Underestimated AMOC Variability and Implications for AMV and Predictability in CMIP Models

NASA Astrophysics Data System (ADS)

Yan, Xiaoqin; Zhang, Rong; Knutson, Thomas R.

2018-05-01

The Atlantic Meridional Overturning Circulation (AMOC) has profound impacts on various climate phenomena. Using both observations and simulations from the Coupled Model Intercomparison Project Phase 3 and 5, here we show that most models underestimate the amplitude of low-frequency AMOC variability. We further show that stronger low-frequency AMOC variability leads to stronger linkages between the AMOC and key variables associated with the Atlantic multidecadal variability (AMV), and between the subpolar AMV signal and northern hemisphere surface air temperature. Low-frequency extratropical northern hemisphere surface air temperature variability might increase with the amplitude of low-frequency AMOC variability. Atlantic decadal predictability is much higher in models with stronger low-frequency AMOC variability and much lower in models with weaker or without AMOC variability. Our results suggest that simulating realistic low-frequency AMOC variability is very important, both for simulating realistic linkages between AMOC and AMV-related variables and for achieving substantially higher Atlantic decadal predictability.

Hydraulics Graphics Package. Users Manual

DTIC Science & Technology

1985-11-01

ENTER: VARIABLE/SEPARATOR/VALUE OR STRING GLBL, TETON DAM FAILURE ENTER: VARIABLE/SEPARATOR/VALUE OR STRING SLOC ,DISCHARGE HISTOGRAM ENTER: VARIABLE...ENTER: VARIABLE/SEPARATOR/VALUE OR STRING YLBL,FLOW IN 1000 CFS ENTER: VARIABLE/SEPARATORVA LUE OR STRING GLBL, TETON DAM FAILURE ENTER: VARIABLE...SEPARATOR/VALUE OR STRING SECNO, 0 ENTER: VARIABLE/SEPARATOR/VALUE OR STRING GO 1ee0. F go L 0 U I Goo. 200. TETON DAM FAILUPE N\\ rLOIJ Alr 4wi. fiNT. I .I

Utilizing the AAVSO's Variable Star Index (VSX) In Undergraduate Research Projects

NASA Astrophysics Data System (ADS)

Larsen, Kristine

2016-01-01

Among the many important services that the American Association of Variable Star Observers (AAVSO) provides to the astronomical community is the Variable Star Index (VSX - https://www.aavso.org/vsx/). This online catalog of variable stars is the repository of data on over 334,000 variable stars, including information on spectral type, range of magnitude, period, and type of variable, among other properties. A number of these stars were identified as being variable through automated telescope surveys, such as ASAS (All Sky Automated Survey). The computer code of this survey classified newly discovered variables as best it could, but a significant number of false classifications have been noted. The reclassification of ASAS variables in the VSX data, as well as a closer look at variables identified as miscellaneous type in VSX, are two of many projects that can be undertaken by interested undergraduates. In doing so, students learn about the physical properties of various types of variable stars as well as statistical analysis and computer software, especially the VStar variable star data visualization and analysis tool that is available to the astronomical community free of charge on the AAVSO website (https://www.aavso.org/vstar-overview). Two such projects are described in this presentation, the first to identify BY Draconis variables erroneously classified as Cepheids in ASAS data, and the second to identify SRD semiregular variables misidentified as "miscellaneous" in VSX.

Canonical Measure of Correlation (CMC) and Canonical Measure of Distance (CMD) between sets of data. Part 3. Variable selection in classification.

PubMed

Ballabio, Davide; Consonni, Viviana; Mauri, Andrea; Todeschini, Roberto

2010-01-11

In multivariate regression and classification issues variable selection is an important procedure used to select an optimal subset of variables with the aim of producing more parsimonious and eventually more predictive models. Variable selection is often necessary when dealing with methodologies that produce thousands of variables, such as Quantitative Structure-Activity Relationships (QSARs) and highly dimensional analytical procedures. In this paper a novel method for variable selection for classification purposes is introduced. This method exploits the recently proposed Canonical Measure of Correlation between two sets of variables (CMC index). The CMC index is in this case calculated for two specific sets of variables, the former being comprised of the independent variables and the latter of the unfolded class matrix. The CMC values, calculated by considering one variable at a time, can be sorted and a ranking of the variables on the basis of their class discrimination capabilities results. Alternatively, CMC index can be calculated for all the possible combinations of variables and the variable subset with the maximal CMC can be selected, but this procedure is computationally more demanding and classification performance of the selected subset is not always the best one. The effectiveness of the CMC index in selecting variables with discriminative ability was compared with that of other well-known strategies for variable selection, such as the Wilks' Lambda, the VIP index based on the Partial Least Squares-Discriminant Analysis, and the selection provided by classification trees. A variable Forward Selection based on the CMC index was finally used in conjunction of Linear Discriminant Analysis. This approach was tested on several chemical data sets. Obtained results were encouraging.

Multiband Fourier Analysis and Interstellar Reddening of the Variable Stars in the Globular Cluster NGC 6402 (M14)

NASA Astrophysics Data System (ADS)

Weinschenk, Sedrick; Murphy, Brian; Villiger, Nathan J.

2018-01-01

We present a detailed study of the variable stars in the globular cluster NGC 6402 (M14). Approximately 1500 B and V band images were collected from July 2016 to August 2017 using the SARA Consortium Jacobus Kaptyen 1-meter telescope located in the Canary Islands. Using difference image analysis, we were able to identify 145 probable variable stars, confirming the 133 previously known variables and adding 12 new variables. The variables consisted of 117 RR Lyrae stars, 18 long period variables, 2 eclipsing variables, 6 Cepheid variables, and 2 SX Phoenix variables. Of the RR Lyrae variables 55 were of fundamental mode RR0 stars, of which 18 exhibited the Blazhko effect, 57 were of 1st overtone RR1, of which 7 appear to exhibit the Blazhko effect, 1 2nd overtone RR2, and 2 double mode variables. We found an average period of 0.59016 days for RR0 stars and 0.30294 days for RR1 stars. Using the multiband light curves of both the RR0 and RR1 variables we found an average E(B-V) of 0.604 with a scatter of 0.15 magnitudes. Using Fourier decomposition of the RR Lyrae light curves we also determined the metallicity and distance of the NGC 6402.

The ASAS-SN Catalog of Variable Stars I: The Serendipitous Survey

NASA Astrophysics Data System (ADS)

Jayasinghe, T.; Kochanek, C. S.; Stanek, K. Z.; Shappee, B. J.; Holoien, T. W.-S.; Thompson, Todd A.; Prieto, J. L.; Dong, Subo; Pawlak, M.; Shields, J. V.; Pojmanski, G.; Otero, S.; Britt, C. A.; Will, D.

2018-04-01

The All-Sky Automated Survey for Supernovae (ASAS-SN) is the first optical survey to routinely monitor the whole sky with a cadence of ˜2 - 3 days down to V≲ 17 mag. ASAS-SN has monitored the whole sky since 2014, collecting ˜100 - 500 epochs of observations per field. The V-band light curves for candidate variables identified during the search for supernovae are classified using a random forest classifier and visually verified. We present a catalog of 66,533 bright, new variable stars discovered during our search for supernovae, including 27,753 periodic variables and 38,780 irregular variables. V-band light curves for the ASAS-SN variables are available through the ASAS-SN variable stars database (https://asas-sn.osu.edu/variables). The database will begin to include the light curves of known variable stars in the near future along with the results for a systematic, all-sky variability survey.

Individual differences in the day-to-day variability of pain, fatigue, and well-being in patients with rheumatic disease: Associations with psychological variables

PubMed Central

Schneider, Stefan; Junghaenel, Doerte U.; Keefe, Francis J.; Schwartz, Joseph E.; Stone, Arthur A.; Broderick, Joan E.

2012-01-01

This paper examines day-to-day variability in rheumatology patients' ratings of pain and related quality-of-life variables as well as predictors of that variability. Data from two studies were used. The hypothesis was that greater psychological distress (i.e., depression and anxiety) and poorer coping appraisals (i.e., higher pain catastrophizing and lower self-efficacy) are associated with more variability. Electronic daily diary ratings were collected from 106 patients from a community rheumatology practice across 28 days (Study 1), and from 194 osteoarthritis patients across 7 days (Study 2). In multilevel modeling analyses, substantial day-to-day variability was evident for all variables in both studies, andindividual patients differed considerably and somewhat reliably in the magnitude of their variability. Higher levels of depression significantly predicted greater variability in pain, as well as in happiness and frustration (Study 1). Lower self-efficacy was associated with more variability in patients' daily satisfaction with accomplishments and in the quality of their day (Study 2). Greater pain catastrophizing and higher depression predicted more variability in interference with social relationships (Study 2). Anxiety was not significantly associated with day-to-day variability. The results of these studies suggest that individual differences in the magnitude of symptom fluctuation may play a vital role in understanding patients' adjustment to pain. Future research will be needed to examine the clinical utility of measuring variability in patients' pain and well being, and to understand whether reducing variability may be an important treatment target. PMID:22349917

A general theoretical framework for interpreting patient-reported outcomes estimated from ordinally scaled item responses.

PubMed

Massof, Robert W

2014-10-01

A simple theoretical framework explains patient responses to items in rating scale questionnaires. Fixed latent variables position each patient and each item on the same linear scale. Item responses are governed by a set of fixed category thresholds, one for each ordinal response category. A patient's item responses are magnitude estimates of the difference between the patient variable and the patient's estimate of the item variable, relative to his/her personally defined response category thresholds. Differences between patients in their personal estimates of the item variable and in their personal choices of category thresholds are represented by random variables added to the corresponding fixed variables. Effects of intervention correspond to changes in the patient variable, the patient's response bias, and/or latent item variables for a subset of items. Intervention effects on patients' item responses were simulated by assuming the random variables are normally distributed with a constant scalar covariance matrix. Rasch analysis was used to estimate latent variables from the simulated responses. The simulations demonstrate that changes in the patient variable and changes in response bias produce indistinguishable effects on item responses and manifest as changes only in the estimated patient variable. Changes in a subset of item variables manifest as intervention-specific differential item functioning and as changes in the estimated person variable that equals the average of changes in the item variables. Simulations demonstrate that intervention-specific differential item functioning produces inefficiencies and inaccuracies in computer adaptive testing. © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Two complementary approaches to quantify variability in heat resistance of spores of Bacillus subtilis.

PubMed

den Besten, Heidy M W; Berendsen, Erwin M; Wells-Bennik, Marjon H J; Straatsma, Han; Zwietering, Marcel H

2017-07-17

Realistic prediction of microbial inactivation in food requires quantitative information on variability introduced by the microorganisms. Bacillus subtilis forms heat resistant spores and in this study the impact of strain variability on spore heat resistance was quantified using 20 strains. In addition, experimental variability was quantified by using technical replicates per heat treatment experiment, and reproduction variability was quantified by using two biologically independent spore crops for each strain that were heat treated on different days. The fourth-decimal reduction times and z-values were estimated by a one-step and two-step model fitting procedure. Grouping of the 20 B. subtilis strains into two statistically distinguishable groups could be confirmed based on their spore heat resistance. The reproduction variability was higher than experimental variability, but both variabilities were much lower than strain variability. The model fitting approach did not significantly affect the quantification of variability. Remarkably, when strain variability in spore heat resistance was quantified using only the strains producing low-level heat resistant spores, then this strain variability was comparable with the previously reported strain variability in heat resistance of vegetative cells of Listeria monocytogenes, although in a totally other temperature range. Strains that produced spores with high-level heat resistance showed similar temperature range for growth as strains that produced low-level heat resistance. Strain variability affected heat resistance of spores most, and therefore integration of this variability factor in modelling of spore heat resistance will make predictions more realistic. Copyright © 2017. Published by Elsevier B.V.

How Variables Uncorrelated with the Dependent Variable Can Actually Make Excellent Predictors: The Important Suppressor Variable Case.

ERIC Educational Resources Information Center

Woolley, Kristin K.

Many researchers are unfamiliar with suppressor variables and how they operate in multiple regression analyses. This paper describes the role suppressor variables play in a multiple regression model and provides practical examples that explain how they can change research results. A variable that when added as another predictor increases the total…

On the explaining-away phenomenon in multivariate latent variable models.

PubMed

van Rijn, Peter; Rijmen, Frank

2015-02-01

Many probabilistic models for psychological and educational measurements contain latent variables. Well-known examples are factor analysis, item response theory, and latent class model families. We discuss what is referred to as the 'explaining-away' phenomenon in the context of such latent variable models. This phenomenon can occur when multiple latent variables are related to the same observed variable, and can elicit seemingly counterintuitive conditional dependencies between latent variables given observed variables. We illustrate the implications of explaining away for a number of well-known latent variable models by using both theoretical and real data examples. © 2014 The British Psychological Society.

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

PubMed

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/.

Spatial Variability of Trace Gases During DISCOVER-AQ: Planning for Geostationary Observations of Atmospheric Composition

NASA Technical Reports Server (NTRS)

Follette-Cook, Melanie B.; Pickering, K.; Crawford, J.; Appel, W.; Diskin, G.; Fried, A.; Loughner, C.; Pfister, G.; Weinheimer, A.

2015-01-01

Results from an in-depth analysis of trace gas variability in MD indicated that the variability in this region was large enough to be observable by a TEMPO-like instrument. The variability observed in MD is relatively similar to the other three campaigns with a few exceptions: CO variability in CA was much higher than in the other regions; HCHO variability in CA and CO was much lower; MD showed the lowest variability in NO2All model simulations do a reasonable job simulating O3 variability. For CO, the CACO simulations largely under over estimate the variability in the observations. The variability in HCHO is underestimated for every campaign. NO2 variability is slightly overestimated in MD, more so in CO. The TX simulation underestimates the variability in each trace gas. This is most likely due to missing emissions sources (C. Loughner, manuscript in preparation).Future Work: Where reasonable, we will use these model outputs to further explore the resolvability from space of these key trace gases using analyses of tropospheric column amounts relative to satellite precision requirements, similar to Follette-Cook et al. (2015).

Lexical and phonological variability in preschool children with speech sound disorder.

PubMed

Macrae, Toby; Tyler, Ann A; Lewis, Kerry E

2014-02-01

The authors of this study examined relationships between measures of word and speech error variability and between these and other speech and language measures in preschool children with speech sound disorder (SSD). In this correlational study, 18 preschool children with SSD, age-appropriate receptive vocabulary, and normal oral motor functioning and hearing were assessed across 2 sessions. Experimental measures included word and speech error variability, receptive vocabulary, nonword repetition (NWR), and expressive language. Pearson product–moment correlation coefficients were calculated among the experimental measures. The correlation between word and speech error variability was slight and nonsignificant. The correlation between word variability and receptive vocabulary was moderate and negative, although nonsignificant. High word variability was associated with small receptive vocabularies. The correlations between speech error variability and NWR and between speech error variability and the mean length of children's utterances were moderate and negative, although both were nonsignificant. High speech error variability was associated with poor NWR and language scores. High word variability may reflect unstable lexical representations, whereas high speech error variability may reflect indistinct phonological representations. Preschool children with SSD who show abnormally high levels of different types of speech variability may require slightly different approaches to intervention.

Variability in large-scale wind power generation: Variability in large-scale wind power generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kiviluoma, Juha; Holttinen, Hannele; Weir, David

2015-10-25

The paper demonstrates the characteristics of wind power variability and net load variability in multiple power systems based on real data from multiple years. Demonstrated characteristics include probability distribution for different ramp durations, seasonal and diurnal variability and low net load events. The comparison shows regions with low variability (Sweden, Spain and Germany), medium variability (Portugal, Ireland, Finland and Denmark) and regions with higher variability (Quebec, Bonneville Power Administration and Electric Reliability Council of Texas in North America; Gansu, Jilin and Liaoning in China; and Norway and offshore wind power in Denmark). For regions with low variability, the maximum 1more » h wind ramps are below 10% of nominal capacity, and for regions with high variability, they may be close to 30%. Wind power variability is mainly explained by the extent of geographical spread, but also higher capacity factor causes higher variability. It was also shown how wind power ramps are autocorrelated and dependent on the operating output level. When wind power was concentrated in smaller area, there were outliers with high changes in wind output, which were not present in large areas with well-dispersed wind power.« less

Independent variable complexity for regional regression of the flow duration curve in ungauged basins

NASA Astrophysics Data System (ADS)

Fouad, Geoffrey; Skupin, André; Hope, Allen

2016-04-01

The flow duration curve (FDC) is one of the most widely used tools to quantify streamflow. Its percentile flows are often required for water resource applications, but these values must be predicted for ungauged basins with insufficient or no streamflow data. Regional regression is a commonly used approach for predicting percentile flows that involves identifying hydrologic regions and calibrating regression models to each region. The independent variables used to describe the physiographic and climatic setting of the basins are a critical component of regional regression, yet few studies have investigated their effect on resulting predictions. In this study, the complexity of the independent variables needed for regional regression is investigated. Different levels of variable complexity are applied for a regional regression consisting of 918 basins in the US. Both the hydrologic regions and regression models are determined according to the different sets of variables, and the accuracy of resulting predictions is assessed. The different sets of variables include (1) a simple set of three variables strongly tied to the FDC (mean annual precipitation, potential evapotranspiration, and baseflow index), (2) a traditional set of variables describing the average physiographic and climatic conditions of the basins, and (3) a more complex set of variables extending the traditional variables to include statistics describing the distribution of physiographic data and temporal components of climatic data. The latter set of variables is not typically used in regional regression, and is evaluated for its potential to predict percentile flows. The simplest set of only three variables performed similarly to the other more complex sets of variables. Traditional variables used to describe climate, topography, and soil offered little more to the predictions, and the experimental set of variables describing the distribution of basin data in more detail did not improve predictions. These results are largely reflective of cross-correlation existing in hydrologic datasets, and highlight the limited predictive power of many traditionally used variables for regional regression. A parsimonious approach including fewer variables chosen based on their connection to streamflow may be more efficient than a data mining approach including many different variables. Future regional regression studies may benefit from having a hydrologic rationale for including different variables and attempting to create new variables related to streamflow.

