets of metal in which the emissivity is controllably variable by heat or electricity. Still another type of enabling and disabling apparatus and method includes metal-to-metal contact devices that can be actuated to establish or break metal-to-metal heat paths or thermal short circuits between the metal sidewalls. 25 figs.

  20. Natural selection of mitochondria during somatic lifetime promotes healthy aging

    DEFF Research Database (Denmark)

    Rodell, Anders; Rasmussen, Lene J; Bergersen, Linda H

    2013-01-01

    Stimulation of mitochondrial biogenesis during life-time challenges both eliminates disadvantageous properties and drives adaptive selection of advantageous phenotypic variations. Intermittent fission and fusion of mitochondria provide specific targets for health promotion by brief temporal...... stressors, interspersed with periods of recovery and biogenesis. For mitochondria, the mechanisms of selection, variability, and heritability, are complicated by interaction of two independent genomes, including the multiple copies of DNA in each mitochondrion, as well as the shared nuclear genome of each...

  1. Machine learning search for variable stars

    Science.gov (United States)

    Pashchenko, Ilya N.; Sokolovsky, Kirill V.; Gavras, Panagiotis

    2018-04-01

    Photometric variability detection is often considered as a hypothesis testing problem: an object is variable if the null hypothesis that its brightness is constant can be ruled out given the measurements and their uncertainties. The practical applicability of this approach is limited by uncorrected systematic errors. We propose a new variability detection technique sensitive to a wide range of variability types while being robust to outliers and underestimated measurement uncertainties. We consider variability detection as a classification problem that can be approached with machine learning. Logistic Regression (LR), Support Vector Machines (SVM), k Nearest Neighbours (kNN), Neural Nets (NN), Random Forests (RF), and Stochastic Gradient Boosting classifier (SGB) are applied to 18 features (variability indices) quantifying scatter and/or correlation between points in a light curve. We use a subset of Optical Gravitational Lensing Experiment phase two (OGLE-II) Large Magellanic Cloud (LMC) photometry (30 265 light curves) that was searched for variability using traditional methods (168 known variable objects) as the training set and then apply the NN to a new test set of 31 798 OGLE-II LMC light curves. Among 205 candidates selected in the test set, 178 are real variables, while 13 low-amplitude variables are new discoveries. The machine learning classifiers considered are found to be more efficient (select more variables and fewer false candidates) compared to traditional techniques using individual variability indices or their linear combination. The NN, SGB, SVM, and RF show a higher efficiency compared to LR and kNN.

  2. Imaging Variable Stars with HST

    Science.gov (United States)

    Karovska, M.

    2012-06-01

    (Abstract only) The Hubble Space Telescope (HST) observations of astronomical sources, ranging from objects in our solar system to objects in the early Universe, have revolutionized our knowledge of the Universe its origins and contents. I highlight results from HST observations of variable stars obtained during the past twenty or so years. Multiwavelength observations of numerous variable stars and stellar systems were obtained using the superb HST imaging capabilities and its unprecedented angular resolution, especially in the UV and optical. The HST provided the first detailed images probing the structure of variable stars including their atmospheres and circumstellar environments. AAVSO observations and light curves have been critical for scheduling of many of these observations and provided important information and context for understanding of the imaging results of many variable sources. I describe the scientific results from the imaging observations of variable stars including AGBs, Miras, Cepheids, semiregular variables (including supergiants and giants), YSOs and interacting stellar systems with a variable stellar components. These results have led to an unprecedented understanding of the spatial and temporal characteristics of these objects and their place in the stellar evolutionary chains, and in the larger context of the dynamic evolving Universe.

