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Sample records for selecting periodic variable

  1. 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.

  2. Model selection in periodic autoregressions

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans); R. Paap (Richard)

    1994-01-01

    textabstractThis paper focuses on the issue of period autoagressive time series models (PAR) selection in practice. One aspect of model selection is the choice for the appropriate PAR order. This can be of interest for the valuation of economic models. Further, the appropriate PAR order is important

  3. Long-Period Solar Variability

    Energy Technology Data Exchange (ETDEWEB)

    GAUTHIER,JOHN H.

    2000-07-20

    Terrestrial climate records and historical observations of the Sun suggest that the Sun undergoes aperiodic oscillations in radiative output and size over time periods of centuries and millenia. Such behavior can be explained by the solar convective zone acting as a nonlinear oscillator, forced at the sunspot-cycle frequency by variations in heliomagnetic field strength. A forced variant of the Lorenz equations can generate a time series with the same characteristics as the solar and climate records. The timescales and magnitudes of oscillations that could be caused by this mechanism are consistent with what is known about the Sun and terrestrial climate.

  4. Variable-Period Undulators for Synchrotron Radiation

    Energy Technology Data Exchange (ETDEWEB)

    Shenoy, Gopal; Lewellen, John; Shu, Deming; Vinokurov, Nikolai

    2005-02-22

    A new and improved undulator design is provided that enables a variable period length for the production of synchrotron radiation from both medium-energy and high energy storage rings. The variable period length is achieved using a staggered array of pole pieces made up of high permeability material, permanent magnet material, or an electromagnetic structure. The pole pieces are separated by a variable width space. The sum of the variable width space and the pole width would therefore define the period of the undulator. Features and advantages of the invention include broad photon energy tunability, constant power operation and constant brilliance operation.

  5. Variable-Period Undulators For Synchrotron Radiation

    Science.gov (United States)

    Shenoy, Gopal; Lewellen, John; Shu, Deming; Vinokurov, Nikolai

    2005-02-22

    A new and improved undulator design is provided that enables a variable period length for the production of synchrotron radiation from both medium-energy and high-energy storage rings. The variable period length is achieved using a staggered array of pole pieces made up of high permeability material, permanent magnet material, or an electromagnetic structure. The pole pieces are separated by a variable width space. The sum of the variable width space and the pole width would therefore define the period of the undulator. Features and advantages of the invention include broad photon energy tunability, constant power operation and constant brilliance operation.

  6. Long-Period Variability in o Ceti

    Science.gov (United States)

    Templeton, Matthew R.; Karovska, Margarita

    2009-02-01

    We carried out a new and sensitive search for long-period variability in the prototype of the Mira class of long-period pulsating variables, o Ceti (Mira A), the closest and brightest Mira variable. We conducted this search using an unbroken light curve from 1902 to the present, assembled from the visual data archives of five major variable star observing organizations from around the world. We applied several time-series analysis techniques to search for two specific kinds of variability: long secondary periods (LSPs) longer than the dominant pulsation period of ~333 days, and long-term period variation in the dominant pulsation period itself. The data quality is sufficient to detect coherent periodic variations with photometric amplitudes of 0.05 mag or less. We do not find evidence for coherent LSPs in o Ceti to a limit of 0.1 mag, where the amplitude limit is set by intrinsic, stochastic, low-frequency variability of approximately 0.1 mag. We marginally detect a slight modulation of the pulsation period similar in timescale to that observed in the Miras with meandering periods, but with a much lower period amplitude of ±2 days. However, we do find clear evidence of a low-frequency power-law component in the Fourier spectrum of o Ceti's long-term light curve. The amplitude of this stochastic variability is approximately 0.1 mag at a period of 1000 days, and it exhibits a turnover for periods longer than this. This spectrum is similar to the red noise spectra observed in red supergiants.

  7. 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.

  8. Pulsation properties of Mira long period variables

    International Nuclear Information System (INIS)

    Cahn, J.H.

    1980-01-01

    A matter of great interest to variable star students concerns the mode of pulsation of Mira long period variables. In this report we first give observational evidence for the pulsation constant Q. We then compare the observations with calculations. Next, we review two interesting groups of papers dealing with hydrodynamic properties of long period variables. In the first, a fully dynamic nonlinear calculation maps out the Mira instability domain. In the second, special attention is paid to shock propagation beyond the photosphere which in large measure accounts for the complex spectra from this region. (orig./WL)

  9. 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.

  10. 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

    efficient at selecting (periodic) variable objects such as RR Lyrae.

  11. Periodicity and stability for variable-time impulsive neural networks.

    Science.gov (United States)

    Li, Hongfei; Li, Chuandong; Huang, Tingwen

    2017-10-01

    The paper considers a general neural networks model with variable-time impulses. It is shown that each solution of the system intersects with every discontinuous surface exactly once via several new well-proposed assumptions. Moreover, based on the comparison principle, this paper shows that neural networks with variable-time impulse can be reduced to the corresponding neural network with fixed-time impulses under well-selected conditions. Meanwhile, the fixed-time impulsive systems can be regarded as the comparison system of the variable-time impulsive neural networks. Furthermore, a series of sufficient criteria are derived to ensure the existence and global exponential stability of periodic solution of variable-time impulsive neural networks, and to illustrate the same stability properties between variable-time impulsive neural networks and the fixed-time ones. The new criteria are established by applying Schaefer's fixed point theorem combined with the use of inequality technique. Finally, a numerical example is presented to show the effectiveness of the proposed results. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Global Magnetic Variability at Planetary Wave Periods

    Science.gov (United States)

    Forbes, J. M.; Behm, J.

    2017-12-01

    Planetary waves (PW) and PW-tide interactions are thought to introduce multi-day periodicities ( 2-20 days) in the electric fields and currents induced by the wind dynamo mechanism in the ionospheric E-region (ca. 100-150 km), and thus can provide important insights on coupling between the lower atmosphere and the ionosphere. Previous studies have used a relatively small subset of available data to infer the existence of these variations in ground magnetic measurements. In some cases connections were made with contemporaneous measurements of neutral wind dynamics. In the present work, we employ ground-based magnetometer data from over 100 stations from the INTERMAGNET network during 2009 to gain a global perspective on eastward- and westward-propagating and zonally-symmetric oscillations with PW periods. Our presentation describes how the unevenly-spaced global data are re-gridded onto an icosahedral grid prior to analysis, and assesses how gaps in the distribution of points across the grid affect extraction of some parts of the spectrum. Consideration is also given to possible contamination by recurrent magnetic activity at subharmonics of 27 days. The global evolution of several PW components during 2009 are depicted and interpreted.

  13. 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.

  14. 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...

  15. PERIODIC AND APERIODIC VARIABILITY IN THE MOLECULAR CLOUD ρ OPHIUCHUS

    International Nuclear Information System (INIS)

    Parks, J. Robert; Plavchan, Peter; Gee, Alan H.; White, Russel J.

    2014-01-01

    Presented are the results of a near-IR photometric survey of 1678 stars in the direction of the ρ Ophiuchus (ρ Oph) star forming region using data from the 2MASS Calibration Database. For each target in this sample, up to 1584 individual J-, H-, and K s -band photometric measurements with a cadence of ∼1 day are obtained over three observing seasons spanning ∼2.5 yr; it is the most intensive survey of stars in this region to date. This survey identifies 101 variable stars with ΔK s -band amplitudes from 0.044 to 2.31 mag and Δ(J – K s ) color amplitudes ranging from 0.053 to 1.47 mag. Of the 72 young ρ Oph star cluster members included in this survey, 79% are variable; in addition, 22 variable stars are identified as candidate members. Based on the temporal behavior of the K s time-series, the variability is distinguished as either periodic, long time-scale or irregular. This temporal behavior coupled with the behavior of stellar colors is used to assign a dominant variability mechanism. A new period-searching algorithm finds periodic signals in 32 variable stars with periods between 0.49 to 92 days. The chief mechanism driving the periodic variability for 18 stars is rotational modulation of cool starspots while 3 periodically vary due to accretion-induced hot spots. The time-series for six variable stars contains discrete periodic ''eclipse-like'' features with periods ranging from 3 to 8 days. These features may be asymmetries in the circumstellar disk, potentially sustained or driven by a proto-planet at or near the co-rotation radius. Aperiodic, long time-scale variations in stellar flux are identified in the time-series for 31 variable stars with time-scales ranging from 64 to 790 days. The chief mechanism driving long time-scale variability is variable extinction or mass accretion rates. The majority of the variable stars (40) exhibit sporadic, aperiodic variability over no discernable time-scale. No chief variability mechanism

  16. PERIODIC AND APERIODIC VARIABILITY IN THE MOLECULAR CLOUD ρ OPHIUCHUS

    Energy Technology Data Exchange (ETDEWEB)

    Parks, J. Robert; Plavchan, Peter; Gee, Alan H. [Infrared Processing and Analysis Center, California Institute of Technology, Mail Code 100-22, 770 South Wilson Avenue, Pasadena, CA 91125 (United States); White, Russel J., E-mail: parksj@chara.gsu.edu [Georgia State University, Department of Physics and Astronomy, 25 Park Place, Room 605, Atlanta, GA 30303 (United States)

    2014-03-01

    Presented are the results of a near-IR photometric survey of 1678 stars in the direction of the ρ Ophiuchus (ρ Oph) star forming region using data from the 2MASS Calibration Database. For each target in this sample, up to 1584 individual J-, H-, and K{sub s} -band photometric measurements with a cadence of ∼1 day are obtained over three observing seasons spanning ∼2.5 yr; it is the most intensive survey of stars in this region to date. This survey identifies 101 variable stars with ΔK{sub s} -band amplitudes from 0.044 to 2.31 mag and Δ(J – K{sub s} ) color amplitudes ranging from 0.053 to 1.47 mag. Of the 72 young ρ Oph star cluster members included in this survey, 79% are variable; in addition, 22 variable stars are identified as candidate members. Based on the temporal behavior of the K{sub s} time-series, the variability is distinguished as either periodic, long time-scale or irregular. This temporal behavior coupled with the behavior of stellar colors is used to assign a dominant variability mechanism. A new period-searching algorithm finds periodic signals in 32 variable stars with periods between 0.49 to 92 days. The chief mechanism driving the periodic variability for 18 stars is rotational modulation of cool starspots while 3 periodically vary due to accretion-induced hot spots. The time-series for six variable stars contains discrete periodic ''eclipse-like'' features with periods ranging from 3 to 8 days. These features may be asymmetries in the circumstellar disk, potentially sustained or driven by a proto-planet at or near the co-rotation radius. Aperiodic, long time-scale variations in stellar flux are identified in the time-series for 31 variable stars with time-scales ranging from 64 to 790 days. The chief mechanism driving long time-scale variability is variable extinction or mass accretion rates. The majority of the variable stars (40) exhibit sporadic, aperiodic variability over no discernable time-scale. No chief

  17. 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.

  18. Periodic optical variability of radio-detected ultracool dwarfs

    International Nuclear Information System (INIS)

    Harding, L. K.; Golden, A.; Singh, Navtej; Sheehan, B.; Butler, R. F.; Hallinan, G.; Boyle, R. P.; Zavala, R. T.

    2013-01-01

    A fraction of very low mass stars and brown dwarfs are known to be radio active, in some cases producing periodic pulses. Extensive studies of two such objects have also revealed optical periodic variability, and the nature of this variability remains unclear. Here, we report on multi-epoch optical photometric monitoring of six radio-detected dwarfs, spanning the ∼M8-L3.5 spectral range, conducted to investigate the ubiquity of periodic optical variability in radio-detected ultracool dwarfs. This survey is the most sensitive ground-based study carried out to date in search of periodic optical variability from late-type dwarfs, where we obtained 250 hr of monitoring, delivering photometric precision as low as ∼0.15%. Five of the six targets exhibit clear periodicity, in all cases likely associated with the rotation period of the dwarf, with a marginal detection found for the sixth. Our data points to a likely association between radio and optical periodic variability in late-M/early-L dwarfs, although the underlying physical cause of this correlation remains unclear. In one case, we have multiple epochs of monitoring of the archetype of pulsing radio dwarfs, the M9 TVLM 513–46546, spanning a period of 5 yr, which is sufficiently stable in phase to allow us to establish a period of 1.95958 ± 0.00005 hr. This phase stability may be associated with a large-scale stable magnetic field, further strengthening the correlation between radio activity and periodic optical variability. Finally, we find a tentative spin-orbit alignment of one component of the very low mass binary, LP 349–25.

  19. Periodic optical variability of radio-detected ultracool dwarfs

    Energy Technology Data Exchange (ETDEWEB)

    Harding, L. K.; Golden, A.; Singh, Navtej; Sheehan, B.; Butler, R. F. [Centre for Astronomy, National University of Ireland, Galway, University Road, Galway (Ireland); Hallinan, G. [Cahill Center for Astrophysics, California Institute of Technology, 1200 East California Boulevard, MC 249-17, Pasadena, CA 91125 (United States); Boyle, R. P. [Vatican Observatory Research Group, Steward Observatory, University of Arizona, Tucson, AZ 85721 (United States); Zavala, R. T., E-mail: lkh@astro.caltech.edu [United States Naval Observatory, Flagstaff Station, Flagstaff, AZ 86001 (United States)

    2013-12-20

    A fraction of very low mass stars and brown dwarfs are known to be radio active, in some cases producing periodic pulses. Extensive studies of two such objects have also revealed optical periodic variability, and the nature of this variability remains unclear. Here, we report on multi-epoch optical photometric monitoring of six radio-detected dwarfs, spanning the ∼M8-L3.5 spectral range, conducted to investigate the ubiquity of periodic optical variability in radio-detected ultracool dwarfs. This survey is the most sensitive ground-based study carried out to date in search of periodic optical variability from late-type dwarfs, where we obtained 250 hr of monitoring, delivering photometric precision as low as ∼0.15%. Five of the six targets exhibit clear periodicity, in all cases likely associated with the rotation period of the dwarf, with a marginal detection found for the sixth. Our data points to a likely association between radio and optical periodic variability in late-M/early-L dwarfs, although the underlying physical cause of this correlation remains unclear. In one case, we have multiple epochs of monitoring of the archetype of pulsing radio dwarfs, the M9 TVLM 513–46546, spanning a period of 5 yr, which is sufficiently stable in phase to allow us to establish a period of 1.95958 ± 0.00005 hr. This phase stability may be associated with a large-scale stable magnetic field, further strengthening the correlation between radio activity and periodic optical variability. Finally, we find a tentative spin-orbit alignment of one component of the very low mass binary, LP 349–25.

  20. 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.

  1. 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.

  2. 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

  3. Selecting Full-Text Undergraduate Periodicals Databases.

    Science.gov (United States)

    Still, Julie M.; Kassabian, Vibiana

    1999-01-01

    Examines how libraries and librarians can compare full-text general periodical indices, using ProQuest Direct, Periodical Abstracts (via Ovid), and EBSCOhost as examples. Explores breadth and depth of coverage; manipulation of results (email/download/print); ease of use (searching); and indexing quirks. (AEF)

  4. note on variable incubation period within a clutch of eggs

    African Journals Online (AJOL)

    Compo Biochem. Physiol. 53A: 1-6. MENDELSOHN, 1. M., BIGOS, H. C. & LEDGER, 1. A. In press. The biology of the black-shouldered. NOTE ON VARIABLE. INCUBATION PERIOD WITHIN A. CLUTCH OF EGGS OF THE. LEOPARD TORTOISE. (GEOCHELONE P ARDALIS). (CHELONIA: CRYPTODIRA: TESTUDINIDAE).

  5. Combination spectra in long-period variable stars

    International Nuclear Information System (INIS)

    Bruce, C.E.R.

    1975-01-01

    The electrical discharge theory of the variation in excitation observed in the atmosphere of the long period variable stars offers an explanation for the combination spectra exhibited by many of these stars, which is shown to be in accord with several of the most outstanding changes in their spectra and magnitude. (author)

  6. Mass transfer and the period gap of cataclysmic variables

    International Nuclear Information System (INIS)

    Verbunt, F.

    1984-01-01

    Three different explanations for the period gap of cataclysmic variables are investigated in some detail, and compared with the observations. The static picture is ruled out; strong continued magnetic braking is shown to be unlikely; disrupted magnetic braking is shown to provide a good explanation. A simple derivation is given for the magnetic braking of a star as a function of the magnetic-field strength and the wind mass flux. A field strength of >= 100 gauss and a wind of 10 -10 Msub(solar mass) yr -1 are needed for the secondary of a cataclysmic variable to explain the braking. These values are rather high, but perhaps not unfeasible. (author)

  7. Globally exponential stability and periodic solutions of CNNS with variable coefficients and variable delays

    International Nuclear Information System (INIS)

    Liu Haifei; Wang Li

    2006-01-01

    In this Letter, by using the inequality method and the Lyapunov functional method, we analyze the globally exponential stability and the existence of periodic solutions of a class of cellular neutral networks with delays and variable coefficients. Some simple and new sufficient conditions ensuring the existence and uniqueness of globally exponential stability of periodic solutions for cellular neutral networks with variable coefficients and delays are obtained. In addition, one example is also worked out to illustrate our theory

  8. Globally exponential stability and periodic solutions of CNNS with variable coefficients and variable delays

    Energy Technology Data Exchange (ETDEWEB)

    Liu Haifei [School of Management and Engineering, Nanjing University, Nanjing 210093 (China)]. E-mail: hfliu80@126.com; Wang Li [School of Management and Engineering, Nanjing University, Nanjing 210093 (China)

    2006-09-15

    In this Letter, by using the inequality method and the Lyapunov functional method, we analyze the globally exponential stability and the existence of periodic solutions of a class of cellular neutral networks with delays and variable coefficients. Some simple and new sufficient conditions ensuring the existence and uniqueness of globally exponential stability of periodic solutions for cellular neutral networks with variable coefficients and delays are obtained. In addition, one example is also worked out to illustrate our theory.

  9. Theoretical growth rates, periods, and pulsation constants for long-period variables

    International Nuclear Information System (INIS)

    Fox, M.W.; Wood, P.R.

    1982-01-01

    Theoretical values of the growth rate, period, and pulsation constant for the first three radial pulsation modes in red giants (Population II and galactic disk) and supergiants have been derived in the linear, nonadiabatic approximation. The effects of altering the surface boundary conditions, the effective temperature (or mixing length), and the opacity in the outer layers have been explored. In the standard models, the Q-value for the first overtone can be much larger (Q 1 1 roughly-equal0.04); in addition, the Q-value for the fundamental mode is reduced from previous values, as is the period ratio P 0 /P 1 . The growth rate for the fundamental mode is found to increase with luminosity on the giant branch while the growth rate for the first overtone decreases. Dynamical instabilities found in previous adiabatic models of extreme red giants do not occur when nonadiabatic effects are included in the models. In some massive, luminous models, period ratios P 0 /P 1 approx.7 occur when P 0 approx.2000--5000 days; it is suggested that the massive galactic supergiants and carbon stars which have secondary periods Papprox.2000--7000 days and primary periods Papprox.300--700 days are first-overtone pulsators in which the long secondary periods are due to excitation of the fundamental mode. Some other consequences of the present results are briefly discussed, with particular emphasis on the mode of pulsation of the Mira variables. Subject headings: stars: long-period variables: stars: pulsation: stars: supergiants

  10. Variable stars in metal-rich globular clusters. IV. Long-period variables in NGC 6496

    Energy Technology Data Exchange (ETDEWEB)

    Abbas, Mohamad A. [Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität Heidelberg, Mönchhofstr. 12-14, D-69120 Heidelberg (Germany); Layden, Andrew C.; Guldenschuh, Katherine A. [Physics and Astronomy Department, Bowling Green State University, Bowling Green, OH 43403 (United States); Reichart, D. E.; Ivarsen, K. M.; Haislip, J. B.; Nysewander, M. C.; LaCluyze, A. P. [Department of Physics and Astronomy, University of North Carolina, Chapel Hill, NC 27599 (United States); Welch, Douglas L., E-mail: mabbas@ari.uni-heidelberg.de, E-mail: laydena@bgsu.edu [Department of Physics and Astronomy, McMaster University, Hamilton, Ontario, L8 S 4M1 (Canada)

    2015-02-01

    We present VI-band photometry for stars in the metal-rich globular cluster NGC 6496. Our time-series data were cadenced to search for long-period variables (LPVs) over a span of nearly two years, and our variability search yielded the discovery of 13 new variable stars, of which 6 are LPVs, 2 are suspected LPVs, and 5 are short-period eclipsing binaries. An additional star was found in the ASAS database, and we clarify its type and period. We argue that all of the eclipsing binaries are field stars, while five to six of the LPVs are members of NGC 6496. We compare the period–luminosity distribution of these LPVs with those of LPVs in the Large Magellanic Cloud and 47 Tucanae, and with theoretical pulsation models. We also present a VI color–magnitude diagram, display the evolutionary states of the variables, and match isochrones to determine a reddening of E(B−V)= 0.21±0.02 mag and apparent distance modulus of 15.60±0.15 mag.

  11. Modeling and designing of variable-period and variable-pole-number undulator

    Directory of Open Access Journals (Sweden)

    I. Davidyuk

    2016-02-01

    Full Text Available The concept of permanent-magnet variable-period undulator (VPU was proposed several years ago and has found few implementations so far. The VPUs have some advantages as compared with conventional undulators, e.g., a wider range of radiation wavelength tuning and the option to increase the number of poles for shorter periods. Both these advantages will be realized in the VPU under development now at Budker INP. In this paper, we present the results of 2D and 3D magnetic field simulations and discuss some design features of this VPU.

  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. Atmospheric kinematics of high velocity long period variables

    International Nuclear Information System (INIS)

    Willson, L.A.

    1982-01-01

    Radial velocities of atomic absorption lines of three long period variables, RT Cyg, Z Oph and S Car, have been analysed in order to understand velocity gradients and discontinuities in their atmospheres. Phase coverage is from five days before maximum to 73 days after maximum for RT Cyg, from 17 days before to 44 days after maximum for Z Oph, and at 9 days before maximum for S Car. On a few spectrograms double lines were seen. All spectrograms were analysed by a four-parameter regression programme to yield the dependence of the radial velocity on the excitation potential, first ionization potential, wavelength and line strength, as indicators of the depth of line formation. The data were analysed to yield the velocity discontinuity across shock waves and velocity gradients between shock waves. Near maximum light the radial velocities cannot be understood by the presence of one shock only but rather require two shocks. The lower shock becomes apparent at the longer wavelengths. Consistent parameters are obtained if these stars are fundamental mode pulsators with total masses in the range of 0.5 to 1.0 solar mass and effective radii in the range of 0.85 to 1.5 x 10 13 cm. (author)

  14. 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,

  15. 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.

  16. Periodic radio variability in NRAO 530: phase dispersion minimization analysis

    International Nuclear Information System (INIS)

    Lu Junchao; Lin Jiming; Qiu Hongbing; Wang Junyi; An Tao

    2012-01-01

    A periodicity analysis of the radio light curves of the blazar NRAO 530 at 14.5, 8.0, and 4.8 GHz is presented employing an improved phase dispersion minimization technique. The result, which shows two persistent periodic components of ∼ 6 and ∼ 10 yr at all three frequencies, is consistent with the results obtained with the Lomb-Scargle periodogram and weighted wavelet Z-transform algorithms. The reliability of the derived periodicities is confirmed by the Monte Carlo numerical simulations which show a high statistical confidence. (Quasi-)Periodic fluctuations of the radio luminosity of NRAO 530 might be associated with the oscillations of the accretion disk triggered by hydrodynamic instabilities of the accreted flow. (research papers)

  17. EXPLORING THE VARIABLE SKY WITH LINEAR. III. CLASSIFICATION OF PERIODIC LIGHT CURVES

    Energy Technology Data Exchange (ETDEWEB)

    Palaversa, Lovro; Eyer, Laurent; Rimoldini, Lorenzo [Observatoire Astronomique de l' Université de Genève, 51 chemin des Maillettes, CH-1290 Sauverny (Switzerland); Ivezić, Željko; Loebman, Sarah; Hunt-Walker, Nicholas; VanderPlas, Jacob; Westman, David; Becker, Andrew C. [Department of Astronomy, University of Washington, P.O. Box 351580, Seattle, WA 98195-1580 (United States); Ruždjak, Domagoj; Sudar, Davor; Božić, Hrvoje [Hvar Observatory, Faculty of Geodesy, Kačićeva 26, 10000 Zagreb (Croatia); Galin, Mario [Faculty of Geodesy, Kačićeva 26, 10000 Zagreb (Croatia); Kroflin, Andrea; Mesarić, Martina; Munk, Petra; Vrbanec, Dijana [Department of Physics, Faculty of Science, University of Zagreb, Bijenička cesta 32, 10000 Zagreb (Croatia); Sesar, Branimir [Division of Physics, Mathematics, and Astronomy, Caltech, Pasadena, CA 91125 (United States); Stuart, J. Scott [Lincoln Laboratory, Massachusetts Institute of Technology, 244 Wood Street, Lexington, MA 02420-9108 (United States); Srdoč, Gregor, E-mail: lovro.palaversa@unige.ch [Saršoni 90, 51216 Viškovo (Croatia); and others

    2013-10-01

    We describe the construction of a highly reliable sample of ∼7000 optically faint periodic variable stars with light curves obtained by the asteroid survey LINEAR across 10,000 deg{sup 2} of the northern sky. The majority of these variables have not been cataloged yet. The sample flux limit is several magnitudes fainter than most other wide-angle surveys; the photometric errors range from ∼0.03 mag at r = 15 to ∼0.20 mag at r = 18. Light curves include on average 250 data points, collected over about a decade. Using Sloan Digital Sky Survey (SDSS) based photometric recalibration of the LINEAR data for about 25 million objects, we selected ∼200,000 most probable candidate variables with r < 17 and visually confirmed and classified ∼7000 periodic variables using phased light curves. The reliability and uniformity of visual classification across eight human classifiers was calibrated and tested using a catalog of variable stars from the SDSS Stripe 82 region and verified using an unsupervised machine learning approach. The resulting sample of periodic LINEAR variables is dominated by 3900 RR Lyrae stars and 2700 eclipsing binary stars of all subtypes and includes small fractions of relatively rare populations such as asymptotic giant branch stars and SX Phoenicis stars. We discuss the distribution of these mostly uncataloged variables in various diagrams constructed with optical-to-infrared SDSS, Two Micron All Sky Survey, and Wide-field Infrared Survey Explorer photometry, and with LINEAR light-curve features. We find that the combination of light-curve features and colors enables classification schemes much more powerful than when colors or light curves are each used separately. An interesting side result is a robust and precise quantitative description of a strong correlation between the light-curve period and color/spectral type for close and contact eclipsing binary stars (β Lyrae and W UMa): as the color-based spectral type varies from K4 to F5, the

  18. A selection of Slovenian literary heroes for the preschool period

    OpenAIRE

    Dolinar, Ana

    2014-01-01

    In preschools, Slovenian literary heroes are being displaced by foreign fantastic heroes that impress children via cartoons, magazines and video games. Slovenian heroes are an important part of our culture and can act as companions of sorts within citizenship education of youngsters. This thesis should serve as a promotion of Slovenian literary heroes for children of all ages, beginning with the preschool period. The thesis defines the selection criterion of characters; it introduces their st...

  19. Periodical cicadas use light for oviposition site selection.

    Science.gov (United States)

    Yang, Louie H

    2006-12-07

    Organisms use incomplete information from local experience to assess the suitability of potential habitat sites over a wide range of spatial and temporal scales. Although ecologists have long recognized the importance of spatial scales in habitat selection, few studies have investigated the temporal scales of habitat selection. In particular, cues in the immediate environment may commonly provide indirect information about future habitat quality. In periodical cicadas (Magicicada spp.), oviposition site selection represents a very long-term habitat choice. Adult female cicadas insert eggs into tree branches during a few weeks in the summer of emergence, but their oviposition choices determine the underground habitats of root-feeding nymphs over the following 13 or 17 years. Here, field experiments are used to show that female cicadas use the local light environment of host trees during the summer of emergence to select long-term host trees. Light environments may also influence oviposition microsite selection within hosts, suggesting a potential behavioural mechanism for associating solar cues with host trees. In contrast, experimental nutrient enrichment of host trees did not influence cicada oviposition densities. These findings suggest that the light environments around host trees may provide a robust predictor of host tree quality in the near future. This habitat selection may influence the spatial distribution of several cicada-mediated ecological processes in eastern North American forests.

  20. 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.

  1. The pulsation mode and period-luminosity relationship of cool variables in globular clusters

    International Nuclear Information System (INIS)

    Whitelock, P.A.

    1986-01-01

    The period-luminosity-temperature relationship for globular cluster red and yellow variables is examined. The results suggest that the higher temperature, more metal-deficient cluster variables pulsate in the fundamental mode, while the lower temperature more metal-rich variables pulsate in the first overtone. On the assumption that this is correct, a relationship between fundamental period and bolometric magnitude is derived for cluster variables with observed periods of between 1 and 300 days. (author)

  2. Nonlinear periodic waves in dusty plasma with variable dust charge

    International Nuclear Information System (INIS)

    Yadav, Lakhan Lal; Bharuthram, R.

    2002-01-01

    Using the reductive perturbation method, we present a theory of nonlinear periodic waves, viz. the cnoidal waves, in a dusty plasma consisting of electrons, ions, and cold dust grains with charge fluctuations, which in the limiting case reduce to dust acoustic solitons. It is found that the frequency of the dust acoustic cnoidal wave increases with its amplitude. The dust charge fluctuations are found to affect the characteristics of the cnoidal waves

  3. Northern Hemisphere moisture variability during the Last Glacial period

    Science.gov (United States)

    Asmerom, Y.; Polyak, V. J.; Lachniet, M. S.

    2013-12-01

    It was previously shown that large oxygen isotope variability related to changing moisture sources in the southwestern United States (SW) match the Greenland ice core temperature record. The variations were attributed to changes in the ratio of winter to summer precipitation delivered to the SW, with lighter winter δ18O values compared to summer monsoon rainfall, due to meridonial shifts in the position of the polar jet stream, which directs winter storm tracks. Cold stadial δ18O excursions are associated with strongly negative values, while interstadials have higher than average δ18O values. Although these data documented moisture source variability to the SW, the question of effective moisture variability remains unanswered. Here we present new high-resolution δ18O and δ13C isotopic data from a precisely dated speleothem, FS-AH1, from Fort Stanton Cave, New Mexico USA. The sample grew continuously between 47.6 and 11.1 kyr. The new chronology is more precise than previous work due to high sample growth rate, new gains in efficiency provided by our upgraded Neptune MC-ICPMS and new more precise determinations of the half-lives of 230Th and 234U. The FS-AH1 δ18O and the Greenland δ18O data (on the GICC05 time scale) show a remarkable match, both with respect to stadials/interstadial amplitudes and variability, and in the overall long-term trend. Our interpretation of the δ18O data remains the same, an indicator of moisture source variability. The δ18O and δ13C isotopic data show no correlation (R2 effective moisture in the soil zone overlying the cave, with low δ13C attributed to high soil productivity, high effective moisture, and wet conditions. The stadial and interstadial events are expressed mutely, if at all, in the δ13C data, while the secular variation follows the change in Northern Hemisphere summer insolation (insolation), similar to other Northern Hemisphere data, such as the strength of the East Asian summer monsoon as recorded in the Hulu

  4. Selective loads periodization attenuates biochemical disturbances and enhances performance in female futsal players during competitive season

    Directory of Open Access Journals (Sweden)

    Ricelli Endrigo Ruppel da Rocha

    2015-06-01

    Full Text Available This study evaluated the effect of selective loads periodization on physical performance and biochemical parameters in professional female futsal players during competitive season. Twelve elite female futsal players from Kindermann team (Brazil participated in the study. Variables of physical performance and erythrogram, leukogram, plasma cortisol, plasma immunoglobulin A (IgA in the beginning of the preparatory period (PP, in the competitive period (CP and in the final competitive period (FCP were evaluated. Using selective loads periodization, all variables of physical performance increased (p < .01 during CP and were maintained during FCP (p < .05. White blood cells did not modify during CP and the increase of FCP in 28% remained within normal ranges. Plasma cortisol also increased during CP (p < .01 and was within the normal ranges during FCP. Plasma IgA also was within the normal ranges during CP and FCP. Selective loads periodization is adequate and attends the requirements of the sport during competitive season in female futsal players.