Recent changes in county-level corn yield variability in the United States from observations and crop models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leng, Guoyong

The United States is responsible for 35% and 60% of global corn supply and exports. Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global food security. Important in this regard is to understand how corn yield variability has evolved geographically in the history and how it relates to climatic and non-climatic factors. Results showed that year-to-year variation of US corn yield has decreased significantly during 1980-2010, mainly in Midwest Corn Belt, Nebraska and western arid regions. Despite the country-scale decreasing variability, corn yield variability exhibited an increasing trend in South Dakota,more » Texas and Southeast growing regions, indicating the importance of considering spatial scales in estimating yield variability. The observed pattern is partly reproduced by process-based crop models, simulating larger areas experiencing increasing variability and underestimating the magnitude of decreasing variability. And 3 out of 11 models even produced a differing sign of change from observations. Hence, statistical model which produces closer agreement with observations is used to explore the contribution of climatic and non-climatic factors to the changes in yield variability. It is found that climate variability dominate the change trends of corn yield variability in the Midwest Corn Belt, while the ability of climate variability in controlling yield variability is low in southeastern and western arid regions. Irrigation has largely reduced the corn yield variability in regions (e.g. Nebraska) where separate estimates of irrigated and rain-fed corn yield exist, demonstrating the importance of non-climatic factors in governing the changes in corn yield variability. The results highlight the distinct spatial patterns of corn yield variability change as well as its influencing factors at the county scale. I also caution the use of process-based crop models, which have substantially underestimated the change trend of corn yield variability, in projecting its future changes.« less

High variability impairs motor learning regardless of whether it affects task performance.

PubMed

Cardis, Marco; Casadio, Maura; Ranganathan, Rajiv

2018-01-01

Motor variability plays an important role in motor learning, although the exact mechanisms of how variability affects learning are not well understood. Recent evidence suggests that motor variability may have different effects on learning in redundant tasks, depending on whether it is present in the task space (where it affects task performance) or in the null space (where it has no effect on task performance). We examined the effect of directly introducing null and task space variability using a manipulandum during the learning of a motor task. Participants learned a bimanual shuffleboard task for 2 days, where their goal was to slide a virtual puck as close as possible toward a target. Critically, the distance traveled by the puck was determined by the sum of the left- and right-hand velocities, which meant that there was redundancy in the task. Participants were divided into five groups, based on both the dimension in which the variability was introduced and the amount of variability that was introduced during training. Results showed that although all groups were able to reduce error with practice, learning was affected more by the amount of variability introduced rather than the dimension in which variability was introduced. Specifically, groups with higher movement variability during practice showed larger errors at the end of practice compared with groups that had low variability during learning. These results suggest that although introducing variability can increase exploration of new solutions, this may adversely affect the ability to retain the learned solution. NEW & NOTEWORTHY We examined the role of introducing variability during motor learning in a redundant task. The presence of redundancy allows variability to be introduced in different dimensions: the task space (where it affects task performance) or the null space (where it does not affect task performance). We found that introducing variability affected learning adversely, but the amount of variability was more critical than the dimension in which variability was introduced.

Variables in psychology: a critique of quantitative psychology.

PubMed

Toomela, Aaro

2008-09-01

Mind is hidden from direct observation; it can be studied only by observing behavior. Variables encode information about behaviors. There is no one-to-one correspondence between behaviors and mental events underlying the behaviors, however. In order to understand mind it would be necessary to understand exactly what information is represented in variables. This aim cannot be reached after variables are already encoded. Therefore, statistical data analysis can be very misleading in studies aimed at understanding mind that underlies behavior. In this article different kinds of information that can be represented in variables are described. It is shown how informational ambiguity of variables leads to problems of theoretically meaningful interpretation of the results of statistical data analysis procedures in terms of hidden mental processes. Reasons are provided why presence of dependence between variables does not imply causal relationship between events represented by variables and absence of dependence between variables cannot rule out the causal dependence of events represented by variables. It is concluded that variable-psychology has a very limited range of application for the development of a theory of mind-psychology.

Vulnerability in Determining the Cost of Information System Project to Avoid Loses

NASA Astrophysics Data System (ADS)

Haryono, Kholid; Ikhsani, Zulfa Amalia

2018-03-01

Context: This study discusses the priority of cost required in software development projects. Objectives: To show the costing models, the variables involved, and how practitioners assess and decide the priorities of each variable. To strengthen the information, each variable also confirmed the risk if ignored. Method: The method is done by two approaches. First, systematic literature reviews to find the models and variables used to decide the cost of software development. Second, confirm and take judgments about the level of importance and risk of each variable to the software developer. Result: Obtained about 54 variables that appear on the 10 models discussed. The variables are categorized into 15 groups based on the similarity of meaning. Each group becomes a variable. Confirmation results with practitioners on the level of importance and risk. It shown there are two variables that are considered very important and high risk if ignored. That is duration and effort. Conclusion: The relationship of variable rates between the results of literature studies and confirmation of practitioners contributes to the use of software business actors in considering project cost variables.

Cognitive Agility Measurement in a Complex Environment

DTIC Science & Technology

2017-04-01

correlate with their corresponding historical psychology tests? EEA3.1: Does the variable for Make Goal cognitive flexibility correlate with the...Stroop Test cognitive flexibility variable? EEA3.2: Does the variable for Make Goal cognitive openness correlate with the AUT cognitive openness...variable? EEA3.3: Does the variable for Make Goal focused attention correlate with the Go, No Go Paradigm focused attention variable? 1.6

Current Directions in Mediation Analysis

PubMed Central

MacKinnon, David P.; Fairchild, Amanda J.

2010-01-01

Mediating variables continue to play an important role in psychological theory and research. A mediating variable transmits the effect of an antecedent variable on to a dependent variable, thereby providing more detailed understanding of relations among variables. Methods to assess mediation have been an active area of research for the last two decades. This paper describes the current state of methods to investigate mediating variables. PMID:20157637

Causal relationship model between variables using linear regression to improve professional commitment of lecturer

NASA Astrophysics Data System (ADS)

Setyaningsih, S.

2017-01-01

The main element to build a leading university requires lecturer commitment in a professional manner. Commitment is measured through willpower, loyalty, pride, loyalty, and integrity as a professional lecturer. A total of 135 from 337 university lecturers were sampled to collect data. Data were analyzed using validity and reliability test and multiple linear regression. Many studies have found a link on the commitment of lecturers, but the basic cause of the causal relationship is generally neglected. These results indicate that the professional commitment of lecturers affected by variables empowerment, academic culture, and trust. The relationship model between variables is composed of three substructures. The first substructure consists of endogenous variables professional commitment and exogenous three variables, namely the academic culture, empowerment and trust, as well as residue variable ɛ y . The second substructure consists of one endogenous variable that is trust and two exogenous variables, namely empowerment and academic culture and the residue variable ɛ 3. The third substructure consists of one endogenous variable, namely the academic culture and exogenous variables, namely empowerment as well as residue variable ɛ 2. Multiple linear regression was used in the path model for each substructure. The results showed that the hypothesis has been proved and these findings provide empirical evidence that increasing the variables will have an impact on increasing the professional commitment of the lecturers.

Generating variable and random schedules of reinforcement using Microsoft Excel macros.

PubMed

Bancroft, Stacie L; Bourret, Jason C

2008-01-01

Variable reinforcement schedules are used to arrange the availability of reinforcement following varying response ratios or intervals of time. Random reinforcement schedules are subtypes of variable reinforcement schedules that can be used to arrange the availability of reinforcement at a constant probability across number of responses or time. Generating schedule values for variable and random reinforcement schedules can be difficult. The present article describes the steps necessary to write macros in Microsoft Excel that will generate variable-ratio, variable-interval, variable-time, random-ratio, random-interval, and random-time reinforcement schedule values.

Variable flexure-based fluid filter

DOEpatents

Brown, Steve B.; Colston, Jr., Billy W.; Marshall, Graham; Wolcott, Duane

2007-03-13

An apparatus and method for filtering particles from a fluid comprises a fluid inlet, a fluid outlet, a variable size passage between the fluid inlet and the fluid outlet, and means for adjusting the size of the variable size passage for filtering the particles from the fluid. An inlet fluid flow stream is introduced to a fixture with a variable size passage. The size of the variable size passage is set so that the fluid passes through the variable size passage but the particles do not pass through the variable size passage.

Clinical Trials With Large Numbers of Variables: Important Advantages of Canonical Analysis.

PubMed

Cleophas, Ton J

2016-01-01

Canonical analysis assesses the combined effects of a set of predictor variables on a set of outcome variables, but it is little used in clinical trials despite the omnipresence of multiple variables. The aim of this study was to assess the performance of canonical analysis as compared with traditional multivariate methods using multivariate analysis of covariance (MANCOVA). As an example, a simulated data file with 12 gene expression levels and 4 drug efficacy scores was used. The correlation coefficient between the 12 predictor and 4 outcome variables was 0.87 (P = 0.0001) meaning that 76% of the variability in the outcome variables was explained by the 12 covariates. Repeated testing after the removal of 5 unimportant predictor and 1 outcome variable produced virtually the same overall result. The MANCOVA identified identical unimportant variables, but it was unable to provide overall statistics. (1) Canonical analysis is remarkable, because it can handle many more variables than traditional multivariate methods such as MANCOVA can. (2) At the same time, it accounts for the relative importance of the separate variables, their interactions and differences in units. (3) Canonical analysis provides overall statistics of the effects of sets of variables, whereas traditional multivariate methods only provide the statistics of the separate variables. (4) Unlike other methods for combining the effects of multiple variables such as factor analysis/partial least squares, canonical analysis is scientifically entirely rigorous. (5) Limitations include that it is less flexible than factor analysis/partial least squares, because only 2 sets of variables are used and because multiple solutions instead of one is offered. We do hope that this article will stimulate clinical investigators to start using this remarkable method.

Power Supply for Variable Frequency Induction Heating Using MERS Soft-Switching High Frequency Inverter

NASA Astrophysics Data System (ADS)

Isobe, Takanori; Kitahara, Tadayuki; Fukutani, Kazuhiko; Shimada, Ryuichi

Variable frequency induction heating has great potential for industrial heating applications due to the possibility of achieving heating distribution control; however, large-scale induction heating with variable frequency has not yet been introduced for practical use. This paper proposes a high frequency soft-switching inverter for induction heating that can achieve variable frequency operation. One challenge of variable frequency induction heating is increasing power electronics ratings. This paper indicates that its current source type dc-link configuration and soft-switching characteristics can make it possible to build a large-scale system with variable frequency capability. A 90-kVA 150-1000Hz variable frequency experimental power supply for steel strip induction heating was developed. Experiments confirmed the feasibility of variable frequency induction heating with proposed converter and the advantages of variable frequency operation.

The variability puzzle in human memory.

PubMed

Kahana, Michael J; Aggarwal, Eash V; Phan, Tung D

2018-04-26

Memory performance exhibits a high level of variability from moment to moment. Much of this variability may reflect inadequately controlled experimental variables, such as word memorability, past practice and subject fatigue. Alternatively, stochastic variability in performance may largely reflect the efficiency of endogenous neural processes that govern memory function. To help adjudicate between these competing views, the authors conducted a multisession study in which subjects completed 552 trials of a delayed free-recall task. Applying a statistical model to predict variability in each subject's recall performance uncovered modest effects of word memorability, proactive interference, and other variables. In contrast to the limited explanatory power of these experimental variables, performance on the prior list strongly predicted current list recall. These findings suggest that endogenous factors underlying successful encoding and retrieval drive variability in performance. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Brain Signal Variability Differentially Affects Cognitive Flexibility and Cognitive Stability.

PubMed

Armbruster-Genç, Diana J N; Ueltzhöffer, Kai; Fiebach, Christian J

2016-04-06

Recent research yielded the intriguing conclusion that, in healthy adults, higher levels of variability in neuronal processes are beneficial for cognitive functioning. Beneficial effects of variability in neuronal processing can also be inferred from neurocomputational theories of working memory, albeit this holds only for tasks requiring cognitive flexibility. However, cognitive stability, i.e., the ability to maintain a task goal in the face of irrelevant distractors, should suffer under high levels of brain signal variability. To directly test this prediction, we studied both behavioral and brain signal variability during cognitive flexibility (i.e., task switching) and cognitive stability (i.e., distractor inhibition) in a sample of healthy human subjects and developed an efficient and easy-to-implement analysis approach to assess BOLD-signal variability in event-related fMRI task paradigms. Results show a general positive effect of neural variability on task performance as assessed by accuracy measures. However, higher levels of BOLD-signal variability in the left inferior frontal junction area result in reduced error rate costs during task switching and thus facilitate cognitive flexibility. In contrast, variability in the same area has a detrimental effect on cognitive stability, as shown in a negative effect of variability on response time costs during distractor inhibition. This pattern was mirrored at the behavioral level, with higher behavioral variability predicting better task switching but worse distractor inhibition performance. Our data extend previous results on brain signal variability by showing a differential effect of brain signal variability that depends on task context, in line with predictions from computational theories. Recent neuroscientific research showed that the human brain signal is intrinsically variable and suggested that this variability improves performance. Computational models of prefrontal neural networks predict differential effects of variability for different behavioral situations requiring either cognitive flexibility or stability. However, this hypothesis has so far not been put to an empirical test. In this study, we assessed cognitive flexibility and cognitive stability, and, besides a generally positive effect of neural variability on accuracy measures, we show that neural variability in a prefrontal brain area at the inferior frontal junction is differentially associated with performance: higher levels of variability are beneficial for the effectiveness of task switching (cognitive flexibility) but detrimental for the efficiency of distractor inhibition (cognitive stability). Copyright © 2016 the authors 0270-6474/16/363978-10$15.00/0.

The role of impulse parameters in force variability

NASA Technical Reports Server (NTRS)

Carlton, L. G.; Newell, K. M.

1986-01-01

One of the principle limitations of the human motor system is the ability to produce consistent motor responses. When asked to repeatedly make the same movement, performance outcomes are characterized by a considerable amount of variability. This occurs whether variability is expressed in terms of kinetics or kinematics. Variability in performance is of considerable importance because for tasks requiring accuracy it is a critical variable in determining the skill of the performer. What has long been sought is a description of the parameter or parameters that determine the degree of variability. Two general experimental protocals were used. One protocal is to use dynamic actions and record variability in kinematic parameters such as spatial or temporal error. A second strategy was to use isometric actions and record kinetic variables such as peak force produced. What might be the important force related factors affecting variability is examined and an experimental approach to examine the influence of each of these variables is provided.

The ASAS-SN catalogue of variable stars I: The Serendipitous Survey

NASA Astrophysics Data System (ADS)

Jayasinghe, T.; Kochanek, C. S.; Stanek, K. Z.; Shappee, B. J.; Holoien, T. W.-S.; Thompson, Toda A.; Prieto, J. L.; Dong, Subo; Pawlak, M.; Shields, J. V.; Pojmanski, G.; Otero, S.; Britt, C. A.; Will, D.

2018-07-01

The All-Sky Automated Survey for Supernovae (ASAS-SN) is the first optical survey to routinely monitor the whole sky with a cadence of ˜2-3 d down to V ≲ 17 mag. ASAS-SN has monitored the whole sky since 2014, collecting ˜100-500 epochs of observations per field. The V-band light curves for candidate variables identified during the search for supernovae are classified using a random forest classifier and visually verified. We present a catalogue of 66 179 bright, new variable stars discovered during our search for supernovae, including 27 479 periodic variables and 38 700 irregular variables. V-band light curves for the ASAS-SN variables are available through the ASAS-SN variable stars data base (https://asas-sn.osu.edu/variables). The data base will begin to include the light curves of known variable stars in the near future along with the results for a systematic, all-sky variability survey.

Analysis of the Relationship Between Climate and NDVI Variability at Global Scales

NASA Technical Reports Server (NTRS)

Zeng, Fan-Wei; Collatz, G. James; Pinzon, Jorge; Ivanoff, Alvaro

2011-01-01

interannual variability in modeled (CASA) C flux is in part caused by interannual variability in Normalized Difference Vegetation Index (NDVI) Fraction of Photosynthetically Active Radiation (FPAR). This study confirms a mechanism producing variability in modeled NPP: -- NDVI (FPAR) interannual variability is strongly driven by climate; -- The climate driven variability in NDVI (FPAR) can lead to much larger fluctuation in NPP vs. the NPP computed from FPAR climatology

Most Likely to Succeed: Exploring Predictor Variables for the Counselor Preparation Comprehensive Examination

ERIC Educational Resources Information Center

Hartwig, Elizabeth Kjellstrand; Van Overschelde, James P.

2016-01-01

The authors investigated predictor variables for the Counselor Preparation Comprehensive Examination (CPCE) to examine whether academic variables, demographic variables, and test version were associated with graduate counseling students' CPCE scores. Multiple regression analyses revealed all 3 variables were statistically significant predictors of…

Regression Analysis with Dummy Variables: Use and Interpretation.

ERIC Educational Resources Information Center

Hinkle, Dennis E.; Oliver, J. Dale

1986-01-01

Multiple regression analysis (MRA) may be used when both continuous and categorical variables are included as independent research variables. The use of MRA with categorical variables involves dummy coding, that is, assigning zeros and ones to levels of categorical variables. Caution is urged in results interpretation. (Author/CH)

Nutrient movement in a 104-year old soil fertility experiment

USDA-ARS?s Scientific Manuscript database

Alabama’s “Cullars Rotation” experiment (circa 1911) is the oldest, continuous soil fertility experiment in the southern U.S. Treatments include 5 K variables, P variables, S variables, soil pH variables and micronutrient variables in 14 treatments involving a 3-yr rotation of (1) cotton-winter legu...