  3. BLAZAR OPTICAL VARIABILITY IN THE PALOMAR-QUEST SURVEY

    International Nuclear Information System (INIS)

    Bauer, Anne; Baltay, Charles; Coppi, Paolo; Ellman, Nancy; Jerke, Jonathan; Rabinowitz, David; Scalzo, Richard

    2009-01-01

    We study the ensemble optical variability of 276 flat-spectrum radio quasars (FSRQs) and 86 BL Lacs in the Palomar-QUEST Survey with the goal of searching for common fluctuation properties, examining the range of behavior across the sample, and characterizing the appearance of blazars in such a survey so that future work can more easily identify such objects. The survey, which covers 15,000 deg 2 multiple times over 3.5 years, allows for the first ensemble blazar study of this scale. Variability amplitude distributions are shown for the FSRQ and BL Lac samples for numerous time lags, and also studied through structure function analyses. Individual blazars show a wide range of variability amplitudes, timescales, and duty cycles. Of the best-sampled objects, 35% are seen to vary by more than 0.4 mag; for these, the fraction of measurements contributing to the high-amplitude variability ranges constantly from about 5% to 80%. Blazar variability has some similarities to that of type I quasi-stellar objects (QSOs) but includes larger amplitude fluctuations on all timescales. FSRQ variability amplitudes are particularly similar to those of QSOs on timescales of several months, suggesting significant contributions from the accretion disk to the variable flux at these timescales. Optical variability amplitudes are correlated with the maximum apparent velocities of the radio jet for the subset of FSRQs with MOJAVE Very Long Baseline Array measurements, implying that the optically variable flux's strength is typically related to that of the radio emission. We also study CRATES radio-selected FSRQ candidates, which show similar variability characteristics to known FSRQs; this suggests a high purity for the CRATES sample.

  4. The effect of virtual reality on gait variability.

    Science.gov (United States)

    Katsavelis, Dimitrios; Mukherjee, Mukul; Decker, Leslie; Stergiou, Nicholas

    2010-07-01

    Optic Flow (OF) plays an important role in human locomotion and manipulation of OF characteristics can cause changes in locomotion patterns. The purpose of the study was to investigate the effect of the velocity of optic flow on the amount and structure of gait variability. Each subject underwent four conditions of treadmill walking at their self-selected pace. In three conditions the subjects walked in an endless virtual corridor, while a fourth control condition was also included. The three virtual conditions differed in the speed of the optic flow displayed as follows--same speed (OFn), faster (OFf), and slower (OFs) than that of the treadmill. Gait kinematics were tracked with an optical motion capture system. Gait variability measures of the hip, knee and ankle range of motion and stride interval were analyzed. Amount of variability was evaluated with linear measures of variability--coefficient of variation, while structure of variability i.e., its organization over time, were measured with nonlinear measures--approximate entropy and detrended fluctuation analysis. The linear measures of variability, CV, did not show significant differences between Non-VR and VR conditions while nonlinear measures of variability identified significant differences at the hip, ankle, and in stride interval. In response to manipulation of the optic flow, significant differences were observed between the three virtual conditions in the following order: OFn greater than OFf greater than OFs. Measures of structure of variability are more sensitive to changes in gait due to manipulation of visual cues, whereas measures of the amount of variability may be concealed by adaptive mechanisms. Visual cues increase the complexity of gait variability and may increase the degrees of freedom available to the subject. Further exploration of the effects of optic flow manipulation on locomotion may provide us with an effective tool for rehabilitation of subjects with sensorimotor issues.

  5. Evaluating the underlying factors behind variable rate debt.

    Science.gov (United States)

    McCue, Michael J; Kim, Tae Hyun Tanny

    2007-01-01

    Recent trends show a greater usage of variable rate debt among health care bond issues. In 2004, 63.4% of the total health care bonds issued were variable rate compared with 30.6% in 1995 (Fitch Ratings, 2005). The purpose of this study is to gain a better understanding of the underlying factors, credit spread, issue characteristics, and issuer factors behind why hospitals and health system borrowers select variable rate debt compared with fixed rate debt. From 2000 to 2004, this study sampled 230 newly issued tax-exempt bonds issued by acute care hospitals and health care systems that included both variable and fixed rate debt issues. Using a logistic regression model, hospitals with variable rate debt issues were assigned a value of 1, whereas hospitals with fixed rate debt issues were assigned a value of 0. This study found a positive association between bond insurance and variable rate debt and a negative association between callable feature and variable rate debt. Facilities located in certificate-of-need states that possessed higher case mix acuity, earned higher profit margins, generated higher debt service coverage, and held less debt were more likely to issue variable rate debt. Overall, hospital managers and board members of hospitals possessing a strong financial performance have an interest in utilizing variable rate debt to lower their cost of capital. In addition, this outcome may also reflect that investment bankers are doing a better job in educating senior hospital management about the interest rate savings benefit of variable rate compared with fixed rate debt.