  5. Opportunistic relaying in multipath and slow fading channel: Relay selection and optimal relay selection period

    KAUST Repository

    Sungjoon Park,

    2011-11-01

    In this paper we present opportunistic relay communication strategies of decode and forward relaying. The channel that we are considering includes pathloss, shadowing, and fast fading effects. We find a simple outage probability formula for opportunistic relaying in the channel, and validate the results by comparing it with the exact outage probability. Also, we suggest a new relay selection algorithm that incorporates shadowing. We consider a protocol of broadcasting the channel gain of the previously selected relay. This saves resources in slow fading channel by reducing collisions in relay selection. We further investigate the optimal relay selection period to maximize the throughput while avoiding selection overhead. © 2011 IEEE.

  6. Directed selective-tunneling of bosons with periodically modulated interaction

    International Nuclear Information System (INIS)

    Lu, Gengbiao; Fu, Li-Bin; Hai, Wenhua; Zou, Mingliang; Guo, Yu

    2015-01-01

    We study the tunneling dynamics of bosons with periodically modulated interaction held in a triple-well potential. In high-frequency approximation, we derive a set of reduced coupled equations and the corresponding Floquet solutions are obtained. Based on the analytical results and their numerical correspondence, the directed selective-tunneling effect of a single atom is demonstrated when all bosons are prepared in middle well initially. A scheme for separating a single atom from N bosons is presented, in which the atom can be trapped in right or left well by adjusting the modulation strength. - Highlights: • The Floquet solutions in a modulating triple-well are obtained analytically. • The directed selective-tunneling effect of a single atom is demonstrated. • We present a manipulation scheme for separating a single atom from N bosons

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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)

  12. 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

  13. Computing Optical Variable Periods of BL Lac Object S5 0716+ 714 ...

    Indian Academy of Sciences (India)

    Computing Optical Variable Periods of BL Lac Object S5 0716+ 714 ... The study of long-term periodical variation is an important way to get the charac- ... continuous Fourier transform together, define a window function, and finally obtain.

  14. 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.

  15. Period of Light Variability in BL Lac ON 231 Xu Yun Bing1, Zhang ...

    Indian Academy of Sciences (India)

    period light variability may be greater than the current observation history and needs further monitoring certification (Zhang et al. 1998). To establish the real periods of ON 231, we employ wavelet analysis and DCF method to search a periodicity in the light curves. 2. Periodicity analysis of ON231. 2.1 Light curve of ON 231.

  16. 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.

  17. 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/.

  18. 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.

  19. 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.

  20. 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....

  1. 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.

  2. 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.

  3. 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

  4. Period changes of cataclysmic variables below the period gap: V2051 Oph, OY Car and Z Cha

    Science.gov (United States)

    Pilarčík, L.; Wolf, M.; Zasche, P.; Vraštil, J.

    2018-04-01

    We present our results of a long-term monitoring of cataclysmic variable stars (CVs). About 40 new eclipses were measured for the three southern SU UMa-type eclipsing CVs: V2051 Oph, OY Car and Z Cha. Based on the current O - C diagrams we confirmed earlier findings that V2051 Oph and OY Car present cyclic changes of their orbital periods lasting 25 and 29 years, respectively. In case of Z Cha we propose the light-time effect caused probably by a presence of the third component orbiting the eclipsing CV with the period of 43.5 years. The minimal mass of this companion results about 15 MJup.

  5. Eight to 14 μm spectral monitoring of long period variable stars with GLADYS.

    Science.gov (United States)

    Levan, P. D.; Sloan, G.; Grasdalen, G.

    The authors describe an ongoing program of spectral monitoring of long period variable stars using GLADYS, a long slit prism spectrometer that employs a 58x62 pixel Si:Ga detector array. The goal is to compare the equivalent widths of the SiC emission features in carbon-rich circumstellar shells, and the silicate emission features in oxygen-rich circumstellar stars, obtained over different phases of the continuum variability cycle. Spectra of long period variables and low amplitude variables recently obtained on the Wyoming Infrared Observatory 2.3 m telescope are presented.

  6. PERIODIC VARIABILITY OF LOW-MASS STARS IN SLOAN DIGITAL SKY SURVEY STRIPE 82

    International Nuclear Information System (INIS)

    Becker, A. C.; Hawley, S. L.; Ivezic, Z.; Kowalski, A. F.; Sesar, B.; Bochanski, J. J.; West, A. A.

    2011-01-01

    We present a catalog of periodic stellar variability in the 'Stripe 82' region of the Sloan Digital Sky Survey. After aggregating and re-calibrating catalog-level data from the survey, we ran a period-finding algorithm (Supersmoother) on all point-source light curves. We used color selection to identify systems that are likely to contain low-mass stars, in particular M dwarfs and white dwarfs. In total, we found 207 candidates, the vast majority of which appear to be in eclipsing binary systems. The catalog described in this paper includes 42 candidate M dwarf/white dwarf pairs, four white dwarf pairs, 59 systems whose colors indicate they are composed of two M dwarfs and whose light-curve shapes suggest they are in detached eclipsing binaries, and 28 M dwarf systems whose light-curve shapes suggest they are in contact binaries. We find no detached systems with periods longer than 3 days, thus the majority of our sources are likely to have experienced orbital spin-up and enhanced magnetic activity. Indeed, 26 of 27 M dwarf systems that we have spectra for show signs of chromospheric magnetic activity, far higher than the 24% seen in field stars of the same spectral type. We also find binaries composed of stars that bracket the expected boundary between partially and fully convective interiors, which will allow the measurement of the stellar mass-radius relationship across this transition. The majority of our contact systems have short orbital periods, with small variance (0.02 days) in the sample near the observed cutoff of 0.22 days. The accumulation of these stars at short orbital period suggests that the process of angular momentum loss, leading to period evolution, becomes less efficient at short periods. These short-period systems are in a novel regime for studying the effects of orbital spin-up and enhanced magnetic activity, which are thought to be the source of discrepancies between mass-radius predictions and measurements of these properties in eclipsing

  7. A period-luminosity relation for supergiant red variables in the Large Magellanic Cloud

    International Nuclear Information System (INIS)

    Feast, M.W.; Catchpole, R.M.; Carter, B.S.; Roberts, G.

    1980-01-01

    Infrared photometry for 24 red supergiant variables in the LMC is used to derive bolometric magnitudes. The existence of a period-luminosity relation for these stars is demonstrated and compared with theory. (author)

  8. 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.

  9. The Properties of Long Period Variables in the LMC from MACHO

    Energy Technology Data Exchange (ETDEWEB)

    Fraser, O J; Hawley, S L; Cook, K H

    2008-05-06

    We present a new analysis of the long period variables in the Large Magellanic Cloud from the MACHO Variable Star Catalog. Three-quarters of our sample of evolved, variable stars have periodic light curves. We characterize the stars in our sample using the multiple periods found in their frequency spectra. Additionally, we use single-epoch 2MASS measurements to construct the average infrared light curves for different groups of these stars. Comparison with evolutionary models shows that stars on the RGB or the Early AGB often show non-periodic variability, but begin to pulsate with periods on the two shortest period-luminosity sequences (1 & 2) when they brighten to K{sub s} {approx} 13. The stars on the Thermally Pulsing AGB are more likely to pulsate with longer periods that lie on the next two P-L sequences (3 & 4), including the sequence associated with the Miras in the LMC. The Petersen diagram and its variants show that multi-periodic stars on each pair of these sequences (3 & 4, and 1 & 2), typically pulsate with periods associated only with that pair. The periods in these multi-periodic stars become longer and stronger as the star evolves. We further constrain the mechanism behind the long secondary periods (LSPs) seen in half of our sample, and find that there is a close match between the luminosity functions of the LSP stars and all of the stars in our sample, and that these star's pulsation amplitudes are relatively wavelength independent. Although this is characteristic of stellar multiplicity, the large number of these variables is problematic for that explanation.

  10. Methods for the Quasi-Periodic Variability Analysis in Blazars Y. Liu ...

    Indian Academy of Sciences (India)

    the variability analysis in blazars in optical and radio bands, to search for possible quasi-periodic signals. 2. Power spectral density (PSD). In statistical signal processing and physics, the power spectral density (PSD) is a positive real function of a frequency variable associated with a stationary stochas- tic process. Intuitively ...

  11. 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.

  12. Seasonal precipitation extreme indices in mainland Portugal: trends and variability in the period 1941-2007

    Science.gov (United States)

    Santo, Fátima E.; Ramos, Alexandre M.; de Lima, M. Isabel P.; Trigo, Ricardo M.

    2013-04-01

    Changes in the precipitation regimes are expected to be accompanied by variations in the occurrence of extreme events, which in turn could be related to low frequency variability. The impact on the society and environment requires that the regional specificities are understood. For mainland Portugal, this work reports the results of the analysis of trends in selected precipitation indices calculated from daily precipitation data from 57 meteorological stations, recorded in the period 1941-2007; additionally we have also investigated the correlations between these indices and several modes of low frequency variability over the area. We focus on exploring regional differences and seasonal variations in the intensity, frequency and duration of extreme precipitation events. The precipitation indices were assessed at the seasonal scale and calculated at both the station and regional scales. Results sometimes highlight marked changes in seasonal precipitation and show that: i) trends in spring and autumn have opposite signals: statistically significant drying trends in the spring are accompanied by a reduction in precipitation extremes; in autumn, wetting trends are detected for all precipitation indices, although overall they are not significant at the 5% level; ii) there seems to be a tendency for a reduction in the duration of the rainy season; iii) the North Atlantic Oscillation (NAO) is the mode of variability that has the highest influence on precipitation extremes over mainland Portugal, particularly in the winter and autumn, and is one of the most important teleconnection patterns in all seasons. This work was partially supported by FEDER (Fundo Europeu de Desenvolvimento Regional) funds through the COMPETE (Programa Operacional Factores de Competitividade) and by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) through project STORMEx FCOMP-01-0124-FEDER-019524 (PTDC/AAC-CLI/121339/2010).

  13. Global stability of almost periodic solution of shunting inhibitory cellular neural networks with variable coefficients

    International Nuclear Information System (INIS)

    Chen Ling; Zhao Hongyong

    2008-01-01

    The paper investigates the almost periodicity of shunting inhibitory cellular neural networks with delays and variable coefficients. Several sufficient conditions are established for the existence and globally exponential stability of almost periodic solutions by employing fixed point theorem and differential inequality technique. The results of this paper are new and they complement previously known results

  14. Period--luminosity--color relations and pulsation modes of pulsating variable stars

    International Nuclear Information System (INIS)

    Breger, M.; Bregman, J.N.

    1975-01-01

    The periods of delta Scuti, RR Lyrae, dwarf Cepheid, and W Virginis variables have been investigated for their dependence on luminosity, color, mass, and pulsation modes. A maximum-likelihood method, which includes consideration of the observational errors in each coordinate, has been applied to obtain observational period-luminosity-color (P-L-C) relations

  15. 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.

  16. 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

  17. 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.

  18. 6-year periodicity and variable synchronicity in a mass-flowering plant.

    Directory of Open Access Journals (Sweden)

    Satoshi Kakishima

    Full Text Available Periodical organisms, such as bamboos and periodical cicadas, are very famous for their synchronous reproduction. In bamboos and other periodical plants, the synchronicity of mass-flowering and withering has been often reported indicating these species are monocarpic (semelparous species. Therefore, synchronicity and periodicity are often suspected to be fairly tightly coupled traits in these periodical plants. We investigate the periodicity and synchronicity of Strobilanthes flexicaulis, and a closely related species S. tashiroi on Okinawa Island, Japan. The genus Strobilanthes is known for several periodical species. Based on 32-year observational data, we confirmed that S. flexicaulis is 6-year periodical mass-flowering monocarpic plant. All the flowering plants had died after flowering. In contrast, we found that S. tashiroi is a polycarpic perennial with no mass-flowering from three-year individual tracking. We also surveyed six local populations of S. flexicaulis and found variation in the synchronicity from four highly synchronized populations (>98% of plants flowering in the mass year to two less synchronized one with 11-47% of plants flowering before and after the mass year. This result might imply that synchrony may be selected for when periodicity is established in monocarpic species. We found the selective advantages for mass-flowering in pollinator activities and predator satiation. The current results suggest that the periodical S. flexicaulis might have evolved periodicity from a non-periodical close relative. The current report should become a key finding for understanding the evolution of periodical plants.

  19. 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.

  20. 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.

  1. 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 ...

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Model atmospheres with periodic shocks. [pulsations and mass loss in variable stars

    Science.gov (United States)

    Bowen, G. H.

    1989-01-01

    The pulsation of a long-period variable star generates shock waves which dramatically affect the structure of the star's atmosphere and produce conditions that lead to rapid mass loss. Numerical modeling of atmospheres with periodic shocks is being pursued to study the processes involved and the evolutionary consequences for the stars. It is characteristic of these complex dynamical systems that most effects result from the interaction of various time-dependent processes.

  7. Acute Phase Proteins and Variables of Protein Metabolism in Dairy Cows during the Pre- and Postpartal Period

    Directory of Open Access Journals (Sweden)

    Cs. Tóthová

    2008-01-01

    Full Text Available The objective of the present study was to compare the concentrations of acute phase proteins and selected variables of protein metabolism in dairy cows of the Slovak Spotted breed from 4 weeks before parturition to 10 weeks after parturition. Acute phase proteins - haptoglobin (Hp and serum amyloid A (SAA - and variables of protein metabolism - total proteins, albumin, urea, creatinine, total immunoglobulins - were evaluated in blood serum. Significant differences were found in average values of the Hp and SAA concentrations in several groups during the monitored period (P P P P P P P P P < 0.001. The above mentioned results indicate that in the time around parturition there are significant changes in concentrations of acute phase proteins, as well as in the whole protein metabolism of dairy cows. These facts suggest that the postparturient period is a critical biological phase, throughout which there is the highest incidence of metabolic disorders.

  8. 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

  9. 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.

  10. Existence and global attractivity of positive periodic solution for competition-predator system with variable delays

    International Nuclear Information System (INIS)

    Zhao Hongyong; Ding Nan

    2006-01-01

    In this paper, Lotka-Volterra competition-predator system with variable delays is considered. Some sufficient conditions ensuring the existence and global attractivity of periodic solution for this system are obtained by using coincidence degree theory and Lyapunov functional method. An example is also worked out to demonstrate the advantages of our results

  11. Heart period variability and psychopathology in urban boys at risk for delinquency.

    Science.gov (United States)

    Pine, D S; Wasserman, G A; Miller, L; Coplan, J D; Bagiella, E; Kovelenku, P; Myers, M M; Sloan, R P

    1998-09-01

    To examine associations between heart period variability (HPV) and psychopathology in young urban boys at risk for delinquency, a series of 697-11-year-old younger brothers of adjudicated delinquents received a standardized psychiatric evaluation and an assessment of heart period variability (HPV). Psychiatric symptoms were rated in two domains: externalizing and internalizing psychopathology. Continuous measures of both externalizing and internalizing psychopathology were associated with reductions in HPV components related to parasympathetic activity. These associations could not be explained by a number of potentially confounding variables, such as age, ethnicity, social class, body size, or family history of hypertension. Although familial hypertension predicted reduced HPV and externalizing psychopathology, associations between externalizing psychopathology and HPV were independent of familial hypertension. Psychiatric symptoms are associated with reduced HPV in young urban boys at risk for delinquency.

  12. SPECTROSCOPIC ORBITAL PERIODS FOR 29 CATACLYSMIC VARIABLES FROM THE SLOAN DIGITAL SKY SURVEY

    Energy Technology Data Exchange (ETDEWEB)

    Thorstensen, John R.; Taylor, Cynthia J.; Peters, Christopher S.; Skinner, Julie N. [Department of Physics and Astronomy 6127 Wilder Laboratory, Dartmouth College Hanover, NH 03755-3528 (United States); Southworth, John [Astrophysics Group Keele University Staffordshire ST5 5BG (United Kingdom); Gänsicke, Boris T. [Department of Physics University of Warwick Coventry CV4 7AL (United Kingdom)

    2015-04-15

    We report follow-up spectroscopy of 29 cataclysmic variables from the Sloan Digital Sky Survey (SDSS), 22 of which were discovered by SDSS and seven of which are previously known systems that were recovered in SDSS. The periods for 16 of these objects were included in the tabulation by Gänsicke et al. While most of the systems have periods less than 2 hr, only one has a period in the 80–86 minutes “spike” found by Gänsicke et al., and 11 have periods longer than 3 hr, indicating that the present sample is skewed toward longer-period, higher-luminosity objects. Seven of the objects have spectra resembling dwarf novae, but have apparently never been observed in outburst, suggesting that many cataclysmics with relatively low variability amplitude remain to be discovered. Some of the objects are notable. SDSS J07568+0858 and SDSS J08129+1911 were previously known to have deep eclipses; in addition to spectroscopy, we use archival data from the Catalina Real Time Transient Survey to refine their periods. We give a parallax-based distance of 195 (+54, −39) pc for LV Cnc (SDSS J09197+0857), which at P{sub orb} = 81 m has the shortest orbital period in our sample. SDSS J08091+3814 shows both the spectroscopic phase offset and phase-dependent absorption found in SW Sextantis stars. The average spectra of SDSS J08055+0720 and SDSS J16191+1351 show contributions from K-type secondaries, and SDSS J080440+0239 shows a contribution from an early M star. We use these to constrain the distances. SDSS J09459+2922 has characteristics typical of a magnetic system. SDSS11324+6249 may be a novalike variable, and if so, its orbital period (99 minutes) is unusually short for that subclass.

  13. 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...

  14. 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

  15. Behavior of Stock Price Variability over Trading and Nontrading Periods, and Daily Return Volatility

    Directory of Open Access Journals (Sweden)

    Sumiyana Sumiyana

    2007-09-01

    This study concludes that return variance over trading and nontrading periods, along with overnight and lunch break nontrading session, and the first and second trading session, has differed significantly. In addition, daily return volatility is also not identical significantly. Subsequently, this study used size, trading volume, bid-ask spreads and up-down market as control variables. This study contradicts to all prior studies. This study especially suggests contra evidence in comparisons with previous concepts and theories in regards to size, trading volume, bid-ask spreads, and up-down market as control variables.

  16. Complexity analyses show two distinct types of nonlinear dynamics in short heart period variability recordings

    Science.gov (United States)

    Porta, Alberto; Bari, Vlasta; Marchi, Andrea; De Maria, Beatrice; Cysarz, Dirk; Van Leeuwen, Peter; Takahashi, Anielle C. M.; Catai, Aparecida M.; Gnecchi-Ruscone, Tomaso

    2015-01-01

    Two diverse complexity metrics quantifying time irreversibility and local prediction, in connection with a surrogate data approach, were utilized to detect nonlinear dynamics in short heart period (HP) variability series recorded in fetuses, as a function of the gestational period, and in healthy humans, as a function of the magnitude of the orthostatic challenge. The metrics indicated the presence of two distinct types of nonlinear HP dynamics characterized by diverse ranges of time scales. These findings stress the need to render more specific the analysis of nonlinear components of HP dynamics by accounting for different temporal scales. PMID:25806002

  17. 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.

  18. Heart rate variability during pre-competition and competition periods in volleyball players

    OpenAIRE

    Podstawski Robert; Boraczyński Michał; Nowosielska-Swadźba Danuta; Zwolińska Danuta

    2014-01-01

    Study aim: Regular exercise training is thought to modify cardiac autonomic control. One of the body’s responses to training stimuli is heart rate variability (HRV). The use of HRV in the management of sport training is a common practice. The objective of the present study was to assess the impact of the physical activity level on HRV of 1st league national volleyball players prior to and during the competition period.

  19. Heart rate variability during pre-competition and competition periods in volleyball players

    Directory of Open Access Journals (Sweden)

    Podstawski Robert

    2014-01-01

    Full Text Available Study aim: Regular exercise training is thought to modify cardiac autonomic control. One of the body’s responses to training stimuli is heart rate variability (HRV. The use of HRV in the management of sport training is a common practice. The objective of the present study was to assess the impact of the physical activity level on HRV of 1st league national volleyball players prior to and during the competition period.

  20. A MODEL FOR (QUASI-)PERIODIC MULTIWAVELENGTH PHOTOMETRIC VARIABILITY IN YOUNG STELLAR OBJECTS

    Energy Technology Data Exchange (ETDEWEB)

    Kesseli, Aurora Y. [Boston University, 725 Commonwealth Ave, Boston, MA 02215 (United States); Petkova, Maya A.; Wood, Kenneth; Gregory, Scott G. [SUPA, School of Physics and Astronomy, University of St Andrews, North Haugh, St Andrews, Fife, KY16 9AD (United Kingdom); Whitney, Barbara A. [Department of Astronomy, University of Wisconsin-Madison, 475 N. Charter St, Madison, WI 53706 (United States); Hillenbrand, L. A. [Astronomy Department, California Institute of Technology, Pasadena, CA 91125 (United States); Stauffer, J. R.; Morales-Calderon, M.; Rebull, L. [Spitzer Science Center, California Institute of Technology, CA 91125 (United States); Alencar, S. H. P., E-mail: aurorak@bu.com [Departamento de Física—ICEx—UFMG, Av. Antônio Carlos, 6627, 30270-901, Belo Horizonte, MG (Brazil)

    2016-09-01

    We present radiation transfer models of rotating young stellar objects (YSOs) with hot spots in their atmospheres, inner disk warps, and other three-dimensional effects in the nearby circumstellar environment. Our models are based on the geometry expected from magneto-accretion theory, where material moving inward in the disk flows along magnetic field lines to the star and creates stellar hot spots upon impact. Due to rotation of the star and magnetosphere, the disk is variably illuminated. We compare our model light curves to data from the Spitzer YSOVAR project to determine if these processes can explain the variability observed at optical and mid-infrared wavelengths in young stars. We focus on those variables exhibiting “dipper” behavior that may be periodic, quasi-periodic, or aperiodic. We find that the stellar hot-spot size and temperature affects the optical and near-infrared light curves, while the shape and vertical extent of the inner disk warp affects the mid-IR light curve variations. Clumpy disk distributions with non-uniform fractal density structure produce more stochastic light curves. We conclude that magneto-accretion theory is consistent with certain aspects of the multiwavelength photometric variability exhibited by low-mass YSOs. More detailed modeling of individual sources can be used to better determine the stellar hot-spot and inner disk geometries of particular sources.

  1. 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

  2. The Medieval Warm Period, the Little Ice Age and simulated climatic variability

    Energy Technology Data Exchange (ETDEWEB)

    Hunt, B.G. [CSIRO Marine and Atmospheric Research, Aspendale, VIC (Australia)

    2006-12-15

    The CSIRO Mark 2 coupled global climatic model has been used to generate a 10,000-year simulation for 'present' climatic conditions. The model output has been analysed to identify sustained climatic fluctuations, such as those attributed to the Medieval Warm Period (MWP) and the Little Ice Age (LIA). Since no external forcing was permitted during the model run all such fluctuations are attributed to naturally occurring climatic variability associated with the nonlinear processes inherent in the climatic system. Comparison of simulated climatic time series for different geographical locations highlighted the lack of synchronicity between these series. The model was found to be able to simulate climatic extremes for selected observations for century timescales, as well as identifying the associated spatial characteristics. Other examples of time series simulated by the model for the USA and eastern Russia had similar characteristics to those attributed to the MWP and the LIA, but smaller amplitudes, and clearly defined spatial patterns. A search for the frequency of occurrence of specified surface temperature anomalies, defined via duration and mean value, revealed that these were primarily confined to polar regions and northern latitudes of Europe, Asia and North America. Over the majority of the oceans and southern hemisphere such climatic fluctuations could not be sustained, for reasons explained in the paper. Similarly, sustained sea-ice anomalies were mainly confined to the northern hemisphere. An examination of mechanisms associated with the sustained climatic fluctuations failed to identify a role for the North Atlantic Oscillation, the El Nino-Southern Oscillation or the Pacific Decadal Oscillation. It was therefore concluded that these fluctuations were generated by stochastic processes intrinsic to the nonlinear climatic system. While a number of characteristics of the MWP and the LIA could have been partially caused by natural processes within

  3. Associations between period 3 gene polymorphisms and sleep- /chronotype-related variables in patients with late-life insomnia.

    Science.gov (United States)

    Mansour, Hader A; Wood, Joel; Chowdari, Kodavali V; Tumuluru, Divya; Bamne, Mikhil; Monk, Timothy H; Hall, Martica H; Buysse, Daniel J; Nimgaonkar, Vishwajit L

    2017-01-01

    A variable number tandem repeat polymorphism (VNTR) in the period 3 (PER3) gene has been associated with heritable sleep and circadian variables, including self-rated chronotypes, polysomnographic (PSG) variables, insomnia and circadian sleep-wake disorders. This report describes novel molecular and clinical analyses of PER3 VNTR polymorphisms to better define their functional consequences. As the PER3 VNTR is located in the exonic (protein coding) region of PER3, we initially investigated whether both alleles (variants) are transcribed into messenger RNA in human fibroblasts. The VNTR showed bi-allelic gene expression. We next investigated genetic associations in relation to clinical variables in 274 older adult Caucasian individuals. Independent variables included genotypes for the PER3 VNTR as well as a representative set of single nucleotide polymorphisms (SNPs) that tag common variants at the PER3 locus (linkage disequilibrium (LD) between genetic variants sleep time and sleep latency, self-rated chronotype, estimated with the Composite Scale (CS), and lifestyle regularity, estimated using the social rhythm metric (SRM). Initially, genetic polymorphisms were individually analyzed in relation to each outcome variable using analysis of variance (ANOVA). Nominally significant associations were further tested using regression analyses that incorporated individual ANOVA-associated DNA variants as potential predictors and each of the selected sleep/circadian variables as outcomes. The covariates included age, gender, body mass index and an index of medical co-morbidity. Significant genetic associations with the VNTR were not detected with the sleep or circadian variables. Nominally significant associations were detected between SNP rs1012477 and CS scores (p = 0.003) and between rs10462021 and SRM (p = 0.047); rs11579477 and average delta power (p = 0.043) (analyses uncorrected for multiple comparisons). In conclusion, alleles of the VNTR are expressed at the

  4. 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.

  5. V2492 Cygni: Optical BVRI Variability During the Period 2010-2017

    Science.gov (United States)

    Ibryamov, Sunay I.; Semkov, Evgeni H.; Peneva, Stoyanka P.

    2018-02-01

    Results from BVRI photometric observations of the young stellar object V2492 Cyg collected during the period from August 2010 to December 2017 are presented. The star is located in the field of the Pelican Nebula and it was discovered in 2010 due to its remarkable increase in the brightness by more than 5 mag in R-band. According to the first hypothesis of the variability, V2492 Cyg is an FUor candidate. During subsequent observations, it was reported that the star shows the characteristics inherent to EXor- and UXor-type variables. The optical data show that during the whole time of observations the star exhibits multiple large amplitude increases and drops in the brightness. In the beginning of 2017, we registered a significant increase in the optical brightness of V2492 Cyg, which seriously exceeds the maximal magnitudes registered after 2010.

  6. Global existence of periodic solutions of BAM neural networks with variable coefficients

    International Nuclear Information System (INIS)

    Guo Shangjiang; Huang Lihong; Dai Binxiang; Zhang Zhongzhi

    2003-01-01

    In this Letter, we study BAM (bidirectional associative memory) networks with variable coefficients. By some spectral theorems and a continuation theorem based on coincidence degree, we not only obtain some new sufficient conditions ensuring the existence, uniqueness, and global exponential stability of the periodic solution but also estimate the exponentially convergent rate. Our results are less restrictive than previously known criteria and can be applied to neural networks with a broad range of activation functions assuming neither differentiability nor strict monotonicity. Moreover, these conclusions are presented in terms of system parameters and can be easily verified for the globally Lipschitz and the spectral radius being less than 1. Therefore, our results should be useful in the design and applications of periodic oscillatory neural circuits for neural networks with delays

  7. 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.

  8. INFRARED PERIOD-LUMINOSITY RELATIONS OF EVOLVED VARIABLE STARS IN THE LARGE MAGELLANIC CLOUD

    International Nuclear Information System (INIS)

    Riebel, David; Meixner, Margaret; Fraser, Oliver; Srinivasan, Sundar; Cook, Kem; Vijh, Uma

    2010-01-01

    We combine variability information from the MAssive Compact Halo Objects survey of the Large Magellanic Cloud with infrared photometry from the Spitzer Space Telescope Surveying the Agents of a Galaxy's Evolution survey to create a data set of ∼30,000 variable red sources. We photometrically classify these sources as being on the first ascent of the red giant branch, or as being in one of three stages along the asymptotic giant branch (AGB): oxygen-rich, carbon-rich, or highly reddened with indeterminate chemistry ('extreme' AGB candidates). We present linear period-luminosity (P-L) relationships for these sources using eight separate infrared bands (J, H, K s , 3.6, 4.5, 5.8, 8.0, and 24 μm) as proxies for the luminosity. We find that the wavelength dependence of the slope of the P-L relationship is different for different photometrically determined classes of AGB stars. Stars photometrically classified as O-rich show the least variation of slope with wavelength, while dust enshrouded extreme AGB stars show a pronounced trend toward steeper slopes with increasing wavelength. We find that O-rich AGB stars pulsating in the fundamental mode obey a period-magnitude relation with a slope of -3.41 ± 0.04 when magnitude is measured in the 3.6 μm band, in contrast to C-rich AGB stars, which obey a relation of slope -3.77 ± 0.05.

  9. Using the Kepler Full Frame Images to Find Long-Period Variables in the Milky Way

    Science.gov (United States)

    Mullen, Melissa A.; Kraemer, Kathleen; Kuchar, T. A.; Sloan, G. C.

    2018-01-01

    We are using the monthly Full Frame Images (FFIs) images from the 4+ year Kepler mission to conduct a uniform census of long-period variables (LPVs, primarily Miras and semiregular variables) in the Milky Way disk. Our goal is to help understand how stellar pulsation and dust production interact as these dying stars eject their envelopes and enrich the interstellar medium with new fusion products and dust. To that end, we are processing the monthly FFIs for the entire 116 square-degree Kepler field to identify the LPVs and determine their period, pulsation mode, and amplitude measured with the same instrument for the 4+ year mission. Since the FFIs are not fully calibrated, we must first remove the instrumental systematics from the data and determine the flux calibration factors that can then be applied to all the stars in the field. To find these corrections, we use aperture photometry and PRF-fitting from well-characterized stars known to be stable – those with exoplanet candidates. We remove effects of the quarterly spacecraft rolls as well as longterm trends in the responsivity, which reduces the scatter in each star from 5-10% to <1-3%. We examine the effects of the optical distortions that are present in the outer parts of the array, as well as source crowding throughout the field. The fluxes from the PRF fits are typically ~1% higher than those from the aperture photometry. We present preliminary results on previously known and new, candidate, variable stars in a test field near the center of the FFIs.This work is supported by NASA ADAP grant NNX16AF45G.

  10. 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...

  11. 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 ...

  12. Dengue dynamics in Binh Thuan province, southern Vietnam: periodicity, synchronicity and climate variability.

    Science.gov (United States)

    Thai, Khoa T D; Cazelles, Bernard; Nguyen, Nam Van; Vo, Long Thi; Boni, Maciej F; Farrar, Jeremy; Simmons, Cameron P; van Doorn, H Rogier; de Vries, Peter J

    2010-07-13

    Dengue is a major global public health problem with increasing incidence and geographic spread. The epidemiology is complex with long inter-epidemic intervals and endemic with seasonal fluctuations. This study was initiated to investigate dengue transmission dynamics in Binh Thuan province, southern Vietnam. Wavelet analyses were performed on time series of monthly notified dengue cases from January 1994 to June 2009 (i) to detect and quantify dengue periodicity, (ii) to describe synchrony patterns in both time and space, (iii) to investigate the spatio-temporal waves and (iv) to associate the relationship between dengue incidence and El Niño-Southern Oscillation (ENSO) indices in Binh Thuan province, southern Vietnam. We demonstrate a continuous annual mode of oscillation and a multi-annual cycle of around 2-3-years was solely observed from 1996-2001. Synchrony in time and between districts was detected for both the annual and 2-3-year cycle. Phase differences used to describe the spatio-temporal patterns suggested that the seasonal wave of infection was either synchronous among all districts or moving away from Phan Thiet district. The 2-3-year periodic wave was moving towards, rather than away from Phan Thiet district. A strong non-stationary association between ENSO indices and climate variables with dengue incidence in the 2-3-year periodic band was found. A multi-annual mode of oscillation was observed and these 2-3-year waves of infection probably started outside Binh Thuan province. Associations with climatic variables were observed with dengue incidence. Here, we have provided insight in dengue population transmission dynamics over the past 14.5 years. Further studies on an extensive time series dataset are needed to test the hypothesis that epidemics emanate from larger cities in southern Vietnam.