Bayesian Adaptive Lasso for Ordinal Regression with Latent Variables

ERIC Educational Resources Information Center

Feng, Xiang-Nan; Wu, Hao-Tian; Song, Xin-Yuan

2017-01-01

We consider an ordinal regression model with latent variables to investigate the effects of observable and latent explanatory variables on the ordinal responses of interest. Each latent variable is characterized by correlated observed variables through a confirmatory factor analysis model. We develop a Bayesian adaptive lasso procedure to conduct…

Body temperature variability (Part 2): masking influences of body temperature variability and a review of body temperature variability in disease.

PubMed

Kelly, Gregory S

2007-03-01

This is the second of a two-part review on body temperature variability. Part 1 discussed historical and modern findings on average body temperatures. It also discussed endogenous sources of temperature variability, including variations caused by site of measurement; circadian, menstrual, and annual biological rhythms; fitness; and aging. Part 2 reviews the effects of exogenous masking agents - external factors in the environment, diet, or lifestyle that can be a significant source of body temperature variability. Body temperature variability findings in disease states are also reviewed.

Generating Variable and Random Schedules of Reinforcement Using Microsoft Excel Macros

PubMed Central

Bancroft, Stacie L; Bourret, Jason C

2008-01-01

Variable reinforcement schedules are used to arrange the availability of reinforcement following varying response ratios or intervals of time. Random reinforcement schedules are subtypes of variable reinforcement schedules that can be used to arrange the availability of reinforcement at a constant probability across number of responses or time. Generating schedule values for variable and random reinforcement schedules can be difficult. The present article describes the steps necessary to write macros in Microsoft Excel that will generate variable-ratio, variable-interval, variable-time, random-ratio, random-interval, and random-time reinforcement schedule values. PMID:18595286

Research related to variable sweep aircraft development

NASA Technical Reports Server (NTRS)

Polhamus, E. C.; Toll, T. A.

1981-01-01

Development in high speed, variable sweep aircraft research is reviewed. The 1946 Langley wind tunnel studies related to variable oblique and variable sweep wings and results from the X-5 and the XF1OF variable sweep aircraft are discussed. A joint program with the British, evaluation of the British "Swallow", development of the outboard pivot wing/aft tail configuration concept by Langley, and the applied research program that followed and which provided the technology for the current, variable sweep military aircraft is outlined. The relative state of variable sweep as a design option is also covered.

Influence of ECG sampling rate in fetal heart rate variability analysis.

PubMed

De Jonckheere, J; Garabedian, C; Charlier, P; Champion, C; Servan-Schreiber, E; Storme, L; Debarge, V; Jeanne, M; Logier, R

2017-07-01

Fetal hypoxia results in a fetal blood acidosis (pH<;7.10). In such a situation, the fetus develops several adaptation mechanisms regulated by the autonomic nervous system. Many studies demonstrated significant changes in heart rate variability in hypoxic fetuses. So, fetal heart rate variability analysis could be of precious help for fetal hypoxia prediction. Commonly used fetal heart rate variability analysis methods have been shown to be sensitive to the ECG signal sampling rate. Indeed, a low sampling rate could induce variability in the heart beat detection which will alter the heart rate variability estimation. In this paper, we introduce an original fetal heart rate variability analysis method. We hypothesize that this method will be less sensitive to ECG sampling frequency changes than common heart rate variability analysis methods. We then compared the results of this new heart rate variability analysis method with two different sampling frequencies (250-1000 Hz).

Change in the magnitude and mechanisms of global temperature variability with warming.

PubMed

Brown, Patrick T; Ming, Yi; Li, Wenhong; Hill, Spencer A

2017-01-01

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modeling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual preindustrial conditions may have only limited relevance for understanding the unforced GMST variability of the future.

Change in the Magnitude and Mechanisms of Global Temperature Variability with Warming

NASA Astrophysics Data System (ADS)

Brown, P. T.; Ming, Y.; Li, W.; Hill, S. A.

2017-12-01

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modeling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual preindustrial conditions may have only limited relevance for understanding the unforced GMST variability of the future.

Learning to visually perceive the relative mass of colliding balls in globally and locally constrained task ecologies.

PubMed

Jacobs, D M; Runeson, S; Michaels, C F

2001-10-01

Novice observers differ from each other in the kinematic variables they use for the perception of kinetic properties, but they converge on more useful variables after practice with feedback. The colliding-balls paradigm was used to investigate how the convergence depends on the relations between the candidate variables and the to-be-perceived property, relative mass. Experiment 1 showed that observers do not change in the variables they use if the variables with which they start allow accurate performance. Experiment 2 showed that, at least for some observers, convergence can be facilitated by reducing the correlations between commonly used nonspecifying variables and relative mass but not by keeping those variables constant. Experiments 3a and 3b further demonstrated that observers learn not to rely on a particular nonspecifying variable if the correlation between that variable and relative mass is reduced.

Variation in Plant Defense Suppresses Herbivore Performance.

PubMed

Pearse, Ian S; Paul, Ryan; Ode, Paul J

2018-06-18

Defensive variability of crops and natural systems can alter herbivore communities and reduce herbivory [1, 2]. However, it is still unknown how defense variability translates into herbivore suppression. Nonlinear averaging and constraints in physiological tracking (also more generally called time-dependent effects) are the two mechanisms by which defense variability might impact herbivores [3, 4]. We conducted a set of experiments manipulating the mean and variability of a plant defense, showing that defense variability does suppress herbivore performance and that it does so through physiological tracking effects that cannot be explained by nonlinear averaging. While nonlinear averaging predicted higher or the same herbivore performance on a variable defense than on an invariable defense, we show that variability actually decreased herbivore performance and population growth rate. Defense variability reduces herbivore performance in a way that is more than the average of its parts. This is consistent with constraints in physiological matching of detoxification systems for herbivores experiencing variable toxin levels in their diet and represents a more generalizable way of understanding the impacts of variability on herbivory [5]. Increasing defense variability in croplands at a scale encountered by individual herbivores can suppress herbivory, even if that is not anticipated by nonlinear averaging. Published by Elsevier Ltd.

Variation in plant defense suppresses herbivore performance

USGS Publications Warehouse

Pearse, Ian; Paul, Ryan; Ode, Paul J.

2018-01-01

Defensive variability of crops and natural systems can alter herbivore communities and reduce herbivory. However, it is still unknown how defense variability translates into herbivore suppression. Nonlinear averaging and constraints in physiological tracking (also more generally called time-dependent effects) are the two mechanisms by which defense variability might impact herbivores. We conducted a set of experiments manipulating the mean and variability of a plant defense, showing that defense variability does suppress herbivore performance and that it does so through physiological tracking effects that cannot be explained by nonlinear averaging. While nonlinear averaging predicted higher or the same herbivore performance on a variable defense than on an invariable defense, we show that variability actually decreased herbivore performance and population growth rate. Defense variability reduces herbivore performance in a way that is more than the average of its parts. This is consistent with constraints in physiological matching of detoxification systems for herbivores experiencing variable toxin levels in their diet and represents a more generalizable way of understanding the impacts of variability on herbivory. Increasing defense variability in croplands at a scale encountered by individual herbivores can suppress herbivory, even if that is not anticipated by nonlinear averaging.

Humidity: A review and primer on atmospheric moisture and human health.

PubMed

Davis, Robert E; McGregor, Glenn R; Enfield, Kyle B

2016-01-01

Research examining associations between weather and human health frequently includes the effects of atmospheric humidity. A large number of humidity variables have been developed for numerous purposes, but little guidance is available to health researchers regarding appropriate variable selection. We examine a suite of commonly used humidity variables and summarize both the medical and biometeorological literature on associations between humidity and human health. As an example of the importance of humidity variable selection, we correlate numerous hourly humidity variables to daily respiratory syncytial virus isolates in Singapore from 1992 to 1994. Most water-vapor mass based variables (specific humidity, absolute humidity, mixing ratio, dewpoint temperature, vapor pressure) exhibit comparable correlations. Variables that include a thermal component (relative humidity, dewpoint depression, saturation vapor pressure) exhibit strong diurnality and seasonality. Humidity variable selection must be dictated by the underlying research question. Despite being the most commonly used humidity variable, relative humidity should be used sparingly and avoided in cases when the proximity to saturation is not medically relevant. Care must be taken in averaging certain humidity variables daily or seasonally to avoid statistical biasing associated with variables that are inherently diurnal through their relationship to temperature. Copyright © 2015 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2008-04-01

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

Children's and adults' interpretation of covariation data: Does symmetry of variables matter?

PubMed

Saffran, Andrea; Barchfeld, Petra; Sodian, Beate; Alibali, Martha W

2016-10-01

In a series of 3 experiments, the authors investigated the influence of symmetry of variables on children's and adults' data interpretation. They hypothesized that symmetrical (i.e., present/present) variables would support correct interpretations more than asymmetrical (i.e., present/absent) variables. Participants were asked to judge covariation in a series of data sets presented in contingency tables and to justify their judgments. Participants in Experiments 1 and 2 were elementary school children (Experiment 1: n = 52 second graders, n = 44 fourth graders; Experiment 2: n = 50 second graders). Participants in Experiment 3 were adults (n = 62). In Experiment 1, children in the symmetrical variables condition performed better than those in the asymmetrical variables condition. Children in the symmetrical variables condition judged more data patterns correctly and they more frequently justified their choices by referring to the complete table. Experiment 2 ruled out the possibility that this effect was caused by differences in question format. Even when question format was held constant, second graders performed better with symmetrical variables. Experiment 3 showed that adults' data interpretation is also affected by symmetry of variables. Collectively, these results indicate that symmetry of variables affects interpretation of covariation data. The authors argue that symmetrical variables provide a context for meaningful comparison. With asymmetrical variables, the importance of the comparison is less salient. Thus, the symmetry of variables should be considered by researchers as well as educators. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Machine learning search for variable stars

NASA Astrophysics Data System (ADS)

Pashchenko, Ilya N.; Sokolovsky, Kirill V.; Gavras, Panagiotis

2018-04-01

Photometric variability detection is often considered as a hypothesis testing problem: an object is variable if the null hypothesis that its brightness is constant can be ruled out given the measurements and their uncertainties. The practical applicability of this approach is limited by uncorrected systematic errors. We propose a new variability detection technique sensitive to a wide range of variability types while being robust to outliers and underestimated measurement uncertainties. We consider variability detection as a classification problem that can be approached with machine learning. Logistic Regression (LR), Support Vector Machines (SVM), k Nearest Neighbours (kNN), Neural Nets (NN), Random Forests (RF), and Stochastic Gradient Boosting classifier (SGB) are applied to 18 features (variability indices) quantifying scatter and/or correlation between points in a light curve. We use a subset of Optical Gravitational Lensing Experiment phase two (OGLE-II) Large Magellanic Cloud (LMC) photometry (30 265 light curves) that was searched for variability using traditional methods (168 known variable objects) as the training set and then apply the NN to a new test set of 31 798 OGLE-II LMC light curves. Among 205 candidates selected in the test set, 178 are real variables, while 13 low-amplitude variables are new discoveries. The machine learning classifiers considered are found to be more efficient (select more variables and fewer false candidates) compared to traditional techniques using individual variability indices or their linear combination. The NN, SGB, SVM, and RF show a higher efficiency compared to LR and kNN.

An 'Observational Large Ensemble' to compare observed and modeled temperature trend uncertainty due to internal variability.

NASA Astrophysics Data System (ADS)

Poppick, A. N.; McKinnon, K. A.; Dunn-Sigouin, E.; Deser, C.

2017-12-01

Initial condition climate model ensembles suggest that regional temperature trends can be highly variable on decadal timescales due to characteristics of internal climate variability. Accounting for trend uncertainty due to internal variability is therefore necessary to contextualize recent observed temperature changes. However, while the variability of trends in a climate model ensemble can be evaluated directly (as the spread across ensemble members), internal variability simulated by a climate model may be inconsistent with observations. Observation-based methods for assessing the role of internal variability on trend uncertainty are therefore required. Here, we use a statistical resampling approach to assess trend uncertainty due to internal variability in historical 50-year (1966-2015) winter near-surface air temperature trends over North America. We compare this estimate of trend uncertainty to simulated trend variability in the NCAR CESM1 Large Ensemble (LENS), finding that uncertainty in wintertime temperature trends over North America due to internal variability is largely overestimated by CESM1, on average by a factor of 32%. Our observation-based resampling approach is combined with the forced signal from LENS to produce an 'Observational Large Ensemble' (OLENS). The members of OLENS indicate a range of spatially coherent fields of temperature trends resulting from different sequences of internal variability consistent with observations. The smaller trend variability in OLENS suggests that uncertainty in the historical climate change signal in observations due to internal variability is less than suggested by LENS.

Reward-Dependent Modulation of Movement Variability

PubMed Central

Izawa, Jun; Shadmehr, Reza

2015-01-01

Movement variability is often considered an unwanted byproduct of a noisy nervous system. However, variability can signal a form of implicit exploration, indicating that the nervous system is intentionally varying the motor commands in search of actions that yield the greatest success. Here, we investigated the role of the human basal ganglia in controlling reward-dependent motor variability as measured by trial-to-trial changes in performance during a reaching task. We designed an experiment in which the only performance feedback was success or failure and quantified how reach variability was modulated as a function of the probability of reward. In healthy controls, reach variability increased as the probability of reward decreased. Control of variability depended on the history of past rewards, with the largest trial-to-trial changes occurring immediately after an unrewarded trial. In contrast, in participants with Parkinson's disease, a known example of basal ganglia dysfunction, reward was a poor modulator of variability; that is, the patients showed an impaired ability to increase variability in response to decreases in the probability of reward. This was despite the fact that, after rewarded trials, reach variability in the patients was comparable to healthy controls. In summary, we found that movement variability is partially a form of exploration driven by the recent history of rewards. When the function of the human basal ganglia is compromised, the reward-dependent control of movement variability is impaired, particularly affecting the ability to increase variability after unsuccessful outcomes. PMID:25740529

Near-infrared Variability in the Orion Nebula Cluster

NASA Astrophysics Data System (ADS)

Rice, Thomas S.; Reipurth, Bo; Wolk, Scott J.; Vaz, Luiz Paulo; Cross, N. J. G.

2015-10-01

Using UKIRT on Mauna Kea, we have carried out a new near-infrared J, H, K monitoring survey of almost a square degree of the star-forming Orion Nebula Cluster with observations on 120 nights over three observing seasons, spanning a total of 894 days. We monitored ˜15,000 stars down to J≈ 20 using the WFCAM instrument, and have extracted 1203 significantly variable stars from our data. By studying variability in young stellar objects (YSOs) in the H - K, K color-magnitude diagram, we are able to distinguish between physical mechanisms of variability. Many variables show color behavior indicating either dust-extinction or disk/accretion activity, but we find that when monitored for longer periods of time, a number of stars shift between these two variability mechanisms. Further, we show that the intrinsic timescale of disk/accretion variability in young stars is longer than that of dust-extinction variability. We confirm that variability amplitude is statistically correlated with evolutionary class in all bands and colors. Our investigations of these 1203 variables have revealed 73 periodic AA Tau type variables, many large-amplitude and long-period (P\\gt 15 days) YSOs, including three stars showing widely spaced periodic brightening events consistent with circumbinary disk activity, and four new eclipsing binaries. These phenomena and others indicate the activity of long-term disk/accretion variability processes taking place in young stars. We have made the light curves and associated data for these 1203 variables available online.

Neural, electrophysiological and anatomical basis of brain-network variability and its characteristic changes in mental disorders.

PubMed

Zhang, Jie; Cheng, Wei; Liu, Zhaowen; Zhang, Kai; Lei, Xu; Yao, Ye; Becker, Benjamin; Liu, Yicen; Kendrick, Keith M; Lu, Guangming; Feng, Jianfeng

2016-08-01

SEE MATTAR ET AL DOI101093/AWW151 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Functional brain networks demonstrate significant temporal variability and dynamic reconfiguration even in the resting state. Currently, most studies investigate temporal variability of brain networks at the scale of single (micro) or whole-brain (macro) connectivity. However, the mechanism underlying time-varying properties remains unclear, as the coupling between brain network variability and neural activity is not readily apparent when analysed at either micro or macroscales. We propose an intermediate (meso) scale analysis and characterize temporal variability of the functional architecture associated with a particular region. This yields a topography of variability that reflects the whole-brain and, most importantly, creates an analytical framework to establish the fundamental relationship between variability of regional functional architecture and its neural activity or structural connectivity. We find that temporal variability reflects the dynamical reconfiguration of a brain region into distinct functional modules at different times and may be indicative of brain flexibility and adaptability. Primary and unimodal sensory-motor cortices demonstrate low temporal variability, while transmodal areas, including heteromodal association areas and limbic system, demonstrate the high variability. In particular, regions with highest variability such as hippocampus/parahippocampus, inferior and middle temporal gyrus, olfactory gyrus and caudate are all related to learning, suggesting that the temporal variability may indicate the level of brain adaptability. With simultaneously recorded electroencephalography/functional magnetic resonance imaging and functional magnetic resonance imaging/diffusion tensor imaging data, we also find that variability of regional functional architecture is modulated by local blood oxygen level-dependent activity and α-band oscillation, and is governed by the ratio of intra- to inter-community structural connectivity. Application of the mesoscale variability measure to multicentre datasets of three mental disorders and matched controls involving 1180 subjects reveals that those regions demonstrating extreme, i.e. highest/lowest variability in controls are most liable to change in mental disorders. Specifically, we draw attention to the identification of diametrically opposing patterns of variability changes between schizophrenia and attention deficit hyperactivity disorder/autism. Regions of the default-mode network demonstrate lower variability in patients with schizophrenia, but high variability in patients with autism/attention deficit hyperactivity disorder, compared with respective controls. In contrast, subcortical regions, especially the thalamus, show higher variability in schizophrenia patients, but lower variability in patients with attention deficit hyperactivity disorder. The changes in variability of these regions are also closely related to symptom scores. Our work provides insights into the dynamic organization of the resting brain and how it changes in brain disorders. The nodal variability measure may also be potentially useful as a predictor for learning and neural rehabilitation. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Postural reconfiguration and cycle-to-cycle variability in patients with work-related musculoskeletal disorders compared to healthy controls and in relation to pain emerging during a repetitive movement task.