  6. The glycoprotein TRP36 of Ehrlichia sp. UFMG-EV and related cattle pathogen Ehrlichia sp. UFMT-BV evolved from a highly variable clade of E. canis under adaptive diversifying selection

    Czech Academy of Sciences Publication Activity Database

    Cabezas-Cruz, A.; Valdés, James J.; de la Fuente, J.

    2014-01-01

    Roč. 7, DEC 10 2014 (2014), s. 584 ISSN 1756-3305 R&D Projects: GA MŠk(CZ) EE2.3.30.0032 Institutional support: RVO:60077344 Keywords : Ehrlichia sp. UFMG-EV * Ehrlichia sp. UFMT-BV * E. mineirensis * Host-shift * Diversifying episodic selection Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.430, year: 2014

  7. Evaluation of and quality assurance in HER2 analysis in breast carcinomas from patients registered in Danish Breast Cancer Group (DBCG) in the period of 2002-2006. A nationwide study including correlation between HER-2 status and other prognostic variables.

    Science.gov (United States)

    Rasmussen, Birgitte Bruun; Andersson, Michael; Christensen, Ib J; Møller, Susanne

    2008-01-01

    In Denmark, analysis for HER2 is situated in the pathology laboratories dealing with breast pathology. The analysis was introduced during the late 1990's, and was gradually intensified in the following years up to now. The present study deals with the experience with the analysis during the last 5 years, from 2002 - 2006. All patients, registered in DBCG (Danish Breast Cancer Group) and with a HER2-test were included. The analysis followed international recommendations, with an initial immunohistochemical (IHC) analysis with a semiquantitative grading of the reaction in four grades, 0 and 1+, defined as HER2-negative, 2+, equivocal and 3+, HER2-positive. In the 2+ group, a FISH-test was applied to identify the presence of gene amplification, defined as a ratio >/=2. We investigated the number of analyses performed, the number of positive cases and the relation between the result of IHC and the result of FISH. Furthermore we looked at the relation to other prognostic factors. The number of analyses gradually increased during the years of investigation, from 30% of patients in 2002 to 71% in 2006. The increase was seen in all laboratories resulting in all laboratories but one having a substantial number of analyses. Sixty-two percent of all cases were HER2-negative, 18% were equivocal and 21% positive in the IHC-analysis. Of the 2+, equivocal cases, 23% had gene-amplification. Thus, 23% of patients were defined as HER2-positive and eligible for treatment with trastuzumab. There was a significant correlation to other prognostic factors. The results are in accordance with what is found elsewhere. The quality of the test is further assured by all laboratories participating in external quality assurance schemes.

  8. Including climate change in energy investment decisions

    International Nuclear Information System (INIS)

    Ybema, J.R.; Boonekamp, P.G.M.; Smit, J.T.J.

    1995-08-01

    To properly take climate change into account in the analysis of energy investment decisions, it is required to apply decision analysis methods that are capable of considering the specific characteristics of climate change (large uncertainties, long term horizon). Such decision analysis methods do exist. They can explicitly include evolving uncertainties, multi-stage decisions, cumulative effects and risk averse attitudes. Various methods are considered in this report and two of these methods have been selected: hedging calculations and sensitivity analysis. These methods are applied to illustrative examples, and its limitations are discussed. The examples are (1a) space heating and hot water for new houses from a private investor perspective and (1b) as example (1a) but from a government perspective, (2) electricity production with an integrated coal gasification combined cycle (ICGCC) with or without CO 2 removal, and (3) national energy strategy to hedge for climate change. 9 figs., 21 tabs., 42 refs., 1 appendix