  13. Dengue dynamics in Binh Thuan province, southern Vietnam: periodicity, synchronicity and climate variability.

    Directory of Open Access Journals (Sweden)

    Khoa T D Thai

    2010-07-01

    Full Text Available Dengue is a major global public health problem with increasing incidence and geographic spread. The epidemiology is complex with long inter-epidemic intervals and endemic with seasonal fluctuations. This study was initiated to investigate dengue transmission dynamics in Binh Thuan province, southern Vietnam.Wavelet analyses were performed on time series of monthly notified dengue cases from January 1994 to June 2009 (i to detect and quantify dengue periodicity, (ii to describe synchrony patterns in both time and space, (iii to investigate the spatio-temporal waves and (iv to associate the relationship between dengue incidence and El Niño-Southern Oscillation (ENSO indices in Binh Thuan province, southern Vietnam.We demonstrate a continuous annual mode of oscillation and a multi-annual cycle of around 2-3-years was solely observed from 1996-2001. Synchrony in time and between districts was detected for both the annual and 2-3-year cycle. Phase differences used to describe the spatio-temporal patterns suggested that the seasonal wave of infection was either synchronous among all districts or moving away from Phan Thiet district. The 2-3-year periodic wave was moving towards, rather than away from Phan Thiet district. A strong non-stationary association between ENSO indices and climate variables with dengue incidence in the 2-3-year periodic band was found.A multi-annual mode of oscillation was observed and these 2-3-year waves of infection probably started outside Binh Thuan province. Associations with climatic variables were observed with dengue incidence. Here, we have provided insight in dengue population transmission dynamics over the past 14.5 years. Further studies on an extensive time series dataset are needed to test the hypothesis that epidemics emanate from larger cities in southern Vietnam.

  14. Physical studies of asteroids. XXXII. Rotation periods and UBVRI-colours for selected asteroids

    Science.gov (United States)

    Piironen, J.; Lagerkvist, C.-I.; Erikson, A.; Oja, T.; Magnusson, P.; Festin, L.; Nathues, A.; Gaul, M.; Velichko, F.

    1998-03-01

    We present lightcurves of selected asteroids. Most of the asteroids were included to obtain refined spin periods. Enhanced periods were determined for 11 Parthenope, 306 Unitas and 372 Palma. We confirmed the spin periods of 8 Flora, 13 Egeria, 71 Niobe, 233 Asterope, 291 Alice, 409 Aspasia, 435 Ella and 512 Taurinensis. We determined also BV-colours for most of the included asteroids and UBVRI-colours for a total of 22 asteroids.

  15. Facing unprecedented drying of the Central Andes? Precipitation variability over the period AD 1000–2100

    International Nuclear Information System (INIS)

    Neukom, Raphael; Salzmann, Nadine; Huggel, Christian; Rohrer, Mario; Calanca, Pierluigi; Acuña, Delia; Christie, Duncan A; Morales, Mariano S

    2015-01-01

    Projected future trends in water availability are associated with large uncertainties in many regions of the globe. In mountain areas with complex topography, climate models have often limited capabilities to adequately simulate the precipitation variability on small spatial scales. Also, their validation is hampered by typically very low station density. In the Central Andes of South America, a semi-arid high-mountain region with strong seasonality, zonal wind in the upper troposphere is a good proxy for interannual precipitation variability. Here, we combine instrumental measurements, reanalysis and paleoclimate data, and a 57-member ensemble of CMIP5 model simulations to assess changes in Central Andes precipitation over the period AD 1000–2100. This new database allows us to put future projections of precipitation into a previously missing multi-centennial and pre-industrial context. Our results confirm the relationship between regional summer precipitation and 200 hPa zonal wind in the Central Andes, with stronger Westerly winds leading to decreased precipitation. The period of instrumental coverage (1965–2010) is slightly dryer compared to pre-industrial times as represented by control simulations, simulations from the past Millennium, ice core data from Quelccaya ice cap and a tree-ring based precipitation reconstruction. The model ensemble identifies a clear reduction in precipitation already in the early 21st century: the 10 year running mean model uncertainty range (ensemble 16–84% spread) is continuously above the pre-industrial mean after AD 2023 (AD 2028) until the end of the 21st century in the RCP2.6 (RCP8.5) emission scenario. Average precipitation over AD 2071–2100 is outside the range of natural pre-industrial variability in 47 of the 57 model simulations for both emission scenarios. The ensemble median fraction of dry years (defined by the 5th percentile in pre-industrial conditions) is projected to increase by a factor of 4 until 2071

  16. 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.

  17. Far Ultraviolet Spectroscopy of Three Long Period Nova-Like Variables, V363 Aur, AC Cnc and RZ Gru

    Science.gov (United States)

    Bisol, Alexandra; Sion, E. M.

    2011-01-01

    We have selected three nova-like variables: V363 Aur, RZ Gru and AC Cnc, all of which are UX UMa types, having similar orbital periods well beyond the 3 to 4 hour range where most nova-likes are found. All should have very similar secondary stars given the fact that they their physical parameters are so similar. V363 Aur is a bona fide SW Sex star, and AC Cnc is a probable one, while RZ Gru is not a member of the SW Sex subclass. Our objective is to carry out the first synthetic spectral analysis of far ultraviolet spectra of the three systems using state-of-the-art models both of accretion disks and photospheres. Therefore we shall compare the distances we obtain from the best fitting synthetic spectral models to other distance estimates in the literature. We present model-derived accretion rates and distances for all three systems. The FUV flux range of RZ Gru and V363 Aur is dominated by radiation from an optically thick, steady state, accretion but for AC Cnc, we find that a hot white dwarf accounts for 70% of the FUV flux. We compare the FUV characteristics and physical properties of these three long period nova-like systems to the properties of other nova-likes at shorter periods. This work was supported in part by NSF grant AST0807892 to Villanova University.

  18. 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…

  19. 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

  20. 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

  1. 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 ...

  2. 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

  3. Speleothem records of western Mediterranean. Hydrological variability along the Last Interglacial Period and marine linkages

    Science.gov (United States)

    Torner, Judit; Cacho, Isabel; Moreno, Ana; Stoll, Heather; Belmonte, Anchel; Sierro, Francisco J.; Frigola, Jaime; Martrat, Belen; Fornós, Joan; Arnau Fernández, Pedro; Hellstrom, John; Cheng, Hai; Edwards, R. Lawrence

    2016-04-01

    This study aims to identify and characterize regional hydrological variability in the western Mediterranean region in base to different geochemical parameters (δ18O, δ13C, and Mg/Ca ratios). Speleothems have been recovered from several caves located in southern central Pyrenees one and the others form the Balearic Islands. Their chronologies have been constructed in base on U/Th absolute dating and indicate that the speleothem sequences cover the end of the last interglacial and the glacial inception. One of the most remarkable features of the records is the intense and abrupt shift toward more arid conditions that marks the end of the last interglacial (MIS 5e). Furthermore, our speleothem records also show relatively humid but highly variable hydrological conditions during the interstadial periods from MIS 5c to 5a. These speleothem records have been compared with new generated western Mediterranean marine records from the Balearic Sea (MD99-2343) and Alboran Sea (OPD-977). Marine records include (1) proxies of sea surface temperature and changes in evaporation-precipitation rates based on pair analysis of δ18O and the Mg/Ca ratios in planktonic foraminifera Globigerina bulloides; (2) proxies of deep-water currents associated with the Western Mediterranean Deep Water (WMDW) based on grain size analyses. The results reveal that arid conditions on land were coeval with cold sea surface sub-stages (MIS 5b and 5d), and also with increases in the intensity of the WMDW-related currents. By contrast, humid and hydrological unstable atmosphere conditions were synchronous with sea surface warm sub-stages, and lower WMDW-related currents intensities (MIS 5a, c and e). Consequently, our results highly evidence a strong atmospheric-oceanic coupling, involving parallel changes in both surface but also deep western Mediterranean Sea conditions during the last interglacial period and the glacial inception.

  4. Features of the heart rate variability in the perioperative period after adenotomy in children

    Directory of Open Access Journals (Sweden)

    Михайло Борисович Пушкар

    2015-03-01

    Full Text Available Aim. Study course of perioperative period after adenotomy in children in different ways of general anesthesia by examining indicators of heart rate variability and efficacy of postoperative analgesia.Materials and methods. To study included 70 children aged from 6 to 8 years, which was held adenotomy. Patients were divided into 3 groups: group I (n = 28 - operated under conditions of intravenous anesthesia based on propofol combined with fentanyl; group II (n=23 – operated under conditions of inhalation anesthesia by sevoflurane in combination with fentanyl and analginum; group III (n=19 – operated under conditions of intravenous anesthesia based on thiopental sodium combined with fentanyl. Differences were considered significant at p <0.05 using Student t-test.Results. Indicators of heart rate variability indicated that in the extubation stage in all groups of patients revealed high activity of the sympathetic tone with the trend of decline in the morning after surgery. Statistically higher activity of the sympathetic part of the autonomic nervous system was in patients of group III - 1 hour after surgery compared with patients groups I and II (p <0,001 and p <0,01, respectively. After 1 hour after surgery on the scales "Faces" and "Oucher" scores indicated that the child "a little hurt" in all groups of patients In the dynamics of observation in all groups tended to reduce the intensity of pain. An interpretation of scores on the FLACC scale indicated that patients in both groups felt comfortable.Conclusions. It was found that in patients in all groups there are changes in the nervous regulation of heart rate variability, characterized by increased activity of the sympathetic division of the autonomic nervous system. Postoperative anesthesia by 10 mg / kg ibuprofen provides effective analgesia

  5. 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, ...

  6. Variability and quasi-decadal changes in the methane budget over the period 2000–2012

    Directory of Open Access Journals (Sweden)

    M. Saunois

    2017-09-01

    Full Text Available Following the recent Global Carbon Project (GCP synthesis of the decadal methane (CH4 budget over 2000–2012 (Saunois et al., 2016, we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven approaches. The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000–2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000–2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008–2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16–32] Tg CH4 yr−1 higher methane emissions over the period 2008–2012 compared to 2002–2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002–2006 and 2008–2012 differs from one atmospheric inversion study to

  7. Variability and quasi-decadal changes in the methane budget over the period 2000-2012

    Science.gov (United States)

    Saunois, Marielle; Bousquet, Philippe; Poulter, Ben; Peregon, Anna; Ciais, Philippe; Canadell, Josep G.; Dlugokencky, Edward J.; Etiope, Giuseppe; Bastviken, David; Houweling, Sander; Janssens-Maenhout, Greet; Tubiello, Francesco N.; Castaldi, Simona; Jackson, Robert B.; Alexe, Mihai; Arora, Vivek K.; Beerling, David J.; Bergamaschi, Peter; Blake, Donald R.; Brailsford, Gordon; Bruhwiler, Lori; Crevoisier, Cyril; Crill, Patrick; Covey, Kristofer; Frankenberg, Christian; Gedney, Nicola; Höglund-Isaksson, Lena; Ishizawa, Misa; Ito, Akihiko; Joos, Fortunat; Kim, Heon-Sook; Kleinen, Thomas; Krummel, Paul; Lamarque, Jean-François; Langenfelds, Ray; Locatelli, Robin; Machida, Toshinobu; Maksyutov, Shamil; Melton, Joe R.; Morino, Isamu; Naik, Vaishali; O'Doherty, Simon; Parmentier, Frans-Jan W.; Patra, Prabir K.; Peng, Changhui; Peng, Shushi; Peters, Glen P.; Pison, Isabelle; Prinn, Ronald; Ramonet, Michel; Riley, William J.; Saito, Makoto; Santini, Monia; Schroeder, Ronny; Simpson, Isobel J.; Spahni, Renato; Takizawa, Atsushi; Thornton, Brett F.; Tian, Hanqin; Tohjima, Yasunori; Viovy, Nicolas; Voulgarakis, Apostolos; Weiss, Ray; Wilton, David J.; Wiltshire, Andy; Worthy, Doug; Wunch, Debra; Xu, Xiyan; Yoshida, Yukio; Zhang, Bowen; Zhang, Zhen; Zhu, Qiuan

    2017-09-01

    Following the recent Global Carbon Project (GCP) synthesis of the decadal methane (CH4) budget over 2000-2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry), inventories of anthropogenic emissions, and data-driven approaches. The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000-2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000-2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008-2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16-32] Tg CH4 yr-1 higher methane emissions over the period 2008-2012 compared to 2002-2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002-2006 and 2008-2012 differs from one atmospheric inversion study to another. However, all top-down studies

  8. ICUD-0147 Extreme event statistics of urban pluvial floods – Return period assessment and rainfall variability impacts

    DEFF Research Database (Denmark)

    Tuyls, Damian Murla; Nielsen, Rasmus; Thorndahl, Søren Liedtke

    2017-01-01

    A return period assessment of urban flood has been performed and its adhered impact of rainfall variability studied over a urban drainage catchment area in Aalborg, Denmark. Recorded rainfall from 7 rain gauges has been used, located in a range of 7.5Km and for a period varying form 18-37 years....... Return period of rainfall and flood at catchment and local scale has been estimated, its derived ambiguities analysed and the variability of rain gauge based rainfall investigated regarding to flood estimation results. Results show a clear contrast between rainfall and flood return period estimates...

  9. Multiple-wavelength Variability and Quasi-periodic Oscillation of PMN J0948+0022

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Jin [Key Laboratory of Space Astronomy and Technology, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012 (China); Zhang, Hai-Ming; Zhu, Yong-Kai; Lu, Rui-Jing; Liang, En-Wei [Guangxi Key Laboratory for Relativistic Astrophysics, Department of Physics, Guangxi University, Nanning 530004 (China); Yi, Ting-Feng [Department of Physics, Yunnan Normal University, Kunming 650500 (China); Yao, Su, E-mail: jinzhang@bao.ac.cn [Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing 100871 (China)

    2017-11-01

    We present a comprehensive analysis of multiple-wavelength observational data of the first GeV-selected narrow-line Seyfert 1 galaxy PMN J0948+0022. We derive its light curves in the γ -ray and X-ray bands from the data observed with Fermi /LAT and Swift /XRT, and generate the optical and radio light curves by collecting the data from the literature. These light curves show significant flux variations. With the LAT data we show that this source is analogous to typical flat spectrum radio quasars in the L {sub γ} –Γ {sub γ} plane, where L {sub γ} and Γ {sub γ} are the luminosity and spectral index in the LAT energy band. The γ -ray flux is correlated with the V-band flux with a lag of ∼44 days, and a moderate quasi-periodic oscillation (QPO) with a periodicity of ∼490 days observed in the LAT light curve. A similar QPO signature is also found in the V-band light curve. The γ -ray flux is not correlated with the radio flux in 15 GHz, and no similar QPO signature is found at a confidence level of 95%. Possible mechanisms of the QPO are discussed. We propose that gravitational-wave observations in the future may clarify the current plausible models for the QPO.

  10. 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.

  11. 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.

  12. Invariant polar bear habitat selection during a period of sea ice loss.

    Science.gov (United States)

    Wilson, Ryan R; Regehr, Eric V; Rode, Karyn D; St Martin, Michelle

    2016-08-17

    Climate change is expected to alter many species' habitat. A species' ability to adjust to these changes is partially determined by their ability to adjust habitat selection preferences to new environmental conditions. Sea ice loss has forced polar bears (Ursus maritimus) to spend longer periods annually over less productive waters, which may be a primary driver of population declines. A negative population response to greater time spent over less productive water implies, however, that prey are not also shifting their space use in response to sea ice loss. We show that polar bear habitat selection in the Chukchi Sea has not changed between periods before and after significant sea ice loss, leading to a 75% reduction of highly selected habitat in summer. Summer was the only period with loss of highly selected habitat, supporting the contention that summer will be a critical period for polar bears as sea ice loss continues. Our results indicate that bears are either unable to shift selection patterns to reflect new prey use patterns or that there has not been a shift towards polar basin waters becoming more productive for prey. Continued sea ice loss is likely to further reduce habitat with population-level consequences for polar bears. © 2016 The Author(s).

  13. Invariant polar bear habitat selection during a period of sea ice loss

    Science.gov (United States)

    Wilson, Ryan R.; Regehr, Eric V.; Rode, Karyn D.; St Martin, Michelle

    2016-01-01

    Climate change is expected to alter many species' habitat. A species' ability to adjust to these changes is partially determined by their ability to adjust habitat selection preferences to new environmental conditions. Sea ice loss has forced polar bears (Ursus maritimus) to spend longer periods annually over less productive waters, which may be a primary driver of population declines. A negative population response to greater time spent over less productive water implies, however, that prey are not also shifting their space use in response to sea ice loss. We show that polar bear habitat selection in the Chukchi Sea has not changed between periods before and after significant sea ice loss, leading to a 75% reduction of highly selected habitat in summer. Summer was the only period with loss of highly selected habitat, supporting the contention that summer will be a critical period for polar bears as sea ice loss continues. Our results indicate that bears are either unable to shift selection patterns to reflect new prey use patterns or that there has not been a shift towards polar basin waters becoming more productive for prey. Continued sea ice loss is likely to further reduce habitat with population-level consequences for polar bears.

  14. 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.

  15. 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, ...

  16. 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…

  17. Selection of detailed items for periodic safety review on PWR radwaste management system

    Energy Technology Data Exchange (ETDEWEB)

    Sung, K. B.; Ahn, Y. S.; Park, Y. S.; Kim, S. H.; Kim, J. T. [Korea Hydric and Nuclear Power Company, Taejon (Korea, Republic of)

    2003-10-01

    Selection of detailed-items for Periodic Safety Review on PWR radwaste management system, the main component could be faithfully clarified according to the purpose of establishment on each system and basic purpose. It is proper to select detailed-items those of radioactivities in the reactor coolant activity levels and the released volume of liquid and gaseous radioactive material on safety performance. It's also proper to select solid radwaste production quantities as detailed-item that it would be predict the next ten years trends after PSR.

  18. 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.

  19. Heart rate variability during sleep in healthy term newborns in the early postnatal period

    International Nuclear Information System (INIS)

    Doyle, O M; Korotchikova, I; Boylan, G B; Lightbody, G; Marnane, W; Kerins, D

    2009-01-01

    Normative time- and frequency-domain heart rate variability (HRV) measures were extracted during quiet sleep (QS) and active sleep (AS) periods in 30 healthy babies. All newborn infants studied were less than 12 h old and the sleep state was classified using multi-channel video EEG. Three bands were extracted from the heart rate (HR) spectrum: very low frequency (VLF), 0.01–0.04 Hz; low frequency (LF), 0.04–0.2 Hz, and high frequency (HF), >0.2 Hz. All metrics were averaged across all patients and per sleep state to produce a table of normative values. A noticeable peak corresponding to activity in the RSA band was found in 80% patients during QS and 0% of patients during AS, although some broadband activity was observed. The majority of HRV metrics showed a statistically significant separation between QS and AS. It can be concluded that (i) activity in the RSA band is present during QS in the healthy newborn, in the first 12 h of life, (ii) HRV measures are affected by sleep state and (iii) the averaged HRV metrics reported here could assist the interpretation of HRV data from newborns with neonatal illnesses

  20. Variable impedance cardiography waveforms: how to evaluate the preejection period more accurately

    International Nuclear Information System (INIS)

    Ermishkin, V V; Kolesnikov, V A; Lukoshkova, E V; Mokh, V P; Sonina, R S; Dupik, N V; Boitsov, S A

    2012-01-01

    Impedance method has been successfully applied for left ventricular function assessment during functional tests. The preejection period (PEP), the interval between Q peak in ECG and a specific mark on impedance cardiogram (ICG) which corresponds to aortic valve opening, is an important indicator of the contractility state and its neurogenic control. Accurate identification of ejection onset by ICG is often problematic, especially in the cardiologic patients, due to peculiar waveforms. An essential obstacle is variability of the shape of the ICG waveform during the exercise and subsequent recovery. A promissing solution can be introduction of an additional pulse sensor placed in the nearby region. We tested this idea in 28 healthy subjects and 6 cardiologic patients using a dual-channel impedance cardiograph for simultaneous recording from the aortic and neck regions, and an earlobe photoplethysmograph. Our findings suggest that incidence of abnormal complicated ICG waveforms increases with age. The combination of standard ICG with ear photoplethysmography and/or additional impedance channel significantly improves the efficacy and accuracy of PEP estimation.

  1. Smoking patterns, depression, and sociodemographic variables among Flemish women during pregnancy and the postpartum period.

    Science.gov (United States)

    De Wilde, Katrien S; Trommelmans, Leen C; Laevens, Hans H; Maes, Lea R; Temmerman, Marleen; Boudrez, Hedwig L

    2013-01-01

    Relationships among feelings of depression, smoking behavior, and educational level during pregnancy have been documented. Feelings of depression may contribute to persistent smoking during pregnancy. No longitudinal studies assessing feelings of depression in women with different antepartum and postpartum smoking patterns are available. The aim was to determine relationships between depressive symptoms, sociodemographic characteristics, and smoking pattern during and after pregnancy. An observational, prospective, noninterventional study was conducted. Data were collected during two stages of pregnancy (T0: postpartum (T2: >6 weeks) in 523 Flemish women. Feelings of depression (measured using the Beck Depression Inventory [BDI]), smoking behavior, and sociodemographic variables were analyzed using a general linear mixed model implemented in SAS Proc MIXED. Smokers and initial smokers reported significantly more depressive symptoms at all time points compared with recent ex-smokers, nonsmokers, and initial nonsmokers (p postpartum. Smoking patterns were associated with depression and showed complex interactions with educational level. Assessment and intervention for both smoking and depression are needed throughout the perinatal period to support the health of mothers, their infants, and families.

  2. Heart rate variability biofeedback intervention for reduction of psychological stress during the early postpartum period.

    Science.gov (United States)

    Kudo, Naoko; Shinohara, Hitomi; Kodama, Hideya

    2014-12-01

    This study examined the effectiveness of heart rate variability (HRV) biofeedback intervention for reduction of psychological stress in women in the early postpartum period. On postpartum day 4, 55 healthy subjects received a brief explanation about HRV biofeedback using a portable device. Among them, 25 mothers who agreed to implement HRV biofeedback at home were grouped as the biofeedback group, and other 30 mothers were grouped as the control group. At 1 month postpartum, there was a significant decrease in total Edinburgh Postnatal Depression Scale score (P biofeedback group; this change was brought about mainly by decreases in items related to anxiety or difficulty sleeping. There was also a significant increase in standard deviation of the normal heartbeat interval (P biofeedback group after adjusting for potential covariates. In conclusion, postpartum women who implemented HRV biofeedback after delivery were relatively free from anxiety and complained less of difficulties sleeping at 1 month postpartum. Although the positive effects of HRV biofeedback may be partly attributable to intervention effects, due to its clinical outcome, HRV biofeedback appears to be recommendable for many postpartum women as a feasible health-promoting measure after childbirth.

  3. Temporal Variability and Characterization of Aerosols across the Pakistan Region during the Winter Fog Periods

    Directory of Open Access Journals (Sweden)

    Muhammad Fahim Khokhar

    2016-05-01

    Full Text Available Fog is a meteorological/environmental phenomenon which happens across the Indo-Gangetic Plains (IGP and leads to significant social and economic problems, especially posing significant threats to public health and causing disruptions in air and road traffic. Meteorological stations in Pakistan provide limited information regarding fog episodes as these provide only point observations. Continuous monitoring, as well as a spatially coherent picture of fog distribution, is possible through the use of satellite observations. This study focuses on the 2012–2015 winter fog episodes over the Pakistan region using the Moderate Resolution Image Spectrometer (MODIS, the Ozone Monitoring Instrument and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO products. The main objective of the study was to map the spatial distribution of aerosols, their types, and to identify the aerosol origins during special weather conditions like fog in Pakistan. The study also included ground monitoring of particulate matter (PM concentrations, which were conducted during the 2014–2015 winter period only. Overall, this study is part of a multi-country project supported by the International Centre for Integrated Mountain Development (ICIMOD, started in 2014–2015 winter period, whereby scientists from Bangladesh, India and Nepal have also conducted measurements at their respective sites. A significant correlation between MODIS (AOD and AERONET Station (AOD data from Lahore was identified. Mass concentration of PM10 at all sampling sites within Lahore city exceeded the National Environmental Quality Standards (NEQS levels on most of the occasions. Smoke and absorbing aerosol were found to be major constituents of winter fog in Pakistan. Furthermore, an extended span of winter fog was also observed in Lahore city during the winter of 2014–2015. The Vertical Feature Mask (VFM provided by CALIPSO satellite confirmed the low-lying aerosol

  4. Complex Dynamics of Droplet Traffic in a Bifurcating Microfluidic Channel: Periodicity, Multistability, and Selection Rules

    Science.gov (United States)

    Sessoms, D. A.; Amon, A.; Courbin, L.; Panizza, P.

    2010-10-01

    The binary path selection of droplets reaching a T junction is regulated by time-delayed feedback and nonlinear couplings. Such mechanisms result in complex dynamics of droplet partitioning: numerous discrete bifurcations between periodic regimes are observed. We introduce a model based on an approximation that makes this problem tractable. This allows us to derive analytical formulae that predict the occurrence of the bifurcations between consecutive regimes, establish selection rules for the period of a regime, and describe the evolutions of the period and complexity of droplet pattern in a cycle with the key parameters of the system. We discuss the validity and limitations of our model which describes semiquantitatively both numerical simulations and microfluidic experiments.

  5. Allee effect in the selection for prime-numbered cycles in periodical cicadas.

    Science.gov (United States)

    Tanaka, Yumi; Yoshimura, Jin; Simon, Chris; Cooley, John R; Tainaka, Kei-ichi

    2009-06-02

    Periodical cicadas are well known for their prime-numbered life cycles (17 and 13 years) and their mass periodical emergences. The origination and persistence of prime-numbered cycles are explained by the hybridization hypothesis on the basis of their lower likelihood of hybridization with other cycles. Recently, we showed by using an integer-based numerical model that prime-numbered cycles are indeed selected for among 10- to 20-year cycles. Here, we develop a real-number-based model to investigate the factors affecting the selection of prime-numbered cycles. We include an Allee effect in our model, such that a critical population size is set as an extinction threshold. We compare the real-number models with and without the Allee effect. The results show that in the presence of an Allee effect, prime-numbered life cycles are most likely to persist and to be selected under a wide range of extinction thresholds.

  6. Spatial variability of maximum annual daily rain under different return periods at the Rio de Janeiro state, Brazil

    Directory of Open Access Journals (Sweden)

    Roriz Luciano Machado

    2010-01-01

    Full Text Available Knowledge of maximum daily rain and its return period in a region is an important tool to soil conservation, hydraulic engineering and preservation of road projects. The objective of this work was to evaluate the spatial variability of maximum annual daily rain considering different return periods, at the Rio de Janeiro State. The data set was composed by historical series of 119 rain gauges, for 36 years of observation. The return periods, estimated by Gumbel distribution, were 2, 5, 10, 25, 50 and 100 years. The spatial variability of the return periods was evaluated by semivariograms. All the return periods presented spatial dependence, with exponential and spherical model fitted to the experimental semivariograms. The parameters of the fitted semivariogram model were very similar; however, it was observed the presence of higher nugget effects for semivariograms of longer return periods. The values of maximum annual daily average rain in all the return periods increased from north to south and from countryside to the coast. In the region between the Serra do Mar range and the coast, besides increasing in magnitude, an increase in the spatial variability of the studied values with increasing return periods was also noticed. This behavior is probably caused by the orographic effect. The interpolated maps were more erratic for higher return periods and at the North, Northeast and Coastal Plain regions, in which the installation of new pluviometric stations are recommended.

  7. 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.

  8. Selection of strategy for electric power engineering development in Russia for period up to 2015

    International Nuclear Information System (INIS)

    Khainson, Ya.I.; Mirkovskaya, R.E.; Artem'eva, N.Yu.

    1993-01-01

    The result of studies, in which an attempt to select a number of real versions for development of electric power engineering for the period up to 2015, as well as to evaluate, compare and select essentially stable trends is made, are discussed. It is shown that these trends remain actual even under market economics conditions. The necessity is emphasized for creation and introduction of new generation of units and electric power plants ecologically clean, reliable and operating in wide unit capacity range. Special attention should be paid to creation of new types of NPPs, underground NPPs as well as low-and intermediate-capacity NPPs necessary for many regions of the country

  9. Influence of Selective Edge Removal and Refractory Period in a Self-Organized Critical Neuron Model

    International Nuclear Information System (INIS)

    Lin Min; Gang, Zhao; Chen Tianlun

    2009-01-01

    A simple model for a set of integrate-and-fire neurons based on the weighted network is introduced. By considering the neurobiological phenomenon in brain development and the difference of the synaptic strength, we construct weighted networks develop with link additions and followed by selective edge removal. The network exhibits the small-world and scale-free properties with high network efficiency. The model displays an avalanche activity on a power-law distribution. We investigate the effect of selective edge removal and the neuron refractory period on the self-organized criticality of the system. (condensed matter: structural, mechanical, and thermal properties)

  10. Light Curve Periodic Variability of Cyg X-1 using Jurkevich Method

    Indian Academy of Sciences (India)

    The Jurkevich method is a useful method to explore periodicity in the unevenly sampled observational data. In this work, we adopted the method to the light curve of Cyg X-1 from 1996 to 2012, and found that there is an interesting period of 370 days, which appears in both low/hard and high/soft states. That period may be ...

  11. An Expression of Periodic Phenomena of Fashion on Sexual Selection Model with Conformity Genes and Memes

    Science.gov (United States)

    Mutoh, Atsuko; Tokuhara, Shinya; Kanoh, Masayoshi; Oboshi, Tamon; Kato, Shohei; Itoh, Hidenori

    It is generally thought that living things have trends in their preferences. The mechanism of occurrence of another trends in successive periods is concerned in their conformity. According to social impact theory, the minority is always exists in the group. There is a possibility that the minority make the transition to the majority by conforming agents. Because of agent's promotion of their conform actions, the majority can make the transition. We proposed an evolutionary model with both genes and memes, and elucidated the interaction between genes and memes on sexual selection. In this paper, we propose an agent model for sexual selection imported the concept of conformity. Using this model we try an environment where male agents and female agents are existed, we find that periodic phenomena of fashion are expressed. And we report the influence of conformity and differentiation on the transition of their preferences.

  12. Radio frequency selective addressing of localized atoms in a periodic potential

    International Nuclear Information System (INIS)

    Ott, H.; De Mirandes, E.; Ferlaino, F.; Roati, G.; Tuerck, V.; Modugno, G.; Inguscio, M.

    2004-01-01

    We study the localization and addressability of ultracold atoms in a combined parabolic and periodic potential. Such a potential supports the existence of localized stationary states and we show that applying a radio frequency field allows us to selectively address atoms in these states. This method is used to measure the energy and momentum distribution of the atoms in the localized states. We also discuss possible extensions of this scheme to address and manipulate atoms in single lattice sites

  13. 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

  14. 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.

  15. Rapid oscillations in cataclysmic variables. VI. Periodicities in erupting dwarf novae

    International Nuclear Information System (INIS)

    Patterson, J.

    1981-01-01

    We report an extensive study of the coherent oscillations observed in high-speed photometry of dwarf novae during eruption. The oscillations are in all cases singly periodic and sinusoidal to the limits of measurement. The detection of oscillations in 14 separate eruptions of AH Her and SY Cnc enables a general study of period variations. The stars trace out characteristic loops (''banana diagrams'') in the period-intensity plane. New detections are also reported for SS Cyg, EM Cyg, and HT Cas

  16. APPLE-II type quasi-periodic variably polarizing undulator at HiSOR

    International Nuclear Information System (INIS)

    Sasaki, Shigemi; Miyamoto, Atsushi; Goto, Kiminori

    2012-01-01

    A newly constructed quasi-periodic APPLE-II undulator was installed in the HiSOR ring at Hiroshima Synchrotron Radiation Center, Hiroshima University during the summer shutdown period in 2011. This 1.8 m-long undulator has a period length of 78 mm. In this article, the mechanism of magnetic field generation for various polarization modes of APPLE undulator, the principle of quasi-periodic undulator and the performance of HiSOR QP-APPLE-II undulator are described. (author)

  17. 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...

  18. 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.

  19. Light Curve Periodic Variability of Cyg X-1 using Jurkevich Method ...

    Indian Academy of Sciences (India)

    Abstract. The Jurkevich method is a useful method to explore periodic- ity in the unevenly sampled observational data. In this work, we adopted the method to the light curve of Cyg X-1 from 1996 to 2012, and found that there is an interesting period of 370 days, which appears in both low/hard and high/soft states.

  20. Periods and light curves of 16 Cepheid variables in IC 1613 not completed by Baade

    International Nuclear Information System (INIS)

    Carlson, G.; Sandage, A.