PubMed

Longo, Alessia; Meulenbroek, Ruud; Haid, Thomas; Federolf, Peter

2018-05-01

Movement variability in sustained repetitive tasks is an important factor in the context of work-related musculoskeletal disorders. While a popular hypothesis suggests that movement variability can prevent overuse injuries, pain evolving during task execution may also cause variability. The aim of the current study was to investigate, first, differences in movement behavior between volunteers with and without work-related pain and, second, the influence of emerging pain on movement variability. Upper-body 3D kinematics were collected as 22 subjects with musculoskeletal disorders and 19 healthy volunteers performed a bimanual repetitive tapping task with a self-chosen and a given rhythm. Three subgroups were formed within the patient group according to the level of pain the participants experienced during the task. Principal component analysis was applied to 30 joint angle coordinates to characterize in a combined analysis the movement variability associated with reconfigurations of the volunteers' postures and the cycle-to-cycle variability that occurred during the execution of the task. Patients with no task-related pain showed lower cycle-to-cycle variability compared to healthy controls. Findings also indicated an increase in movement variability as pain emerged, manifesting both as frequent postural changes and large cycle-to-cycle variability. The findings suggested a relationship between work-related musculoskeletal disorders and movement variability but further investigation is needed on this issue. Additionally, the findings provided clear evidence that pain increased motor variability. Postural reconfigurations and cycle-to-cycle variability should be considered jointly when investigating movement variability and musculoskeletal disorders. Copyright © 2018 Elsevier Ltd. All rights reserved.

Optimization of a GO2/GH2 Swirl Coaxial Injector Element

NASA Technical Reports Server (NTRS)

Tucker, P. Kevin; Shyy, Wei; Vaidyanathan, Rajkumar

1999-01-01

An injector optimization methodology, method i, is used to investigate optimal design points for a gaseous oxygen/gaseous hydrogen (GO2/GH2) swirl coaxial injector element. The element is optimized in terms of design variables such as fuel pressure drop, DELTA P(sub f), oxidizer pressure drop, DELTA P(sub 0) combustor length, L(sub comb), and full cone swirl angle, theta, for a given mixture ratio and chamber pressure. Dependent variables such as energy release efficiency, ERE, wall heat flux, Q(sub w) injector heat flux, Q(sub inj), relative combustor weight, W(sub rel), and relative injector cost, C(sub rel), are calculated and then correlated with the design variables. An empirical design methodology is used to generate these responses for 180 combinations of input variables. Method i is then used to generate response surfaces for each dependent variable. Desirability functions based on dependent variable constraints are created and used to facilitate development of composite response surfaces representing some, or all, of the five dependent variables in terms of the input variables. Two examples illustrating the utility and flexibility of method i are discussed in detail. First, joint response surfaces are constructed by sequentially adding dependent variables. Optimum designs are identified after addition of each variable and the effect each variable has on the design is shown. This stepwise demonstration also highlights the importance of including variables such as weight and cost early in the design process. Secondly, using the composite response surface that includes all five dependent variables, unequal weights are assigned to emphasize certain variables relative to others. Here, method i is used to enable objective trade studies on design issues such as component life and thrust to weight ratio.

Hierarchical Synthesis of Coastal Ecosystem Health Indicators at Karimunjawa National Marine Park

NASA Astrophysics Data System (ADS)

Danu Prasetya, Johan; Ambariyanto; Supriharyono; Purwanti, Frida

2018-02-01

The coastal ecosystem of Karimunjawa National Marine Park (KNMP) is facing various pressures, including from human activity. Monitoring the health condition of coastal ecosystems periodically is needed as an evaluation of the ecosystem condition. Systematic and consistent indicators are needed in monitoring of coastal ecosystem health. This paper presents hierarchical synthesis of coastal ecosystem health indicators using Analytic Hierarchy Process (AHP) method. Hierarchical synthesis is obtained from process of weighting by paired comparison based on expert judgments. The variables of coastal ecosystem health indicators in this synthesis consist of 3 level of variable, i.e. main variable, sub-variable and operational variable. As a result of assessment, coastal ecosystem health indicators consist of 3 main variables, i.e. State of Ecosystem, Pressure and Management. Main variables State of Ecosystem and Management obtain the same value i.e. 0.400, while Pressure value was 0.200. Each main variable consist of several sub-variable, i.e. coral reef, reef fish, mangrove and seagrass for State of Ecosystem; fisheries and marine tourism activity for Pressure; planning and regulation, institutional and also infrastructure and financing for Management. The highest value of sub-variable of main variable State of Ecosystem, Pressure and Management were coral reef (0.186); marine tourism pressure (0.133) and institutional (0.171), respectively. The highest value of operational variable of main variable State of Ecosystem, Pressure and Management were percent of coral cover (0.058), marine tourism pressure (0.133) and presence of zonation plan, regulation also socialization of monitoring program (0.53), respectively. Potential pressure from marine tourism activity is the variable that most affect the health of the ecosystem. The results of this research suggest that there is a need to develop stronger conservation strategies to facing with pressures from marine tourism activities.

The Viewing Geometry of Brown Dwarfs Influences Their Observed Colors and Variability Amplitudes

NASA Astrophysics Data System (ADS)

Vos, Johanna M.; Allers, Katelyn N.; Biller, Beth A.

2017-06-01

In this paper we study the full sample of known Spitzer [3.6 μm] and J-band variable brown dwarfs. We calculate the rotational velocities, v\\sin I, of 16 variable brown dwarfs using archival Keck NIRSPEC data and compute the inclination angles of 19 variable brown dwarfs. The results obtained show that all objects in the sample with mid-IR variability detections are inclined at an angle > 20^\\circ , while all objects in the sample displaying J-band variability have an inclination angle > 35^\\circ . J-band variability appears to be more affected by inclination than Spitzer [3.6 μm] variability, and is strongly attenuated at lower inclinations. Since J-band observations probe deeper into the atmosphere than mid-IR observations, this effect may be due to the increased atmospheric path length of J-band flux at lower inclinations. We find a statistically significant correlation between the color anomaly and inclination of our sample, where field objects viewed equator-on appear redder than objects viewed at lower inclinations. Considering the full sample of known variable L, T, and Y spectral type objects in the literature, we find that the variability properties of the two bands display notably different trends that are due to both intrinsic differences between bands and the sensitivity of ground-based versus space-based searches. However, in both bands we find that variability amplitude may reach a maximum at ˜7-9 hr periods. Finally, we find a strong correlation between color anomaly and variability amplitude for both the J-band and mid-IR variability detections, where redder objects display higher variability amplitudes.

On measuring bird habitat: influence of observer variability and sample size

Treesearch

William M. Block; Kimberly A. With; Michael L. Morrison

1987-01-01

We studied the effects of observer variability when estimating vegetation characteristics at 75 0.04-ha bird plots. Observer estimates were significantly different for 31 of 49 variables. Multivariate analyses showed significant interobserver differences for five of the seven classes of variables studied. Variable classes included the height, number, and diameter of...

An evaluation of FIA's stand age variable

Treesearch

John D. Shaw

2015-01-01

The Forest Inventory and Analysis Database (FIADB) includes a large number of measured and computed variables. The definitions of measured variables are usually well-documented in FIA field and database manuals. Some computed variables, such as live basal area of the condition, are equally straightforward. Other computed variables, such as individual tree volume,...

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

ERIC Educational Resources Information Center

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…

When Can Information from Ordinal Scale Variables Be Integrated?

ERIC Educational Resources Information Center

Kemp, Simon; Grace, Randolph C.

2010-01-01

Many theoretical constructs of interest to psychologists are multidimensional and derive from the integration of several input variables. We show that input variables that are measured on ordinal scales cannot be combined to produce a stable weakly ordered output variable that allows trading off the input variables. Instead a partial order is…

Variable Stars Observed in the Galactic Disk by AST3-1 from Dome A, Antarctica

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Lingzhi; Ma, Bin; Hu, Yi

AST3-1 is the second-generation wide-field optical photometric telescope dedicated to time-domain astronomy at Dome A, Antarctica. Here, we present the results of an i -band images survey from AST3-1 toward one Galactic disk field. Based on time-series photometry of 92,583 stars, 560 variable stars were detected with i magnitude ≤16.5 mag during eight days of observations; 339 of these are previously unknown variables. We tentatively classify the 560 variables as 285 eclipsing binaries (EW, EB, and EA), 27 pulsating variable stars ( δ Scuti, γ Doradus, δ Cephei variable, and RR Lyrae stars), and 248 other types of variables (unclassifiedmore » periodic, multiperiodic, and aperiodic variable stars). Of the eclipsing binaries, 34 show O’Connell effects. One of the aperiodic variables shows a plateau light curve and another variable shows a secondary maximum after peak brightness. We also detected a complex binary system with an RS CVn-like light-curve morphology; this object is being followed-up spectroscopically using the Gemini South telescope.« less

Variable Selection in the Presence of Missing Data: Imputation-based Methods.

PubMed

Zhao, Yize; Long, Qi

2017-01-01

Variable selection plays an essential role in regression analysis as it identifies important variables that associated with outcomes and is known to improve predictive accuracy of resulting models. Variable selection methods have been widely investigated for fully observed data. However, in the presence of missing data, methods for variable selection need to be carefully designed to account for missing data mechanisms and statistical techniques used for handling missing data. Since imputation is arguably the most popular method for handling missing data due to its ease of use, statistical methods for variable selection that are combined with imputation are of particular interest. These methods, valid used under the assumptions of missing at random (MAR) and missing completely at random (MCAR), largely fall into three general strategies. The first strategy applies existing variable selection methods to each imputed dataset and then combine variable selection results across all imputed datasets. The second strategy applies existing variable selection methods to stacked imputed datasets. The third variable selection strategy combines resampling techniques such as bootstrap with imputation. Despite recent advances, this area remains under-developed and offers fertile ground for further research.

Can statistical linkage of missing variables reduce bias in treatment effect estimates in comparative effectiveness research studies?

PubMed

Crown, William; Chang, Jessica; Olson, Melvin; Kahler, Kristijan; Swindle, Jason; Buzinec, Paul; Shah, Nilay; Borah, Bijan

2015-09-01

Missing data, particularly missing variables, can create serious analytic challenges in observational comparative effectiveness research studies. Statistical linkage of datasets is a potential method for incorporating missing variables. Prior studies have focused upon the bias introduced by imperfect linkage. This analysis uses a case study of hepatitis C patients to estimate the net effect of statistical linkage on bias, also accounting for the potential reduction in missing variable bias. The results show that statistical linkage can reduce bias while also enabling parameter estimates to be obtained for the formerly missing variables. The usefulness of statistical linkage will vary depending upon the strength of the correlations of the missing variables with the treatment variable, as well as the outcome variable of interest.

VizieR Online Data Catalog: AAVSO International Variable Star Index VSX (Watson+, 2006-2014)

NASA Astrophysics Data System (ADS)

Watson, C.; Henden, A. A.; Price, A.

2017-05-01

This file contains Galactic stars known or suspected to be variable. It lists all stars that have an entry in the AAVSO International Variable Star Index (VSX; http://www.aavso.org/vsx). The database consisted initially of the General Catalogue of Variable Stars (GCVS) and the New Catalogue of Suspected Variables (NSV) and was then supplemented with a large number of variable star catalogues, as well as individual variable star discoveries or variables found in the literature. Effort has also been invested to update the entries with the latest information regarding position, type and period and to remove duplicates. The VSX database is being continually updated and maintained. For historical reasons some objects outside of the Galaxy have been included. (3 data files).

The spanning set indicates that variability during the stance period of running is affected by footwear.

PubMed

Kurz, Max J; Stergiou, Nicholas

2003-04-01

Sensory information the foot receives appears to be related to kinematic variability. Since footwear material densities affect sensory information, footwear may be an important factor that dictates variability. This study hypothesized that modifications in footwear would result in changes in kinematic variability during the running stance period. Subjects ran on a treadmill for three conditions: hard shoe, soft shoe and barefoot. The spanning sets of the mean ensemble curves of the knee and ankle changes for each condition were used to define variability. Variability was significantly larger in the barefoot condition in comparison with the two footwear conditions for both joints. These results suggest that variability can be affected by peripheral sensory information. The spanning set methodology can be utilized to examine changes in variability.

Clustering of Variables for Mixed Data

NASA Astrophysics Data System (ADS)

Saracco, J.; Chavent, M.

2016-05-01

This chapter presents clustering of variables which aim is to lump together strongly related variables. The proposed approach works on a mixed data set, i.e. on a data set which contains numerical variables and categorical variables. Two algorithms of clustering of variables are described: a hierarchical clustering and a k-means type clustering. A brief description of PCAmix method (that is a principal component analysis for mixed data) is provided, since the calculus of the synthetic variables summarizing the obtained clusters of variables is based on this multivariate method. Finally, the R packages ClustOfVar and PCAmixdata are illustrated on real mixed data. The PCAmix and ClustOfVar approaches are first used for dimension reduction (step 1) before applying in step 2 a standard clustering method to obtain groups of individuals.

VizieR Online Data Catalog: AAVSO International Variable Star Index VSX (Watson+, 2006-2014)

NASA Astrophysics Data System (ADS)

Watson, C.; Henden, A. A.; Price, A.

2018-05-01

This file contains Galactic stars known or suspected to be variable. It lists all stars that have an entry in the AAVSO International Variable Star Index (VSX; http://www.aavso.org/vsx). The database consisted initially of the General Catalogue of Variable Stars (GCVS) and the New Catalogue of Suspected Variables (NSV) and was then supplemented with a large number of variable star catalogues, as well as individual variable star discoveries or variables found in the literature. Effort has also been invested to update the entries with the latest information regarding position, type and period and to remove duplicates. The VSX database is being continually updated and maintained. For historical reasons some objects outside of the Galaxy have been included. (3 data files).

The EPOCH Project. I. Periodic variable stars in the EROS-2 LMC database

NASA Astrophysics Data System (ADS)

Kim, Dae-Won; Protopapas, Pavlos; Bailer-Jones, Coryn A. L.; Byun, Yong-Ik; Chang, Seo-Won; Marquette, Jean-Baptiste; Shin, Min-Su

2014-06-01

The EPOCH (EROS-2 periodic variable star classification using machine learning) project aims to detect periodic variable stars in the EROS-2 light curve database. In this paper, we present the first result of the classification of periodic variable stars in the EROS-2 LMC database. To classify these variables, we first built a training set by compiling known variables in the Large Magellanic Cloud area from the OGLE and MACHO surveys. We crossmatched these variables with the EROS-2 sources and extracted 22 variability features from 28 392 light curves of the corresponding EROS-2 sources. We then used the random forest method to classify the EROS-2 sources in the training set. We designed the model to separate not only δ Scuti stars, RR Lyraes, Cepheids, eclipsing binaries, and long-period variables, the superclasses, but also their subclasses, such as RRab, RRc, RRd, and RRe for RR Lyraes, and similarly for the other variable types. The model trained using only the superclasses shows 99% recall and precision, while the model trained on all subclasses shows 87% recall and precision. We applied the trained model to the entire EROS-2 LMC database, which contains about 29 million sources, and found 117 234 periodic variable candidates. Out of these 117 234 periodic variables, 55 285 have not been discovered by either OGLE or MACHO variability studies. This set comprises 1906 δ Scuti stars, 6607 RR Lyraes, 638 Cepheids, 178 Type II Cepheids, 34 562 eclipsing binaries, and 11 394 long-period variables. catalog of these EROS-2 LMC periodic variable stars is available at http://stardb.yonsei.ac.kr and at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/566/A43

An outline of graphical Markov models in dentistry.

PubMed

Helfenstein, U; Steiner, M; Menghini, G

1999-12-01

In the usual multiple regression model there is one response variable and one block of several explanatory variables. In contrast, in reality there may be a block of several possibly interacting response variables one would like to explain. In addition, the explanatory variables may split into a sequence of several blocks, each block containing several interacting variables. The variables in the second block are explained by those in the first block; the variables in the third block by those in the first and the second block etc. During recent years methods have been developed allowing analysis of problems where the data set has the above complex structure. The models involved are called graphical models or graphical Markov models. The main result of an analysis is a picture, a conditional independence graph with precise statistical meaning, consisting of circles representing variables and lines or arrows representing significant conditional associations. The absence of a line between two circles signifies that the corresponding two variables are independent conditional on the presence of other variables in the model. An example from epidemiology is presented in order to demonstrate application and use of the models. The data set in the example has a complex structure consisting of successive blocks: the variable in the first block is year of investigation; the variables in the second block are age and gender; the variables in the third block are indices of calculus, gingivitis and mutans streptococci and the final response variables in the fourth block are different indices of caries. Since the statistical methods may not be easily accessible to dentists, this article presents them in an introductory form. Graphical models may be of great value to dentists in allowing analysis and visualisation of complex structured multivariate data sets consisting of a sequence of blocks of interacting variables and, in particular, several possibly interacting responses in the final block.

Optimization of a GO2/GH2 Impinging Injector Element

NASA Technical Reports Server (NTRS)

Tucker, P. Kevin; Shyy, Wei; Vaidyanathan, Rajkumar

2001-01-01

An injector optimization methodology, method i, is used to investigate optimal design points for a gaseous oxygen/gaseous hydrogen (GO2/GH2) impinging injector element. The unlike impinging element, a fuel-oxidizer- fuel (F-O-F) triplet, is optimized in terms of design variables such as fuel pressure drop, (Delta)P(sub f), oxidizer pressure drop, (Delta)P(sub o), combustor length, L(sub comb), and impingement half-angle, alpha, for a given mixture ratio and chamber pressure. Dependent variables such as energy release efficiency, ERE, wall heat flux, Q(sub w), injector heat flux, Q(sub inj), relative combustor weight, W(sub rel), and relative injector cost, C(sub rel), are calculated and then correlated with the design variables. An empirical design methodology is used to generate these responses for 163 combinations of input variables. Method i is then used to generate response surfaces for each dependent variable. Desirability functions based on dependent variable constraints are created and used to facilitate development of composite response surfaces representing some, or all, of the five dependent variables in terms of the input variables. Three examples illustrating the utility and flexibility of method i are discussed in detail. First, joint response surfaces are constructed by sequentially adding dependent variables. Optimum designs are identified after addition of each variable and the effect each variable has on the design is shown. This stepwise demonstration also highlights the importance of including variables such as weight and cost early in the design process. Secondly, using the composite response surface which includes all five dependent variables, unequal weights are assigned to emphasize certain variables relative to others. Here, method i is used to enable objective trade studies on design issues such as component life and thrust to weight ratio. Finally, specific variable weights are further increased to illustrate the high marginal cost of realizing the last increment of injector performance and thruster weight.