  9. Selected writings

    CERN Document Server

    Galilei, Galileo

    2012-01-01

    'Philosophy is written in this great book which is continually open before our eyes - I mean the universe...' Galileo's astronomical discoveries changed the way we look at the world, and our place in the universe. Threatened by the Inquisition for daring to contradict the literal truth of the Bible, Galileo ignited a scientific revolution when he asserted that the Earth moves. This generous selection from his writings contains all the essential texts for a reader to appreciate his lasting significance. Mark Davie's new translation renders Galileo's vigorous Italian prose into clear modern English, while William R. Shea's version of the Latin Sidereal Message makes accessible the book that created a sensation in 1610 with its account of Galileo's observations using the newly invented telescope. All Galileo's contributions to the debate on science and religion are included, as well as key documents from his trial before the Inquisition in 1633. A lively introduction and clear notes give an overview of Galileo's...

  10. Site selection

    International Nuclear Information System (INIS)

    Olsen, C.W.

    1983-07-01

    The conditions and criteria for selecting a site for a nuclear weapons test at the Nevada Test Site are summarized. Factors considered are: (1) scheduling of drill rigs, (2) scheduling of site preparation (dirt work, auger hole, surface casing, cementing), (3) schedule of event (when are drill hole data needed), (4) depth range of proposed W.P., (5) geologic structure (faults, Pz contact, etc.), (6) stratigraphy (alluvium, location of Grouse Canyon Tuff, etc.), (7) material properties (particularly montmorillonite and CO 2 content), (8) water table depth, (9) potential drilling problems (caving), (10) adjacent collapse craters and chimneys, (11) adjacent expended but uncollapsed sites, (12) adjacent post-shot or other small diameter holes, (13) adjacent stockpile emplacement holes, (14) adjacent planned events (including LANL), (15) projected needs of Test Program for various DOB's and operational separations, and (16) optimal use of NTS real estate

  11. Evidence from Students’ Information Seeking Diaries Underscores the Importance of Including Librarians in Undergraduate Education. A Review of: Lee, J. Y., Paik, W., & Joo, S. (2012. Information resource selection of undergraduate students in academic search tasks. Information Research, 17(1, paper511. Retrieved 8 Aug., 2012 from http://informationr.net/ir/17-1/paper511.html

    Directory of Open Access Journals (Sweden)

    Maria Melssen

    2012-12-01

    Full Text Available Objective – To determine what informationresources undergraduate students choose tocomplete assignments for their courses, whythey choose those resources, the process ofselecting those resources and the factors thatcontributed to selecting the resources, andtheir perceptions of those resources.Design – Semi-structured information seekingdiary.Setting – Private university in Seoul, Korea.Subjects – 233 undergraduate students fromall majors and all years.Methods – Students selected one assignmentfrom their elective course and recorded thefollowing in a diary: what the assignment was,the topic they needed to research to completethe assignment, resources used, the factors thatcontributed to choosing the resources, andperceptions of those resources.Main Results – Data were analyzed bothqualitatively and quantitatively. The factorsthat affected the students’ resource selectionwere analyzed qualitatively using an opencoding method created by the researchers. Thefactors were not predetermined by theresearchers, but were selected based on thefactors identified by the students. Onlineresources (67.1% were the most frequentlyselected resources by the students compared tohuman resources (11.5%, print materials (11.5%, and mass media (3%. Students used an average of 5.28 resources to complete one assignment. Factors that affected the students’ selection of resources were the type of information provided by the resource, the features of the resource, the search strategy used when searching in the resource, and the students’ interaction with other people when selecting and using the resource. More than one factor typically contributed to the students’ selection of the resource. The students’ perceptions of the resources they selected were analyzed quantitatively: perceptions were analyzed in six content areas using a five point scale. Correlations and similarities across the six content areas were also analyzed. Perceptions of resources

  12. Analysis of general and specific combining abilities of popcorn populations, including selfed parents

    Directory of Open Access Journals (Sweden)