    1990-01-01

    New periods and light curves are presented for 16 of the faintest Cepheids in IC 1613 which had not been finished by Baade. Magnitudes have been reduced to Freedman's new photometric scale. The P-L relation is extended to periods of 2 days using these new data. Comparison of the total Cepheid data now available in IC 1613 with the data in LMC shows no significant slope difference in the two P-L relations for periods of less than 10 days despite the lower metallicity of the young stars in IC 1613. Fifty new faint Cepheid candidates have been found in IC 1613 by blinking plates not used for this purpose by Baade. Most of these stars will have probable periods of less than 2 days, which will eventually permit an extension of the P-L relation in IC 1613 to fainter magnitudes when the photometry and period determinations are completed. 18 refs

  1. 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.

  2. 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...

  3. 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.

  4. 17 CFR 270.22e-1 - Exemption from section 22(e) of the Act during annuity payment period of variable annuity...

    Science.gov (United States)

    2010-04-01

    ...) of the Act during annuity payment period of variable annuity contracts participating in certain... from section 22(e) of the Act during annuity payment period of variable annuity contracts participating... payment period of variable annuity contracts participating in such account, be exempt from the provisions...

  5. Multi-period project portfolio selection under risk considerations and stochastic income

    Science.gov (United States)

    Tofighian, Ali Asghar; Moezzi, Hamid; Khakzar Barfuei, Morteza; Shafiee, Mahmood

    2018-02-01

    This paper deals with multi-period project portfolio selection problem. In this problem, the available budget is invested on the best portfolio of projects in each period such that the net profit is maximized. We also consider more realistic assumptions to cover wider range of applications than those reported in previous studies. A novel mathematical model is presented to solve the problem, considering risks, stochastic incomes, and possibility of investing extra budget in each time period. Due to the complexity of the problem, an effective meta-heuristic method hybridized with a local search procedure is presented to solve the problem. The algorithm is based on genetic algorithm (GA), which is a prominent method to solve this type of problems. The GA is enhanced by a new solution representation and well selected operators. It also is hybridized with a local search mechanism to gain better solution in shorter time. The performance of the proposed algorithm is then compared with well-known algorithms, like basic genetic algorithm (GA), particle swarm optimization (PSO), and electromagnetism-like algorithm (EM-like) by means of some prominent indicators. The computation results show the superiority of the proposed algorithm in terms of accuracy, robustness and computation time. At last, the proposed algorithm is wisely combined with PSO to improve the computing time considerably.

  6. 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

  7. 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

  8. 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)

  9. Event Processing and Variable Part of Sample Period Determining in Combined Systems Using GA

    Science.gov (United States)

    Strémy, Maximilián; Závacký, Pavol; Jedlička, Martin

    2011-01-01

    This article deals with combined dynamic systems and usage of modern techniques in dealing with these systems, focusing particularly on sampling period design, cyclic processing tasks and related processing algorithms in the combined event management systems using genetic algorithms.

  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. The Correlation between Clinical Variables and Sleep Onset Rapid Eye Movement Period Frequencies in Narcoleptic Patients

    Directory of Open Access Journals (Sweden)

    Jin Hwa Jeong

    2010-11-01

    Full Text Available Background and Objective A diagnosis of narcolepsy is defined by less than 8 minutes of mean sleep latency, and two or more sleep onset rapid eye movement periods on the Multiple Sleep Latency Test. This study examined the relationship between the sleep onset rapid eye movement period frequencies during Multiple Sleep Latency Test and narcoleptic symptom severity. Methods From March 2004 to August 2009, 126 patients suffering from excessive daytime sleepiness who visited the Sleep Disorders Clinic of St. Vincent’s Hospital at the Catholic University of Korea were tested by polysomnography and Multiple Sleep Latency Test. Subjects were divided into three groups according to the number of sleep onset rapid eye movement periods that appeared on the Multiple Sleep Latency Test. Symptom severity instruments included the Epworth Sleepiness Scale and the Stanford Center for Narcolepsy Sleep Inventory, and various sleep parameters. In addition, we performed human leukocyte antigen genotyping for human leukocyte antigen-DQB1*0602 on all patients. Results Among the three groups classified by the number of sleep onset rapid eye movement periods during Multiple Sleep Latency Test, we found no significant differences in demographic features, Epworth Sleepiness Scale, and most polysomnographic findings. However, we observed cataplexy, hypnagogic hallucination, sleep paralysis, and human leukocyte antigen-DQB1*0602 positivity more frequently in groups with higher sleep onset rapid eye movement period frequencies. In addition, the proportions of stage II sleep, REM sleep latency from polysomnography, and mean sleep latency and mean REM sleep latency from the Multiple Sleep Latency Test significantly decreased with increasing sleep onset rapid eye movement period frequency. Conclusions In this study, we demonstrated that sleep onset rapid eye movement period frequency during Multiple Sleep Latency Test correlated with sleep architecture, daytime symptom

  12. Closed Loop Sawtooth Period Control Using Variable Eccd Injection Angles on Tore Supra

    International Nuclear Information System (INIS)

    Lennholm, M.; Eriksson, L.G.; Turco, F.; Bouquey, F.; Darbos, C.; Dumont, R.; Giruzzi, G.; Jung, M.; Lambert, R.; Magne, R.; Molina, D.; Moreau, P.; Rimini, F.; Segui, J.L.; Song, S.; Traisnel, E.

    2009-01-01

    Closed loop control of the period of fast ion stabilized sawtooth has been demonstrated for the first time on Tore Supra by varying the electron cyclotron current drive (ECCD) injection angles in real time. Fast ions generated by up to 4 MW of central ion cyclotron resonance heating (ICRH) increased the sawtooth period from the ohmic value of 25 ms to 60 to 100 ms. This sawtooth period was reduced to 30 ms by the addition of only 300 kW of ECCD. In ICRH heated shots where the normalized minor radius of the ECCD absorption location was swept from 0.4 to 0.05 in 4 s, the sawtooth period showed an abrupt change from 70 to 30 ms when the ECCD deposition normalized minor radius reached ∼ 0.2. This short period was then maintained until the absorption location moved well inside the sawtooth inversion radius at which point it abruptly returned to 70 ins. A closed loop controller was implemented that allowed the sawtooth period to be switched in real time between short and long sawteeth with a response time of the order of 1 s. (authors)

  13. INFRARED SPECTROSCOPY OF SYMBIOTIC STARS. VII. BINARY ORBIT AND LONG SECONDARY PERIOD VARIABILITY OF CH CYGNI

    International Nuclear Information System (INIS)

    Hinkle, Kenneth H.; Joyce, Richard R.; Fekel, Francis C.

    2009-01-01

    High-dispersion spectroscopic observations are used to refine orbital elements for the symbiotic binary CH Cyg. The current radial velocities, added to a previously published 13 year time series of infrared velocities for the M giant in the CH Cyg symbiotic system, more than double the length of the time series to 29 years. The two previously identified velocity periods are confirmed. The long period, revised to 15.6 ± 0.1 yr, is shown to result from a binary orbit with a 0.7 M sun white dwarf and 2 M sun M giant. Mass transfer to the white dwarf is responsible for the symbiotic classification. CH Cyg is the longest period S-type symbiotic known. Similarities with the longer period D-type systems are noted. The 2.1 year period is shown to be on Wood's sequence D, which contains stars identified as having long secondary periods (LSP). The cause of the LSP variation in CH Cyg and other stars is unknown. From our review of possible causes, we identify g-mode nonradial pulsation as the leading mechanism for LSP variation in CH Cyg. If g-mode pulsation is the cause of the LSPs, a radiative region is required near the photosphere of pulsating asymptotic giant branch stars.

  14. 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.

  15. 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.

  16. Comparing low frequency heart rate variability and preejection period: Two sides of a different coin.

    NARCIS (Netherlands)

    Goedhart, A.D.; Willemsen, G.; Houtveen, J.H.; Boomsma, D.I.; de Geus, E.J.C.

    2008-01-01

    It has been hypothesized that the ratio of heart rate variability in the low- (LF) and high- (HF) frequency bands may capture variation in cardiac sympathetic control. Here we tested the temporal stability of the LF/HF ratio in 24-h ambulatory recordings and compared this ratio to the preejection

  17. Activity and selectivity control through periodic composition forcing over Fischer-Tropsch catalysts

    Energy Technology Data Exchange (ETDEWEB)

    Silveston, P L; Hudgins, R R; Adesina, A A; Ross, G S; Feimer, J L

    1986-01-01

    Data collected under steady-state and periodic composition forcing of the Fischer-Tropsch synthesis over three commonly used catalysts demonstrate that both activity and selectivity can be changed by the latter operating mode. Synthesis of hydrocarbons up to C/sub 7/are favored at the expense of the higher carbon numbers for the Co catalyst, while for the Ru catalyst, only the C/sub 3/ and lower species are favored. Only methane production is stimulated with the Fe catalyst. Fe and Ru catalysts shift production from alkenes to alkanes. Transient data is interpreted in the paper.

  18. 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.

  19. 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.

  20. Rapid climate variability during warm and cold periods in polar regions and Europe

    DEFF Research Database (Denmark)

    Masson-Delmotte, V.; Landais, A.; Combourieu-Nebout, N.

    2005-01-01

    Typical rapid climate events punctuating the last glacial period in Greenland, Europe and Antarctica are compared to two rapid events occurring under warmer conditions: (i) Dansgaard-Oeschger event 25, the first abrupt warming occurring during last glacial inception; (ii) 8.2 ka BP event, the only...... rapid cooling recorded during the Holocene in Greenland ice cores and in Ammersee, Germany. The rate of warming during previous warmer interglacial periods is estimated from polar ice cores to 1.5 °C per millennium, without abrupt changes. Climate change expected for the 21st century should however...

  1. 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.

  2. X-Ray Quasi-periodic Oscillations in the Lense–Thirring Precession Model. I. Variability of Relativistic Continuum

    Science.gov (United States)

    You, Bei; Bursa, Michal; Życki, Piotr T.

    2018-05-01

    We develop a Monte Carlo code to compute the Compton-scattered X-ray flux arising from a hot inner flow that undergoes Lense–Thirring precession. The hot flow intercepts seed photons from an outer truncated thin disk. A fraction of the Comptonized photons will illuminate the disk, and the reflected/reprocessed photons will contribute to the observed spectrum. The total spectrum, including disk thermal emission, hot flow Comptonization, and disk reflection, is modeled within the framework of general relativity, taking light bending and gravitational redshift into account. The simulations are performed in the context of the Lense–Thirring precession model for the low-frequency quasi-periodic oscillations, so the inner flow is assumed to precess, leading to periodic modulation of the emitted radiation. In this work, we concentrate on the energy-dependent X-ray variability of the model and, in particular, on the evolution of the variability during the spectral transition from hard to soft state, which is implemented by the decrease of the truncation radius of the outer disk toward the innermost stable circular orbit. In the hard state, where the Comptonizing flow is geometrically thick, the Comptonization is weakly variable with a fractional variability amplitude of ≤10% in the soft state, where the Comptonizing flow is cooled down and thus becomes geometrically thin, the fractional variability of the Comptonization is highly variable, increasing with photon energy. The fractional variability of the reflection increases with energy, and the reflection emission for low spin is counterintuitively more variable than the one for high spin.

  3. 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.

  4. Multimodel simulations of Arctic Ocean sea surface height variability in the period 1970-2009

    DEFF Research Database (Denmark)

    Koldunov, Nikolay V.; Serra, Nuno; Koehl, Armin

    2014-01-01

    analysis of the three time periods 1987-1992, 1993-2002, and 2003-2009, corresponding to the transition times between cyclonic and anticyclonic regimes of the atmospheric circulation over the Arctic, revealed an unusual increase of SSH in the Amerasian basin during 2003-2009. Results from this model...

  5. ASSOCIATING LONG-TERM {gamma}-RAY VARIABILITY WITH THE SUPERORBITAL PERIOD OF LS I +61 Degree-Sign 303

    Energy Technology Data Exchange (ETDEWEB)

    Ackermann, M.; Buehler, R. [Deutsches Elektronen Synchrotron DESY, D-15738 Zeuthen (Germany); Ajello, M. [Space Sciences Laboratory, 7 Gauss Way, University of California, Berkeley, CA 94720-7450 (United States); Ballet, J.; Casandjian, J. M. [Laboratoire AIM, CEA-IRFU/CNRS/Universite Paris Diderot, Service d' Astrophysique, CEA Saclay, F-91191 Gif sur Yvette (France); Barbiellini, G. [Istituto Nazionale di Fisica Nucleare, Sezione di Trieste, I-34127 Trieste (Italy); Bastieri, D.; Buson, S. [Istituto Nazionale di Fisica Nucleare, Sezione di Padova, I-35131 Padova (Italy); Bellazzini, R.; Bregeon, J. [Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, I-56127 Pisa (Italy); Bonamente, E.; Cecchi, C. [Istituto Nazionale di Fisica Nucleare, Sezione di Perugia, I-06123 Perugia (Italy); Brandt, T. J. [NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Brigida, M. [Dipartimento di Fisica ' ' M. Merlin' ' dell' Universita e del Politecnico di Bari, I-70126 Bari (Italy); Bruel, P. [Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, F-91128 Palaiseau (France); Caliandro, G. A. [Institute of Space Sciences (IEEE-CSIC), Campus UAB, E-08193 Barcelona (Spain); Cameron, R. A. [W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305 (United States); Caraveo, P. A. [INAF-Istituto di Astrofisica Spaziale e Fisica Cosmica, I-20133 Milano (Italy); Cavazzuti, E. [Agenzia Spaziale Italiana (ASI) Science Data Center, I-00044 Frascati (Roma) (Italy); Chekhtman, A., E-mail: andrea.caliandro@ieec.uab.es, E-mail: hadasch@ieec.uab.es, E-mail: dtorres@ieec.uab.es [Center for Earth Observing and Space Research, College of Science, George Mason University, Fairfax, VA 22030 (United States); and others

    2013-08-20

    Gamma-ray binaries are stellar systems for which the spectral energy distribution (discounting the thermal stellar emission) peaks at high energies. Detected from radio to TeV gamma rays, the {gamma}-ray binary LS I +61 Degree-Sign 303 is highly variable across all frequencies. One aspect of this system's variability is the modulation of its emission with the timescale set by the {approx}26.4960 day orbital period. Here we show that, during the time of our observations, the {gamma}-ray emission of LS I +61 Degree-Sign 303 also presents a sinusoidal variability consistent with the previously known superorbital period of 1667 days. This modulation is more prominently seen at orbital phases around apastron, whereas it does not introduce a visible change close to periastron. It is also found in the appearance and disappearance of variability at the orbital period in the power spectrum of the data. This behavior could be explained by a quasi-cyclical evolution of the equatorial outflow of the Be companion star, whose features influence the conditions for generating gamma rays. These findings open the possibility to use {gamma}-ray observations to study the outflows of massive stars in eccentric binary systems.

  6. ASSOCIATING LONG-TERM γ-RAY VARIABILITY WITH THE SUPERORBITAL PERIOD OF LS I +61°303

    International Nuclear Information System (INIS)

    Ackermann, M.; Buehler, R.; Ajello, M.; Ballet, J.; Casandjian, J. M.; Barbiellini, G.; Bastieri, D.; Buson, S.; Bellazzini, R.; Bregeon, J.; Bonamente, E.; Cecchi, C.; Brandt, T. J.; Brigida, M.; Bruel, P.; Caliandro, G. A.; Cameron, R. A.; Caraveo, P. A.; Cavazzuti, E.; Chekhtman, A.

    2013-01-01

    Gamma-ray binaries are stellar systems for which the spectral energy distribution (discounting the thermal stellar emission) peaks at high energies. Detected from radio to TeV gamma rays, the γ-ray binary LS I +61°303 is highly variable across all frequencies. One aspect of this system's variability is the modulation of its emission with the timescale set by the ∼26.4960 day orbital period. Here we show that, during the time of our observations, the γ-ray emission of LS I +61°303 also presents a sinusoidal variability consistent with the previously known superorbital period of 1667 days. This modulation is more prominently seen at orbital phases around apastron, whereas it does not introduce a visible change close to periastron. It is also found in the appearance and disappearance of variability at the orbital period in the power spectrum of the data. This behavior could be explained by a quasi-cyclical evolution of the equatorial outflow of the Be companion star, whose features influence the conditions for generating gamma rays. These findings open the possibility to use γ-ray observations to study the outflows of massive stars in eccentric binary systems

  7. Fringe-period selection for a multifrequency fringe-projection phase unwrapping method

    International Nuclear Information System (INIS)

    Zhang, Chunwei; Zhao, Hong; Jiang, Kejian

    2016-01-01

    The multi-frequency fringe-projection phase unwrapping method (MFPPUM) is a typical phase unwrapping algorithm for fringe projection profilometry. It has the advantage of being capable of correctly accomplishing phase unwrapping even in the presence of surface discontinuities. If the fringe frequency ratio of the MFPPUM is too large, fringe order error (FOE) may be triggered. FOE will result in phase unwrapping error. It is preferable for the phase unwrapping to be kept correct while the fewest sets of lower frequency fringe patterns are used. To achieve this goal, in this paper a parameter called fringe order inaccuracy (FOI) is defined, dominant factors which may induce FOE are theoretically analyzed, a method to optimally select the fringe periods for the MFPPUM is proposed with the aid of FOI, and experiments are conducted to research the impact of the dominant factors in phase unwrapping and demonstrate the validity of the proposed method. Some novel phenomena are revealed by these experiments. The proposed method helps to optimally select the fringe periods and detect the phase unwrapping error for the MFPPUM. (paper)

  8. 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.

  9. ASSESSING GLOBAL CLIMATE VARIABILITY UNDER COLDEST AND WARMEST PERIODS AT DIFFERENT LATITUDINAL REGIONS

    Directory of Open Access Journals (Sweden)

    Eleonora Runtunuwu

    2016-10-01

    Full Text Available Effect of climate change on water balance will play a key role in the biosphere system. To study the global climate change impact on water balance during 95-year period (1901-1995, long-term grid climatic data including global mean monthly temperature and precipitation at 0.5 x 0.5 degree resolution were analysed. The trend and variation of climate change, the time series of monthly air temperature and precipitation data were aggregated into annual arithmetic means for two extreme periods (1901-1920 and 1990-1995. The potential evapotranspiration (Eo was calculated using Thornthwaite method.The changes in mean annual value were obtained by subtracting the maximum period data from 1990 to 1995 (Max with the minimum period data from 1901 to 1920 (Min. The results revealed that over 95-year period, mean global air temperature increased by 0.57oC. The temperature increase varied greatly in Asia, with more than 3.0oC, especially at 45-70oN, as well over the northern part of America (60-65oN and Europe (55- 75oN. In low latitude across Asia, Africa, and South America, the variation was less than 1.5oC. In 80-85ºN region, the variation was relatively small and at higher latitudes it increasedsignificantly. Precipitation varied temporally and spatially. In the 40-45ºN and 40-45ºS regions, increasing precipitation of more than 100 mm occurred during the June-August andSeptember-November, especially in the northern hemisphere. The Eo increase of 2000 mm during 95 years occurred in the tropical northern America, middle Africa, and South-East Asia. A grid in Central Java of Indonesia showed that the Eo increase of 2500 mm during 95 years resulted in the decrease of growing period by 100 days. In coping with climate change, adjustment of cropping calendar is imperative.

  10. THE ACS LCID PROJECT. I. SHORT-PERIOD VARIABLES IN THE ISOLATED DWARF SPHEROIDAL GALAXIES CETUS AND TUCANA

    International Nuclear Information System (INIS)

    Bernard, Edouard J.; Monelli, Matteo; Gallart, Carme

    2009-01-01

    We present the first study of the variable star populations in the isolated dwarf spheroidal galaxies (dSphs) Cetus and Tucana. Based on Hubble Space Telescope images obtained with the Advanced Camera for Surveys in the F475W and F814W bands, we identified 180 and 371 variables in Cetus and Tucana, respectively. The vast majority are RR Lyrae stars. In Cetus, we also found three anomalous Cepheids (ACs), four candidate binaries and one candidate long-period variable (LPV), while six ACs and seven LPV candidates were found in Tucana. Of the RR Lyrae stars, 147 were identified as fundamental mode (RRab) and only eight as first-overtone mode (RRc) in Cetus, with mean periods of 0.614 and 0.363 day, respectively. In Tucana, we found 216 RRab and 82 RRc giving mean periods of 0.604 and 0.353 day. These values place both galaxies in the so-called Oosterhoff Gap, as is generally the case for dSph. We calculated the distance modulus to both galaxies using different approaches based on the properties of RRab and RRc, namely, the luminosity-metallicity and period-luminosity-metallicity relations, and found values in excellent agreement with previous estimates using independent methods: (m - M) 0,Cet = 24.46 ± 0.12 and (m - M) 0,Tuc = 24.74 ± 0.12, corresponding to 780 ± 40 kpc and 890 ± 50 kpc. We also found numerous RR Lyrae variables pulsating in both modes simultaneously (RRd): 17 in Cetus and 60 in Tucana. Tucana is, after Fornax, the second dSph in which such a large fraction of RRd (∼17%) has been observed. We provide the photometry and pulsation parameters for all the variables, and compare the latter with values from the literature for well studied dSph of the Local Group and Galactic globular clusters. The parallel WFPC2 fields were also searched for variables, as they lie well within the tidal radius of Cetus, and at its limit in the case of Tucana. No variables were found in the latter, while 15 were discovered in the outer field of Cetus (11 RRab, three RRc

  11. 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.

  12. 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.

  13. Periodic imidazolium-bridged hybrid monolith for high-efficiency capillary liquid chromatography with enhanced selectivity.

    Science.gov (United States)

    Qiao, Xiaoqiang; Zhang, Niu; Han, Manman; Li, Xueyun; Qin, Xinying; Shen, Shigang

    2017-03-01

    A novel periodic imidazolium-bridged hybrid monolithic column was developed. With diene imidazolium ionic liquid 1-allyl-3-vinylimidazolium bromide as both cross-linker and organic functionalized reagent, a new periodic imidazolium-bridged hybrid monolithic column was facilely prepared in capillary with homogeneously distributed cationic imidazolium by a one-step free-radical polymerization with polyhedral oligomeric silsesquioxane methacryl substituted. The successful preparation of the new column was verified by Fourier transform infrared spectroscopy, scanning electron microscopy, elemental analysis, and surface area analysis. Most interestingly, the bonded amount of 1-allyl-3-vinylimidazolium bromide of the new column is three times higher than that of the conventional imidazolium-embedded hybrid monolithic column and the specific surface area of the column reached 478 m 2 /g. The new column exhibited high stability, excellent separation efficiency, and enhanced separation selectivity. The column efficiency reached 151 000 plates/m for alkylbenzenes. Furthermore, the new column was successfully used for separation of highly polar nucleosides and nucleic acid bases with pure water as mobile phase and even bovine serum albumin tryptic digest. All these results demonstrate the periodic imidazolium-bridged hybrid monolithic column is a good separation media and can be used for chromatographic separation of small molecules and complex biological samples with high efficiency. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. QUASI-PERIODIC OSCILLATIONS AND BROADBAND VARIABILITY IN SHORT MAGNETAR BURSTS

    Energy Technology Data Exchange (ETDEWEB)

    Huppenkothen, Daniela; Watts, Anna L.; Uttley, Phil; Van der Horst, Alexander J.; Van der Klis, Michiel [Astronomical Institute ' ' Anton Pannekoek' ' , University of Amsterdam, Postbus 94249, 1090-GE Amsterdam (Netherlands); Kouveliotou, Chryssa [Office of Science and Technology, ZP12, NASA Marshall Space Flight Center, Huntsville, AL 35812 (United States); Goegues, Ersin [Sabanc Latin-Small-Letter-Dotless-I University, Orhanl Latin-Small-Letter-Dotless-I -Tuzla, Istanbul 34956 (Turkey); Granot, Jonathan [The Open University of Israel, 1 University Road, P.O. Box 808, Ra' anana 43537 (Israel); Vaughan, Simon [X-Ray and Observational Astronomy Group, University of Leicester, Leicester LE1 7RH (United Kingdom); Finger, Mark H., E-mail: D.Huppenkothen@uva.nl [Universities Space Research Association, Huntsville, AL 35805 (United States)

    2013-05-01

    The discovery of quasi-periodic oscillations (QPOs) in magnetar giant flares has opened up prospects for neutron star asteroseismology. However, with only three giant flares ever recorded, and only two with data of sufficient quality to search for QPOs, such analysis is seriously data limited. We set out a procedure for doing QPO searches in the far more numerous, short, less energetic magnetar bursts. The short, transient nature of these bursts requires the implementation of sophisticated statistical techniques to make reliable inferences. Using Bayesian statistics, we model the periodogram as a combination of red noise at low frequencies and white noise at high frequencies, which we show is a conservative approach to the problem. We use empirical models to make inferences about the potential signature of periodic and QPOs at these frequencies. We compare our method with previously used techniques and find that although it is on the whole more conservative, it is also more reliable in ruling out false positives. We illustrate our Bayesian method by applying it to a sample of 27 bursts from the magnetar SGR J0501+4516 observed by the Fermi Gamma-ray Burst Monitor, and we find no evidence for the presence of QPOs in any of the bursts in the unbinned spectra, but do find a candidate detection in the binned spectra of one burst. However, whether this signal is due to a genuine quasi-periodic process, or can be attributed to unmodeled effects in the noise is at this point a matter of interpretation.

  15. Geographic variability of fatal road traffic injuries in Spain during the period 2002–2004: an ecological study

    Directory of Open Access Journals (Sweden)

    Jimenez-Puente Alberto

    2007-09-01

    Full Text Available Abstract Background The aim of the present study is to describe the inter-province variability of Road Traffic Injury (RTI mortality on Spanish roads, adjusted for vehicle-kilometres travelled, and to assess the possible role played by the following explicative variables: sociodemographic, structural, climatic and risk conducts. Methods An ecological study design was employed. The mean annual rate of RTI deaths was calculated for the period 2002–2004, adjusted for vehicle-kilometres travelled, in the 50 provinces of Spain. The RTI death rate was related with the independent variables described above, using simple and multiple linear regression analysis with backward step-wise elimination. The level of statistical significance was taken as p Results In the period 2002–2004 there were 12,756 RTI deaths in Spain (an average of 4,242 per year, SD = 356.6. The mean number of deaths due to RTI per 100 million vehicle-kilometres (mvk travelled was 1.76 (SD = 0.51, with a minimum value of 0.66 (in Santa Cruz de Tenerife and a maximum of 3.31 (in the province of Lugo. All other variables being equal, a higher proportion of kilometres available on high capacity roads, and a higher cultural and education level were associated with lower death rates due to RTI, while the opposite was true for the rate of alcohol consumers and the road traffic volume of heavy vehicles. The variables included in the model accounted for 55.4% of the variability in RTI mortality. Conclusion Adjusting RTI mortality rates for the number of vehicle-kilometres travelled enables us to identify the high variability of this cause of death, and its relation with risk factors other than those inherent to human behaviour, such as the type of roads and the type of vehicles using them.

  16. 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...

  17. Millennial-scale climate variability during the Last Glacial period in the tropical Andes

    Science.gov (United States)

    Fritz, S. C.; Baker, P. A.; Ekdahl, E.; Seltzer, G. O.; Stevens, L. R.

    2010-04-01

    Millennial-scale climate variation during the Last Glacial period is evident in many locations worldwide, but it is unclear if such variation occurred in the interior of tropical South America, and, if so, how the low-latitude variation was related to its high-latitude counterpart. A high-resolution record, derived from the deep drilling of sediments on the floor of Lake Titicaca in the southern tropical Andes, is presented that shows clear evidence of millennial-scale climate variation between ˜60 and 20 ka BP. This variation is manifested by alternations of two interbedded sedimentary units. The two units have distinctive sedimentary, geochemical, and paleobiotic properties that are controlled by the relative abundance of terrigenous or nearshore components versus pelagic components. The sediments of more terrigenous or nearshore nature likely were deposited during regionally wetter climates when river transport of water and sediment was higher, whereas the sediments of more pelagic character were deposited during somewhat drier climates regionally. The majority of the wet periods inferred from the Lake Titicaca sediment record are correlated with the cold events in the Greenland ice cores and North Atlantic sediment cores, indicating that increased intensity of the South American summer monsoon was part of near-global scale climate excursions.

  18. 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)

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Selective vancomycin detection using optical fibre long period gratings functionalised with molecularly imprinted polymer nanoparticles.

    Science.gov (United States)

    Korposh, Sergiy; Chianella, Iva; Guerreiro, Antonio; Caygill, Sarah; Piletsky, Sergey; James, Stephen W; Tatam, Ralph P

    2014-05-07

    An optical fibre long period grating (LPG) sensor modified with molecularly imprinted polymer nanoparticles (nanoMIPs) for the specific detection of antibiotics is presented. The operation of the sensor is based on the measurement of changes in refractive index induced by the interaction of nanoMIPs deposited onto the cladding of the LPG with free vancomycin (VA). The binding of nanoMIPs to vancomycin was characterised by a binding constant of 4.3 ± 0.1 × 10(-8) M. The lowest concentration of analyte measured by the fibre sensor was 10 nM. In addition, the sensor exhibited selectivity, as much smaller responses were obtained for high concentrations (∼700 μM) of other commonly prescribed antibiotics such as amoxicillin, bleomycin and gentamicin. In addition, the response of the sensor was characterised in a complex matrix, porcine plasma, spiked with 10 μM of VA.

  4. 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.

  5. Non-radial oscillations of rotating stars and their relevance to the short-period oscillations of cataclysmic variables

    International Nuclear Information System (INIS)

    Papaloizou, J.; Pringle, J.E.

    1978-01-01

    The usual hypothesis, that the short-period coherent oscillations seen in cataclysmic variables are attributable to g modes in a slowly rotating white dwarf, is considered. It is shown that this hypothesis is untenable for three main reasons: (i) the observed periods are too short for reasonable white dwarf models, (ii) the observed variability of the oscillations is too rapid and (iii) the expected rotation of the white dwarf, due to accretion, invalidates the slow rotation assumption on which standard g-mode theory is based. The low-frequency spectrum of a rotating pulsating star is investigated taking the effects of rotation fully into account. In this case there are two sets of low-frequency modes, the g modes, and modes similar to Rossby waves in the Earth's atmosphere and oceans, which are designated r modes. Typical periods for such modes are 1/m times the rotation period of the white dwarfs outer layers (m is the aximuthal wavenumber). It is concluded that non-radial oscillations of rotating white dwarfs can account for the properties of the oscillations seen in dwarf novae. Application of these results to other systems is also discussed. (author)

  6. Selection of doublet cellular patterns in directional solidification through spatially periodic perturbations

    International Nuclear Information System (INIS)

    Losert, W.; Stillman, D.A.; Cummins, H.Z.; Kopczynski, P.; Rappel, W.; Karma, A.

    1998-01-01

    Pattern formation at the solid-liquid interface of a growing crystal was studied in directional solidification using a perturbation technique. We analyzed both experimentally and numerically the stability range and dynamical selection of cellular arrays of 'doublets' with asymmetric tip shapes, separated by alternate deep and shallow grooves. Applying an initial periodic perturbation of arbitrary wavelength to the unstable planar interface allowed us to force the interface to evolve into doublet states that would not otherwise be dynamically accessible from a planar interface. We determined systematically the ranges of wavelength corresponding to stable singlets, stable doublets, and transient unstable patterns. Experimentally, this was accomplished by applying a brief UV light pulse of a desired spatial periodicity to the planar interface during the planar-cellular transient using the model alloy Succinonitrile-Coumarin 152. Numerical simulations of the nonlinear evolution of the interface were performed starting from a small sinusoidal perturbation of the steady-state planar interface. These simulations were carried out using a computationally efficient phase-field symmetric model of directional solidification with recently reformulated asymptotics and vanishing kinetics [A. Karma and W.-J. Rappel, Phys. Rev. E 53 R3017 (1996); Phys. Rev. Lett. 77, 4050 (1996); Phys. Rev. E 57, 4323 (1998)], which allowed us to simulate spatially extended arrays that can be meaningfully compared to experiments. Simulations and experiments show remarkable qualitative agreement in the dynamic evolution, steady-state structure, and instability mechanisms of doublet cellular arrays. copyright 1998 The American Physical Society

  7. Periodic table of virus capsids: implications for natural selection and design.

    Science.gov (United States)

    Mannige, Ranjan V; Brooks, Charles L

    2010-03-04

    For survival, most natural viruses depend upon the existence of spherical capsids: protective shells of various sizes composed of protein subunits. So far, general evolutionary pressures shaping capsid design have remained elusive, even though an understanding of such properties may help in rationally impeding the virus life cycle and designing efficient nano-assemblies. This report uncovers an unprecedented and species-independent evolutionary pressure on virus capsids, based on the the notion that the simplest capsid designs (or those capsids with the lowest "hexamer complexity", C(h)) are the fittest, which was shown to be true for all available virus capsids. The theories result in a physically meaningful periodic table of virus capsids that uncovers strong and overarching evolutionary pressures, while also offering geometric explanations to other capsid properties (rigidity, pleomorphy, auxiliary requirements, etc.) that were previously considered to be unrelatable properties of the individual virus. Apart from describing a universal rule for virus capsid evolution, our work (especially the periodic table) provides a language with which highly diverse virus capsids, unified only by geometry, may be described and related to each other. Finally, the available virus structure databases and other published data reiterate the predicted geometry-derived rules, reinforcing the role of geometry in the natural selection and design of virus capsids.