Lumbar kinematic variability during gait in chronic low back pain and associations with pain, disability and isolated lumbar extension strength.

PubMed

Steele, James; Bruce-Low, Stewart; Smith, Dave; Jessop, David; Osborne, Neil

2014-12-01

Chronic low back pain is a multifactorial condition with many dysfunctions including gait variability. The lumbar spine and its musculature are involved during gait and in chronic low back pain the lumbar extensors are often deconditioned. It was therefore of interest to examine relationships between lumbar kinematic variability during gait, with pain, disability and isolated lumbar extension strength in participants with chronic low back pain. Twenty four participants with chronic low back pain were assessed for lumbar kinematics during gait, isolated lumbar extension strength, pain, and disability. Angular displacement and kinematic waveform pattern and offset variability were examined. Angular displacement and kinematic waveform pattern and offset variability differed across movement planes; displacement was highest and similar in frontal and transverse planes, and pattern variability and offset variability higher in the sagittal plane compared to frontal and transverse planes which were similar. Spearman's correlations showed significant correlations between transverse plane pattern variability and isolated lumbar extension strength (r=-.411) and disability (r=.401). However, pain was not correlated with pattern variability in any plane. The r(2) values suggested 80.5% to 86.3% of variance was accounted for by other variables. Considering the lumbar extensors role in gait, the relationship between both isolated lumbar extension strength and disability with transverse plane pattern variability suggests that gait variability may result in consequence of lumbar extensor deconditioning or disability accompanying chronic low back pain. However, further study should examine the temporality of these relationships and other variables might account for the unexplained variance. Copyright © 2014 Elsevier Ltd. All rights reserved.

Variable Selection through Correlation Sifting

NASA Astrophysics Data System (ADS)

Huang, Jim C.; Jojic, Nebojsa

Many applications of computational biology require a variable selection procedure to sift through a large number of input variables and select some smaller number that influence a target variable of interest. For example, in virology, only some small number of viral protein fragments influence the nature of the immune response during viral infection. Due to the large number of variables to be considered, a brute-force search for the subset of variables is in general intractable. To approximate this, methods based on ℓ1-regularized linear regression have been proposed and have been found to be particularly successful. It is well understood however that such methods fail to choose the correct subset of variables if these are highly correlated with other "decoy" variables. We present a method for sifting through sets of highly correlated variables which leads to higher accuracy in selecting the correct variables. The main innovation is a filtering step that reduces correlations among variables to be selected, making the ℓ1-regularization effective for datasets on which many methods for variable selection fail. The filtering step changes both the values of the predictor variables and output values by projections onto components obtained through a computationally-inexpensive principal components analysis. In this paper we demonstrate the usefulness of our method on synthetic datasets and on novel applications in virology. These include HIV viral load analysis based on patients' HIV sequences and immune types, as well as the analysis of seasonal variation in influenza death rates based on the regions of the influenza genome that undergo diversifying selection in the previous season.

Operator’s Manual for Variable Weight, Variable C.G. Helmet Simulator

DTIC Science & Technology

1981-09-01

fdoestify by block nufber) - A variable weight, variable CG helmet simulator has been designed to measure the effect of US Army headgear on muscle...any variable weights in the boxes, is 2.5 lb, slightly less than the weight of most quality crash helmets made by reputable manufacturers. The addition...of variable weights to the boxes can alter the center of gravity to simulate the effect of equipment attached to the out- side of a helmet. The

Affected States Soft Independent Modeling by Class Analogy from the Relation Between Independent Variables, Number of Independent Variables and Sample Size

PubMed Central

Kanık, Emine Arzu; Temel, Gülhan Orekici; Erdoğan, Semra; Kaya, İrem Ersöz

2013-01-01

Objective: The aim of study is to introduce method of Soft Independent Modeling of Class Analogy (SIMCA), and to express whether the method is affected from the number of independent variables, the relationship between variables and sample size. Study Design: Simulation study. Material and Methods: SIMCA model is performed in two stages. In order to determine whether the method is influenced by the number of independent variables, the relationship between variables and sample size, simulations were done. Conditions in which sample sizes in both groups are equal, and where there are 30, 100 and 1000 samples; where the number of variables is 2, 3, 5, 10, 50 and 100; moreover where the relationship between variables are quite high, in medium level and quite low were mentioned. Results: Average classification accuracy of simulation results which were carried out 1000 times for each possible condition of trial plan were given as tables. Conclusion: It is seen that diagnostic accuracy results increase as the number of independent variables increase. SIMCA method is a method in which the relationship between variables are quite high, the number of independent variables are many in number and where there are outlier values in the data that can be used in conditions having outlier values. PMID:25207065

Does ecosystem variability explain phytoplankton diversity? Solving an ecological puzzle with long-term data sets

NASA Astrophysics Data System (ADS)

Sarker, Subrata; Lemke, Peter; Wiltshire, Karen H.

2018-05-01

Explaining species diversity as a function of ecosystem variability is a long-term discussion in community-ecology research. Here, we aimed to establish a causal relationship between ecosystem variability and phytoplankton diversity in a shallow-sea ecosystem. We used long-term data on biotic and abiotic factors from Helgoland Roads, along with climate data to assess the effect of ecosystem variability on phytoplankton diversity. A point cumulative semi-variogram method was used to estimate the long-term ecosystem variability. A Markov chain model was used to estimate dynamical processes of species i.e. occurrence, absence and outcompete probability. We identified that the 1980s was a period of high ecosystem variability while the last two decades were comparatively less variable. Ecosystem variability was found as an important predictor of phytoplankton diversity at Helgoland Roads. High diversity was related to low ecosystem variability due to non-significant relationship between probability of a species occurrence and absence, significant negative relationship between probability of a species occurrence and probability of a species to be outcompeted by others, and high species occurrence at low ecosystem variability. Using an exceptional marine long-term data set, this study established a causal relationship between ecosystem variability and phytoplankton diversity.

Costs of solar and wind power variability for reducing CO2 emissions.

PubMed

Lueken, Colleen; Cohen, Gilbert E; Apt, Jay

2012-09-04

We compare the power output from a year of electricity generation data from one solar thermal plant, two solar photovoltaic (PV) arrays, and twenty Electric Reliability Council of Texas (ERCOT) wind farms. The analysis shows that solar PV electricity generation is approximately one hundred times more variable at frequencies on the order of 10(-3) Hz than solar thermal electricity generation, and the variability of wind generation lies between that of solar PV and solar thermal. We calculate the cost of variability of the different solar power sources and wind by using the costs of ancillary services and the energy required to compensate for its variability and intermittency, and the cost of variability per unit of displaced CO(2) emissions. We show the costs of variability are highly dependent on both technology type and capacity factor. California emissions data were used to calculate the cost of variability per unit of displaced CO(2) emissions. Variability cost is greatest for solar PV generation at $8-11 per MWh. The cost of variability for solar thermal generation is $5 per MWh, while that of wind generation in ERCOT was found to be on average $4 per MWh. Variability adds ~$15/tonne CO(2) to the cost of abatement for solar thermal power, $25 for wind, and $33-$40 for PV.

Affected States soft independent modeling by class analogy from the relation between independent variables, number of independent variables and sample size.

PubMed

Kanık, Emine Arzu; Temel, Gülhan Orekici; Erdoğan, Semra; Kaya, Irem Ersöz

2013-03-01

The aim of study is to introduce method of Soft Independent Modeling of Class Analogy (SIMCA), and to express whether the method is affected from the number of independent variables, the relationship between variables and sample size. Simulation study. SIMCA model is performed in two stages. In order to determine whether the method is influenced by the number of independent variables, the relationship between variables and sample size, simulations were done. Conditions in which sample sizes in both groups are equal, and where there are 30, 100 and 1000 samples; where the number of variables is 2, 3, 5, 10, 50 and 100; moreover where the relationship between variables are quite high, in medium level and quite low were mentioned. Average classification accuracy of simulation results which were carried out 1000 times for each possible condition of trial plan were given as tables. It is seen that diagnostic accuracy results increase as the number of independent variables increase. SIMCA method is a method in which the relationship between variables are quite high, the number of independent variables are many in number and where there are outlier values in the data that can be used in conditions having outlier values.

Periodic and Aperiodic Variability in the Molecular Cloud ρ Ophiuchus

NASA Astrophysics Data System (ADS)

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

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 Ks -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 ΔKs -band amplitudes from 0.044 to 2.31 mag and Δ(J - Ks ) 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 Ks 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 could be identified for these variable stars.

A Detailed Survey of Pulsating Variables in Five Globular Clusters (Abstract)

NASA Astrophysics Data System (ADS)

Murphy, B. W.

2016-12-01

(Abstract only) Globular clusters are ideal laboratories for conducting a stellar census. Of particular interest are pulsating variables, which provide astronomers with a tool to probe the properties of the stars and the cluster. We observed each of five globular clusters hundreds to thousands of times over a time span ranging from 2 to 4 years in B, V, and I filters using the SARA 0.6-meter telescope located at Cerro Tololo Interamerican Observatory and the 0.9-meter telescope located at Kitt Peak, Arizona. The images were analyzed using difference image analysis to identify and produce light curves of all variables found in each cluster. In total we identified 377 variables with 140 of these being newly discovered increasing the number of known variables stars in these clusters by 60%. Of the total we have identified 319 RR Lyrae variables (193 RR0, 18 RR01, 101 RR1, 7 RR2), 9 SX Phe stars, 5 Cepheid variables, 11 eclipsing variables, and 33 long period variables. For IC4499 we identified 64 RR0, 18 RR01, 14 RR1, 4 RR2, 1 SX Phe, 1 eclipsing binary, and 2 long period variables. For NGC4833 we identified 10 RR0, 7 RR1, 3 RR2, 6 SX Phe, 5 eclipsing binaries, and 9 long period variables. For NGC6171 (M107) we identified 14 RR0, 7 RR1, and 1 SX Phe. For NGC6402 (M14) we identified 55 RR0, 57 RR1, 1 RR2, 1 SX Phe, 6 Cepheids, 1 eclipsing binary, and 15 long period variables. For NGC6584 we identified 50 RR0, 16 RR1, 4 eclipsing binaries, and 7 long period variables. From our extensive data set we were able to obtain sufficient temporal and complete phase coverage of the RR Lyrae variables. This has allowed us not only to properly classify each of the RR Lyrae variables but also to use Fourier decomposition of the B, V, and I light curves to further analyze the properties of the variable stars and hence the physical properties of each globular cluster.

Variable Pitch Propellers

NASA Technical Reports Server (NTRS)

1920-01-01

In this report are described four different types of propellers which appeared at widely separated dates, but which were exhibited together at the last Salon de l'Aeronautique. The four propellers are the Chaviere variable pitch propeller, the variable pitch propeller used on the Clement Bayard dirigible, the variable pitch propeller used on Italian dirigibles, and the Levasseur variable pitch propeller.

Relating brain signal variability to knowledge representation.

PubMed

Heisz, Jennifer J; Shedden, Judith M; McIntosh, Anthony R

2012-11-15

We assessed the hypothesis that brain signal variability is a reflection of functional network reconfiguration during memory processing. In the present experiments, we use multiscale entropy to capture the variability of human electroencephalogram (EEG) while manipulating the knowledge representation associated with faces stored in memory. Across two experiments, we observed increased variability as a function of greater knowledge representation. In Experiment 1, individuals with greater familiarity for a group of famous faces displayed more brain signal variability. In Experiment 2, brain signal variability increased with learning after multiple experimental exposures to previously unfamiliar faces. The results demonstrate that variability increases with face familiarity; cognitive processes during the perception of familiar stimuli may engage a broader network of regions, which manifests as higher complexity/variability in spatial and temporal domains. In addition, effects of repetition suppression on brain signal variability were observed, and the pattern of results is consistent with a selectivity model of neural adaptation. Crown Copyright © 2012. Published by Elsevier Inc. All rights reserved.

All varieties of encoding variability are not created equal: Separating variable processing from variable tasks

PubMed Central

Huff, Mark J.; Bodner, Glen E.

2014-01-01

Whether encoding variability facilitates memory is shown to depend on whether item-specific and relational processing are both performed across study blocks, and whether study items are weakly versus strongly related. Variable-processing groups studied a word list once using an item-specific task and once using a relational task. Variable-task groups’ two different study tasks recruited the same type of processing each block. Repeated-task groups performed the same study task each block. Recall and recognition were greatest in the variable-processing group, but only with weakly related lists. A variable-processing benefit was also found when task-based processing and list-type processing were complementary (e.g., item-specific processing of a related list) rather than redundant (e.g., relational processing of a related list). That performing both item-specific and relational processing across trials, or within a trial, yields encoding-variability benefits may help reconcile decades of contradictory findings in this area. PMID:25018583

Variability in reaction time performance of younger and older adults.

PubMed

Hultsch, David F; MacDonald, Stuart W S; Dixon, Roger A

2002-03-01

Age differences in three basic types of variability were examined: variability between persons (diversity), variability within persons across tasks (dispersion), and variability within persons across time (inconsistency). Measures of variability were based on latency performance from four measures of reaction time (RT) performed by a total of 99 younger adults (ages 17--36 years) and 763 older adults (ages 54--94 years). Results indicated that all three types of variability were greater in older compared with younger participants even when group differences in speed were statistically controlled. Quantile-quantile plots showed age and task differences in the shape of the inconsistency distributions. Measures of within-person variability (dispersion and inconsistency) were positively correlated. Individual differences in RT inconsistency correlated negatively with level of performance on measures of perceptual speed, working memory, episodic memory, and crystallized abilities. Partial set correlation analyses indicated that inconsistency predicted cognitive performance independent of level of performance. The results indicate that variability of performance is an important indicator of cognitive functioning and aging.

CAN'T MISS--conquer any number task by making important statistics simple. Part 1. Types of variables, mean, median, variance, and standard deviation.

PubMed

Hansen, John P

2003-01-01

Healthcare quality improvement professionals need to understand and use inferential statistics to interpret sample data from their organizations. In quality improvement and healthcare research studies all the data from a population often are not available, so investigators take samples and make inferences about the population by using inferential statistics. This three-part series will give readers an understanding of the concepts of inferential statistics as well as the specific tools for calculating confidence intervals for samples of data. This article, Part 1, presents basic information about data including a classification system that describes the four major types of variables: continuous quantitative variable, discrete quantitative variable, ordinal categorical variable (including the binomial variable), and nominal categorical variable. A histogram is a graph that displays the frequency distribution for a continuous variable. The article also demonstrates how to calculate the mean, median, standard deviation, and variance for a continuous variable.

Change in the magnitude and mechanisms of global temperature variability with warming

PubMed Central

Brown, Patrick T.; Ming, Yi; Li, Wenhong; Hill, Spencer A.

2017-01-01

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modeling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual preindustrial conditions may have only limited relevance for understanding the unforced GMST variability of the future. PMID:29391875

Natural trophic variability in a large, oligotrophic, near-pristine lake

USGS Publications Warehouse

Young, Talia; Jensen, Olaf P.; Weidel, Brian C.; Chandra, Sudeep

2015-01-01

Conclusions drawn from stable isotope data can be limited by an incomplete understanding of natural isotopic variability over time and space. We quantified spatial and temporal variability in fish carbon and nitrogen stable isotopes in Lake Hövsgöl, Mongolia, a large, remote, oligotrophic lake with an unusually species-poor fish community. The fish community demonstrated a high degree of trophic level overlap. Variability in δ13C was inversely related to littoral-benthic dependence, with pelagic species demonstrating more δ13C variability than littoral-benthic species. A mixed effects model suggested that space (sampling location) had a greater impact than time (collection year) on both δ13C and δ15N variability. The observed variability in Lake Hövsgöl was generally greater than isotopic variability documented in other large, oligotrophic lakes, similar to isotopic shifts attributed to introduced species, and less than isotopic shifts attributed to anthropogenic chemical changes such as eutrophication. This work complements studies on isotopic variability and changes in other lakes around the world.

The Subaru/XMM-Newton Deep Survey (SXDS). V. Optically Faint Variable Object Survey

NASA Astrophysics Data System (ADS)

Morokuma, Tomoki; Doi, Mamoru; Yasuda, Naoki; Akiyama, Masayuki; Sekiguchi, Kazuhiro; Furusawa, Hisanori; Ueda, Yoshihiro; Totani, Tomonori; Oda, Takeshi; Nagao, Tohru; Kashikawa, Nobunari; Murayama, Takashi; Ouchi, Masami; Watson, Mike G.; Richmond, Michael W.; Lidman, Christopher; Perlmutter, Saul; Spadafora, Anthony L.; Aldering, Greg; Wang, Lifan; Hook, Isobel M.; Knop, Rob A.