    José Marcelo Soriano Viana

    2003-12-01

    Full Text Available Estimation of general and specific combining ability effects in a diallel analysis of cross-pollinating populations, including the selfed parents, is presented in this work. The restrictions considered satisfy the parametric values of the GCA and SCA effects. The method is extended to self-pollinating populations (suitable for other species, without the selfed parents. The analysis of changes in population means due to inbreeding (sensitivity to inbreeding also permits to assess the predominant direction of dominance deviations and the relative genetic variability in each parent population. The methodology was used to select popcorn populations for intra- and inter-population breeding programs and for hybrid production, developed at the Federal University of Viçosa, MG, Brazil. Two yellow pearl grain popcorn populations were selected.

  13. Variable importance in latent variable regression models

    NARCIS (Netherlands)

    Kvalheim, O.M.; Arneberg, R.; Bleie, O.; Rajalahti, T.; Smilde, A.K.; Westerhuis, J.A.

    2014-01-01

    The quality and practical usefulness of a regression model are a function of both interpretability and prediction performance. This work presents some new graphical tools for improved interpretation of latent variable regression models that can also assist in improved algorithms for variable

  14. Addressing Stillbirth in India Must Include Men.

    Science.gov (United States)

    Roberts, Lisa; Montgomery, Susanne; Ganesh, Gayatri; Kaur, Harinder Pal; Singh, Ratan

    2017-07-01

    Millennium Development Goal 4, to reduce child mortality, can only be achieved by reducing stillbirths globally. A confluence of medical and sociocultural factors contribute to the high stillbirth rates in India. The psychosocial aftermath of stillbirth is a well-documented public health problem, though less is known of the experience for men, particularly outside of the Western context. Therefore, men's perceptions and knowledge regarding reproductive health, as well as maternal-child health are important. Key informant interviews (n = 5) were analyzed and 28 structured interviews were conducted using a survey based on qualitative themes. Qualitative themes included men's dual burden and right to medical and reproductive decision making power. Wives were discouraged from expressing grief and pushed to conceive again. If not successful, particularly if a son was not conceived, a second wife was considered a solution. Quantitative data revealed that men with a history of stillbirths had greater anxiety and depression, perceived less social support, but had more egalitarian views towards women than men without stillbirth experience. At the same time fathers of stillbirths were more likely to be emotionally or physically abusive. Predictors of mental health, attitudes towards women, and perceived support are discussed. Patriarchal societal values, son preference, deficient women's autonomy, and sex-selective abortion perpetuate the risk for future poor infant outcomes, including stillbirth, and compounds the already higher risk of stillbirth for males. Grief interventions should explore and take into account men's perceptions, attitudes, and behaviors towards reproductive decision making.

  15. Variabilidade genética e limite da seleção em populações de diferentes tipos de acasalamento Genetic variability and selection limit in populations of different mating designs

    Directory of Open Access Journals (Sweden)

    E.E. Cunha

    2004-04-01

    Full Text Available Populações de cinco diferentes tipos de acasalamento, submetidas à seleção baseada no melhor preditor linear não-viesado (BLUP, foram avaliadas quanto às perdas genéticas por fixação de alelos desfavoráveis e limite da seleção, durante 50 gerações. Foram utilizados dados simulados na obtenção do genoma dos indivíduos de todas as populações. Uma característica quantitativa de herdabilidade 0,10 foi estudada em populações de seleção, com a seguinte estrutura de dados: razão sexual de 10, 20, 25 e 50 e tamanho efetivo da população de 36,36, 19,05, 15,38, e 7,84, respectivamente. Para cada razão sexual, formaram-se populações correspondentes aos tipos de acasalamento efetuados entre os reprodutores, em todas as gerações: acasalamentos preferenciais entre meios-irmãos e irmãos completos, acasalamentos preferenciais entre meios-irmãos, acasalamentos ao acaso, exclusão de acasalamentos entre irmãos completos e exclusão de acasalamentos entre meios-irmãos e irmãos completos. Valores percentuais mais baixos para locos fixados desfavoravelmente e limite da seleção mais alto foram observados na menor razão sexual (d= 10, na qual houve também melhor distinção entre os tipos de acasalamento estudados.Populations of five different mating designs, submitted to selection based on best linear unbiased predicto (BLUPr, were evaluated regarding to genetic losses by fixation of unfavorable alleles and selection limit, during 50 generations. Simulated data were used to obtain the genome of all individuals of the populations. A quantitative trait with heritability of 0.10 was studied in the selected populations, with the following structure: sexual ratio of 10, 20, 25, and 50 and effective population size of 36.36, 19.05, 15.38 and 7.84, respectively. For each sexual ratio different populations were generated corresponding to the following mating designs: preferential matings between half and full sibs, preferential