  8. Evaluation and selection of NPPs for medium term period around 2020

    International Nuclear Information System (INIS)

    Zezula, L.

    2004-01-01

    The Czech Republic is one of the European countries where a nuclear option remains open as a part of an energy mix. This will help the country to meet its international commitments under the Kyoto Protocol. Moreover the country has also its own industrial potential which can significantly contribute to possible construction of a new nuclear source both in the Czech Republic and abroad. Therefore, the selection of a new nuclear source which could be connected to the national grid after 2020 is actually a pressing issue. General features of economics assessment philosophy as to electricity generation costs are briefly discussed, and an overview of basic economic assessment methods is presented. An example of the economic calculations for a small grid is also given. General approach to the evaluation of advanced nuclear power plants projects (feasible for the period around 2020) are discussed. A simple method of the preliminary evaluation and selection of a suitable type of the plant is presented and general targets which are prerequisite and follow also from important international activities (GIF project and INPRO project) are elucidated. (author)

  9. Purine Turnover Metabolites and Selected Antioxidants in Blood of Goats during the Periparturient Period

    Directory of Open Access Journals (Sweden)

    Ewa Skotnicka

    2010-01-01

    Full Text Available The aim of this study was to examine the relationships between the erythrocyte concentrations of ATP, ADP, AMP, NAD+, NADP+ and adenylate energy charge (AEC and their metabolites: inosine (Ino, hypoxanthine (Hyp, uric acid (UA, selected blood antioxidants: superoxide dismutase (SOD, glutathione reductase (GR of goats during the periparturient period. The study was conducted on 12 clinically healthy pregnant goats (Capra hircus - 75% genotype of the Polish noble white aged between 2-3 years. Blood was taken from the external jugular vein early in the morning before feeding and obtained twice (4 weeks and 1 week before delivery and twice (2 and 3 weeks after delivery. The ATP concentration did not change significantly. One week before delivery ADP, AMP and Ino concentrations were significantly higher and AEC value significantly lower compared to values in the third week after delivery (p ≤ 0.02, p ≤ 0.05, p ≤ 0.03 and p ≤ 0.01, respectively. One week before and two weeks after delivery we observed a significant increase in SOD and GR activities and an increase in NAD+ and NADP+ concentrations but a significant decrease in Hyp and UA concentrations. Constant ATP concentration and the changes in the dynamics and tendency of Hyp and UA concentrations show that in the periparturient period in goats, purine metabolism undergoes adaptive changes. The balance between resynthetic processes and adenine nucleotide degradation is retained in order to level the oxygen and energy lacks. The results of our study show that the maintenance of prooxidative homeostasis in goats of peripartal period depends mainly on enzymatic mechanisms.

  10. Periparturient Period in Terms of Body Condition Score and Selected Parameters of Hormonal Profiles

    Directory of Open Access Journals (Sweden)

    Vargová M.

    2016-03-01

    Full Text Available The majority of all diseases in dairy cows occur during the period from three weeks before parturition to three weeks after parturition, in the periparturient or transitional period. The objective of this study was to evaluate the dynamics of selected parameters of: the hormonal profiles, the body condition score (BCS and their interrelationships. The study was carried out on 15 dairy cows of the Slovak Pied Cattle, from three weeks before to nine weeks after parturition, which were divided into six groups. The concentrations of leptin during ante partum increased from 23.08 ± 10.58 ng.ml−1 to 26.80 ± 11.47 ng.ml−1, then gradually decreased (P > 0.05, and conversely, the concentrations of ghrelin before parturition were found to be decreasing and during the postpartal period, the concentrations increased, with the highest value of 35.94 ± 16.85 pg.ml−1. In the case of insulin, we found the opposite tendency of ghrelin. We observed significantly higher values of BCS in dry cows than in cows after parturition (P < 0.001. Comparing the BCS and the parameter of the hormonal profiles, we found both positive and negative correlations: leptin and ghrelin (r = −0.235, P < 0.05, and BCS and insulin (r = 0.232, P < 0.05, and BCS and leptin (r = 0.360, P < 0.001. The interrelationships between the hormones and the body condition score, provided evidence that the variations in concentrations of leptin, ghrelin and insulin were related to variations in the BCS.

  11. Spatial variability in oviposition damage by periodical cicadas in a fragmented landscape.

    Science.gov (United States)

    Cook, William M; Holt, Robert D; Yao, Jin

    2001-03-01

    Effects of the periodical cicada (Magicicada spp.) on forest dynamics are poorly documented. A 1998 emergence of M. cassini in eastern Kansas led to colonization of a fragmented experimental landscape undergoing secondary succession. We hypothesized that per-tree rates of oviposition damage by cicadas would reflect: (1) distance from the source of the emergence, (2) patch size, and (3) local tree density. Ovipositing females displayed clear preferences for host species and damage incidence showed predictable spatial patterns. Two species (smooth sumac, Rhus glabra, and eastern red cedar, Juniperus virginiana) were rarely attacked, whereas others (rough-leaved dogwood, Cornus drummondii; slippery elm, Ulmus rubra; box elder, Acer negundo, and honey locust, Gleditsia triacanthos) were strongly attacked. The dominant early successional tree, dogwood, received on average the most attacks. As predicted, attacks per stem declined strongly with distance from the emergence source, and with local stem density (a "dilution" effect). Contrary to expectations, there were more attacks per stem on larger patches. Because ovipositing cicadas cut damaging slits in host tree branches, potentially affecting tree growth rate, competitive ability, and capacity to reproduce, cicada damage could potentially influence spatial variation in secondary succession.

  12. Effect of climatic variability on childhood diarrhea and its high risk periods in northwestern parts of Ethiopia

    Science.gov (United States)

    Kumie, Abera; Worku, Alemayehu; C. Bagtzoglou, Amvrossios; Anagnostou, Emmanouil

    2017-01-01

    Background Increasing climate variability as a result of climate change will be one of the public health challenges to control infectious diseases in the future, particularly in sub-Saharan Africa including Ethiopia. Objective To investigate the effect of climate variability on childhood diarrhea (CDD) and identify high risk periods of diarrheal diseases. Methods The study was conducted in all districts located in three Zones (Awi, West and East Gojjam) of Amhara Region in northwestern parts of Ethiopia. Monthly CDD cases for 24 months (from July 2013 to June 2015) reported to each district health office from the routine surveillance system were used for the study. Temperature, rainfall and humidity data for each district were extracted from satellite precipitation estimates and global atmospheric reanalysis. The space-time permutation scan statistic was used to identify high risk periods of CDD. A negative binomial regression was used to investigate the relationship between cases of CDD and climate variables. Statistical analyses were conducted using SaTScan program and StataSE v. 12. Results The monthly average incidence rate of CDD was 11.4 per 1000 (95%CI 10.8–12.0) with significant variation between males [12.5 per 1000 (95%CI 11.9 to 13.2)] and females [10.2 per 1000 (95%CI 9.6 to 10.8)]. The space-time permutation scan statistic identified the most likely high risk period of CDD between March and June 2014 located in Huletej Enese district of East Gojjam Zone. Monthly average temperature and monthly average rainfall were positively associated with the rate of CDD, whereas the relative humidity was negatively associated with the rate of CDD. Conclusions This study found that the most likely high risk period is in the beginning of the dry season. Climatic factors have an association with the occurrence of CDD. Therefore, CDD prevention and control strategy should consider local weather variations to improve programs on CDD. PMID:29073259

  13. 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.

  14. 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...

  15. Spatial and temporal variability of precipitation in Serbia for the period 1961-2010

    Science.gov (United States)

    Milovanović, Boško; Schuster, Phillip; Radovanović, Milan; Vakanjac, Vesna Ristić; Schneider, Christoph

    2017-10-01

    Monthly, seasonal and annual sums of precipitation in Serbia were analysed in this paper for the period 1961-2010. Latitude, longitude and altitude of 421 precipitation stations and terrain features in their close environment (slope and aspect of terrain within a radius of 10 km around the station) were used to develop a regression model on which spatial distribution of precipitation was calculated. The spatial distribution of annual, June (maximum values for almost all of the stations) and February (minimum values for almost all of the stations) precipitation is presented. Annual precipitation amounts ranged from 500 to 600 mm to over 1100 mm. June precipitation ranged from 60 to 140 mm and February precipitation from 30 to 100 mm. The validation results expressed as root mean square error (RMSE) for monthly sums ranged from 3.9 mm in October (7.5% of the average precipitation for this month) to 6.2 mm in April (10.4%). For seasonal sums, RMSE ranged from 10.4 mm during autumn (6.1% of the average precipitation for this season) to 20.5 mm during winter (13.4%). On the annual scale, RMSE was 68 mm (9.5% of the average amount of precipitation). We further analysed precipitation trends using Sen's estimation, while the Mann-Kendall test was used for testing the statistical significance of the trends. For most parts of Serbia, the mean annual precipitation trends fell between -5 and +5 and +5 and +15 mm/decade. June precipitation trends were mainly between -8 and +8 mm/decade. February precipitation trends generally ranged from -3 to +3 mm/decade.

  16. 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

  17. 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.

  18. 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

  19. 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.

  20. 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...

  1. 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,

  2. 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.

  3. 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...

  4. 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.

  5. 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.

  6. 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.

  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. 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...

  9. Archeointensities in Greece during the Neolithic period: New insights into material selection and secular variation curve

    Science.gov (United States)

    Fanjat, G.; Aidona, E.; Kondopoulou, D.; Camps, P.; Rathossi, C.; Poidras, T.

    2013-02-01

    Numerous archeomagnetic studies have provided high quality data for both the direction and the intensity of the geomagnetic field, essentially in Europe for the last 10 millennia. In particular, Greece supplies a lot of archeological materials due to its impressive cultural heritage and volcanic activity, so that numerous data have been obtained from burnt clays or historical lava flows. The most recent Greek secular variation curves are available for the last 8 millennia for the intensity and the last 6 millennia for the direction. Nevertheless, the coverage still presents several gaps for periods older than 2500 BC. In an effort to complete the Greek curve and extend it to older times, we present the archeointensity results from three Neolithic settlements in Northern Greece. The samples are of two different natures: burnt structures from Avgi (5250 ± 150 BC) and Vasili (4800 ± 200 BC), as well as ceramics from Dikili Tash (4830 ± 80 BC) and Vasili (4750 ± 250 BC). The samples have been subjected to standard rock magnetic analyses in order to estimate the thermal stability and the domain state of the magnetic carriers before archeointensity measurements. Surprisingly, very few ceramic samples provided reliable archeointensities whereas samples from burnt structures presented a very good success rate. Complementary studies showed that a detailed examination of the matrix color, following archeological information and classification standards can be a decisive test for pre-selection of sherds. In spite of these unsuccessful measurements from ceramics, we obtained an intensity value of 73.5 ± 1.1 μT for Dikili Tash, a higher value than the other data obtained in the same area, during the same period. However we do not have evidences for a technical artefact during the experiment. The burnt structures yielded two reliable archeointensities of 36.1 ± 1.8 μT and 46.6 ± 3.4 μT for Avgi and Vasili, respectively. Finally, we achieved a new archeomagnetic dating

  10. 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.

  11. 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

  12. A NEW SUB-PERIOD-MINIMUM CATACLYSMIC VARIABLE WITH PARTIAL HYDROGEN DEPLETION AND EVIDENCE OF SPIRAL DISK STRUCTURE

    International Nuclear Information System (INIS)

    Littlefield, C.; Garnavich, P.; Magno, K.; Applegate, A.; Pogge, R.; Irwin, J.; Marion, G. H.; Kirshner, R.; Vinkó, J.

    2013-01-01

    We present time-resolved spectroscopy and photometry of CSS 120422:111127+571239 (=SBS 1108+574), a recently discovered SU UMa-type dwarf nova whose 55 minute orbital period is well below the cataclysmic variable (CV) period minimum of ∼78 minutes. In contrast with most other known CVs, its spectrum features He I emission of comparable strength to the Balmer lines, implying a hydrogen abundance less than 0.1 of long-period CVs—but still at least 10 times higher than that in AM CVn stars. Together, the short orbital period and remarkable helium-to-hydrogen ratio suggest that mass transfer in CSS 120422 began near the end of the donor star's main-sequence lifetime, meaning that this CV is a strong candidate progenitor of an AM CVn system as described by Podsiadlowski et al. Moreover, a Doppler tomogram of the Hα line reveals two distinct regions of enhanced emission. While one is the result of the stream-disk impact, the other is probably attributable to spiral disk structure generated when material in the outer disk achieves a 2:1 orbital resonance with respect to the donor.

  13. 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...

  14. RADIO MONITORING OF THE PERIODICALLY VARIABLE IR SOURCE LRLL 54361: NO DIRECT CORRELATION BETWEEN THE RADIO AND IR EMISSIONS

    Energy Technology Data Exchange (ETDEWEB)

    Forbrich, Jan, E-mail: jan.forbrich@univie.ac.at [University of Vienna, Department of Astrophysics, Türkenschanzstraße 17, A-1180 Vienna (Austria); Rodríguez, Luis F.; Palau, Aina; Zapata, Luis A. [Instituto de Radioastronomía y Astrofísica, UNAM, Apdo. Postal 3-72 (Xangari), 58089 Morelia, Michoacán (Mexico); Muzerolle, James [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Gutermuth, Robert A. [Department of Astronomy, University of Massachusetts, Amherst, MA 01003 (United States)

    2015-11-20

    LRLL 54361 is an infrared source located in the star-forming region IC 348 SW. Remarkably, its infrared luminosity increases by a factor of 10 over roughly one week every 25.34 days. To understand the origin of these remarkable periodic variations, we obtained sensitive 3.3 cm JVLA radio continuum observations of LRLL 54361 and its surroundings in six different epochs: three of them during the IR-on state and three during the IR-off state. The radio source associated with LRLL 54361 remained steady and did not show a correlation with the IR variations. We suggest that the IR is tracing the results of fast (with a timescale of days) pulsed accretion from an unseen binary companion, while the radio traces an ionized outflow with an extent of ∼100 AU that smooths out the variability over a period of the order of a year. The average flux density measured in these 2014 observations, 27 ± 5 μJy, is about a factor of two less than that measured about 1.5 years before, 53 ± 11 μJy, suggesting that variability in the radio is present, but over larger timescales than in the IR. We discuss other sources in the field, in particular two infrared/X-ray stars that show rapidly varying gyrosynchrotron emission.

  15. 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.

  16. 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

  17. 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)

  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. Dry period cooling ameliorates physiological variables and blood acid base balance, improving milk production in murrah buffaloes

    Science.gov (United States)

    Aarif, Ovais; Aggarwal, Anjali

    2016-03-01

    This study aimed to evaluate the impact of evaporative cooling during late gestation on physiological responses, blood gas and acid base balance and subsequent milk production of Murrah buffaloes. To investigate this study sixteen healthy pregnant dry Murrah buffaloes (second to fourth parity) at sixty days prepartum were selected in the months of May to June and divided into two groups of eight animals each. One group of buffaloes (Cooled/CL) was managed under fan and mist cooling system during dry period. Group second buffaloes (Noncooled/NCL) remained as control without provision of cooling during dry period. The physiological responses viz. Rectal temperature (RT), Respiratory rate (RR) and Pulse rate were significantly ( P Milk yield, FCM, fat yield, lactose yield and total solid yield was significantly higher ( P < 0.05) in cooled group of Murrah buffaloes.

  2. Genome variability of foot-and-mouth disease virus during the short period of the 2010 epidemic in Japan.

    Science.gov (United States)

    Nishi, Tatsuya; Yamada, Manabu; Fukai, Katsuhiko; Shimada, Nobuaki; Morioka, Kazuki; Yoshida, Kazuo; Sakamoto, Kenichi; Kanno, Toru; Yamakawa, Makoto

    2017-02-01

    Foot-and-mouth disease virus (FMDV) is highly contagious and has a high mutation rate, leading to extensive genetic variation. To investigate how FMDV genetically evolves over a short period of an epidemic after initial introduction into an FMD-free area, whole L-fragment sequences of 104 FMDVs isolated from the 2010 epidemic in Japan, which continued for less than three months were determined and phylogenetically and comparatively analyzed. Phylogenetic analysis of whole L-fragment sequences showed that these isolates were classified into a single group, indicating that FMDV was introduced into Japan in the epidemic via a single introduction. Nucleotide sequences of 104 virus isolates showed more than 99.56% pairwise identity rates without any genetic deletion or insertion, although no sequences were completely identical with each other. These results indicate that genetic substitutions of FMDV occurred gradually and constantly during the epidemic and generation of an extensive mutant virus could have been prevented by rapid eradication strategy. From comparative analysis of variability of each FMDV protein coding region, VP4 and 2C regions showed the highest average identity rates and invariant rates, and were confirmed as highly conserved. In contrast, the protein coding regions VP2 and VP1 were confirmed to be highly variable regions with the lowest average identity rates and invariant rates, respectively. Our data demonstrate the importance of rapid eradication strategy in an FMD epidemic and provide valuable information on the genome variability of FMDV during the short period of an epidemic. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  3. 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.

  4. 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...

  5. 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...

  6. 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...

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. Variability of the total ozone trend over Europe for the period 1950─2004 derived from reconstructed data

    Directory of Open Access Journals (Sweden)

    J. L. Borkowski

    2008-06-01

    Full Text Available The total ozone data over Europe are available for only few ground-based stations in the pre-satellite era disallowing examination of the spatial trend variability over the whole continent. A need of having gridded ozone data for a trend analysis and input to radiative transfer models stimulated a reconstruction of the daily ozone values since January 1950. Description of the reconstruction model and its validation were a subject of our previous paper. The data base used was built within the objectives of the COST action 726 "Long-term changes and climatology of UV radiation over Europe". Here we focus on trend analyses. The long-term variability of total ozone is discussed using results of a flexible trend model applied to the reconstructed total ozone data for the period 1950–2004. The trend pattern, which comprises both anthropogenic and "natural" component, is not a priori assumed but it comes from a smooth curve fit to the zonal monthly means and monthly grid values. The ozone long-term changes are calculated separately for cold (October–next year April and warm (May–September seasons. The confidence intervals for the estimated ozone changes are derived by the block bootstrapping. The statistically significant negative trends are found almost over the whole Europe only in the period 1985–1994. Negative trends up to −3% per decade appeared over small areas in earlier periods when the anthropogenic forcing on the ozone layer was weak . The statistically positive trends are found only during warm seasons 1995–2004 over Svalbard archipelago. The reduction of ozone level in 2004 relative to that before the satellite era is not dramatic, i.e., up to ~−5% and ~−3.5% in the cold and warm subperiod, respectively. Present ozone level is still depleted over many popular resorts in southern Europe and northern Africa. For high latitude regions the trend overturning could be inferred in last decade (1995–2004 as the ozone depleted

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Environmental radiation monitoring results for the period 1984-95 in and around Variable Energy Cyclotron Centre, Calcutta

    International Nuclear Information System (INIS)

    Basu, A.S.; Khasnabis, B.K.; Bar, M.

    1997-04-01

    Variable Energy Cyclotron (VEC) located at Bidhan Nagar, Calcutta is being used for accelerating charged particles and does not contribute to any radioactive releases to the environment. However, it being a nuclear facility, the area surrounding the facility is being routinely monitored for background radiation exposure using thermoluminescent dosimeters. This report gives the summary of the results of the survey carried out over a period of 12 years, 1984-1995. It is observed that the general radiation background in areas far removed from the facility (up to 25 km) is higher than that existing within the boundaries of VEC centre (160±21 mR/year as against 121±20 mR/year)

  20. 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....

  1. Identification and period investigation of pulsation variable star UY Camelopardalis, an RR Lyrae star in binary system

    Science.gov (United States)

    Li, Lin-Jia; Qian, Sheng-Bang; Voloshina, Irina; Metlov, Vladimir G.; Zhu, Li-Ying; Liao, Wen-Ping

    2018-06-01

    We present photometric measurements of the short period variable star UY Cam, which has been classified as a δ Scuti or c-type RR Lyrae (RRc) variable in different catalogs. Based on the analyses on Fourier coefficients and (NUV - V)0, we find that UY Cam is probably an RRc star. We obtain 58 new times of light maximum for UY Cam based on several sky surveys and our observations. Combining these with the times of light maximum in literature, a total of 154 times of light maximum are used to analyze the O - C diagram of UY Cam. The results show that the O - C pattern can be described by a downward parabolic component with a rate of -6.86 ± 0.47 × 10-11 d d-1, and a cyclic variation with a period of 65.7 ± 2.4 yr. We suppose these components are caused by the stellar evolution and the light travel time effect (LiTE) of a companion in elliptical orbit, respectively. By calculation, the minimum mass of the potential companion is about 0.17 M⊙, and its mass should be less than or equal to the pulsation primary star when the inclination i > 22.5°D. Therefore, the companion should be a low-mass star, like a late-type main-sequence star or a white dwarf. Due to the unique property of UY Cam, we suggest that more observations and studies on UY Cam and other RRc stars are needed to check the nature of these stars, including the pulsations and binarities.

  2. Reflections on Teaching Periodic Table Concepts: A Case Study of Selected Schools in South Africa

    Science.gov (United States)

    Mokiwa, Hamza Omari

    2017-01-01

    The Periodic Table of Elements is central to the study of modern Physics and Chemistry. It is however, considered by teachers as difficult to teach. This paper reports on a case study exploring reflections on teaching periodic table concepts in five secondary schools from South Africa. Qualitative methodology of interviews and document analysis…

  3. Long-period variables in the Large Magellanic Cloud. II. Infrared photometry, spectral classification, AGB evolution, and spatial distribution

    International Nuclear Information System (INIS)

    Hughes, S.M.G.; Wood, P.R.

    1990-01-01

    Infrared JHK photometry and visual spectra have been obtained for a large sample of long-period variables (LPVs) in the Large Magellanic Cloud (LMC). Various aspects of the asymptotic giant branch (AGB) evolution of LPVs are discussed using these data. The birth/death rate of LPVs of different ages in the LMC is compared with the birth rates of appropriate samples of planetary nebulas, clump stars, Cepheids, and OH/IR stars. It appears that there are much fewer large-amplitude LPVs per unit galactic stellar mass in the LMC than in the Galaxy. It is suggested that this may be due to the fact that the evolved intermediate-age AGB stars in the LMC often turn into carbon stars, which tend to have smaller pulsation amplitudes than M stars. There is also a major discrepancy between the number of LPVs in the LMC (and in the Galaxy) and the number predicted by the theories of AGB evolution, pulsation, and mass loss. A distance modulus to the LMC of 18.66 + or - 0.05 is derived by comparing the LMC LPVs with P about 200 days with the 47 Tucanae Mira variables in the (K, log P) plane. 64 refs

  4. Variability of cannabis potency in the Venice area (Italy): a survey over the period 2010-2012.

    Science.gov (United States)

    Zamengo, Luca; Frison, Giampietro; Bettin, Chiara; Sciarrone, Rocco

    2014-01-01

    Cannabis is the most widely used illicit substance globally, with an estimated annual prevalence in 2010 of 2.6-5.0% of the adult population. Concerns have been expressed about increases in the potency of cannabis products. A high tetrahydrocannabinol (THC) content can increase anxiety, depression, and psychotic symptoms, and can increase the risk of dependence and adverse effects on the respiratory and cardiovascular systems in regular users. The aim of this study was to report statistical data about the potency of cannabis products seized in the north-east of Italy, in a geographical area centred in Venice and extending for more than 10,000  km(2) with a population of more than two million, by investigating the variability observed in THC levels of about 4000 samples of cannabis products analyzed over the period 2010-2012. Overall median THC content showed an increasing trend over the study period from about 6.0% to 8.1% (6.2-8.9% for cannabis resin, 5.1-7.6% for herbal cannabis). The variation in the THC content of individual samples was very large, ranging from 0.3% to 31% for cannabis resin and from 0.1 to 19% for herbal cannabis. Median CBN:THC ratios showed a slightly decreasing trend over the study period, from 0.09 (2010) to 0.03 (2012), suggesting an increasing freshness of submitted materials. Median CBD:THC ratios also showed a decreasing trend over the study from about 0.52 (2010) to 0.18 (2012), likely due to the increase in submissions of materials from indoor and domestic cultivation with improved breeding methods. Copyright © 2013 John Wiley & Sons, Ltd.

  5. 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.

  6. 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.

  7. 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.

  8. Phenology of seed and leaves rain in response to periodic climatic variability in a seasonal wet tropical forest

    Science.gov (United States)

    Matteo, D.; Wright, S. J.; Davies, S. J.; Muller-Landau, H. C.; Wolfe, B.; Detto, M.

    2016-12-01

    Phenology, by controlling the rhythms of plants, plays a fundamental role in regulating access to resources, ecosystem processes, competition among species, interactions with consumers and feedbacks to the climate. In high biodiverse tropical forests, where phenology of flowering and leafing are complex, an adequate representation of phenology must take into account a given set of climatic, edaphic and biotic factors. Climatic factors are particularly important because plants may use them as cues for timing different phenological phases and be influenced by their intensity. Climatic variability can be periodic, if events occur with regular frequency, or aperiodic. One prominent periodic large-scale pattern that causes unusual weather is ENSO event. In general, Central America tends to be dry and warm during a mature phase of an ENSO event, which usually peaks between October and January with a frequency of 2-3 events per decade. Because in many tropical areas the effect of ENSO is highly prominent, it is plausible that plants have adapted their growth and reproduction mechanisms to synchronize ENSO phases, in a similar way that plants do during the seasonal cycle. We used a long dataset (30+ years) of fruits and leaves rains of tropical trees and lianas to determine ecosystem response and species specific response of these phenological events to local climate variability corresponding to the modes of ENSO. Specifically, we tested the hypothesis that phenological responses to ENSO are similar to response to seasonal cycles, i.e., higher litterfall before a warm-dry phase and higher fruiting after such phase, with strong correlation between seeds and leaves. At sub-community level, we evaluated whether evergreen and deciduous, biotic and abiotic dispersers and free and climbing life forms, have the same response to ENSO in terms of leaves and seeds rain. At species level we tested the hypothesis that species with low photosynthetic capacity leaves are more responsive

  9. Pulsations and period changes of the non-Blazhko RR lyrae variable Y oct observed from Dome A, Antarctica

    Energy Technology Data Exchange (ETDEWEB)

    Zhihua, Huang; Jianning, Fu; Weikai, Zong; Lingzhi, Wang; Zonghong, Zhu [Department of Astronomy, Beijing Normal University, Beijing 100875 (China); M, Macri Lucas; Lifan, Wang [Mitchell Institute for Fundamental Physics and Astronomy, Department of Physics and Astronomy, Texas A and M University, College Station, TX (United States); Ashley, Michael C. B.; S, Lawrence Jon; Daniel, Luong-Van [School of Physics, University of New South Wales, NSW (Australia); Xiangqun, Cui; Long-Long, Feng; Xuefei, Gong; Qiang, Liu; Huigen, Yang; Xiangyan, Yuan; Xu, Zhou; Zhenxi, Zhu [Chinese Center for Antarctic Astronomy, Nanjing (China); R, Pennypacker Carl [Center for Astrophysics, Lawrence Berkeley National Laboratory, Berkeley, CA (United States); G, York Donald, E-mail: jnfu@bnu.edu.cn [Department of Astronomy and Astrophysics and Enrico Fermi Institute, University of Chicago, Chicago, IL (United States)

    2015-01-01

    During the operation of the Chinese Small Telescope Array (CSTAR) in Dome A of Antarctica in the years 2008, 2009, and 2010, large amounts of photometric data have been obtained for variable stars in the CSTAR field. We present here the study of one of six RR Lyrae variables, Y Oct, observed with CSTAR in Dome A, Antarctica. Photometric data in the i band were obtained in 2008 and 2010, with a duty cycle (defined as the fraction of time representing scientifically available data to CSTAR observation time) of about 44% and 52%, respectively. In 2009, photometric data in the g and r bands were gathered for this star, with a duty cycle of 65% and 60%, respectively. Fourier analysis of the data in the three bands only shows the fundamental frequency and its harmonics, which is characteristic of the non-Blazhko RR Lyrae variables. Values of the fundamental frequency and the amplitudes, as well as the total pulsation amplitude, are obtained from the data in the three bands separately. The amplitude of the fundamental frequency and the total pulsation amplitude in the g band are the largest, and those in the i band the smallest. Two-hundred fifty-one times of maximum are obtained from the three seasons of data, which are analyzed together with 38 maximum times provided in the GEOS RR Lyrae database. A period change rate of −0.96 ± 0.07 days Myr{sup −1} is then obtained, which is a surprisingly large negative value. Based on relations available in the literature, the following physical parameters are derived: [Fe/H] = −1.41 ± 0.14, M{sub V} = 0.696 ± 0.014 mag, V−K = 1.182 ± 0.028 mag, logT{sub eff} = 3.802 ± 0.003 K, logg = 2.705 ± 0.004, logL/L{sub ⊙} = 1.625 ± 0.013, and logM/M{sub ⊙} = −0.240 ± 0.019.

  10. The variability in Oxford hip and knee scores in the preoperative period: is there an ideal time to score?

    Science.gov (United States)

    Quah, C; Holmes, D; Khan, T; Cockshott, S; Lewis, J; Stephen, A

    2018-01-01

    Background All NHS-funded providers are required to collect and report patient-reported outcome measures for hip and knee arthroplasty. Although there are established guidelines for timing such measures following arthroplasty, there are no specific time-points for collection in the preoperative period. The primary aim of this study was to identify whether there was a significant amount of variability in the Oxford hip and knee scores prior to surgical intervention when completed in the outpatient clinic at the time of listing for arthroplasty or when completed at the preoperative assessment clinic. Methods A prospective cohort study of patients listed for primary hip or knee arthroplasty was conducted. Patients were asked to fill in a preoperative Oxford score in the outpatient clinic at the time of listing. They were then invited to fill in the official outcome measures questionnaire at the preoperative assessment clinic. The postoperative Oxford score was then completed when the patient was seen again at their postoperative follow up in clinic. Results Of the total of 109 patients included in this study period, there were 18 (17%) who had a worse score of 4 or more points difference and 43 (39.4%) who had an improvement of 4 or more points difference when the scores were compared between time of listing at the outpatient and at the preoperative assessment clinic. There was a statistically significant difference (P = 0.0054) in the mean Oxford scores. Conclusions The results of our study suggest that there should be standardisation of timing for completing the preoperative patient-reported outcome measures.

  11. 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.

  12. 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.

  13. Chelating extractants of improved selectivity. Progress report for period November 1, 1977--July 31 1978

    International Nuclear Information System (INIS)

    Freiser, H.

    1978-08-01

    During the current contract period, the high susceptibility of lanthanide chelate stability to steric hindrance was confirmed. The increase in coordination number of lanthanides from lanthanum to ytterbium as evidenced from extraction equilibria serves to increase their separability. 8-Quinolinol immobilized on silica can separate lanthanide ions

  14. 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.

  15. 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

  16. 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.

  17. 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

  18. Effects of an energy-dense diet and nicotinic acid supplementation on production and metabolic variables of primiparous or multiparous cows in periparturient period.