2008-03-01

We present our survey for optically faint variable objects using multiepoch (8-10 epochs over 2-4 years) i'-band imaging data obtained with Subaru Suprime-Cam over 0.918 deg2 in the Subaru/XMM-Newton Deep Field (SXDF). We found 1040 optically variable objects by image subtraction for all the combinations of images at different epochs. This is the first statistical sample of variable objects at depths achieved with 8-10 m class telescopes or the Hubble Space Telescope. The detection limit for variable components is i'vari ~ 25.5 mag. These variable objects were classified into variable stars, supernovae (SNe), and active galactic nuclei (AGNs), based on the optical morphologies, magnitudes, colors, and optical-mid-infrared colors of the host objects, spatial offsets of variable components from the host objects, and light curves. Detection completeness was examined by simulating light curves for periodic and irregular variability. We detected optical variability for 36% +/- 2% (51% +/- 3% for a bright sample with i' < 24.4 mag) of X-ray sources in the field. Number densities of variable objects as functions of time intervals Δ t and variable component magnitudes i'vari are obtained. Number densities of variable stars, SNe, and AGNs are 120, 489, and 579 objects deg-2, respectively. Bimodal distributions of variable stars in the color-magnitude diagrams indicate that the variable star sample consists of bright (V ~ 22 mag) blue variable stars of the halo population and faint (V ~ 23.5 mag) red variable stars of the disk population. There are a few candidates of RR Lyrae providing a possible number density of ~10-2 kpc-3 at a distance of >150 kpc from the Galactic center. Based in part on data collected at Subaru Telescope, which is operated by the National Astronomical Observatory of Japan. Based on observations (program GN-2002B-Q-30) obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (US), the Particle Physics and Astronomy Research Council (UK), the National Research Council (Canada), CONICYT (Chile), the Australian Research Council (Australia), CNPq (Brazil), and CONICET (Argentina).

Using structural equation modeling to investigate relationships among ecological variables

USGS Publications Warehouse

Malaeb, Z.A.; Kevin, Summers J.; Pugesek, B.H.

2000-01-01

Structural equation modeling is an advanced multivariate statistical process with which a researcher can construct theoretical concepts, test their measurement reliability, hypothesize and test a theory about their relationships, take into account measurement errors, and consider both direct and indirect effects of variables on one another. Latent variables are theoretical concepts that unite phenomena under a single term, e.g., ecosystem health, environmental condition, and pollution (Bollen, 1989). Latent variables are not measured directly but can be expressed in terms of one or more directly measurable variables called indicators. For some researchers, defining, constructing, and examining the validity of latent variables may be the end task of itself. For others, testing hypothesized relationships of latent variables may be of interest. We analyzed the correlation matrix of eleven environmental variables from the U.S. Environmental Protection Agency's (USEPA) Environmental Monitoring and Assessment Program for Estuaries (EMAP-E) using methods of structural equation modeling. We hypothesized and tested a conceptual model to characterize the interdependencies between four latent variables-sediment contamination, natural variability, biodiversity, and growth potential. In particular, we were interested in measuring the direct, indirect, and total effects of sediment contamination and natural variability on biodiversity and growth potential. The model fit the data well and accounted for 81% of the variability in biodiversity and 69% of the variability in growth potential. It revealed a positive total effect of natural variability on growth potential that otherwise would have been judged negative had we not considered indirect effects. That is, natural variability had a negative direct effect on growth potential of magnitude -0.3251 and a positive indirect effect mediated through biodiversity of magnitude 0.4509, yielding a net positive total effect of 0.1258. Natural variability had a positive direct effect on biodiversity of magnitude 0.5347 and a negative indirect effect mediated through growth potential of magnitude -0.1105 yielding a positive total effects of magnitude 0.4242. Sediment contamination had a negative direct effect on biodiversity of magnitude -0.1956 and a negative indirect effect on growth potential via biodiversity of magnitude -0.067. Biodiversity had a positive effect on growth potential of magnitude 0.8432, and growth potential had a positive effect on biodiversity of magnitude 0.3398. The correlation between biodiversity and growth potential was estimated at 0.7658 and that between sediment contamination and natural variability at -0.3769.

Radio variability in complete samples of extragalactic radio sources at 1.4 GHz

NASA Astrophysics Data System (ADS)

Rys, S.; Machalski, J.

1990-09-01

Complete samples of extragalactic radio sources obtained in 1970-1975 and the sky survey of Condon and Broderick (1983) were used to select sources variable at 1.4 GHz, and to investigate the characteristics of variability in the whole population of sources at this frequency. The radio structures, radio spectral types, and optical identifications of the selected variables are discussed. Only compact flat-spectrum sources vary at 1.4 GHz, and all but four are identified with QSOs, BL Lacs, or other (unconfirmed spectroscopically) stellar objects. No correlation of degree of variability at 1.4 GHz with Galactic latitude or variability at 408 MHz has been found, suggesting that most of the 1.4-GHz variability is intrinsic and not caused by refractive scintillations. Numerical models of the variability have been computed.

Intraindividual variability in physical and emotional functioning: comparison of adults with traumatic brain injuries and healthy adults.

PubMed

Burton, Catherine L; Hultsch, David F; Strauss, Esther; Hunter, Michael A

2002-08-01

Recent research has shown that individuals with certain neurological conditions demonstrate greater intraindividual variability on cognitive tasks compared to healthy controls. The present study investigated intraindividual variability in the domains of physical functioning and affect/stress in three groups: adults with mild head injuries, adults with moderate/severe head injuries, and healthy adults. Participants were assessed on 10 occasions and results indicated that (a) individuals with head injuries demonstrated greater variability in dominant finger dexterity and right grip strength than the healthy controls; (b) increased variability tended to be associated with poorer performance/report both within and across tasks; and (c) increased variability on one task was associated with increased variability on other tasks. The findings suggest that increased variability in physical function, as well as cognitive function, represents an indicator of neurological compromise.

Evaluation of Kurtosis into the product of two normally distributed variables

NASA Astrophysics Data System (ADS)

Oliveira, Amílcar; Oliveira, Teresa; Seijas-Macías, Antonio

2016-06-01

Kurtosis (κ) is any measure of the "peakedness" of a distribution of a real-valued random variable. We study the evolution of the Kurtosis for the product of two normally distributed variables. Product of two normal variables is a very common problem for some areas of study, like, physics, economics, psychology, … Normal variables have a constant value for kurtosis (κ = 3), independently of the value of the two parameters: mean and variance. In fact, the excess kurtosis is defined as κ- 3 and the Normal Distribution Kurtosis is zero. The product of two normally distributed variables is a function of the parameters of the two variables and the correlation between then, and the range for kurtosis is in [0, 6] for independent variables and in [0, 12] when correlation between then is allowed.

Accounting for Parcel-Allocation Variability in Practice: Combining Sources of Uncertainty and Choosing the Number of Allocations.

PubMed

Sterba, Sonya K; Rights, Jason D

2016-01-01

Item parceling remains widely used under conditions that can lead to parcel-allocation variability in results. Hence, researchers may be interested in quantifying and accounting for parcel-allocation variability within sample. To do so in practice, three key issues need to be addressed. First, how can we combine sources of uncertainty arising from sampling variability and parcel-allocation variability when drawing inferences about parameters in structural equation models? Second, on what basis can we choose the number of repeated item-to-parcel allocations within sample? Third, how can we diagnose and report proportions of total variability per estimate arising due to parcel-allocation variability versus sampling variability? This article addresses these three methodological issues. Developments are illustrated using simulated and empirical examples, and software for implementing them is provided.

Sub-daily Statistical Downscaling of Meteorological Variables Using Neural Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Jitendra; Brooks, Bjørn-Gustaf J.; Thornton, Peter E

2012-01-01

A new open source neural network temporal downscaling model is described and tested using CRU-NCEP reanal ysis and CCSM3 climate model output. We downscaled multiple meteorological variables in tandem from monthly to sub-daily time steps while also retaining consistent correlations between variables. We found that our feed forward, error backpropagation approach produced synthetic 6 hourly meteorology with biases no greater than 0.6% across all variables and variance that was accurate within 1% for all variables except atmospheric pressure, wind speed, and precipitation. Correlations between downscaled output and the expected (original) monthly means exceeded 0.99 for all variables, which indicates thatmore » this approach would work well for generating atmospheric forcing data consistent with mass and energy conserved GCM output. Our neural network approach performed well for variables that had correlations to other variables of about 0.3 and better and its skill was increased by downscaling multiple correlated variables together. Poor replication of precipitation intensity however required further post-processing in order to obtain the expected probability distribution. The concurrence of precipitation events with expected changes in sub ordinate variables (e.g., less incident shortwave radiation during precipitation events) were nearly as consistent in the downscaled data as in the training data with probabilities that differed by no more than 6%. Our downscaling approach requires training data at the target time step and relies on a weak assumption that climate variability in the extrapolated data is similar to variability in the training data.« less

Impact of Reconstruction Algorithms on CT Radiomic Features of Pulmonary Tumors: Analysis of Intra- and Inter-Reader Variability and Inter-Reconstruction Algorithm Variability.

PubMed

Kim, Hyungjin; Park, Chang Min; Lee, Myunghee; Park, Sang Joon; Song, Yong Sub; Lee, Jong Hyuk; Hwang, Eui Jin; Goo, Jin Mo

2016-01-01

To identify the impact of reconstruction algorithms on CT radiomic features of pulmonary tumors and to reveal and compare the intra- and inter-reader and inter-reconstruction algorithm variability of each feature. Forty-two patients (M:F = 19:23; mean age, 60.43±10.56 years) with 42 pulmonary tumors (22.56±8.51mm) underwent contrast-enhanced CT scans, which were reconstructed with filtered back projection and commercial iterative reconstruction algorithm (level 3 and 5). Two readers independently segmented the whole tumor volume. Fifteen radiomic features were extracted and compared among reconstruction algorithms. Intra- and inter-reader variability and inter-reconstruction algorithm variability were calculated using coefficients of variation (CVs) and then compared. Among the 15 features, 5 first-order tumor intensity features and 4 gray level co-occurrence matrix (GLCM)-based features showed significant differences (p<0.05) among reconstruction algorithms. As for the variability, effective diameter, sphericity, entropy, and GLCM entropy were the most robust features (CV≤5%). Inter-reader variability was larger than intra-reader or inter-reconstruction algorithm variability in 9 features. However, for entropy, homogeneity, and 4 GLCM-based features, inter-reconstruction algorithm variability was significantly greater than inter-reader variability (p<0.013). Most of the radiomic features were significantly affected by the reconstruction algorithms. Inter-reconstruction algorithm variability was greater than inter-reader variability for entropy, homogeneity, and GLCM-based features.

Blood Pressure Variability and Cognitive Function Among Older African Americans: Introducing a New Blood Pressure Variability Measure.

PubMed

Tsang, Siny; Sperling, Scott A; Park, Moon Ho; Helenius, Ira M; Williams, Ishan C; Manning, Carol

2017-09-01

Although blood pressure (BP) variability has been reported to be associated with cognitive impairment, whether this relationship affects African Americans has been unclear. We sought correlations between systolic and diastolic BP variability and cognitive function in community-dwelling older African Americans, and introduced a new BP variability measure that can be applied to BP data collected in clinical practice. We assessed cognitive function in 94 cognitively normal older African Americans using the Mini-Mental State Examination (MMSE) and the Computer Assessment of Mild Cognitive Impairment (CAMCI). We used BP measurements taken at the patients' three most recent primary care clinic visits to generate three traditional BP variability indices, range, standard deviation, and coefficient of variation, plus a new index, random slope, which accounts for unequal BP measurement intervals within and across patients. MMSE scores did not correlate with any of the BP variability indices. Patients with greater diastolic BP variability were less accurate on the CAMCI verbal memory and incidental memory tasks. Results were similar across the four BP variability indices. In a sample of cognitively intact older African American adults, BP variability did not correlate with global cognitive function, as measured by the MMSE. However, higher diastolic BP variability correlated with poorer verbal and incidental memory. By accounting for differences in BP measurement intervals, our new BP variability index may help alert primary care physicians to patients at particular risk for cognitive decline.

Optical photometric variable stars towards the Galactic H II region NGC 2282

NASA Astrophysics Data System (ADS)

Dutta, Somnath; Mondal, Soumen; Joshi, Santosh; Jose, Jessy; Das, Ramkrishna; Ghosh, Supriyo

2018-05-01

We report here CCD I-band time series photometry of a young (2-5 Myr) cluster NGC 2282, in order to identify and understand the variability of pre-main-sequence (PMS) stars. The I-band photometry, down to ˜20.5 mag, enables us to probe the variability towards the lower mass end (˜0.1 M⊙) of PMS stars. From the light curves of 1627 stars, we identified 62 new photometric variable candidates. Their association with the region was established from H α emission and infrared (IR) excess. Among 62 variables, 30 young variables exhibit H α emission, near-IR (NIR)/mid-IR (MIR) excess or both and are candidate members of the cluster. Out of 62 variables, 41 are periodic variables, with a rotation rate ranging from 0.2-7 d. The period distribution exhibits a median period at ˜1 d, as in many young clusters (e.g. NGC 2264, ONC, etc.), but it follows a unimodal distribution, unlike others that have bimodality, with slow rotators peaking at ˜6-8 d. To investigate the rotation-disc and variability-disc connection, we derived the NIR excess from Δ(I - K) and the MIR excess from Spitzer [3.6]-[4.5] μm data. No conclusive evidence of slow rotation with the presence of discs around stars and fast rotation for discless stars is obtained from our periodic variables. A clear increasing trend of the variability amplitude with IR excess is found for all variables.

A Detailed Study of the Variable Stars in Five Galactic Globular Clusters: IC4499, NGC4833, NGC6171 (M107), NGC6402 (M14), and NGC6584

NASA Astrophysics Data System (ADS)

Murphy, Brian W.; Darragh, Andrew; Hettinger, Paul; Hibshman, Adam; Johnson, Elliott W.; Liu, Z. J.; Pajkos, Michael A.; Stephenson, Hunter R.; Vondersaar, John R.; Conroy, Kyle E.; McCombs, Thayne A.; Reinhardt, Erik D.; Toddy, Joseph

2015-08-01

We present the results of an extensive study intended to search for and properly classify the variable stars in five galactic globular clusters. Each of the five clusters was observed hundreds to thousands of times over a time span ranging from 2 to 4 years using the SARA 0.6m located at Cerro Tololo Interamerican Observatory. The images were analyzed using the image subtract method of Alard (2000) to identify and produce light curves of all variables found in each cluster. In total we identified 373 variables with 140 of these being newly discovered increasing the number of known variables stars in these clusters by 60%. Of the total we have identified 312 RR Lyrae variables (187 RR0, 18 RR01, 99 RR1, 8 RR2), 9 SX Phe stars, 6 Cepheid variables, 11 eclipsing variables, and 35 long period variables. For IC4499 we identified 64 RR0, 18 RR01, 14 RR1, 4 RR2, 1 SX Phe, 1 eclipsing binary, and 2 long period variables. For NGC4833 we identified 10 RR0, 7 RR1, 2 RR2, 6 SX Phe, 5 eclipsing binaries, and 9 long period variables. For NGC6171 (M107) we identified 13 RR0, 7 RR1, and 1 SX Phe. For NGC6402 (M14) we identified 52 RR0, 56 RR1, 1 RR2, 1 SX Phe, 6 Cepheids, 1 eclipsing binary, and 15 long period variables. For NGC6584 we identified 48 RR0, 15 RR1, 1 RR2, 5 eclipsing binaries, and 9 long period variables. Using the RR Lyrae variables we found the mean V magnitude of the horizontal branch to be VHB = ⟨V ⟩RR = 17.63, 15.51, 15.72, 17.13, and 16.37 magnitudes for IC4499, NGC4833, NGC6171 (M107), NGC6402 (M14), and NGC6584, respectively. From our extensive data set we were able to obtain sufficient temporal and complete phase coverage of the RR Lyrae variables. This has allowed us not only to properly classify each of the RR Lyrae variables but also to use Fourier decomposition of the light curves to further analyze the properties of the variable stars and hence physical properties of each clusters. In this poster we will give the temperature, radius, stellar mass, metallicity, and helium abundance of the set of RR Lyrae variable stars found in each of the five globular clusters.

Using a respiratory navigator significantly reduces variability when quantifying left ventricular torsion with cardiovascular magnetic resonance.

PubMed

Hamlet, Sean M; Haggerty, Christopher M; Suever, Jonathan D; Wehner, Gregory J; Andres, Kristin N; Powell, David K; Charnigo, Richard J; Fornwalt, Brandon K

2017-03-01

Left ventricular (LV) torsion is an important indicator of cardiac function that is limited by high inter-test variability (50% of the mean value). We hypothesized that this high inter-test variability is partly due to inconsistent breath-hold positions during serial image acquisitions, which could be significantly improved by using a respiratory navigator for cardiovascular magnetic resonance (CMR) based quantification of LV torsion. We assessed respiratory-related variability in measured LV torsion with two distinct experimental protocols. First, 17 volunteers were recruited for CMR with cine displacement encoding with stimulated echoes (DENSE) in which a respiratory navigator was used to measure and then enforce variability in end-expiratory position between all LV basal and apical acquisitions. From these data, we quantified the inter-test variability of torsion in the absence and presence of enforced end-expiratory position variability, which established an upper bound for the expected torsion variability. For the second experiment (in 20 new, healthy volunteers), 10 pairs of cine DENSE basal and apical images were each acquired from consecutive breath-holds and consecutive navigator-gated scans (with a single acceptance position). Inter-test variability of torsion was compared between the breath-hold and navigator-gated scans to quantify the variability due to natural breath-hold variation. To demonstrate the importance of these variability reductions, we quantified the reduction in sample size required to detect a clinically meaningful change in LV torsion with the use of a respiratory navigator. The mean torsion was 3.4 ± 0.2°/cm. From the first experiment, enforced variability in end-expiratory position translated to considerable variability in measured torsion (0.56 ± 0.34°/cm), whereas inter-test variability with consistent end-expiratory position was 57% lower (0.24 ± 0.16°/cm, p < 0.001). From the second experiment, natural respiratory variability from consecutive breath-holds translated to a variability in torsion of 0.24 ± 0.10°/cm, which was significantly higher than the variability from navigator-gated scans (0.18 ± 0.06°/cm, p = 0.02). By using a respiratory navigator with DENSE, theoretical sample sizes were reduced from 66 to 16 and 26 to 15 as calculated from the two experiments. A substantial portion (22-57%) of the inter-test variability of LV torsion can be reduced by using a respiratory navigator to ensure a consistent breath-hold position between image acquisitions.