  16. An Efficient Method for Synthesis of Planar Multibody Systems including Shape of Bodies as Design Variables

    DEFF Research Database (Denmark)

    Hansen, Michael R.; Hansen, John Michael

    1998-01-01

    A point contact joint has been developed and implemented in a joint coordinate based planar multibody dynamics analysis program that also supports revolute and translational joints. Further, a segment library for the definition of the contours of the point contact joints has been integrated...

  17. Classification and prediction of port variables

    Energy Technology Data Exchange (ETDEWEB)

    Molina Serrano, B.

    2016-07-01

    Many variables are included in planning and management of port terminals. They can beeconomic, social, environmental and institutional. Agent needs to know relationshipbetween these variables to modify planning conditions. Use of Bayesian Networks allowsfor classifying, predicting and diagnosing these variables. Bayesian Networks allow forestimating subsequent probability of unknown variables, basing on know variables.In planning level, it means that it is not necessary to know all variables because theirrelationships are known. Agent can know interesting information about how port variablesare connected. It can be interpreted as cause-effect relationship. Bayesian Networks can beused to make optimal decisions by introduction of possible actions and utility of theirresults.In proposed methodology, a data base has been generated with more than 40 port variables.They have been classified in economic, social, environmental and institutional variables, inthe same way that smart port studies in Spanish Port System make. From this data base, anetwork has been generated using a non-cyclic conducted grafo which allows for knowingport variable relationships - parents-children relationships-. Obtained network exhibits thateconomic variables are – in cause-effect terms- cause of rest of variable typologies.Economic variables represent parent role in the most of cases. Moreover, whenenvironmental variables are known, obtained network allows for estimating subsequentprobability of social variables.It has been concluded that Bayesian Networks allow for modeling uncertainty in aprobabilistic way, even when number of variables is high as occurs in planning andmanagement of port terminals. (Author)

  18. Variable importance analysis based on rank aggregation with applications in metabolomics for biomarker discovery.

    Science.gov (United States)

    Yun, Yong-Huan; Deng, Bai-Chuan; Cao, Dong-Sheng; Wang, Wei-Ting; Liang, Yi-Zeng

    2016-03-10

    Biomarker discovery is one important goal in metabolomics, which is typically modeled as selecting the most discriminating metabolites for classification and often referred to as variable importance analysis or variable selection. Until now, a number of variable importance analysis methods to discover biomarkers in the metabolomics studies have been proposed. However, different methods are mostly likely to generate different variable ranking results due to their different principles. Each method generates a variable ranking list just as an expert presents an opinion. The problem of inconsistency between different variable ranking methods is often ignored. To address this problem, a simple and ideal solution is that every ranking should be taken into account. In this study, a strategy, called rank aggregation, was employed. It is an indispensable tool for merging individual ranking lists into a single "super"-list reflective of the overall preference or importance within the population. This "super"-list is regarded as the final ranking for biomarker discovery. Finally, it was used for biomarkers discovery and selecting the best variable subset with the highest predictive classification accuracy. Nine methods were used, including three univariate filtering and six multivariate methods. When applied to two metabolic datasets (Childhood overweight dataset and Tubulointerstitial lesions dataset), the results show that the performance of rank aggregation has improved greatly with higher prediction accuracy compared with using all variables. Moreover, it is also better than penalized method, least absolute shrinkage and selectionator operator (LASSO), with higher prediction accura