    Science.gov (United States)

    Tienken, Reka; Kersten, Susanne; Frahm, Jana; Meyer, Ulrich; Locher, Lena; Rehage, Jürgen; Huber, Korinna; Kenéz, Ákos; Sauerwein, Helga; Mielenz, Manfred; Dänicke, Sven

    2015-01-01

    It is well observed that feeding energy-dense diets in dairy cows during the dry period can cause metabolic imbalances after parturition. Especially dairy cows with high body condition score (BCS) and fed an energy-dense diet were prone to develop production diseases due to metabolic disturbances postpartum. An experiment was conducted to determine the effects of an energy-dense diet and nicotinic acid (NA) on production and metabolic variables of primiparous and multiparous cows in late pregnancy and early lactation which were not pre-selected for high BCS. Thirty-six multiparous and 20 primiparous German Holstein cows with equal body conditions were fed with energy-dense (60% concentrate/40% roughage mixture; HC group) or adequate (30% concentrate/70% roughage mixture; LC group) diets prepartum. After parturition, concentrate proportion was dropped to 30% for all HC and LC groups and was increased to 50% within 16 days for LC and within 24 days for HC cows. In addition, half of the cows per group received 24 g NA supplement per day and cow aimed to attenuate the lipid mobilisation postpartum. Feeding energy-dense diets to late-pregnant dairy cows elevated the dry matter (p metabolic deviation postpartum as the effects of prepartum concentrate feeding were not carried over into postpartum period. Multiparous cows responded more profoundly to energy-dense feeding prepartum compared with primiparous cows, and parity-related differences in the transition from late pregnancy to lactation were obvious pre- and postpartum. The supplementation with 24 g NA did not reveal any effect on energy metabolism. This study clearly showed that energy-dense feeding prepartum did not result in metabolic imbalances postpartum in multiparous and primiparous cows not selected for high BCS. A genetic predisposition for an anabolic metabolic status as indicated by high BCS may be crucial for developing production diseases at the onset of lactation.

  19. Selection statements of the Federal Government of Germany of the 8th legislative period. Pt. 2

    International Nuclear Information System (INIS)

    Mayer, G.

    1980-02-01

    This selection of opinions of the Government of the Federal Republic of Germany covers the total fuel circuit. It is classified in a lucid index and the complete texts of the questioning of the Bundestag and the answers given by the Federal Government. Questions and answers are put directly one after the other to obtain a better view. (Publications of the Bundestag and plenary minutes). (HP) [de

  20. Waterfowl habitat use and selection during the remigial moult period in the northern hemisphere

    Science.gov (United States)

    Fox, Anthony D.; Flint, Paul L.; Hohman, William L.; Savard, Jean-Pierre L.

    2014-01-01

    This paper reviews factors affecting site selection amongst waterfowl (Anatidae) during the flightless remigial moult, emphasising the roles of predation and food supply (especially protein and energy). The current literature suggests survival during flightless moult is at least as high as at other times of the annual cycle, but documented cases of predation of flightless waterfowl under particular conditions lead us to infer that habitat selection is generally highly effective in mitigating or avoiding predation. High energetic costs of feather replacement and specific amino-acid requirements for their construction imply adoption of special energetic and nutritional strategies at a time when flightlessness limits movements. Some waterfowl meet their energy needs from endogenous stores accumulated prior to remigial moult, others rely on exogenous supply, but this varies with species, age, reproductive status and site. Limited evidence suggests feather proteins are derived from endogenous and exogenous sources which may affect site selection. Remigial moult does not occur independently of other annual cycle events and is affected by reproductive investment and success. Hence, moult strategies are affected by age, sex and reproductive history, and may be influenced by the need to attain a certain internal state for the next stage in the annual cycle (e.g. autumn migration). We know little about habitat selection during moult and urge more research of this poorly known part of the annual cycle, with particular emphasis on identifying key concentrations and habitats for specific flyway populations and the effects of disturbance upon these. This knowledge will better inform conservation actions and management actions concerning waterfowl during moult and the habitats that they exploit.

  1. 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.

  2. 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

  3. Quantum model for a periodically driven selectivity filter in a K+ ion channel

    International Nuclear Information System (INIS)

    Cifuentes, A A; Semião, F L

    2014-01-01

    In this work, we present a quantum transport model for the selectivity filter in the KcsA potassium ion channel. This model is fully consistent with the fact that two conduction pathways are involved in the translocation of ions through the filter, and we show that the presence of a second path may actually bring advantages for the filter as a result of quantum interference. To highlight interferences and resonances in the model, we consider the selectivity filter to be driven by a controlled time-dependent external field, which changes the free-energy scenario and consequently the conduction of the ions. In particular, we demonstrate that the two-pathway conduction mechanism is more advantageous for the filter when dephasing in the transient configurations is lower than in the main configurations. As a matter of fact, K + ions in the main configurations are highly coordinated by oxygen atoms of the filter backbone, and this increases noise. Moreover, we also show that for a wide range of dephasing rates and driving frequencies, the two-pathway conduction used by the filter leads to higher ionic currents than the single–path model. (paper)

  4. 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)

  5. 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.

  6. [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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. State updating and calibration period selection to improve dynamic monthly streamflow forecasts for an environmental flow management application

    Science.gov (United States)

    Gibbs, Matthew S.; McInerney, David; Humphrey, Greer; Thyer, Mark A.; Maier, Holger R.; Dandy, Graeme C.; Kavetski, Dmitri

    2018-02-01

    Monthly to seasonal streamflow forecasts provide useful information for a range of water resource management and planning applications. This work focuses on improving such forecasts by considering the following two aspects: (1) state updating to force the models to match observations from the start of the forecast period, and (2) selection of a shorter calibration period that is more representative of the forecast period, compared to a longer calibration period traditionally used. The analysis is undertaken in the context of using streamflow forecasts for environmental flow water management of an open channel drainage network in southern Australia. Forecasts of monthly streamflow are obtained using a conceptual rainfall-runoff model combined with a post-processor error model for uncertainty analysis. This model set-up is applied to two catchments, one with stronger evidence of non-stationarity than the other. A range of metrics are used to assess different aspects of predictive performance, including reliability, sharpness, bias and accuracy. The results indicate that, for most scenarios and metrics, state updating improves predictive performance for both observed rainfall and forecast rainfall sources. Using the shorter calibration period also improves predictive performance, particularly for the catchment with stronger evidence of non-stationarity. The results highlight that a traditional approach of using a long calibration period can degrade predictive performance when there is evidence of non-stationarity. The techniques presented can form the basis for operational monthly streamflow forecasting systems and provide support for environmental decision-making.

  14. 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

  15. Variability of blood pressure and blood glucose during perioperative period for patients with secondary neovascular glaucoma after silicone oil removed in PDR

    Directory of Open Access Journals (Sweden)

    Fu-Lin Gao

    2015-06-01

    Full Text Available AIM:To research blood pressure and blood glucose variability during peroperative period for patients with secondary neovasular glaucoma(NVGafter silicone oil removed in proliferative diabetic retinaopathy(PDR.METHODS: Totally, 271 patients(271 eyesundergone surgery of vitrectomy and silicon-oil tamponade combined with cataract were respective analyzed. Fourteen patients(14 eyeswith secondary NVG after silicon oil removed and randomly controlled group of no NVG according with ages, operation method in the same time were studied. The blood pressure and blood glucose variability during peroperative period was analyzed, and did comparison after excluded contralateral eye. The complications of 271 patients were surveyed in following-up period 1~12mo. The incidence of NVG, the time, blood pressure, blood glucose and glycated hemoglobin(Hbc%variability during peroperative period was statisticed and compared by software of SPSS 11.0.RESULTS: Fourteen eyes(5.2%of 271 cases was with secondary NVG(female: 4 eyes, 28.6%; male: 10 eyes, 71.4%, average ages was 57.07 years(49~68 years. NVG presented in the 107~ 135d after vitrectomy and 7~45d(average 31.78dafter silicon-oil removed. Diabetes mellitus was 10~15(average 13.2a. In NVG group, the variability of blood glucose was 4.0~10.2mmol/L(mean 8.52±3.24mmol/L, variable coefficient was 0.48. In NNVG group, the variability of blood glucose was 5.0~8.2mmol/L(mean 7.22±0.24mmol/L, variable coefficient was 0.43. It was significantly difference in comparison in variable coefficient(PPPPCONCLUSION: There are significant variability on fasting blood glucose, daytime SBP and night DBP during perioperative in PDR patients with secondary NVG. It might be occurred 1wk after silicone oil removal surgery.

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

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    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

  17. THE ACS LCID PROJECT. I. SHORT-PERIOD VARIABLES IN THE ISOLATED DWARF SPHEROIDAL GALAXIES CETUS AND TUCANA

    NARCIS (Netherlands)

    Bernard, Edouard J.; Monelli, Matteo; Gallart, Carme; Drozdovsky, Igor; Stetson, Peter B.; Aparicio, Antonio; Cassisi, Santi; Mayer, Lucio; Cole, Andrew A.; Hidalgo, Sebastian L.; Skillman, Evan D.; Tolstoy, Eline

    2009-01-01

    We present the first study of the variable star populations in the isolated dwarf spheroidal galaxies (dSphs) Cetus and Tucana. Based on Hubble Space Telescope images obtained with the Advanced Camera for Surveys in the F475W and F814W bands, we identified 180 and 371 variables in Cetus and Tucana,

  18. 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

  19. Periodic, complexiton solutions and stability for a (2+1)-dimensional variable-coefficient Gross-Pitaevskii equation in the Bose-Einstein condensation

    Science.gov (United States)

    Yin, Hui-Min; Tian, Bo; Zhao, Xin-Chao

    2018-06-01

    This paper presents an investigation of a (2 + 1)-dimensional variable-coefficient Gross-Pitaevskii equation in the Bose-Einstein condensation. Periodic and complexiton solutions are obtained. Solitons solutions are also gotten through the periodic solutions. Numerical solutions via the split step method are stable. Effects of the weak and strong modulation instability on the solitons are shown: the weak modulation instability permits an observable soliton, and the strong one overwhelms its development.

  20. A period-luminosity relation for Mira variables in globular clusters and its impact on the distance scale

    International Nuclear Information System (INIS)

    Menzies, J.W.; Whitelock, P.A.

    1985-01-01

    JHKL photometry is presented for 31 red variables in 15 galactic globular clusters. The photometry of the Mira variables is used to find absolute bolometric magnitudes and an Msub(bol)-log P relation which differs from the one found for LMC Miras. This can be understood only if there is some systematic error in the globular cluster and/or LMC distance scales or if there is some fundamental difference between the cluster Miras and those in the LMC. (author)

  1. 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.

  2. 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.

  3. Multi-Period Mean-Variance Portfolio Selection with Uncertain Time Horizon When Returns Are Serially Correlated

    Directory of Open Access Journals (Sweden)

    Ling Zhang

    2012-01-01

    Full Text Available We study a multi-period mean-variance portfolio selection problem with an uncertain time horizon and serial correlations. Firstly, we embed the nonseparable multi-period optimization problem into a separable quadratic optimization problem with uncertain exit time by employing the embedding technique of Li and Ng (2000. Then we convert the later into an optimization problem with deterministic exit time. Finally, using the dynamic programming approach, we explicitly derive the optimal strategy and the efficient frontier for the dynamic mean-variance optimization problem. A numerical example with AR(1 return process is also presented, which shows that both the uncertainty of exit time and the serial correlations of returns have significant impacts on the optimal strategy and the efficient frontier.

  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. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Semantic Wavelet-Induced Frequency-Tagging (SWIFT Periodically Activates Category Selective Areas While Steadily Activating Early Visual Areas.

    Directory of Open Access Journals (Sweden)

    Roger Koenig-Robert

    Full Text Available Primate visual systems process natural images in a hierarchical manner: at the early stage, neurons are tuned to local image features, while neurons in high-level areas are tuned to abstract object categories. Standard models of visual processing assume that the transition of tuning from image features to object categories emerges gradually along the visual hierarchy. Direct tests of such models remain difficult due to confounding alteration in low-level image properties when contrasting distinct object categories. When such contrast is performed in a classic functional localizer method, the desired activation in high-level visual areas is typically accompanied with activation in early visual areas. Here we used a novel image-modulation method called SWIFT (semantic wavelet-induced frequency-tagging, a variant of frequency-tagging techniques. Natural images modulated by SWIFT reveal object semantics periodically while keeping low-level properties constant. Using functional magnetic resonance imaging (fMRI, we indeed found that faces and scenes modulated with SWIFT periodically activated the prototypical category-selective areas while they elicited sustained and constant responses in early visual areas. SWIFT and the localizer were selective and specific to a similar extent in activating category-selective areas. Only SWIFT progressively activated the visual pathway from low- to high-level areas, consistent with predictions from standard hierarchical models. We confirmed these results with criterion-free methods, generalizing the validity of our approach and show that it is possible to dissociate neural activation in early and category-selective areas. Our results provide direct evidence for the hierarchical nature of the representation of visual objects along the visual stream and open up future applications of frequency-tagging methods in fMRI.

  11. 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.

  12. Radio and γ -Ray Variability in the BL Lac PKS 0219−164: Detection of Quasi-periodic Oscillations in the Radio Light Curve

    Energy Technology Data Exchange (ETDEWEB)

    Bhatta, Gopal, E-mail: gopalbhatta716@gmail.com [Astronomical Observatory of the Jagiellonian University, ul. Orla 171, 30-244 Kraków (Poland); Mt. Suhora Observatory, Pedagogical University, ul. Podchorazych 2, 30-084 Kraków (Poland)

    2017-09-20

    In this work, we explore the long-term variability properties of the blazar PKS 0219−164 in the radio and the γ -ray regime, utilizing the OVRO 15 GHz and the Fermi /LAT observations from the period 2008–2017. We found that γ -ray emission is more variable than the radio emission implying that γ -ray emission possibly originated in more compact regions while the radio emission represented continuum emission from the large-scale jets. Also, in the γ -ray, the source exhibited spectral variability, characterized by the softer-when-brighter trend, a less frequently observed feature in the high-energy emission by BL Lacs. In radio, using Lomb–Scargle periodogram and weighted wavelet z -transform, we detected a strong signal of quasi-periodic oscillation (QPO) with a periodicity of 270 ± 26 days with possible harmonics of 550 ± 42 and 1150 ± 157 day periods. At a time when detections of QPOs in blazars are still under debate, the observed QPO with high statistical significance (∼97%–99% global significance over underlying red-noise processes) and persistent over nearly 10 oscillations could make one of the strongest cases for the detection of QPOs in blazar light curves. We discuss various blazar models that might lead to the γ -ray and radio variability, QPO, and the achromatic behavior seen in the high-energy emission from the source.

  13. Is Heart Period Variability Associated with the Administration of Lifesaving Interventions in Individual Prehospital Trauma Patients with Normal Standard Vital Signs?

    Science.gov (United States)

    2010-08-01

    heart period variability as an indicator of mortality in intensive care unit patients many hours before death. Similarly, re- cent studies using data...the Department of Health and Kinesiology (CAR), The University of Texas at San Antonio, San An- tonio, TX; U.S. Army Institute of Surgical Research (CAR

  14. Task-irrelevant distractors in the delay period interfere selectively with visual short-term memory for spatial locations.

    Science.gov (United States)

    Marini, Francesco; Scott, Jerry; Aron, Adam R; Ester, Edward F

    2017-07-01

    Visual short-term memory (VSTM) enables the representation of information in a readily accessible state. VSTM is typically conceptualized as a form of "active" storage that is resistant to interference or disruption, yet several recent studies have shown that under some circumstances task-irrelevant distractors may indeed disrupt performance. Here, we investigated how task-irrelevant visual distractors affected VSTM by asking whether distractors induce a general loss of remembered information or selectively interfere with memory representations. In a VSTM task, participants recalled the spatial location of a target visual stimulus after a delay in which distractors were presented on 75% of trials. Notably, the distractor's eccentricity always matched the eccentricity of the target, while in the critical conditions the distractor's angular position was shifted either clockwise or counterclockwise relative to the target. We then computed estimates of recall error for both eccentricity and polar angle. A general interference model would predict an effect of distractors on both polar angle and eccentricity errors, while a selective interference model would predict effects of distractors on angle but not on eccentricity errors. Results showed that for stimulus angle there was an increase in the magnitude and variability of recall errors. However, distractors had no effect on estimates of stimulus eccentricity. Our results suggest that distractors selectively interfere with VSTM for spatial locations.

  15. Control and Health Monitoring of Variable Speed Wind Power Generation Systems; Period of Performance: 10 July 1997 - 10 July 2000

    Energy Technology Data Exchange (ETDEWEB)

    Song, Y. D.; Bikdash, M.; Schulz, M. J.

    2001-09-01

    This document reports accomplishments on variable speed control, furling analysis, and health monitoring of wind turbines. There are three parts, prepared by Song, Bikdash, and Schulz, respectively. The first part discusses variable-speed control of wind turbines, exploring a memory-based method for wind speed prediction and wind turbine control. The second part addresses the yaw dynamics of wind turbines, including modeling, analysis, and control. The third part of the report discusses new analytical techniques that were developed and tested to detect initial damage to prevent failures of wind turbine rotor blades.

  16. 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.

  17. 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.

  18. 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

    Full Text Available Abstract Background Several malaria risk maps have been developed in recent years, many from the prevalence of infection data collated by the MARA (Mapping Malaria Risk in Africa project, and using various environmental data sets as predictors. Variable selection is a major obstacle due to analytical problems caused by over-fitting, confounding and non-independence in the data. Testing and comparing every combination of explanatory variables in a Bayesian spatial framework remains unfeasible for most researchers. The aim of this study was to develop a malaria risk map using a systematic and practicable variable selection process for spatial analysis and mapping of historical malaria risk in Botswana. Results Of 50 potential explanatory variables from eight environmental data themes, 42 were significantly associated with malaria prevalence in univariate logistic regression and were ranked by the Akaike Information Criterion. Those correlated with higher-ranking relatives of the same environmental theme, were temporarily excluded. The remaining 14 candidates were ranked by selection frequency after running automated step-wise selection procedures on 1000 bootstrap samples drawn from the data. A non-spatial multiple-variable model was developed through step-wise inclusion in order of selection frequency. Previously excluded variables were then re-evaluated for inclusion, using further step-wise bootstrap procedures, resulting in the exclusion of another variable. Finally a Bayesian geo-statistical model using Markov Chain Monte Carlo simulation was fitted to the data, resulting in a final model of three predictor variables, namely summer rainfall, mean annual temperature and altitude. Each was independently and significantly associated with malaria prevalence after allowing for spatial correlation. This model was used to predict malaria prevalence at unobserved locations, producing a smooth risk map for the whole country. Conclusion We have

  19. 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

  20. 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.

  1. 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.

  2. INTAKES OF SELECTED NUTRIENTS, BONE MINERALISATION AND DENSITY OF ADOLESCENT FEMALE SWIMMERS OVER A THREE-YEAR PERIOD

    Directory of Open Access Journals (Sweden)

    Jan Czeczelewski

    2013-01-01

    Full Text Available The aim of this study was to conduct three-year monitoring of bone mineralization (BMC and bone mineral density (BMD of adolescent girls engaged in swimming at the time of attaining the peak bone mass and of their counterparts leading a rather sedentary life, considering the intakes of calcium, phosphorus and protein, as well as the proportions among those nutrients. Two groups of girls aged 11–13 years were studied 3 times at yearly intervals: untrained controls (n = 20 and those engaged in competitive swimming (n = 20. Bone density was determined by dual-energy X-ray absorptiometry (DXA in the lumbar spine (L2 – L4. Nutrient intakes (energy, protein, calcium, phosphorus were assessed from 24-h recalls. The group of swimmers had significantly lower BMI values than the control group. No systematic, significant between-group differences were found in nutrient intake or in bone mineralization variables. Calcium intake was below the recommended norm in all subjects but mean values of bone mineralization variables (BMC, BMD steadily increased in both groups. The BMD z-scores proved negative throughout the three-year period of early adolescence in both groups of girls and that decrease was significant in swimmers. This could have been due to insufficient calcium intake as well as to inadequate calcium-to-phosphate and protein-to-calcium ratios and, when continued, might result in a decreased bone mass in adulthood.

  3. Consequences of dry period length and dietary energy source on physiological health variables in dairy cows and calves

    NARCIS (Netherlands)

    Mayasari, Nova

    2017-01-01

    During the transition period, dairy cows experience a negative energy balance (NEB) caused by the high energy requirement for milk yield, while feed intake is limited. Severity of the NEB has been associated with an increased incidence of metabolic disorders and infectious

  4. 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

  5. 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.

  6. 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

  7. [The variability of vegetation beginning date of greenness period in spring in the north-south transect of eastern China based on NOAA NDVI].

    Science.gov (United States)

    Wang, Zhi; Liu, Shi-rong; Sun, Peng-sen; Guo, Zhi-hua; Zhou, Lian-di

    2010-10-01

    NDVI based on NOAA/AVHRR from 1982 to 2003 are used to monitor variable rules for the growing season in spring of vegetation in the north-south transect of eastern China (NSTEC). The following, mainly, are included: (1) The changing speed of greenness period in spring of most regions in NSTEC is slow and correlation with the year is not distinct; (2) The regions in which greenness period in spring distinctly change mainly presented an advance; (3) The regions in which inter-annual fluctuation of greenness period in spring is over 10 days were found in 3 kinds of areas: the area covered with agricultural vegetation types; the areas covered with evergreen vegetation types; the areas covered with steppe vegetation types; (4) changes of vegetation greenness period in spring have spatio-temporal patterns.

  8. 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

  9. Variable-Speed Generation Subsystem Using the Doubly-Fed Generator; Period of Performance February 9, 1994 - April 30, 1999

    Energy Technology Data Exchange (ETDEWEB)

    Weigand, C.H.; Lauw, H.K.; Marckx, D.A. (Electronic Power Conditioning Incorporated)

    2000-12-18

    Over the past decade, fixed-speed, utility-scale wind turbines have technically advanced to a point where they can economically complete against nuclear and fossil-fuel-based power plants in geographical areas with a sufficient wind resource. The objective of this subcontract was to compare various electrical topologies allowing variable-speed turbine operation, identify the most suitable for a 275-kW (or larger) utility-scale wind turbine, and then design, build, lab test, and field test this variable-speed generation subsystem based on the previously identified optimum approach. Preliminary tests of the controls for a doubly fed variable-speed generation system rated at 750 kW were performed on a wind turbine. A 275-kW VSGS was thoroughly tested in the laboratory and on a wind turbine. Using field-oriented control, excellent dynamic behavior of the drive train was demonstrated, acoustic tests revealed an 11 dB reduction in turbine noise in low-wind, low-RPM operation compared to fixed-speed operation. The overall efficiency of the electrical system suffered from inadequate efficiency of the power converter at low power. Consequently, a different converter topology has been proposed that will satisfy both efficiency and power quality requirements for future use. This report provides information on all aspects of the project, including events that were unanticipated at the outset. A great deal of information is available in the references, comprised of NREL reports, journal articles, and conference papers on specific project results.

  10. 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,…

  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. Dynamic and Regression Modeling of Ocean Variability in the Tide-Gauge Record at Seasonal and Longer Periods

    Science.gov (United States)

    Hill, Emma M.; Ponte, Rui M.; Davis, James L.

    2007-01-01

    Comparison of monthly mean tide-gauge time series to corresponding model time series based on a static inverted barometer (IB) for pressure-driven fluctuations and a ocean general circulation model (OM) reveals that the combined model successfully reproduces seasonal and interannual changes in relative sea level at many stations. Removal of the OM and IB from the tide-gauge record produces residual time series with a mean global variance reduction of 53%. The OM is mis-scaled for certain regions, and 68% of the residual time series contain a significant seasonal variability after removal of the OM and IB from the tide-gauge data. Including OM admittance parameters and seasonal coefficients in a regression model for each station, with IB also removed, produces residual time series with mean global variance reduction of 71%. Examination of the regional improvement in variance caused by scaling the OM, including seasonal terms, or both, indicates weakness in the model at predicting sea-level variation for constricted ocean regions. The model is particularly effective at reproducing sea-level variation for stations in North America, Europe, and Japan. The RMS residual for many stations in these areas is 25-35 mm. The production of "cleaner" tide-gauge time series, with oceanographic variability removed, is important for future analysis of nonsecular and regionally differing sea-level variations. Understanding the ocean model's strengths and weaknesses will allow for future improvements of the model.

  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. Effect of periodic wetting and drying on selective sorption of 137Cs by mixtures of soil and organomineral sorbent

    Science.gov (United States)

    Popov, V. E.; Maslova, K. M.; Stepina, I. A.

    2014-05-01

    The incubation of sandy soddy-podzolic soil with a three-component organomineral sorbent (OMS) on the basis of sapropel, neutralized hydrolysis lignin, and clay-salt slime under alternating wetting-drying (W-D) conditions for two years has increased the selective sorption of 137Cs by 2.5-5 times. The addition of 5% OMS increases the effect of periodic W-D cycles on the selective sorption of 137Cs compared to the addition of 10% OMS. The relationship between the 137Cs interception potential and the number of W-D cycles has been predicted on the basis of the additivity rule and under the assumption that this potential linearly depends on the number of W-D cycles. The predicted values of the 137Cs interception potential almost coincide with the experimental data for the mixtures of sandy soddy-podzolic soil with 10% OMS and are lower than the experimental values by 60% for the mixtures of soil with 10% OMS.

  16. 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

  17. Links between Patagonian Ice Sheet fluctuations and Antarctic dust variability during the last glacial period (MIS 4-2)

    Science.gov (United States)

    Kaiser, Jérôme; Lamy, Frank

    2010-06-01

    Antarctic and Greenland ice-core records reveal large fluctuations of dust input on both orbital and millennial time-scales with potential global climate implications. At least during glacial periods, the Antarctic dust fluctuations appear to be largely controlled by environmental changes in southern South America. We compare dust flux records from two Antarctic ice-cores to variations in the composition of the terrigenous supply at ODP Site 1233 located off southern Chile and known to record fluctuations in the extent of the northern part of the Patagonian ice-sheet (NPIS) during the last glacial period (Marine Isotope Stage, MIS, 4 to 2). Within age uncertainties, millennial-scale glacial advances (retreats) of the NPIS correlate to Antarctic dust maxima (minima). In turn, NPIS fluctuations were closely related to offshore sea surface temperature (SST) changes. This pattern suggests a causal link involving changes in temperature, in rock flour availability, in latitudinal extensions of the westerly winds and in foehn winds in the southern Pampas and Patagonia. We further suggest that the long-term trend of dust accumulation is partly linked to the sea-level related changes in the size if the Patagonian source area due to the particular morphology of the Argentine shelf. We suggest that sea-level drops at the beginning of MIS 4 and MIS 2 were important for long-term dust increases, while changes in the Patagonian dust source regions primarily control the early dust decrease during the MIS 4/3 transition and Termination 1.

  18. 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.

  19. 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...

  20. 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.

  1. 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.

  2. NEAR-INFRARED PERIODIC AND OTHER VARIABLE FIELD STARS IN THE FIELD OF THE CYGNUS OB7 STAR-FORMING REGION

    Energy Technology Data Exchange (ETDEWEB)

    Wolk, Scott J.; Rice, Thomas S. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Aspin, Colin A. [Institute for Astronomy, University of Hawaii at Manoa, 640 North Aohoku Place, Hilo, HI 96720 (United States)

    2013-04-15

    We present a subset of the results of a three-season, 124 night, near-infrared monitoring campaign of the dark clouds Lynds 1003 and Lynds 1004 in the Cygnus OB7 star-forming region. In this paper, we focus on the field star population. Using three seasons of UKIRT J, H, and K-band observations spanning 1.5 years, we obtained high-quality photometry on 9200 stars down to J = 17 mag, with photometric uncertainty better than 0.04 mag. After excluding known disk-bearing stars we identify 149 variables-1.6% of the sample. Of these, about 60 are strictly periodic, with periods predominantly <2 days. We conclude this group is dominated by eclipsing binaries. A few stars have long period signals of between 20 and 60 days. About 25 stars have weak modulated signals, but it was not clear if these were periodic. Some of the stars in this group may be diskless young stellar objects with relatively large variability due to cool starspots. The remaining {approx}60 stars showed variations which appear to be purely stochastic.

  3. Genetic variability of the phloem sap metabolite content of maize (Zea mays L.) during the kernel-filling period.

    Science.gov (United States)

    Yesbergenova-Cuny, Zhazira; Dinant, Sylvie; Martin-Magniette, Marie-Laure; Quilleré, Isabelle; Armengaud, Patrick; Monfalet, Priscilla; Lea, Peter J; Hirel, Bertrand

    2016-11-01

    Using a metabolomic approach, we have quantified the metabolite composition of the phloem sap exudate of seventeen European and American lines of maize that had been previously classified into five main groups on the basis of molecular marker polymorphisms. In addition to sucrose, glutamate and aspartate, which are abundant in the phloem sap of many plant species, large quantities of aconitate and alanine were also found in the phloem sap exudates of maize. Genetic variability of the phloem sap composition was observed in the different maize lines, although there was no obvious relationship between the phloem sap composition and the five previously classified groups. However, following hierarchical clustering analysis there was a clear relationship between two of the subclusters of lines defined on the basis of the composition of the phloem sap exudate and the earliness of silking date. A comparison between the metabolite contents of the ear leaves and the phloem sap exudates of each genotype, revealed that the relative content of most of the carbon- and nitrogen-containing metabolites was similar. Correlation studies performed between the metabolite content of the phloem sap exudates and yield-related traits also revealed that for some carbohydrates such as arabitol and sucrose there was a negative or positive correlation with kernel yield and kernel weight respectively. A posititive correlation was also found between kernel number and soluble histidine. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  4. High Intrapatient Variability of Tacrolimus Exposure in the Early Period After Liver Transplantation Is Associated With Poorer Outcomes.

    Science.gov (United States)

    Rayar, Michel; Tron, Camille; Jézéquel, Caroline; Beaurepaire, Jean Marie; Petitcollin, Antoine; Houssel-Debry, Pauline; Camus, Christophe; Verdier, Marie Clémence; Dehlawi, Ammar; Lakéhal, Mohamed; Desfourneaux, Véronique; Meunier, Bernard; Sulpice, Laurent; Bellissant, Eric; Boudjema, Karim; Lemaitre, Florian

    2018-03-01

    Tacrolimus (TAC) is the cornerstone of immunosuppressive regimen in liver transplantation (LT). Its pharmacokinetics is characterized by a high interpatient and intrapatient variability (IPV) leading to an unpredictable dose-response relationship. The aim of our study was to evaluate the impact of TAC IPV (IPV) on graft and patient outcomes after LT. We retrospectively analyzed 812 LT recipients treated with TAC. The IPV of TAC concentrations was estimated by calculating the coefficient of variation (CV) of whole blood trough concentrations. Patients were categorized in 2 groups: low IPV (CV < 40%) and high IPV (CV ≥ 40%). There were significantly more neurologic complications (31.2% vs 16.6%, P < 0.001), cardiovascular complications (19.7% vs 9.7%, P < 0.001), and acute renal failure requiring dialysis (8.5% vs 2.2%, P < 0.001) in the high CV group than in the low CV group. Moreover, graft survival was significantly poorer in the high CV group (hazard ratio, 1.42; 95% confidence interval, 1.04-1.95; P = 0.03). A pretransplantation elevated Model for End-Stage Liver Disease score (P < 0.001) and Child-Pugh grade (P < 0.001) were identified as risk factors for presenting a high CV. A high CV of TAC concentrations was found to be predictive of TAC-related toxicity and poorer survival.

  5. 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.

  6. Who theorizes age? The "socio-demographic variables" device and age-period-cohort analysis in the rhetoric of survey research.

    Science.gov (United States)

    Rughiniș, Cosima; Humă, Bogdana

    2015-12-01

    In this paper we argue that quantitative survey-based social research essentializes age, through specific rhetorical tools. We outline the device of 'socio-demographic variables' and we discuss its argumentative functions, looking at scientific survey-based analyses of adult scientific literacy, in the Public Understanding of Science research field. 'Socio-demographics' are virtually omnipresent in survey literature: they are, as a rule, used and discussed as bundles of independent variables, requiring little, if any, theoretical and measurement attention. 'Socio-demographics' are rhetorically effective through their common-sense richness of meaning and inferential power. We identify their main argumentation functions as 'structure building', 'pacification', and 'purification'. Socio-demographics are used to uphold causal vocabularies, supporting the transmutation of the descriptive statistical jargon of 'effects' and 'explained variance' into 'explanatory factors'. Age can also be studied statistically as a main variable of interest, through the age-period-cohort (APC) disambiguation technique. While this approach has generated interesting findings, it did not mitigate the reductionism that appears when treating age as a socio-demographic variable. By working with age as a 'socio-demographic variable', quantitative researchers convert it (inadvertently) into a quasi-biological feature, symmetrical, as regards analytical treatment, with pathogens in epidemiological research. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. 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...

  8. [The effects of 16-weeks pilates mat program on anthropometric variables and body composition in active adult women after a short detraining period].