A Longitudinal Study of Academic Progress Rate as a Result of Team and Institutional Variables at NCAA Division I Schools

ERIC Educational Resources Information Center

Hale, Jimmie Edwin

2014-01-01

This study explained Academic Progress Rate (APR) levels and differences in APR (DAPR) with team and institutional variables. Team variables included team gender, sport profile, and squad size. Institutional variables included individual variables aggregated to the institutional level. The data analyzed in this study was derived from the National…

Validity of a Residualized Dependent Variable after Pretest Covariance Adjustments: Still the Same Variable?

ERIC Educational Resources Information Center

Nimon, Kim; Henson, Robin K.

2015-01-01

The authors empirically examined whether the validity of a residualized dependent variable after covariance adjustment is comparable to that of the original variable of interest. When variance of a dependent variable is removed as a result of one or more covariates, the residual variance may not reflect the same meaning. Using the pretest-posttest…

Quantifying the Model-Related Variability of Biomass Stock and Change Estimates in the Norwegian National Forest Inventory

Treesearch

Johannes Breidenbach; Clara Antón-Fernández; Hans Petersson; Ronald E. McRoberts; Rasmus Astrup

2014-01-01

National Forest Inventories (NFIs) provide estimates of forest parameters for national and regional scales. Many key variables of interest, such as biomass and timber volume, cannot be measured directly in the field. Instead, models are used to predict those variables from measurements of other field variables. Therefore, the uncertainty or variability of NFI estimates...

New SX Phoenicis Variables in the Globular Cluster NGC 4833

NASA Astrophysics Data System (ADS)

Darragh, A. N.; Murphy, B. W.

2012-07-01

We report the discovery of 6 SX Phoenicis stars in the southern globular cluster NGC 4833. Images were obtained from January through June 2011 with the Southeastern Association for Research in Astronomy 0.6 meter telescope located at Cerro Tololo Interamerican Observatory. The ISIS image subtraction method was used to search for variable stars in the cluster. We confirmed 17 previously cataloged variables and have identified 10 new variables. Of the total number of confirmed variables in our 10×10 arcmin^2 field, we classified 10 RRab variables, with a mean period of 0.69591 days, 7 RRc, with a mean period of 0.39555 days, 2 possible RRe variables with a mean period of 0.30950 days, a W Ursae Majoris contact binary, an Algol-type binary, and the 6 SX Phoenicis stars with a mean period of 0.05847 days. The periods, relative numbers of RRab and RRc variables, and Bailey diagram are indicative of the cluster being of the Oosterhoff type II. We present the phased-light curves, periods of previously known variables and the periods and classifications of the newly discovered variables, and their location on the color-magnitude diagram.

Mixed geographically weighted regression (MGWR) model with weighted adaptive bi-square for case of dengue hemorrhagic fever (DHF) in Surakarta

NASA Astrophysics Data System (ADS)

Astuti, H. N.; Saputro, D. R. S.; Susanti, Y.

2017-06-01

MGWR model is combination of linear regression model and geographically weighted regression (GWR) model, therefore, MGWR model could produce parameter estimation that had global parameter estimation, and other parameter that had local parameter in accordance with its observation location. The linkage between locations of the observations expressed in specific weighting that is adaptive bi-square. In this research, we applied MGWR model with weighted adaptive bi-square for case of DHF in Surakarta based on 10 factors (variables) that is supposed to influence the number of people with DHF. The observation unit in the research is 51 urban villages and the variables are number of inhabitants, number of houses, house index, many public places, number of healthy homes, number of Posyandu, area width, level population density, welfare of the family, and high-region. Based on this research, we obtained 51 MGWR models. The MGWR model were divided into 4 groups with significant variable is house index as a global variable, an area width as a local variable and the remaining variables vary in each. Global variables are variables that significantly affect all locations, while local variables are variables that significantly affect a specific location.

A particle swarm optimization variant with an inner variable learning strategy.

PubMed

Wu, Guohua; Pedrycz, Witold; Ma, Manhao; Qiu, Dishan; Li, Haifeng; Liu, Jin

2014-01-01

Although Particle Swarm Optimization (PSO) has demonstrated competitive performance in solving global optimization problems, it exhibits some limitations when dealing with optimization problems with high dimensionality and complex landscape. In this paper, we integrate some problem-oriented knowledge into the design of a certain PSO variant. The resulting novel PSO algorithm with an inner variable learning strategy (PSO-IVL) is particularly efficient for optimizing functions with symmetric variables. Symmetric variables of the optimized function have to satisfy a certain quantitative relation. Based on this knowledge, the inner variable learning (IVL) strategy helps the particle to inspect the relation among its inner variables, determine the exemplar variable for all other variables, and then make each variable learn from the exemplar variable in terms of their quantitative relations. In addition, we design a new trap detection and jumping out strategy to help particles escape from local optima. The trap detection operation is employed at the level of individual particles whereas the trap jumping out strategy is adaptive in its nature. Experimental simulations completed for some representative optimization functions demonstrate the excellent performance of PSO-IVL. The effectiveness of the PSO-IVL stresses a usefulness of augmenting evolutionary algorithms by problem-oriented domain knowledge.

Energy density and variability in abundance of pigeon guillemot prey: Support for the quality-variability trade-off hypothesis

USGS Publications Warehouse

Litzow, Michael A.; Piatt, John F.; Abookire, Alisa A.; Robards, Martin D.

2004-01-01

1. The quality-variability trade-off hypothesis predicts that (i) energy density (kJ g-1) and spatial-temporal variability in abundance are positively correlated in nearshore marine fishes; and (ii) prey selection by a nearshore piscivore, the pigeon guillemot (Cepphus columba Pallas), is negatively affected by variability in abundance. 2. We tested these predictions with data from a 4-year study that measured fish abundance with beach seines and pigeon guillemot prey utilization with visual identification of chick meals. 3. The first prediction was supported. Pearson's correlation showed that fishes with higher energy density were more variable on seasonal (r = 0.71) and annual (r = 0.66) time scales. Higher energy density fishes were also more abundant overall (r = 0.85) and more patchy at a scale of 10s of km (r = 0.77). 4. Prey utilization by pigeon guillemots was strongly non-random. Relative preference, defined as the difference between log-ratio transformed proportions of individual prey taxa in chick diets and beach seine catches, was significantly different from zero for seven of the eight main prey categories. 5. The second prediction was also supported. We used principal component analysis (PCA) to summarize variability in correlated prey characteristics (energy density, availability and variability in abundance). Two PCA scores explained 32% of observed variability in pigeon guillemot prey utilization. Seasonal variability in abundance was negatively weighted by these PCA scores, providing evidence of risk-averse selection. Prey availability, energy density and km-scale variability in abundance were positively weighted. 6. Trophic interactions are known to create variability in resource distribution in other systems. We propose that links between resource quality and the strength of trophic interactions may produce resource quality-variability trade-offs.

Automatic identification of variables in epidemiological datasets using logic regression.

PubMed

Lorenz, Matthias W; Abdi, Negin Ashtiani; Scheckenbach, Frank; Pflug, Anja; Bülbül, Alpaslan; Catapano, Alberico L; Agewall, Stefan; Ezhov, Marat; Bots, Michiel L; Kiechl, Stefan; Orth, Andreas

2017-04-13

For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable. For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated. In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables. We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies.

Quantifying Variability of Avian Colours: Are Signalling Traits More Variable?

PubMed Central

Delhey, Kaspar; Peters, Anne

2008-01-01

Background Increased variability in sexually selected ornaments, a key assumption of evolutionary theory, is thought to be maintained through condition-dependence. Condition-dependent handicap models of sexual selection predict that (a) sexually selected traits show amplified variability compared to equivalent non-sexually selected traits, and since males are usually the sexually selected sex, that (b) males are more variable than females, and (c) sexually dimorphic traits more variable than monomorphic ones. So far these predictions have only been tested for metric traits. Surprisingly, they have not been examined for bright coloration, one of the most prominent sexual traits. This omission stems from computational difficulties: different types of colours are quantified on different scales precluding the use of coefficients of variation. Methodology/Principal Findings Based on physiological models of avian colour vision we develop an index to quantify the degree of discriminable colour variation as it can be perceived by conspecifics. A comparison of variability in ornamental and non-ornamental colours in six bird species confirmed (a) that those coloured patches that are sexually selected or act as indicators of quality show increased chromatic variability. However, we found no support for (b) that males generally show higher levels of variability than females, or (c) that sexual dichromatism per se is associated with increased variability. Conclusions/Significance We show that it is currently possible to realistically estimate variability of animal colours as perceived by them, something difficult to achieve with other traits. Increased variability of known sexually-selected/quality-indicating colours in the studied species, provides support to the predictions borne from sexual selection theory but the lack of increased overall variability in males or dimorphic colours in general indicates that sexual differences might not always be shaped by similar selective forces. PMID:18301766

Geostatistical Analysis of Mesoscale Spatial Variability and Error in SeaWiFS and MODIS/Aqua Global Ocean Color Data

NASA Astrophysics Data System (ADS)

Glover, David M.; Doney, Scott C.; Oestreich, William K.; Tullo, Alisdair W.

2018-01-01

Mesoscale (10-300 km, weeks to months) physical variability strongly modulates the structure and dynamics of planktonic marine ecosystems via both turbulent advection and environmental impacts upon biological rates. Using structure function analysis (geostatistics), we quantify the mesoscale biological signals within global 13 year SeaWiFS (1998-2010) and 8 year MODIS/Aqua (2003-2010) chlorophyll a ocean color data (Level-3, 9 km resolution). We present geographical distributions, seasonality, and interannual variability of key geostatistical parameters: unresolved variability or noise, resolved variability, and spatial range. Resolved variability is nearly identical for both instruments, indicating that geostatistical techniques isolate a robust measure of biophysical mesoscale variability largely independent of measurement platform. In contrast, unresolved variability in MODIS/Aqua is substantially lower than in SeaWiFS, especially in oligotrophic waters where previous analysis identified a problem for the SeaWiFS instrument likely due to sensor noise characteristics. Both records exhibit a statistically significant relationship between resolved mesoscale variability and the low-pass filtered chlorophyll field horizontal gradient magnitude, consistent with physical stirring acting on large-scale gradient as an important factor supporting observed mesoscale variability. Comparable horizontal length scales for variability are found from tracer-based scaling arguments and geostatistical decorrelation. Regional variations between these length scales may reflect scale dependence of biological mechanisms that also create variability directly at the mesoscale, for example, enhanced net phytoplankton growth in coastal and frontal upwelling and convective mixing regions. Global estimates of mesoscale biophysical variability provide an improved basis for evaluating higher resolution, coupled ecosystem-ocean general circulation models, and data assimilation.

Developmental differences in intra-individual variability in children with ADHD and ASD.

PubMed

van Belle, Janna; van Hulst, Branko M; Durston, Sarah

2015-12-01

Intra-individual variability reflects temporal variation within an individual's performance on a cognitive task. Children with developmental disorders, such as ADHD and ASD show increased levels of intra-individual variability. In typical development, intra-individual variability decreases sharply between the ages 6 and 20. The tight link between intra-individual variability and age has led to the suggestion that it may be marker of neural development. As there is accumulating evidence that ADHD and ASD are characterised by atypical neurodevelopmental trajectories, we set out to explore developmental changes in intra-individual variability in subjects with ADHD and ASD. We used propensity score matching to match a cross-sectional sample of children with ADHD, ASD and control subjects (N = 405, aged 6-19 years old) for age, IQ and gender. We used ex-Gaussian distribution parameters to characterise intra-individual variability on fast responses (sigma) and slow responses (tau). Results showed that there was a similar decrease in mean response times with age across groups, and an interaction between age and group for measures of variability, where there was a much lower rate of change in the variability parameters (sigma and tau) for subjects with ASD compared with the other two groups. Subjects with ADHD had higher intra-individual variability, reflected by both sigma and tau, but the rate of decrease in variability with age was similar to that of the controls. These results suggest that subjects with ADHD, ASD and controls differ in the rate at which intra-individual variability decreases during development, and support the idea that intra-individual variability may be a marker of neural development, mimicking the neurodevelopmental changes in these disorders. © 2015 Association for Child and Adolescent Mental Health.

Increased gait variability may not imply impaired stride-to-stride control of walking in healthy older adults: Winner: 2013 Gait and Clinical Movement Analysis Society Best Paper Award.

PubMed

Dingwell, Jonathan B; Salinas, Mandy M; Cusumano, Joseph P

2017-06-01

Older adults exhibit increased gait variability that is associated with fall history and predicts future falls. It is not known to what extent this increased variability results from increased physiological noise versus a decreased ability to regulate walking movements. To "walk", a person must move a finite distance in finite time, making stride length (L n ) and time (T n ) the fundamental stride variables to define forward walking. Multiple age-related physiological changes increase neuromotor noise, increasing gait variability. If older adults also alter how they regulate their stride variables, this could further exacerbate that variability. We previously developed a Goal Equivalent Manifold (GEM) computational framework specifically to separate these causes of variability. Here, we apply this framework to identify how both young and high-functioning healthy older adults regulate stepping from each stride to the next. Healthy older adults exhibited increased gait variability, independent of walking speed. However, despite this, these healthy older adults also concurrently exhibited no differences (all p>0.50) from young adults either in how their stride variability was distributed relative to the GEM or in how they regulated, from stride to stride, either their basic stepping variables or deviations relative to the GEM. Using a validated computational model, we found these experimental findings were consistent with increased gait variability arising solely from increased neuromotor noise, and not from changes in stride-to-stride control. Thus, age-related increased gait variability likely precedes impaired stepping control. This suggests these changes may in turn precede increased fall risk. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantifying Variability in Growth and Thermal Inactivation Kinetics of Lactobacillus plantarum.

PubMed

Aryani, D C; den Besten, H M W; Zwietering, M H

2016-08-15

The presence and growth of spoilage organisms in food might affect the shelf life. In this study, the effects of experimental, reproduction, and strain variabilities were quantified with respect to growth and thermal inactivation using 20 Lactobacillus plantarum strains. Also, the effect of growth history on thermal resistance was quantified. The strain variability in μmax was similar (P > 0.05) to reproduction variability as a function of pH, aw, and temperature, while being around half of the reproduction variability (P < 0.05) as a function of undissociated lactic acid concentration [HLa]. The cardinal growth parameters were estimated for the L. plantarum strains, and the pHmin was between 3.2 and 3.5, the aw,min was between 0.936 and 0.953, the [HLamax], at pH 4.5, was between 29 and 38 mM, and the Tmin was between 3.4 and 8.3°C. The average D values ranged from 0.80 min to 19 min at 55°C, 0.22 to 3.9 min at 58°C, 3.1 to 45 s at 60°C, and 1.8 to 19 s at 63°C. In contrast to growth, the strain variability in thermal resistance was on average six times higher than the reproduction variability and more than ten times higher than the experimental variability. The strain variability was also 1.8 times higher (P < 0.05) than the effect of growth history. The combined effects of strain variability and growth history on D value explained all of the variability as found in the literature, although with bias. Based on an illustrative milk-processing chain, strain variability caused ∼2-log10 differences in growth between the most and least robust strains and >10-log10 differences after thermal treatment. Accurate control and realistic prediction of shelf life is complicated by the natural diversity among microbial strains, and limited information on microbiological variability is available for spoilage microorganisms. Therefore, the objectives of the present study were to quantify strain variability, reproduction (biological) variability, and experimental variability with respect to the growth and thermal inactivation kinetics of Lactobacillus plantarum and to quantify the variability in thermal resistance attributed to growth history. The quantitative knowledge obtained on experimental, reproduction, and strain variabilities can be used to improve experimental designs and to adequately select strains for challenge growth and inactivation tests. Moreover, the integration of strain variability in prediction of microbial growth and inactivation kinetics will result in more realistic predictions of L. plantarum dynamics along the food production chain. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Variable stars in the Pegasus dwarf galaxy (DDO 216)

NASA Technical Reports Server (NTRS)

Hoessel, J. G.; Abbott, Mark J.; Saha, A.; Mossman, Amy E.; Danielson, G. Edward

1990-01-01

Observations obtained over a period of five years of the resolved stars in the Pegasus dwarf irregular galaxy (DDO 216) have been searched for variable stars. Thirty-one variables were found, and periods established for 12. Two of these variable stars are clearly eclipsing variables, seven are very likely Cepheid variables, and the remaining three are probable Cepheids. The period-luminosity relation for the Cepheids indicates a distance modulus for Pegasus of m - M = 26.22 + or - 0.20. This places Pegasus very near the zero-velocity surface of the Local Group.

Surgeon and type of anesthesia predict variability in surgical procedure times.

PubMed

Strum, D P; Sampson, A R; May, J H; Vargas, L G

2000-05-01

Variability in surgical procedure times increases the cost of healthcare delivery by increasing both the underutilization and overutilization of expensive surgical resources. To reduce variability in surgical procedure times, we must identify and study its sources. Our data set consisted of all surgeries performed over a 7-yr period at a large teaching hospital, resulting in 46,322 surgical cases. To study factors associated with variability in surgical procedure times, data mining techniques were used to segment and focus the data so that the analyses would be both technically and intellectually feasible. The data were subdivided into 40 representative segments of manageable size and variability based on headers adopted from the common procedural terminology classification. Each data segment was then analyzed using a main-effects linear model to identify and quantify specific sources of variability in surgical procedure times. The single most important source of variability in surgical procedure times was surgeon effect. Type of anesthesia, age, gender, and American Society of Anesthesiologists risk class were additional sources of variability. Intrinsic case-specific variability, unexplained by any of the preceding factors, was found to be highest for shorter surgeries relative to longer procedures. Variability in procedure times among surgeons was a multiplicative function (proportionate to time) of surgical time and total procedure time, such that as procedure times increased, variability in surgeons' surgical time increased proportionately. Surgeon-specific variability should be considered when building scheduling heuristics for longer surgeries. Results concerning variability in surgical procedure times due to factors such as type of anesthesia, age, gender, and American Society of Anesthesiologists risk class may be extrapolated to scheduling in other institutions, although specifics on individual surgeons may not. This research identifies factors associated with variability in surgical procedure times, knowledge of which may ultimately be used to improve surgical scheduling and operating room utilization.