    Science.gov (United States)

    Vaquero-Cristóbal, Raquel; Alacid, Fernando; Esparza-Ros, Francisco; Muyor, José M; López-Miñarro, Pedro Ángel

    2015-04-01

    previous studies have analysed the effect of mat Pilates practice on anthropometric variables and body composition in sedentaries. To date no researchs have investigated the benefits of Pilates on these variables after a short detraining period. to determine the effect of a 16-week mat Pilates program on anthropometric variables, body composition and somatotype of women with previous practice experience after three weeks of detraining period. twenty-one women underwent a complete anthropometric assessment according with ISAK guidelines before and after a 16 week mat Pilates program (two days, one hour). All women had one to three years of mat Pilates experience and came to three weeks of detraining period (Christmas holiday). women showed significant decreases for body mass, BMI, upper limb (biceps and triceps) and trunk (subscapular, iliac crest, supraspinale and abdominal) individual skinfolds, 6 and 8 skinfold sums, endomorphy and fat mass; and a significant increases for muscle mass. The mean somatotype was classified as mesomorphic endomorph in the pre- (4.91, 4.01, 1.47) and post-test (4.68, 4.16, 1.69). Eight women changed their somatotype clasification after the intervention program. the practice of mat Pilates for 16 weeks caused changes associated with health state improvements on anthropometric variables, especially on skinfolds which significantly decreased, body composition (fat and muscle masses decreased and increased, respectively) and somatotype (there was a significantly decreased on the endomorph component in experienced women after three week of detraning. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

  9. 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.

  10. 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.

  11. 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.

  12. 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…

  13. 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...

  14. 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…

  15. 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,

  16. 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...

  17. 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

  18. 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.

  19. 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.

  20. 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...

  1. 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

  2. Effects of Selected Variables on Musicians' Ratings of High-Level Piano Performances

    Science.gov (United States)

    Wapnick, Joel; Ryan, Charlene; Lacaille, Nathalie; Darrow, Alice-Ann

    2004-01-01

    The purpose of this study was to ascertain whether judgments of solo performances recorded at a well-known international piano competition would be affected by musical characteristics such as style (classic period versus early 20th-century Russian) and tempo (slow versus fast). Evaluators rated performances on six test items: tone quality, note…

  3. 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

  4. 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…

  5. 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.

  6. 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)

  7. 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

  8. 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

  9. Long-period variables in the Magellanic Clouds: Supergiants, AGB stars, supernova precursors, planetary nebula precursors, and enrichment of the interstellar medium

    International Nuclear Information System (INIS)

    Wood, P.; Bessell, M.S.; Fox, M.W.

    1983-01-01

    Infrared JHK magnitudes and low-dispersion red spectra have been obtained for 90 long-period variables (LPVs) in the Small and Large Magellanic Clouds. The LPVs fall into two distinct groups, core helium (or carbon) burning supergiants and stars on the asymptotic giant branch (AGB). The supergiants have small pulsation amplitudes in K ( or approx. =5 M/sub sun/ produce supernovae while less massive stars produce planetary nebulae with nebula masses from approx.0.1--2.1 M/sub sun/. The coreburning red supergiants appear highly overluminous for their pulsation mass, indicating that they have lost up to half their mass since the main-sequence phase

  10. 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.

  11. 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

  12. 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.

  13. 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)

  14. 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...

  15. Climate variability in Andalusia (southern Spain during the period 1701–1850 based on documentary sources: evaluation and comparison with climate model simulations

    Directory of Open Access Journals (Sweden)

    J. P. Montávez Gómez

    2012-01-01

    Full Text Available In this work, a reconstruction of climatic conditions in Andalusia (southern Iberian Peninsula during the period 1701–1850, as well as an evaluation of its associated uncertainties, is presented. This period is interesting because it is characterized by a minimum in solar irradiance (Dalton Minimum, around 1800, as well as intense volcanic activity (for instance, the eruption of Tambora in 1815, at a time when any increase in atmospheric CO2 concentrations was of minor importance. The reconstruction is based on the analysis of a wide variety of documentary data. The reconstruction methodology is based on counting the number of extreme events in the past, and inferring mean value and standard deviation using the assumption of normal distribution for the seasonal means of climate variables. This reconstruction methodology is tested within the pseudoreality of a high-resolution paleoclimate simulation performed with the regional climate model MM5 coupled to the global model ECHO-G. The results show that the reconstructions are influenced by the reference period chosen and the threshold values used to define extreme values. This creates uncertainties which are assessed within the context of climate simulation. An ensemble of reconstructions was obtained using two different reference periods (1885–1915 and 1960–1990 and two pairs of percentiles as threshold values (10–90 and 25–75. The results correspond to winter temperature, and winter, spring and autumn rainfall, and they are compared with simulations of the climate model for the considered period. The mean value of winter temperature for the period 1781–1850 was 10.6 ± 0.1 °C (11.0 °C for the reference period 1960–1990. The mean value of winter rainfall for the period 1701–1850 was 267 ± 18 mm (224 mm for 1960–1990. The mean values of spring and autumn rainfall were 164 ± 11 and 194 ± 16 mm (129 and 162 mm for 1960–1990, respectively. Comparison of the distribution

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. Interannual variability of Danube waters propagation in summer period of 1992-2015 and its influence on the Black Sea ecosystem

    Science.gov (United States)

    Kubryakov, A. A.; Stanichny, S. V.; Zatsepin, A. G.

    2018-03-01

    The propagation of the Danube River plume has strong interannual variability that impacts the local balance of nutrients and the thermohaline structure in the western Black Sea. In the present study, we use a particle-tracking model based on satellite altimetry measurements and wind reanalysis data, as well as satellite measurements (SeaWiFS, MODIS), to investigate the interannual variability in the Danube plume pathways during the summer from 1993 to 2015. The wind conditions largely define the variability in the Danube water propagation. Relatively low-frequency variability (on periods of a week to months) in the wind stress curl modulates the intensity of the geostrophic Rim Current and related mesoscale eddy dynamics. High-frequency offshore wind-drift currents transport the plume across isobaths and provide an important transport link between shelf and offshore circulation. Inherent plume dynamics play an additional role in the near-mouth transport of the plume and its connection with offshore circulation. During the years with prevailing northeast winds ( 30% of studied cases), which are usually accompanied by increased wind curl over the Black Sea and higher Danube discharge, an alongshore southward current at the NorthWestern Shelf (NWS) is formed near the western Black Sea coast. Advected southward, the Danube waters are entrained in the Rim Current jet, which transports them along the west coast of the basin. The strong Rim Current, fewer eddies and downwelling winds substantially decrease the cross-shelf exchange of nutrients. During the years with prevailing southeastern winds ( 40%), the Rim Current is less intense. Mesoscale eddies effectively trap the Danube waters, transporting them to the deep western part of the basin. The low- and high-frequency southeastern wind-drift currents contribute significantly to cross-isobath plume transport and its connection with offshore circulation. During several years ( 15%), the Danube waters moved eastward to

  1. 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.

  2. 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.

  3. 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.

  4. Ti-6Al-4V triply periodic minimal surface structures for bone implants fabricated via selective laser melting.

    Science.gov (United States)

    Yan, Chunze; Hao, Liang; Hussein, Ahmed; Young, Philippe

    2015-11-01

    Triply periodic minimal surface (TPMS) structures have already been shown to be a versatile source of biomorphic scaffold designs. Therefore, in this work, Ti-6Al-4V Gyroid and Diamond TPMS lattices having an interconnected high porosity of 80-95% and pore sizes in the range of 560-1600 μm and 480-1450 μm respectively were manufactured by selective laser melting (SLM) for bone implants. The manufacturability, microstructure and mechanical properties of the Ti-6Al-4V TPMS lattices were evaluated. Comparison between 3D micro-CT reconstructed models and original CAD models of the Ti-6Al-4V TPMS lattices shows excellent reproduction of the designs. The as-built Ti-6Al-4V struts exhibit the microstructure of columnar grains filled with very fine and orthogonally oriented α' martensitic laths with the width of 100-300 nm and have the microhardness of 4.01 ± 0.34 GPa. After heat treatment at 680°C for 4h, the α' martensite was converted to a mixture of α and β, in which the α phase being the dominant fraction is present as fine laths with the width of 500-800 nm and separated by a small amount of narrow, interphase regions of dark β phase. Also, the microhardness is decreased to 3.71 ± 0.35 GPa due to the coarsening of the microstructure. The 80-95% porosity TPMS lattices exhibit a comparable porosity with trabecular bone, and the modulus is in the range of 0.12-1.25 GPa and thus can be adjusted to the modulus of trabecular bone. At the same range of porosity of 5-10%, the moduli of cortical bone and of the Ti-6Al-4V TPMS lattices are in a similar range. Therefore, the modulus and porosity of Ti-6Al-4V TPMS lattices can be tailored to the levels of human bones and thus reduce or avoid "stress shielding" and increase longevity of implants. Due to the biomorphic designs, and high interconnected porosity and stiffness comparable to human bones, SLM-made Ti-6Al-4V TPMS lattices can be a promising material for load bearing bone implants. Copyright © 2015 Elsevier

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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)

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. Runoff Variability in the Scott River (SW Spitsbergen in Summer Seasons 2012–2013 in Comparison with the Period 1986–2009

    Directory of Open Access Journals (Sweden)

    Franczak Łukasz

    2016-09-01

    Full Text Available River runoff variability in the Scott River catchment in the summer seasons 2012 and 2013 has been presented in comparison to the multiannual river runoff in 1986–2009. Both in particular seasons and in the analysed multiannual, high variability of discharge rate was recorded. In the research periods 2012–2013, a total of 11 952 water stages and 20 flow rates were measured in the analysed cross-section for the determination of 83 daylong discharges. The mean multiannual discharge of the Scott River amounted to 0.96 m3·s−1. The value corresponds to a specific runoff of 94.6 dm3·s−1·km2, and the runoff layer 937 mm. The maximum values of daily discharge amounted to 5.07 m3·s−1, and the minimum values to 0.002 m3·s−1. The highest runoff occurs in the second and third decade of July, and in the first and second decade of August. The regime of the river is determined by a group of factors, and particularly meteorological conditions affecting the intensity of ablation, and consequently river runoff volume. We found a significant correlation (0.60 in 2012 and 0.67 in 2013 between the air temperature and the Scott River discharge related to the Scott Glacier ice melt.

  17. Event-Related Potentials (ERPs) in Second Language Research: A Brief Introduction to the Technique, a Selected Review, and an Invitation to Reconsider Critical Periods in L2

    Science.gov (United States)

    Steinhauer, Karsten

    2014-01-01

    This article provides a selective overview of recent event-related brain potential (ERP) studies in L2 morpho-syntax, demonstrating that the ERP evidence supporting the critical period hypothesis (CPH) may be less compelling than previously thought. The article starts with a general introduction to ERP methodology and language-related ERP profiles…

  18. Snow Precipitation and Snow Cover Climatic Variability for the Period 1971–2009 in the Southwestern Italian Alps: The 2008–2009 Snow Season Case Study

    Directory of Open Access Journals (Sweden)

    Simona Fratianni

    2010-10-01

    Full Text Available Snow cover greatly influences the climate in the Alpine region and is one of the most relevant parameters for the climate change analysis. Nevertheless, snow precipitation variability is a relatively underexplored field of research because of the lack of long-term, continuous and homogeneous time series. After a historical research aiming to recover continuous records, three high quality time series of snow precipitation and snow depth recorded in the southwestern Italian Alps were analyzed. The comparison between the climatological indices over the 30 years reference period 1971–2000 and the decade 2000–2009 outlined a general decrease in the amount of snow precipitation, and a shift in the seasonal distribution of the snow precipitation in the most recent period. In the analysis of the last decade snow seasons characteristics, the attention was focused on the heavy snowfalls that occurred in Piedmont during the 2008–2009 snow season: MODerate resolution Imager Spectroradiometer (MODIS snow cover products were used to evaluate snow cover extension at different times during the snow season, and the results were set in relation to the temperatures.

  19. 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

  20. 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.

  1. 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.

  2. Distribution, variability, and predictors of urinary bisphenol A levels in 50 North Carolina adults over a six-week monitoring period.

    Science.gov (United States)

    Morgan, Marsha K; Nash, Maliha; Barr, Dana Boyd; Starr, James M; Scott Clifton, M; Sobus, Jon R

    2018-03-01

    Bisphenol A (BPA) is commonly manufactured to make polycarbonate plastics and epoxy resins for use in consumer products and packaged goods. BPA has been found in several different types of environmental media (e.g., food, dust, and air). Many cross-sectional studies have frequently detected BPA concentrations in adult urine samples. However, limited data are available on the temporal variability and important predictors of urinary BPA concentrations in adults. In this work, the major objectives were to: 1) quantify BPA levels in duplicate-diet solid food, drinking water, hard floor surface wipe, and urine samples (first-morning void [FMV], bedtime, and 24-h) collected from adults over a six-week monitoring period; 2) determine the temporal variability of urinary BPA levels using concentration, specific gravity (SG) adjusted, creatinine (CR) adjusted, and excretion rate values, and; 3) examine associations between available study factors and urinary BPA concentrations. In 2009-2011, a convenience sample of 50 adults was recruited from residential settings in North Carolina. The participants completed diaries and collected samples during weeks 1, 2, and/or 6 of a six-week monitoring period. BPA was detected in 38%, 4%, and 99% of the solid food (n=775), drinking water (n=50), and surface wipe samples (n=138), respectively. Total BPA (free plus conjugated) was detected in 98% of the 2477 urine samples. Median urinary BPA levels were 2.07ng/mL, 2.20ng/mL-SG, 2.29ng/mg, and 2.31ng/min for concentration, SG-adjusted, CR-adjusted, and excretion rate values, respectively. The intraclass correlation coefficient (ICC) estimates for BPA showed poor reproducibility (≤0.35) for all urine sample types and methods over a day, week, and six weeks. CR-adjusted bedtime voids collected over six-weeks required the fewest, realistic number of samples (n=11) to obtain a reliable biomarker estimate (ICC=0.80). Results of linear mixed-effects models showed that sex, race, season, and CR

  3. New Plants at Prague Castle and Hradčany in the Early Modern Period. A History of Selected Species

    Czech Academy of Sciences Publication Activity Database

    Beneš, J.; Čulíková, Věra; Kosňovská, J.; Frolík, Jan; Matiášek, Josef

    2012-01-01

    Roč. 3, č. 1 (2012), s. 103-114 ISSN 1804-848X Institutional research plan: CEZ:AV0Z80020508 Keywords : Prague Castle * Early Modern Period * archaeobotany Subject RIV: AC - Archeology, Anthropology, Ethnology http://www.iansa.eu/papers/IANSA-2012-01-benes.pdf

  4. 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.

  5. 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.

  6. 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

  7. 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

  8. Atypical auditory refractory periods in children from lower socio-economic status backgrounds: ERP evidence for a role of selective attention.

    Science.gov (United States)

    Stevens, Courtney; Paulsen, David; Yasen, Alia; Neville, Helen

    2015-02-01

    Previous neuroimaging studies indicate that lower socio-economic status (SES) is associated with reduced effects of selective attention on auditory processing. Here, we investigated whether lower SES is also associated with differences in a stimulus-driven aspect of auditory processing: the neural refractory period, or reduced amplitude response at faster rates of stimulus presentation. Thirty-two children aged 3 to 8 years participated, and were divided into two SES groups based on maternal education. Event-related brain potentials were recorded to probe stimuli presented at interstimulus intervals (ISIs) of 200, 500, or 1000 ms. These probes were superimposed on story narratives when attended and ignored, permitting a simultaneous experimental manipulation of selective attention. Results indicated that group differences in refractory periods differed as a function of attention condition. Children from higher SES backgrounds showed full neural recovery by 500 ms for attended stimuli, but required at least 1000 ms for unattended stimuli. In contrast, children from lower SES backgrounds showed similar refractory effects to attended and unattended stimuli, with full neural recovery by 500 ms. Thus, in higher SES children only, one functional consequence of selective attention is attenuation of the response to unattended stimuli, particularly at rapid ISIs, altering basic properties of the auditory refractory period. Together, these data indicate that differences in selective attention impact basic aspects of auditory processing in children from lower SES backgrounds. Copyright © 2013 Elsevier B.V. All rights reserved.

  9. 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.

  10. 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.

  11. 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.

  12. 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)

  13. 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.

  14. Thyroid Cancer Incidences From Selected South America Population-Based Cancer Registries: An Age-Period-Cohort Study

    Directory of Open Access Journals (Sweden)

    Anne Karin da Mota Borges

    2017-08-01

    Full Text Available Purpose: The incidence of thyroid cancer (TC has increased substantially worldwide. However, there is a lack of knowledge about age-period-cohort (APC effects on incidence rates in South American countries. This study describes the TC incidence trends and analyzes APC effects in Cali, Colombia; Costa Rica; Goiânia, Brazil; and Quito, Ecuador. Materials and Methods: Data were obtained from the Cancer Incidence in Five Continents series, and the crude and age-standardized incidence rates were calculated. Trends were assessed using the estimated annual percentage change, and APC models were estimated using Poisson regression for individuals between age 20 and 79 years. Results: An increasing trend in age-standardized incidence rates was observed among women from Goiânia (9.2%, Costa Rica (5.7%, Quito (4.0%, and Cali (3.4%, and in men from Goiânia (10.0% and Costa Rica (3.4%. The APC modeling showed that there was a period effect in all regions and for both sexes. Increasing rate ratios were observed among women over the periods. The best fit model was the APC model in women from all regions and in men from Quito, whereas the age-cohort model showed a better fit in men from Cali and Costa Rica, and the age-drift model showed a better fit among men from Goiânia. Conclusion: These findings suggest that overdiagnosis is a possible explanation for the observed increasing pattern of TC incidence. However, some environmental exposures may also have contributed to the observed increase.

  15. Pretreatment plasma homovanillic acid in schizophrenia and schizoaffective disorder: the influence of demographic variables and the inpatient drug-free period.

    Science.gov (United States)

    Sharma, R P; Javaid, J I; Davis, J M; Janicak, P G

    1998-09-15

    The relationship between plasma homovanillic acid (pHVA) and schizophrenic symptoms has not been conclusively determined. We reexamine pHVA levels in a new sample of patients with emphasis on demographic variables and the drug-free period. Plasma HVA levels were studied in 54 schizophrenic and schizoaffective-disordered, drug-free inpatients suffering from a psychotic exacerbation. A significant correlation was observed between pHVA levels and the number of inpatient drug-free days in the total sample, as well as the schizophrenic patient subsample. Further, pHVA was significantly and positively correlated with the duration of illness in the schizophrenic patient subsample. Plasma HVA correlations with behavior, as measured by Brief Psychiatric Rating Scale factors (anxiety/depression and hostility/suspiciousness), emerged only when considering schizophrenic patients drug-free for more than 2 weeks. No correlation was found between pHVA and the age of illness onset or the duration of the delay of treatment of the first psychotic episode. The effects of antipsychotic withdrawal on levels of pHVA in clinical populations may have to be examined and controlled for in future studies attempting to study the relationship between this metabolite and behavior in acutely ill, drug-free schizophrenic patients.

  16. Multi-period fuzzy mean-semi variance portfolio selection problem with transaction cost and minimum transaction lots using genetic algorithm

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Barati

    2016-04-01

    Full Text Available Multi-period models of portfolio selection have been developed in the literature with respect to certain assumptions. In this study, for the first time, the portfolio selection problem has been modeled based on mean-semi variance with transaction cost and minimum transaction lots considering functional constraints and fuzzy parameters. Functional constraints such as transaction cost and minimum transaction lots were included. In addition, the returns on assets parameters were considered as trapezoidal fuzzy numbers. An efficient genetic algorithm (GA was designed, results were analyzed using numerical instances and sensitivity analysis were executed. In the numerical study, the problem was solved based on the presence or absence of each mode of constraints including transaction costs and minimum transaction lots. In addition, with the use of sensitivity analysis, the results of the model were presented with the variations of minimum expected rate of programming periods.

  17. Evaluation of selected recurrence measures in discriminating pre-ictal and inter-ictal periods from epileptic EEG data

    Energy Technology Data Exchange (ETDEWEB)

    Ngamga, Eulalie Joelle [Potsdam Institute for Climate Impact Research, Telegraphenberg A 31, 14473 Potsdam (Germany); Bialonski, Stephan [Max-Planck-Institute for the Physics of Complex Systems, Nöthnitzer Straße 38, 01187 Dresden (Germany); Marwan, Norbert, E-mail: marwan@pik-potsdam.de [Potsdam Institute for Climate Impact Research, Telegraphenberg A 31, 14473 Potsdam (Germany); Kurths, Jürgen [Potsdam Institute for Climate Impact Research, Telegraphenberg A 31, 14473 Potsdam (Germany); Department of Physics, Humboldt University Berlin, 12489 Berlin (Germany); Institute for Complex Systems and Mathematical Biology, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom); Geier, Christian [Department of Epileptology, University of Bonn, Sigmund-Freud-Straße 25, 53105 Bonn (Germany); Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Nussallee 14–16, 53115 Bonn (Germany); Lehnertz, Klaus [Department of Epileptology, University of Bonn, Sigmund-Freud-Straße 25, 53105 Bonn (Germany); Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Nussallee 14–16, 53115 Bonn (Germany); Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53175 Bonn (Germany)

    2016-04-01

    We investigate the suitability of selected measures of complexity based on recurrence quantification analysis and recurrence networks for an identification of pre-seizure states in multi-day, multi-channel, invasive electroencephalographic recordings from five epilepsy patients. We employ several statistical techniques to avoid spurious findings due to various influencing factors and due to multiple comparisons and observe precursory structures in three patients. Our findings indicate a high congruence among measures in identifying seizure precursors and emphasize the current notion of seizure generation in large-scale epileptic networks. A final judgment of the suitability for field studies, however, requires evaluation on a larger database. - Highlights: • Recurrence-based analysis of brain dynamics in human epilepsy. • Comparison of recurrence quantification and recurrence network measures. • Statistically significant precursory structures in three out of five patients. • High congruence among measures in characterizing brain dynamics.

  18. Evaluation of selected recurrence measures in discriminating pre-ictal and inter-ictal periods from epileptic EEG data

    International Nuclear Information System (INIS)

    Ngamga, Eulalie Joelle; Bialonski, Stephan; Marwan, Norbert; Kurths, Jürgen; Geier, Christian; Lehnertz, Klaus

    2016-01-01

    We investigate the suitability of selected measures of complexity based on recurrence quantification analysis and recurrence networks for an identification of pre-seizure states in multi-day, multi-channel, invasive electroencephalographic recordings from five epilepsy patients. We employ several statistical techniques to avoid spurious findings due to various influencing factors and due to multiple comparisons and observe precursory structures in three patients. Our findings indicate a high congruence among measures in identifying seizure precursors and emphasize the current notion of seizure generation in large-scale epileptic networks. A final judgment of the suitability for field studies, however, requires evaluation on a larger database. - Highlights: • Recurrence-based analysis of brain dynamics in human epilepsy. • Comparison of recurrence quantification and recurrence network measures. • Statistically significant precursory structures in three out of five patients. • High congruence among measures in characterizing brain dynamics.

  19. 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/...

  20. Distinguishing the impacts of human activities and climate variability on runoff and sediment load change based on paired periods with similar weather conditions

    NARCIS (Netherlands)

    Wang, Fei; Hessel, Rudi; Mu, Xingmin; Maroulis, Jerry; Zhao, Guangju; Geissen, Violette; Ritsema, Coen

    2015-01-01

    Runoff and sediment loads from river basin are largely affected by the interplay of climate variability and human activities within the basin. However, distinguishing the impacts of climate variability and human activities would vastly improve our knowledge of water resources, climate variability

  1. Reference gene selection for real-time quantitative PCR analysis of the mouse uterus in the peri-implantation period.

    Directory of Open Access Journals (Sweden)

    Pengfei Lin

    Full Text Available The study of uterine gene expression patterns is valuable for understanding the biological and molecular mechanisms that occur during embryo implantation. Real-time quantitative RT-PCR (qRT-PCR is an extremely sensitive technique that allows for the precise quantification of mRNA abundance; however, selecting stable reference genes suitable for the normalization of qRT-PCR data is required to avoid the misinterpretation of experimental results and erroneous analyses. This study employs several mouse models, including an early pregnancy, a pseudopregnancy, a delayed implantation and activation, an artificial decidualization and a hormonal treatment model; ten candidate reference genes (PPIA, RPLP0, HPRT1, GAPDH, ACTB, TBP, B2M, 18S, UBC and TUBA that are found in uterine tissues were assessed for their suitability as internal controls for relative qRT-PCR quantification. GeNorm(PLUS, NormFinder, and BestKeeper were used to evaluate these candidate reference genes, and all of these methods identified RPLP0 and GAPDH as the most stable candidates and B2M and 18S as the least stable candidates. However, when the different models were analyzed separately, the reference genes exhibited some variation in their expression levels.

  2. Inter-annual variability of aerosol optical depth over the tropical Atlantic Ocean based on MODIS-Aqua observations over the period 2002-2012

    Science.gov (United States)

    Gkikas, Antonis; Hatzianastassiou, Nikolaos

    2013-04-01

    The tropical Atlantic Ocean is affected by dust and biomass burning aerosol loads transported from the western parts of the Saharan desert and the sub-Sahel regions, respectively. The spatial and temporal patterns of this transport are determined by the aerosol emission rates, their deposition (wet and dry), by the latitudinal shift of the Intertropical Convergence Zone (ITCZ) and the prevailing wind fields. More specifically, in summer, Saharan dust aerosols are transported towards the Atlantic Ocean, even reaching the Gulf of Mexico, while in winter the Atlantic Ocean transport takes place in more southern latitudes, near the equator, sometimes reaching the northern parts of South America. In the later case, dust is mixed with biomass burning aerosols originating from agricultural activities in the sub-Sahel, associated with prevailing north-easterly airflow (Harmattan winds). Satellite observations are the appropriate tool for describing this African aerosol export, which is important to atmospheric, oceanic and climate processes, offering the advantage of complete spatial coverage. In the present study, we use satellite measurements of aerosol optical depth at 550nm (AOD550nm), on a daily and monthly basis, derived from MODIS-Aqua platform, at 1ox1o spatial resolution (Level 3), for the period 2002-2012. The primary objective is to determine the pixel-level and regional mean anomalies of AOD550nm over the entire study period. The regime of the anomalies of African export is interpreted in relation to the aerosol source areas, precipitation, wind patterns and temporal variability of the North Atlantic Oscillation Index (NAOI). In order to ensure availability of AOD over the Sahara desert, MODIS-Aqua Deep Blue products are also used. As for precipitation, Global Precipitation Climatology Project (GPCP) data at 2.5ox2.5o are used. The wind fields are taken from the National Center for Environmental Prediction (NCEP). Apart from the regime of African aerosol export

  3. 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.

  4. Rats free to select between pure protein and a fat-carbohydrate mix ingest high-protein mixed meals during the dark period and protein meals during the light period.

    Science.gov (United States)

    Makarios-Lahham, Lina; Roseau, Suzanne M; Fromentin, Gilles; Tome, Daniel; Even, Patrick C

    2004-03-01

    Rats that are allowed to select their diets [dietary self- selection (DSS)] often ingest >30% of their daily energy in the form of protein. Such an intake may seem unhealthy, but the consistency of this choice suggests that it is motivated by physiologic drives. To gain a clearer understanding of how protein selection is structured during DSS, we adapted 12 rats to a standard diet (14% Protein) and then allowed them to choose between two diets, i.e., total milk protein (P) and a mix of carbohydrates and lipids (FC). The protein intake during DSS rose above 40%; assuming an intermeal interval of 10 min, 70% of the energy intake occurred with meals that included both P and FC, with the sequence of FC followed by P preferred to the sequence of P followed by FC (70 vs. 30%, P energy intake during the light period was reduced to only 10% of the daily energy intake [vs. 30% with the control P14 diet or a with a high-protein diet (50%)], and 90% of the intake was in the form of pure protein meals. In complementary studies, we verified that the high protein intake also occurred when rats were offered casein and whey and was not due to the high palatability of the milk protein. We conclude that a specific feeding pattern accompanies high protein intake in rats allowed DSS. The mechanisms underlying this behavior and its potential beneficial/adverse consequences over the long term still must be clarified.

  5. Correlation between SiO v = 3 J = 1 → 0 maser excitation and the light curve of a long-period variable star

    Science.gov (United States)

    Oyadomari, Miyako; Imai, Hiroshi; Nagayama, Takumi; Oyama, Tomoaki; Matsumoto, Naoko; Nakashima, Jun-ichi; Cho, Se-Hyung

    2018-03-01

    In order to understand the excitation mechanisms of silicon monoxide (SiO) masers around long-period variables (LPVs), we have investigated distributions of the SiO v = 2 and v = 3 J = 1 → 0 masers around 12 LPVs by very long baseline interferometry (VLBI) observations with the VLBI Exploration of Radio Astrometry (VERA) and the Nobeyama 45 m telescopes. VLBI fringes of the v = 3 maser emission were detected for five LPVs. The composite maps of the v = 2 and v = 3 masers were made for T Cep, W Hya, WX Psc, and R Leo using the spectral line phase-referencing technique. The v = 2 maser spots were distributed in a ring-like form around the central stars, while it is difficult to recognize any specific morphology in the v = 3 maser distributions due to the small number of v = 3 spots detected. However in T Cep, we find that the distribution of the v = 3 maser spots correlates well with the v = 2 masers within a few milliarcseconds (0.2-0.3 au) in position and 1 km s-1 in line-of-sight velocity at the light curve phase of ϕ = 0.28 (ϕ = 0.0 and 1.0 correspond to the visible light maxima). This correlation implies that the mechanism of line-overlapping between the mid-infrared lines of H2O and SiO molecules works in T Cep at ϕ = 0.28. We discuss the possibility that the line-overlapping may work at the limited duration from the maximum to the minimum of the stellar light curve.

  6. 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.

  7. The validity of the PAM-RL device for evaluating periodic limb movements in sleep and an investigation on night-to-night variability of periodic limb movements during sleep in patients with restless legs syndrome or periodic limb movement disorder using this system.

    Science.gov (United States)

    Kobayashi, Mina; Namba, Kazuyoshi; Ito, Eiki; Nishida, Shingo; Nakamura, Masaki; Ueki, Yoichiro; Furudate, Naomichi; Kagimura, Tatsuo; Usui, Akira; Inoue, Yuichi

    2014-01-01

    The status of night-to-night variability for periodic limb movements in sleep (PLMS) has not been clarified. With this in mind, we investigated the validity of PLMS measurement by actigraphy with the PAM-RL device in Japanese patients with suspected restless legs syndrome (RLS) or periodic limb movement disorder (PLMD) and the night-to-night variability of PLMS among the subjects. Forty-one subjects (mean age, 52.1±16.1 years) underwent polysomnography (PSG) and PAM-RL measurement simultaneously. Thereafter, subjects used the PAM-RL at home on four more consecutive nights. The correlation between PLMS index on PSG (PLMSI-PSG) and PLM index on PAM-RL (PLMI-PAM) was 0.781 (PPAM-RL. PAM-RL is thought to be valuable for assessing PLMS even in Japanese subjects. Recording of PAM-RL for three or more consecutive nights may be required to ensure the screening reliability of a patient with suspected pathologically frequent PLMS. Copyright © 2013 Elsevier B.V. All rights reserved.

  8. 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

  9. 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.

  10. 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.

  11. Evaluation of selected physicochemical parameters of extra virgin olive oil commercialized in the Czech market and stored during a period of 5 months

    Directory of Open Access Journals (Sweden)

    Richardos Nikolaos Salek

    2017-01-01

    Full Text Available The scope of this work was to evaluate the development of selected physicochemical parameters (free acidity, peroxide value and specific extinction coefficients in ultraviolet of extra virgin olive oil, commercialized in the Czech market and stored for a time period of 5 months (at 20 ±5 °C. The tested extra virgin olive oil samples were stored under conditions simulating domestic and commercial storage environment, in which the impact of light and headspace volume were also examined. Moreover, all the analyzed samples fell within the established "extra virgin olive oil category", thus proving their legitimacy, authentication and excellent quality. Furthermore, all the monitored physicochemical parameters were affected by the progress of the storage period, the rising volume of headspace (due to more available oxygen in the container and exposition to light, resulting in decreasing quality of the examined extra virgin olive oil samples. In addition, the storage of extra virgin olive oil samples in dark containers reported sufficient resistance to oxidation processes up to a period of 3 months, however, after this period signs of oil quality deterioration were reported. Nevertheless, if exposition to light occurred, accelerated decrease in the quality of the extra virgin olive oil samples was observed.

  12. 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.

  13. Effects of a Period of Selected Activity on Lung Capacities in Children 5-10 Years with Asthma Caused by Exercise

    Directory of Open Access Journals (Sweden)

    Gholamreza Sharifi

    2014-09-01

    Full Text Available Background: Aasthma due to causing disruption in the work of breathing and obstruction of the pulmonary tract creates the physical restrictions in the social, emotional and psychological, aspects and performing daily life activities, hence the present study is conducted to determine the impact of a period of selected activity on some spirometry parameters of children from 5 to 10 years old suffering from asthma caused by exercise.Materials and Methods: In this half experimental respiratory research, respiratory indexes of 11 children including 5 boys under the age of 10 years old suffering from asthma caused by exercise were measured before and after eight weeks of selected exercises and pranayama by spirometry were measured.Results: The results showed that the selected exercise routine improves on the status of activities and being short of breath (Z=0/003. Also the average of spirometry indexes prior to a ten minutes exercise, before and after the intervention, compared with the average of spirometry indexes after a ten minute exercise, before and after intervention in the parameters: (fev1 the volume of the expiratory force in the first second, and (PEF the maximum expiratory flow, the results are statistically significant (p 0.05.Conclusions: The present study shows the impact of the selected exercises in improving mobility status and being short of breath and reducing asthma symptoms caused by exercise (EIA as well as strengthening the respiratory muscles significantly.

  14. Selective appearance of several laser-induced periodic surface structure patterns on a metal surface using structural colors produced by femtosecond laser pulses

    Energy Technology Data Exchange (ETDEWEB)

    Yao Jianwu; Zhang Chengyun; Liu Haiying; Dai Qiaofeng; Wu Lijun [Laboratory of Photonic Information Technology, School of Information and Optoelectronic Science and Engineering, South China Normal University, Guangzhou 510006 (China); Lan, Sheng, E-mail: slan@scnu.edu.cn [Laboratory of Photonic Information Technology, School of Information and Optoelectronic Science and Engineering, South China Normal University, Guangzhou 510006 (China); Gopal, Achanta Venu [Department of Condensed Matter Physics and Material Science, Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai 400005 (India); Trofimov, Vyacheslav A.; Lysak, Tatiana M. [Department of Computational Mathematics and Cybernetics, M. V. Lomonosov Moscow State University, Moscow 119992 (Russian Federation)

    2012-07-15

    Ripples with a subwavelength period were induced on the surface of a stainless steel (301 L) foil by femtosecond laser pulses. By optimizing the irradiation fluence of the laser pulses and the scanning speed of the laser beam, ripples with large amplitude ({approx}150 nm) and uniform period could be obtained, rendering vivid structural colors when illuminating the surface with white light. It indicates that these ripples act as a surface grating that diffracts light efficiently. The strong dependence of the ripple orientation on the polarization of laser light offers us the opportunity of decorating different regions of the surface with different types of ripples. As a result, different patterns can be selectively displayed with structural color when white light is irradiated on the surface from different directions. More interestingly, we demonstrated the possibility of decorating the same region with two or more types of ripples with different orientations. In this way, different patterns with spatial overlapping can be selectively displayed with structural color. This technique may find applications in the fields of anti-counterfeiting, color display, decoration, encryption and optical data storage.

  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. Variability of bisphenol-A concentrations in first morning, bedtime, and 24-hour urine samples in 50 North Carolina adults over a six-week period

    Science.gov (United States)

    Bisphenol-A (BPA) is a high-production volume chemical that is used to make a number of consumer products and packaged goods. Many cross-sectional studies have frequently reported detecting BPA in urine. However, limited data exist on the temporal variability of urinary BPA conce...

  19. Understanding Variability, Habit and the Effect of Long Period Activity Plan in Modal Choices: A Day to Day, Week to Week Analysis on Panel Data

    DEFF Research Database (Denmark)

    Cherchi, Elisabetta; Cirillo, Cinzia

    2014-01-01

    Understanding variability in individual behaviour is crucial for the comprehension of travel patterns and for the development and evaluation of planning policies. In the last 30 years a vast body of research has approached the issue in a variety of ways, but there are no studies on the intrinsic ...

  20. 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....

  1. Effect of different periods of chronic heat stress with or without vitamin C supplementation on bone and selected serum parameters of broiler chickens.

    Science.gov (United States)

    Mosleh, Najmeh; Shomali, Tahoora; Nematollahi, Fahimeh; Ghahramani, Zahra; Ahrari Khafi, Mohammad Saeid; Namazi, Fatemeh

    2018-04-01

    This study evaluates the effect of different periods of chronic heat stress (CHS) on selected bone and serum parameters of broiler chickens with or without vitamin C administration. Ninety 23-day-old chickens were randomly allocated into seven groups: (1) control, (2) short-term CHS (5 days), (3) short-term CHS + vitamin C (12 g/100 l drinking water of a 50% product), (4) medium-term CHS (10 days), (5) medium-term CHS + vitamin C, (6) long-term CHS (20 days) and (7) long-term CHS + vitamin C. In heat-stressed groups the temperature was increased to 39 ± 1°C for 8 h/day. At the end of the experiment, blood samples were collected and shank, keel and tibia bones were removed. CHS was not associated with a drastic change in serum Ca and corticosterone, or bone characteristics (both cortical and trabecular bones in radiographical and histological evaluation), or birds' performance. Oxidative stress was present especially with short-term CHS. CHS, especially for short or medium periods, showed a tendency to increase serum vitamin C and administration of this vitamin did not make a significant change in its serum levels although it ameliorated oxidative stress. In conclusion, it seems that CHS is not associated with an appreciable change in broiler performance, bone characteristics, or selected serum parameters; and simultaneous vitamin C administration at the dosage of 12 g/100 l in drinking water has no beneficial effect apart from reducing oxidative stress especially in short-term chronically heat-stressed birds.

  2. Selective propagation of mouse-passaged scrapie prions with long incubation period from a mixed prion population using GT1-7 cells.

    Directory of Open Access Journals (Sweden)

    Kohtaro Miyazawa

    Full Text Available In our previous study, we demonstrated the propagation of mouse-passaged scrapie isolates with long incubation periods (L-type derived from natural Japanese sheep scrapie cases in murine hypothalamic GT1-7 cells, along with disease-associated prion protein (PrPSc accumulation. We here analyzed the susceptibility of GT1-7 cells to scrapie prions by exposure to infected mouse brains at different passages, following interspecies transmission. Wild-type mice challenged with a natural sheep scrapie case (Kanagawa exhibited heterogeneity of transmitted scrapie prions in early passages, and this mixed population converged upon one with a short incubation period (S-type following subsequent passages. However, when GT1-7 cells were challenged with these heterologous samples, L-type prions became dominant. This study demonstrated that the susceptibility of GT1-7 cells to L-type prions was at least 105 times higher than that to S-type prions and that L-type prion-specific biological characteristics remained unchanged after serial passages in GT1-7 cells. This suggests that a GT1-7 cell culture model would be more useful for the economical and stable amplification of L-type prions at the laboratory level. Furthermore, this cell culture model might be used to selectively propagate L-type scrapie prions from a mixed prion population.

  3. Quasi-periodic photonic crystal Fabry–Perot optical filter based on Si/SiO2 for visible-laser spectral selectivity

    Science.gov (United States)

    Qi, Dong; Wang, Xian; Cheng, Yongzhi; Chen, Fu; Liu, Lei; Gong, Rongzhou

    2018-06-01

    We report on a 1D quasi-periodic photonic crystal Fabry–Perot optical filter Cs(Si/SiO2)3(SiO2/Si)3 for spectral selectivity of visible light and 1.55 µm laser. A material transparency interval of 1.03–2.06 µm makes Si a unique choice of high refractive index material. Owing to the CIE 1931 standard and equal inclination interference, the designed structure can be successfully fabricated with a certain color (brown, khaki, or blue) corresponding to the different Cs physical thickness d and response R(λ). In addition, the peak transmittance T max of the proposed structure can reach as high as 92.56% (Cs  =  20 nm), 90.83% (Cs  =  40 nm), and 88.85% (Cs  =  60 nm) with a relatively narrow full width at half maximum of 4.4, 4.6, and 4.8 nm at 1.55 µm. The as-prepared structure indicates that it is feasible for a photonic crystal Fabry–Perot optical filter to achieve visible-laser (1.55 µm) spectral selectivity.

  4. Understanding Variability, Habit and the Effect of Long Period Activity Plan in Modal Choices: A Day to Day, Week to Week Analysis on Panel Data

    DEFF Research Database (Denmark)

    Cherchi, Elisabetta; Cirillo, Cinzia

    2014-01-01

    Understanding variability in individual behaviour is crucial for the comprehension of travel patterns and for the development and evaluation of planning policies. In the last 30 years a vast body of research has approached the issue in a variety of ways, but there are no studies on the intrinsic ...... choice made is influenced by the duration of the activity and the weekly structure of the activities. Finally, models improve significantly when panel correlation is accounted for. But it seems that inertia can explain to some extent for panel effect.......Understanding variability in individual behaviour is crucial for the comprehension of travel patterns and for the development and evaluation of planning policies. In the last 30 years a vast body of research has approached the issue in a variety of ways, but there are no studies on the intrinsic...... variability in the individual preferences for mode choices in absence of external changes (or shocks) in the transportation infrastructures (i.e. introduction of new modes or major reorganization of the transportation system). This requires using continuous panel data. Few papers have studied mode choice...

  5. 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

  6. 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...

  7. Daily Course of CO2 Fluxes in the Atmosphere-Water System and Variable Fluorescence of Phytoplankton during the Open-Water Period for Lake Baikal according to Long-Term Measurements

    Science.gov (United States)

    Zavoruev, V. V.; Domysheva, V. M.; Pestunov, D. A.; Sakirko, M. V.; Panchenko, M. V.

    2018-04-01

    The process of gas exchange of CO2 in the atmosphere-water system and its relation to the daily course of variable fluorescence of phytoplankton is studied on the basis of long-term (2004-2014) measurements during the open water period for Lake Baikal. It is found that the decrease in photosynthetic activity of plankton is almost synchronous to the increase in the CO2 flux from atmosphere to water. It follows from comparison of the spring and summer data with December measurements that the daily decrease in variable fluorescence of phytoplankton is caused by the internal daily rhythm of the photosynthetic activity of plankton.

  8. 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.

  9. Temporal variability of benzene concentration in the ambient air of Delhi: a comparative assessment of pre- and post-CNG periods.

    Science.gov (United States)

    Khillare, P S; Hoque, Raza Rafiqul; Shridhar, Vijay; Agarwal, Tripti; Balachandran, S

    2008-06-15

    CNG (compressed natural gas) was fully implemented in public transport system in Delhi in December 2002. The study assesses the benzene concentration trends at two busy traffic intersections and a background site in Delhi, India. Monitoring was done for two different time periods viz; in the year 2001-2002 (pre-CNG) and two winter months (January and February) of the year 2007 (post-CNG) to assess the impact of various policy measures adopted by the government of Delhi to improve the air quality in the city. Annual average benzene concentration for the pre-CNG period was found to be 86.47+/-53.24 microg m(-3). Average benzene concentrations for the winter months (January-February) of pre- and post-CNG periods were 116.32+/-51.65 microg m(-3) and 187.49+/-22.50 microg m(-3), respectively. Enhanced values could be solely attributed to the increase in the vehicular population from 3.5 million in the year 2001-2002 to approximately 5.1 millions in the year 2007.

  10. The MACHO Project LMC Variable Star Inventory. VIII. The Recent Star Formation History of the Large Magellanic Cloud from the Cepheid Period Distribution

    International Nuclear Information System (INIS)

    Alcock, C.; Allsman, R.A.; Alves, D.R.; Axelrod, T.S.; Becker, A.C.; Bennett, D.P.; Bersier, D.F.; Cook, K.H.; Freeman, K.C.; Griest, K.; Guern, J.A.; Lehner, M.; Marshall, S.L.; Minniti, D.; Peterson, B.A.; Pratt, M.R.; Quinn, P.J.; Rodgers, A.W.; Stubbs, C.W.

    1999-01-01

    We present an analysis of the period distribution of about 1800 Cepheids in the LMC, based on data obtained by the MACHO microlensing experiment and on a previous catalog by C. H. Payne Gaposchkin. Using stellar evolution and pulsation models, we construct theoretical period-frequency distributions that are compared with the observations. These models reveal that a significant burst of star formation has occurred recently in the LMC (∼1.15x10 8 yr). We also show that during the last ∼10 8 yr, the main center of star formation has been propagating from southeast to northwest along the bar. We find that the evolutionary masses of Cepheids are still smaller than pulsation masses by ∼7% and that the red edge of the Cepheid instability strip could be slightly bluer than indicated by theory. There are approximately 600 Cepheids with periods below ∼2.5 days that cannot be explained by evolution theory. We suggest that they are anomalous Cepheids and that a number of these stars are double-mode Cepheids. copyright copyright 1999. The American Astronomical Society

  11. 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…

  12. 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.

  13. 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...

  14. 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.

  15. Phase synchronization of baroclinic waves in a differentially heated rotating annulus experiment subject to periodic forcing with a variable duty cycle.

    Science.gov (United States)

    Read, P L; Morice-Atkinson, X; Allen, E J; Castrejón-Pita, A A

    2017-12-01

    A series of laboratory experiments in a thermally driven, rotating fluid annulus are presented that investigate the onset and characteristics of phase synchronization and frequency entrainment between the intrinsic, chaotic, oscillatory amplitude modulation of travelling baroclinic waves and a periodic modulation of the (axisymmetric) thermal boundary conditions, subject to time-dependent coupling. The time-dependence is in the form of a prescribed duty cycle in which the periodic forcing of the boundary conditions is applied for only a fraction δ of each oscillation. For the rest of the oscillation, the boundary conditions are held fixed. Two profiles of forcing were investigated that capture different parts of the sinusoidal variation and δ was varied over the range 0.1≤δ≤1. Reducing δ was found to act in a similar way to a reduction in a constant coupling coefficient in reducing the width of the interval in forcing frequency or period over which complete synchronization was observed (the "Arnol'd tongue") with respect to the detuning, although for the strongest pulse-like forcing profile some degree of synchronization was discernible even at δ=0.1. Complete phase synchronization was obtained within the Arnol'd tongue itself, although the strength of the amplitude modulation of the baroclinic wave was not significantly affected. These experiments demonstrate a possible mechanism for intraseasonal and/or interannual "teleconnections" within the climate system of the Earth and other planets that does not rely on Rossby wave propagation across the planet along great circles.

  16. Live imaging-based model selection reveals periodic regulation of the stochastic G1/S phase transition in vertebrate axial development.

    Directory of Open Access Journals (Sweden)

    Mayu Sugiyama

    2014-12-01

    Full Text Available In multicellular organism development, a stochastic cellular response is observed, even when a population of cells is exposed to the same environmental conditions. Retrieving the spatiotemporal regulatory mode hidden in the heterogeneous cellular behavior is a challenging task. The G1/S transition observed in cell cycle progression is a highly stochastic process. By taking advantage of a fluorescence cell cycle indicator, Fucci technology, we aimed to unveil a hidden regulatory mode of cell cycle progression in developing zebrafish. Fluorescence live imaging of Cecyil, a zebrafish line genetically expressing Fucci, demonstrated that newly formed notochordal cells from the posterior tip of the embryonic mesoderm exhibited the red (G1 fluorescence signal in the developing notochord. Prior to their initial vacuolation, these cells showed a fluorescence color switch from red to green, indicating G1/S transitions. This G1/S transition did not occur in a synchronous manner, but rather exhibited a stochastic process, since a mixed population of red and green cells was always inserted between newly formed red (G1 notochordal cells and vacuolating green cells. We termed this mixed population of notochordal cells, the G1/S transition window. We first performed quantitative analyses of live imaging data and a numerical estimation of the probability of the G1/S transition, which demonstrated the existence of a posteriorly traveling regulatory wave of the G1/S transition window. To obtain a better understanding of this regulatory mode, we constructed a mathematical model and performed a model selection by comparing the results obtained from the models with those from the experimental data. Our analyses demonstrated that the stochastic G1/S transition window in the notochord travels posteriorly in a periodic fashion, with doubled the periodicity of the neighboring paraxial mesoderm segmentation. This approach may have implications for the characterization of

  17. 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.

  18. 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.

  19. 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.

  20. 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...

  1. 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/...

  2. 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.

  3. Influence of ERβ selective agonism during the neonatal period on the sexual differentiation of the rat hypothalamic-pituitary-gonadal (HPG axis

    Directory of Open Access Journals (Sweden)

    Patisaul Heather B

    2012-01-01

    Full Text Available Abstract Background It is well established that sexual differentiation of the rodent hypothalamic-pituitary-gonadal (HPG axis is principally orchestrated by estrogen during the perinatal period. Here we sought to better characterize the mechanistic role the beta form of the estrogen receptor (ERβ plays in this process. Methods To achieve this, we exposed neonatal female rats to three doses (0.5, 1 and 2 mg/kg of the ERβ selective agonist diarylpropionitrile (DPN using estradiol benzoate (EB as a positive control. Measures included day of vaginal opening, estrous cycle quality, GnRH and Fos co-localization following ovariectomy and hormone priming, circulating luteinizing hormone (LH levels and quantification of hypothalamic kisspeptin immunoreactivity. A second set of females was then neonatally exposed to DPN, the ERα agonist propyl-pyrazole-triol (PPT, DPN+PPT, or EB to compare the impact of ERα and ERβ selective agonism on kisspeptin gene expression in pre- and post-pubescent females. Results All three DPN doses significantly advanced the day of vaginal opening and induced premature anestrus. GnRH and Fos co-labeling, a marker of GnRH activation, following ovariectomy and hormone priming was reduced by approximately half at all doses; the magnitude of which was not as large as with EB or what we have previously observed with the ERα agonist PPT. LH levels were also correspondingly lower, compared to control females. No impact of DPN was observed on the density of kisspeptin immunoreactive (-ir fibers or cell bodies in the arcuate (ARC nucleus, and kisspeptin-ir was only significantly reduced by the middle (1 mg/kg DPN dose in the preoptic region. The second experiment revealed that EB, PPT and the combination of DPN+PPT significantly abrogated preoptic Kiss1 expression at both ages but ARC expression was only reduced by EB. Conclusion Our results indicate that selective agonism of ERβ is not sufficient to completely achieve male

  4. Variability of 137Cs and 40K soil-to-fruit transfer factor in tropical lemon trees during the fruit development period

    International Nuclear Information System (INIS)

    Velasco, H.; Cid, A.S.; Anjos, R.M.; Zamboni, C.B.; Rizzotto, M.; Valladares, D.L.; Juri Ayub, J.

    2012-01-01

    In this investigation we evaluate the soil uptake of 137 Cs and 40 K by tropical plants and their consequent translocation to fruits, by calculating the soil-to-fruit transfer factors defined as F v = [concentration of radionuclide in fruit (Bq kg −1 dry mass)/concentration of radionuclide in soil (Bq kg −1 dry mass in upper 20 cm)]. In order to obtain F v values, the accumulation of these radionuclides in fruits of lemon trees (Citrus limon B.) during the fruit growth was measured. A mathematical model was calibrated from the experimental data allowing simulating the incorporation process of these radionuclides by fruits. Although the fruit incorporates a lot more potassium than cesium, both radionuclides present similar absorption patterns during the entire growth period. F v ranged from 0.54 to 1.02 for 40 K and from 0.02 to 0.06 for 137 Cs. Maximum F v values are reached at the initial time of fruit growth and decrease as the fruit develops, being lowest at the maturation period. As a result of applying the model a decreasing exponential function is derived for F v as time increases. The agreement between the theoretical approach and the experimental values is satisfactory. - Highlights: ► We assessed the transfer of 137 Cs and 40 K from soil to fruits in tropical plants. ► A mathematical model was developed to describe the dry mass growth of lemon fruits. ► The transfer factors ranged from 0.54 to 1.02 for 40 K and from 0.02 to 0.06 for 137 Cs. ► Maximum values of transfer factors were reached in the initial phase of fruit growth. ► The agreement between the theoretical and the experimental results was satisfactory.

  5. Multicriteria approach to interpret the variability of the levels of particulate matter and gaseous pollutants in the Madrid metropolitan area, during the 1999-2012 period

    Science.gov (United States)

    Salvador, P.; Artíñano, B.; Viana, M. M.; Alastuey, A.; Querol, X.

    2015-05-01

    The evolution of the mean levels of particulate matter (PM) and gaseous pollutants recorded in the Madrid metropolitan area from 1999 to 2012, were investigated focussing on the impact of mitigation strategies and economic scenarios. Temporal trends have shown that SO2, CO, NO, PM10 and NO2 levels at Madrid kerbside and urban-background sites have been decreasing over the 1999-2012 period, with statistical significance. A small contribution to the annual decreasing rates of SO2, NO and NO2 obtained at these sites could be attributed to the reduction in the regional background levels. The reduction in the emissions of atmospheric pollutants from specific sources of the urban agglomeration, explained most of the annual decreasing rates obtained at the kerbside and urban-background sites. From 1999 to 2007 a reduction of the emissions from road traffic and residential heating was produced, as a consequence of the implementation of a number of management strategies promoted and adopted by European and national public administrations. In contrast, from 2008 to 2012 a deep decrease in fuel consumption and a reduction of construction-demolition and roadwork activities took place in the Madrid metropolitan area, as a consequence of the economic recession. The expected overcoming of the economic crisis within the next few years, will presumably give rise to similar levels of PM and gaseous pollutants as those existing previously to the crisis period. The introduction of new Euro 6/VI vehicles which emit considerably less NOx than previous generation diesel vehicles, as well as the implementation of strategies aimed at reducing resuspended mineral dust from road traffic and construction-demolition activities are thus encouraged.

  6. Kerathocyst odontogenic tumor: Importance of selection the best treatment modality and a periodical follow-up to prevent from recurrence: A case report and literature review

    Directory of Open Access Journals (Sweden)

    Nasim Jafaripozve

    2013-01-01

    Full Text Available The keratocystic odontogenic tumor (KCOT is a relatively common oral and maxillofacial lesion with specific characteristics such us rapid growth, extension into the surrounding tissues and high rates of recurrence. Various treatment modalities have been reported. Due to the very thin and friable lining characteristic of the tumor, enucleation can be difficult undertaken and for this reason it is associated with the highest recurrence rates. A 22-year-old male referred to our clinic due to a slight expansion in the right mandible from 2 years ago. He has a history of occurrence of KCOT in this region that was treated surgically by enucleation and curettage 5 years ago. Cone beam computed tomography showed a multilocular radiolucent lesion that extended from the angle of the mandible to the symphysis. Incisional biopsy showed a KCOT recurrence that surgically treated with resection of the right mandible by continuity preservation. Selection of the best treatment modality and also a periodical lifelong follow-up is very important to reduce the rate of recurrence and morbidity of the patient.

  7. Microstructural and surface modifications and hydroxyapatite coating of Ti-6Al-4V triply periodic minimal surface lattices fabricated by selective laser melting.

    Science.gov (United States)

    Yan, Chunze; Hao, Liang; Hussein, Ahmed; Wei, Qingsong; Shi, Yusheng

    2017-06-01

    Ti-6Al-4V Gyroid triply periodic minimal surface (TPMS) lattices were manufactured by selective laser melting (SLM). The as-built Ti-6Al-4V lattices exhibit an out-of-equilibrium microstructure with very fine α' martensitic laths. When subjected to the heat treatment of 1050°C for 4h followed by furnace cooling, the lattices show a homogenous and equilibrium lamellar α+β microstructure with less dislocation and crystallographic defects compared with the as-built α' martensite. The as-built lattices present very rough strut surfaces bonded with plenty of partially melted metal particles. The sand blasting nearly removed all the bonded metal particles, but created many tiny cracks. The HCl etching eliminated these tiny cracks, and subsequent NaOH etching resulted in many small and shallow micro-pits and develops a sodium titanate hydrogel layer on the surfaces of the lattices. When soaked in simulated body fluid (SBF), the Ti-6Al-4V TPMS lattices were covered with a compact and homogeneous biomimetic hydroxyapatite (HA) layer. This work proposes a new method for making Ti-6Al-4V TPMS lattices with a homogenous and equilibrium microstructure and biomimetic HA coating, which show both tough and bioactive characteristics and can be promising materials usable as bone substitutes. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. 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....

  9. 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.

  10. The multi-period solution of a linear system of equations with the operator of differentiation along the main diagonal of the space of independent variables and delayed arguments

    Science.gov (United States)

    Sartabanov, Zhaishylyk A.

    2017-09-01

    A new approach to the study of periodic by all independent variables system of equations with a differentiation operator solutions along the direction of the main diagonal and with delayed arguments is proposed. The essence of the approach is to reduce the study of the multi-periodic solution of a linear inhomogeneous system to the construction of a solution of a simpler linear differential-difference system on the basis of the method of variating arbitrary constants of the complete integral of a homogeneous system. An integral representation of the unique multiperiodic solution of an inhomogeneous system is presented, expressed by a functional series of terms given by multiple repeated integrals. An estimate is given for the norm of a multi-periodic solution.

  11. 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.

  12. 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.

  13. 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.

  14. Phytoplankton dynamics in relation to seasonal variability and upwelling and relaxation patterns at the mouth of Ria de Aveiro (West Iberian Margin over a four-year period.

    Directory of Open Access Journals (Sweden)

    Tânia Vidal

    Full Text Available From June 2004 to December 2007, samples were weekly collected at a fixed station located at the mouth of Ria de Aveiro (West Iberian Margin. We examined the seasonal and inter-annual fluctuations in composition and community structure of the phytoplankton in relation to the main environmental drivers and assessed the influence of the oceanographic regime, namely changes in frequency and intensity of upwelling events, over the dynamics of the phytoplankton assemblage. The samples were consistently handled and a final subset of 136 OTUs (taxa with relative abundance > 0.01% was subsequently submitted to various multivariate analyses. The phytoplankton assemblage showed significant changes at all temporal scales but with an overriding importance of seasonality over longer- (inter-annual or shorter-term fluctuations (upwelling-related. Sea-surface temperature, salinity and maximum upwelling index were retrieved as the main driver of seasonal change. Seasonal signal was most evident in the fluctuations of chlorophyll a concentration and in the high turnover from the winter to spring phytoplankton assemblage. The seasonal cycle of production and succession was disturbed by upwelling events known to disrupt thermal stratification and induce changes in the phytoplankton assemblage. Our results indicate that both the frequency and intensity of physical forcing were important drivers of such variability, but the outcome in terms of species composition was highly dependent on the available local pool of species and the timing of those events in relation to the seasonal cycle. We conclude that duration, frequency and intensity of upwelling events, which vary seasonally and inter-annually, are paramount for maintaining long-term phytoplankton diversity likely by allowing unstable coexistence and incorporating species turnover at different scales. Our results contribute to the understanding of the complex mechanisms of coastal phytoplankton dynamics in

  15. Mean-periodic functions

    Directory of Open Access Journals (Sweden)

    Carlos A. Berenstein

    1980-01-01

    Full Text Available We show that any mean-periodic function f can be represented in terms of exponential-polynomial solutions of the same convolution equation f satisfies, i.e., u∗f=0(μ∈E′(ℝn. This extends to n-variables the work of L. Schwartz on mean-periodicity and also extends L. Ehrenpreis' work on partial differential equations with constant coefficients to arbitrary convolutors. We also answer a number of open questions about mean-periodic functions of one variable. The basic ingredient is our work on interpolation by entire functions in one and several complex variables.

  16. Evaluation of hematologic, blood gas, and select biochemical variables in ovine whole blood stored in CPDA-1 bags.

    Science.gov (United States)

    Sousa, Rejane S; Barrêto, Raimundo A; Sousa, Isadora K F; Chaves, Dowglish F; Soares, Herbert S; Barros, Isabella O; Minervino, Antonio H H; Ortolani, Enrico L

    2013-03-01

    The economic consequences from mortality of sheep after blood loss can be considerable. To date there are no reports addressing hematologic, blood gas, and biochemical changes in ovine blood stored in CPDA-1 bags. The aim of this study was to investigate hematologic, blood gas, and biochemical alterations resulting from storage of ovine blood in CPDA-1 bags to establish transfusion protocols in sheep. From each of 7 healthy 8-month-old sheep 450 mL of blood were collected into CPDA-1 bags and stored for 35 days in at 3-6°C. Samples were taken from the bags at days 0, 7, 14, 21, and 35. Whole blood was used to assess PCV, MCV, RBC count, pH, pO2 , pCO2 , and concentrations of bicarbonate, sodium, and lactate. Plasma was used to measure potassium, hemoglobin, and glucose concentrations. The PCV remained stable throughout the storage period, while plasma hemoglobin and MCV began to increase on days 7 and 21, respectively. The RBC count began to decrease on day 21. Blood pH decreased and pCO2 increased steadily throughout the storage period. Potassium concentration increased from 3.8 to 18.3 mmol/L on day 7 and remained high thereafter. In contrast, sodium concentration began to decrease on day 7. The results show that ovine blood undergoes hematologic, blood gas, and biochemical changes during storage. Further studies are required to establish RBC viability in CPDA-1 bags after a storage period of 35 days. © 2012 American Society for Veterinary Clinical Pathology.

  17. 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.

  18. 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.

  19. Population fluctuations of Pyrodinium bahamense and Ceratium furca (Dinophyceae in Laguna Grande, Puerto Rico, and environmental variables associated during a three-year period

    Directory of Open Access Journals (Sweden)

    Miguel P. Sastre

    2013-12-01

    Full Text Available Bioluminescent bays and lagoons are unique natural environments and popular tourist attractions. However, the bioluminescence in many of these water bodies has declined, principally due to anthropogenic activities. In the Caribbean, the bioluminescence in these bays and lagoons is mostly produced by the dinoflagellate Pyrodinium bahamense var. bahamense. Laguna Grande is one of the three year-round bioluminescent water bodies in Puerto Rico that are known to remain but P. bahamense var. bahamense density fluctuations have not been studied. In this study we describe water quality parameters and density fluctuations of the most common dinoflagellates in Laguna Grande, P. bahamense var. bahamense and Ceratium furca, over a three-year period. For this, three sampling stations were established in Laguna Grande from which water samples were collected in triplicate and analyzed for temperature, phosphates, nitrates, salinity, water transparency, fluorescence, and dinoflagellate densities, at the water surface and at 2m depth, from May 2003 to May 2006. The results showed a density fluctuation pattern for P. bahamense var. bahamense, where higher densities were observed mainly from April to September, and lower densities from October to February. Density fluctuations of C. furca were more erratic and a repetitive pattern was not observed. Densities of P. bahamense var. bahamense ranged from 0.48 to 90 978 cells/L and densities of C. furca ranged from 0 to 11 200 cells/L. The mean population density throughout the sampling period was significantly higher in P. bahamense var. bahamense (mean=18 958.5 cells/L than in C. furca (mean=2 601.9 cells/L. Population densities of P. bahamense var. bahamense were negatively correlated with C. furca densities during the first year of sampling; however, they were positively correlated during the third year. Non-significant differences between surface and 2m depth samples were observed for temperature

  20. 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 Focused Survey, 451 source-water samples and 744 field quality-control (QC) samples were collected from 78 ground-water, 39 reservoir and (or) lake, and 17 river and (or) stream source waters at fixed intervals for a period of 1 year.Using a common assessment level of 0.2 μg/L (micrograms per liter) (2.0 μg/L for methyl ethyl ketone), 37 of the 66 VOCs analyzed were detected in both surveys. However, VOCs, especially MTBE and other gasoline oxygenates, were detected more frequently in the Focused Survey than in the Random Survey. MTBE was detected in 55.5 percent of the CWSs sampled in the Focused Survey and in 8.7 percent of those sampled in the Random Survey. Little difference in occurrence, however, was observed for trihalomethanes (THMs), which were detected in 16.4 and 14.8 percent of Focused Survey and Random Survey CWSs, respectively. This may indicate a pervasive occurrence of THMs in several source-water types, regardless of CWS size or geographic location.Using data at or above the method detection limit to assess temporal variability and anthropogenic factors associated with frequent detection of select VOCs, concentrations in the Focused Survey in ground-water, reservoir, and river source waters were typically less than 1 μg/L. Also, at a 95-percent confidence interval, no statistically significant differences were observed in comparing concentrations in the first and second ground-water sample. A weak seasonal pattern was observed in samples collected from reservoirs and lakes where gasoline oxygenates and other gasoline compounds were detected more frequently during spring and summer, presumedly a result of increased use of motorized watercraft during these seasons. In contrast, seasonal patterns were not observed in samples collected from rivers and streams. The lack of seasonal differences in river and stream source waters sampled may indicate a common and continuous source of contamination.The most frequently detected VOC (MTBE) and the two

  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. 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...

  4. 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 t