An assessment of the impact of demographic, cognitive, and non-cognitive variables on student success in a community college science course

NASA Astrophysics Data System (ADS)

Mackey, Audrey Leroy

The impact of demographic, cognitive, and non-cognitive variables on academic success among community college science students was studied. Demographic variables included gender, employment status, and ethnicity. Cognitive variables included college grade point average, assessment status, course prerequisites, college course success ratios, final course grade, withdrawal patterns, and curriculum format. Non-cognitive variables included enrollment status, educational objectives, academic expectations, and career goals. The sample population included students enrolled in human anatomy courses (N = 191) at a large metropolitan community college located in central Texas. Variables that potentially influence attrition and achievement in college level science courses were examined. Final course grade and withdrawal phenomena were treated as dependent variables, while all other variables were treated as independent variables. No significant differences were found to exist between any of the demographic variables studied and the numbers of students who withdrew passing or failing. A difference was shown to be associated with the ethnicity variable and achievement levels. Educational objectives and career goals were shown to have an impact on the number of students who withdrew failing. The career goals variable and the academic expectations variable were shown to have an impact on achievement among daytime and evening students. College grade point average and course success ratios were shown to make a difference among students who withdrew passing. None of the other cognitive variables studied were shown to influence the numbers of students who withdrew passing or failing. College grade point average and course prerequisites, however, were shown to make a difference in achievement. The collaborative learning instructional format was found to have no impact on attrition or achievement, however, mean scores earned by students experiencing the collaborative learning format were higher than mean scores among other students. These results are extremely valuable when engaging in the process of developing advising strategies and instructional methodologies for community college science students.

Quantitative assessment of prevalence of pre-analytical variables and their effect on coagulation assay. Can intervention improve patient safety?

PubMed

Bhushan, Ravi; Sen, Arijit

2017-04-01

Very few Indian studies exist on evaluation of pre-analytical variables affecting "Prothrombin Time" the commonest coagulation assay performed. The study was performed in an Indian tertiary care setting with an aim to assess quantitatively the prevalence of pre-analytical variables and their effects on the results (patient safety), for Prothrombin time test. The study also evaluated their effects on the result and whether intervention, did correct the results. The firstly evaluated the prevalence for various pre-analytical variables detected in samples sent for Prothrombin Time testing. These samples with the detected variables wherever possible were tested and result noted. The samples from the same patients were repeated and retested ensuring that no pre-analytical variable is present. The results were again noted to check for difference the intervention produced. The study evaluated 9989 samples received for PT/INR over a period of 18 months. The prevalence of different pre-analytical variables was found to be 862 (8.63%). The proportion of various pre-analytical variables detected were haemolysed samples 515 (5.16%), over filled vacutainers 62 (0.62%), under filled vacutainers 39 (0.39%), low values 205 (2.05%), clotted samples 11 (0.11%), wrong labeling 4 (0.04%), wrong vacutainer use 2 (0.02%), chylous samples 7 (0.07%) and samples with more than one variable 17 (0.17%). The comparison of percentage of samples showing errors were noted for the first variables since they could be tested with and without the variable in place. The reduction in error percentage was 91.5%, 69.2%, 81.5% and 95.4% post intervention for haemolysed, overfilled, under filled and samples collected with excess pressure at phlebotomy respectively. Correcting the variables did reduce the error percentage to a great extent in these four variables and hence the variables are found to affect "Prothrombin Time" testing and can hamper patient safety.

Simulated decadal modes of the NH atmospheric circulation arising from intra-decadal variability, external forcing and slow-decadal climate processes

NASA Astrophysics Data System (ADS)

Lou, Jiale; Zheng, Xiaogu; Frederiksen, Carsten S.; Liu, Haibo; Grainger, Simon; Ying, Kairan

2017-04-01

A decadal variance decomposition method is applied to the Northern Hemisphere (NH) 500-hPa geopotential height (GPH) and the sea level pressure (SLP) taken from the last millennium (850-1850 AD) experiment with the coupled climate model CCSM4, to estimate the contribution of the intra-decadal variability to the inter-decadal variability. By removing the intra-decadal variability from the total inter-decadal variability, the residual variability is more likely to be associated with slowly varying external forcings and slow-decadal climate processes, and therefore is referred to as slow-decadal variability. The results show that the (multi-)decadal changes of the NH 500-hPa GPH are primarily dominated by slow-decadal variability, whereas the NH SLP field is primarily dominated by the intra-decadal variability. At both pressure levels, the leading intra-decadal modes each have features related to the El Niño-southern oscillation, the intra-decadal variability of the Pacific decadal oscillation (PDO) and the Arctic oscillation (AO); while the leading slow-decadal modes are associated with external radiative forcing (mostly with volcanic aerosol loadings), the Atlantic multi-decadal oscillation and the slow-decadal variability of AO and PDO. Moreover, the radiative forcing has much weaker effect to the SLP than that to the 500-hPa GPH.

Farmers' Perceptions of Climate Variability and Factors Influencing Adaptation: Evidence from Anhui and Jiangsu, China

NASA Astrophysics Data System (ADS)

Kibue, Grace Wanjiru; Liu, Xiaoyu; Zheng, Jufeng; zhang, Xuhui; Pan, Genxing; Li, Lianqing; Han, Xiaojun

2016-05-01

Impacts of climate variability and climate change are on the rise in China posing great threat to agriculture and rural livelihoods. Consequently, China is undertaking research to find solutions of confronting climate change and variability. However, most studies of climate change and variability in China largely fail to address farmers' perceptions of climate variability and adaptation. Yet, without an understanding of farmers' perceptions, strategies are unlikely to be effective. We conducted questionnaire surveys of farmers in two farming regions, Yifeng, Jiangsu and Qinxi, Anhui achieving 280 and 293 responses, respectively. Additionally, we used climatological data to corroborate the farmers' perceptions of climate variability. We found that farmers' were aware of climate variability such that were consistent with climate records. However, perceived impacts of climate variability differed between the two regions and were influenced by farmers' characteristics. In addition, the vast majorities of farmers were yet to make adjustments in their farming practices as a result of numerous challenges. These challenges included socioeconomic and socio-cultural barriers. Results of logit modeling showed that farmers are more likely to adapt to climate variability if contact with extension services, frequency of seeking information, household heads' education, and climate variability perceptions are improved. These results suggest the need for policy makers to understand farmers' perceptions of climate variability and change in order to formulate policies that foster adaptation, and ultimately protect China's agricultural assets.

Multicollinearity in canonical correlation analysis in maize.

PubMed

Alves, B M; Cargnelutti Filho, A; Burin, C

2017-03-30

The objective of this study was to evaluate the effects of multicollinearity under two methods of canonical correlation analysis (with and without elimination of variables) in maize (Zea mays L.) crop. Seventy-six maize genotypes were evaluated in three experiments, conducted in a randomized block design with three replications, during the 2009/2010 crop season. Eleven agronomic variables (number of days from sowing until female flowering, number of days from sowing until male flowering, plant height, ear insertion height, ear placement, number of plants, number of ears, ear index, ear weight, grain yield, and one thousand grain weight), 12 protein-nutritional variables (crude protein, lysine, methionine, cysteine, threonine, tryptophan, valine, isoleucine, leucine, phenylalanine, histidine, and arginine), and 6 energetic-nutritional variables (apparent metabolizable energy, apparent metabolizable energy corrected for nitrogen, ether extract, crude fiber, starch, and amylose) were measured. A phenotypic correlation matrix was first generated among the 29 variables for each of the experiments. A multicollinearity diagnosis was later performed within each group of variables using methodologies such as variance inflation factor and condition number. Canonical correlation analysis was then performed, with and without the elimination of variables, among groups of agronomic and protein-nutritional, and agronomic and energetic-nutritional variables. The canonical correlation analysis in the presence of multicollinearity (without elimination of variables) overestimates the variability of canonical coefficients. The elimination of variables is an efficient method to circumvent multicollinearity in canonical correlation analysis.

Farmers' Perceptions of Climate Variability and Factors Influencing Adaptation: Evidence from Anhui and Jiangsu, China.

PubMed

Kibue, Grace Wanjiru; Liu, Xiaoyu; Zheng, Jufeng; Zhang, Xuhui; Pan, Genxing; Li, Lianqing; Han, Xiaojun

2016-05-01

Impacts of climate variability and climate change are on the rise in China posing great threat to agriculture and rural livelihoods. Consequently, China is undertaking research to find solutions of confronting climate change and variability. However, most studies of climate change and variability in China largely fail to address farmers' perceptions of climate variability and adaptation. Yet, without an understanding of farmers' perceptions, strategies are unlikely to be effective. We conducted questionnaire surveys of farmers in two farming regions, Yifeng, Jiangsu and Qinxi, Anhui achieving 280 and 293 responses, respectively. Additionally, we used climatological data to corroborate the farmers' perceptions of climate variability. We found that farmers' were aware of climate variability such that were consistent with climate records. However, perceived impacts of climate variability differed between the two regions and were influenced by farmers' characteristics. In addition, the vast majorities of farmers were yet to make adjustments in their farming practices as a result of numerous challenges. These challenges included socioeconomic and socio-cultural barriers. Results of logit modeling showed that farmers are more likely to adapt to climate variability if contact with extension services, frequency of seeking information, household heads' education, and climate variability perceptions are improved. These results suggest the need for policy makers to understand farmers' perceptions of climate variability and change in order to formulate policies that foster adaptation, and ultimately protect China's agricultural assets.

Examining shifts in zooplankton community as a response of environmental change in Lakes

NASA Astrophysics Data System (ADS)

Ghadouani, Anas; Mines, Conor; Legendre, Pierre; Yan, Norman

2014-05-01

We examined 20 years of zooplankton samples from Harp Lake for shifts in zooplankton variability following invasion by zooplankton predator Bythotrephes longimanus, using organism body size—as measured at high resolution by Laser Optical Plankton Counter (LOPC)—as the primary metric of investigation. A period of transitory high variability in the 2yr post-invasion was observed for both body size compositional variability and aggregate variability metrics, with both measures of variability shifting from low or intermediate to high variability immediately following invasion, before shifting again to intermediate variability, 2 yr post-invasion. Aggregate and compositional variability dynamics were also considered in combination over the study period, revealing that the period of transitory high variability coincided with a shift from a community-wide stasis variability pattern to one of asynchrony, before a shift back to stasis 2 yr post-invasion. These dynamics were related to changes in the significant zooplankton species within the Harp Lake community over the pre- and post- invasion periods, and are likely to be indicative of changes in the stability in the zooplankton community following invasion by Bythotrephes. The dual consideration of aggregate and compositional variability as measured by LOPC was found to provide a valuable means to assess the ecological effects of biological invasion on zooplankton communities as a whole, extending our knowledge of the effects of invasion beyond that already revealed through more traditional taxonomic investigation.

Atmospheric Teleconnection and Climate Variability: Affecting Rice Productivity of Bihar, India

NASA Astrophysics Data System (ADS)

Saini, A.

2017-12-01

Climate variability brought various negative results to the environment around us and area under rice crop in Bihar has also faced a lot of negative impacts due to variability in temperature and rainfall. Location of Bihar in Northern Plain of India automatically makes it prime location for agriculture and therefore variability in climatic variables brings highly sensitive results to the agricultural production (especially rice). In this study, rainfall and temperature variables are taken into consideration to investigate the impact on rice cultivated area. Change in climate variable with the passage of time is prevailing since the start of geological time scale, how the variability in climate variables has affected the major crops. Climate index of Pacific Ocean and Indian Ocean influences the seasonal weather in Bihar and therefore role of ENSO and IOD is an interesting point of inquiry. Does there exists direct relation between climate variability and area under agricultural crops? How many important variables directly signals towards the change in area under agriculture production? These entire questions are answered with respect to change in area under rice cultivation of Bihar State of India. Temperature, rainfall and ENSO are a good indicator with respect to rice cultivation in Indian subcontinent. Impact on the area under rice has been signaled through ONI, Niño3 and DMI. Increasing range of temperature in the rice productivity declining years is observed since 1990.

Autosomal Dominant Cataract: Intrafamilial Phenotypic Variability, Interocular Asymmetry, and Variable Progression in Four Chilean Families

PubMed Central

Shafie, Suraiya M.; Barria von-Bischhoffshausen, Fernando R.; Bateman, J. Bronwyn

2006-01-01

PURPOSE To document intrafamilial and interocular phenotypic variability of autosomal dominant cataract (ADC). DESIGN Prospective observational case series. METHODS We performed ophthalmologic examination in four Chilean ADC families. RESULTS The families exhibited variability with respect to morphology, location with the lens, color and density of cataracts among affected members. We documented asymmetry between eyes in the morphology, location within the lens, color and density of cataracts, and a variable rate of progression. CONCLUSIONS The cataracts in these families exhibit wide intrafamilial and interocular phenotypic variability, supporting the premise that the mutated genes are expressed differentially in individuals and between eyes; other genes or environmental factors may be the bases for this variability. Marked progression among some family members underscores the variable clinical course of a common mutation within a family. Like retinitis pigmentosa, classification of ADC will be most useful if based on the gene and specific mutation. PMID:16564818

Meta-analysis of correlates of provider behavior in medical encounters.

PubMed

Hall, J A; Roter, D L; Katz, N R

1988-07-01

This article summarizes the results of 41 independent studies containing correlates of objectively measured provider behaviors in medical encounters. Provider behaviors were grouped a priori into the process categories of information giving, questions, competence, partnership building, and socioemotional behavior. Total amount of communication was also included. All correlations between variables within these categories and external variables (patient outcome variables or patient and provider background variables) were extracted. The most frequently occurring outcome variables were satisfaction, recall, and compliance, and the most frequently occurring background variables were the patient's gender, age, and social class. Average correlations and combined significance levels were calculated for each combination of process category and external variable. Results showed significant relations of small to moderate average magnitude between these external variables and almost all of the provider behavior categories. A theory of provider-patient reciprocation is proposed to account for the pattern of results.

Variable mechanical ventilation

PubMed Central

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

2017-01-01

Objective To review the literature on the use of variable mechanical ventilation and the main outcomes of this technique. Methods 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". Results A total of 36 studies were selected. Of these, 24 were original studies, including 21 experimental studies and three clinical studies. Conclusion 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. PMID:28444076

Output variability across animals and levels in a motor system

PubMed Central

Norris, Brian J; Günay, Cengiz; Kueh, Daniel

2018-01-01

Rhythmic behaviors vary across individuals. We investigated the sources of this output variability across a motor system, from the central pattern generator (CPG) to the motor plant. In the bilaterally symmetric leech heartbeat system, the CPG orchestrates two coordinations in the bilateral hearts with different intersegmental phase relations (Δϕ) and periodic side-to-side switches. Population variability is large. We show that the system is precise within a coordination, that differences in repetitions of a coordination contribute little to population output variability, but that differences between bilaterally homologous cells may contribute to some of this variability. Nevertheless, much output variability is likely associated with genetic and life history differences among individuals. Variability of Δϕ were coordination-specific: similar at all levels in one, but significantly lower for the motor pattern than the CPG pattern in the other. Mechanisms that transform CPG output to motor neurons may limit output variability in the motor pattern. PMID:29345614

Examining Impulse-Variability in Kicking.

PubMed

Chappell, Andrew; Molina, Sergio L; McKibben, Jonathon; Stodden, David F

2016-07-01

This study examined variability in kicking speed and spatial accuracy to test the impulse-variability theory prediction of an inverted-U function and the speed-accuracy trade-off. Twenty-eight 18- to 25-year-old adults kicked a playground ball at various percentages (50-100%) of their maximum speed at a wall target. Speed variability and spatial error were analyzed using repeated-measures ANOVA with built-in polynomial contrasts. Results indicated a significant inverse linear trajectory for speed variability (p < .001, η2= .345) where 50% and 60% maximum speed had significantly higher variability than the 100% condition. A significant quadratic fit was found for spatial error scores of mean radial error (p < .0001, η2 = .474) and subject-centroid radial error (p < .0001, η2 = .453). Findings suggest variability and accuracy of multijoint, ballistic skill performance may not follow the general principles of impulse-variability theory or the speed-accuracy trade-off.

A neural circuit mechanism for regulating vocal variability during song learning in zebra finches.

PubMed

Garst-Orozco, Jonathan; Babadi, Baktash; Ölveczky, Bence P

2014-12-15

Motor skill learning is characterized by improved performance and reduced motor variability. The neural mechanisms that couple skill level and variability, however, are not known. The zebra finch, a songbird, presents a unique opportunity to address this question because production of learned song and induction of vocal variability are instantiated in distinct circuits that converge on a motor cortex analogue controlling vocal output. To probe the interplay between learning and variability, we made intracellular recordings from neurons in this area, characterizing how their inputs from the functionally distinct pathways change throughout song development. We found that inputs that drive stereotyped song-patterns are strengthened and pruned, while inputs that induce variability remain unchanged. A simple network model showed that strengthening and pruning of action-specific connections reduces the sensitivity of motor control circuits to variable input and neural 'noise'. This identifies a simple and general mechanism for learning-related regulation of motor variability.

System and method of modulating electrical signals using photoconductive wide bandgap semiconductors as variable resistors

DOEpatents

Harris, John Richardson; Caporaso, George J; Sampayan, Stephen E

2013-10-22

A system and method for producing modulated electrical signals. The system uses a variable resistor having a photoconductive wide bandgap semiconductor material construction whose conduction response to changes in amplitude of incident radiation is substantially linear throughout a non-saturation region to enable operation in non-avalanche mode. The system also includes a modulated radiation source, such as a modulated laser, for producing amplitude-modulated radiation with which to direct upon the variable resistor and modulate its conduction response. A voltage source and an output port, are both operably connected to the variable resistor so that an electrical signal may be produced at the output port by way of the variable resistor, either generated by activation of the variable resistor or propagating through the variable resistor. In this manner, the electrical signal is modulated by the variable resistor so as to have a waveform substantially similar to the amplitude-modulated radiation.

CORRELATION PURSUIT: FORWARD STEPWISE VARIABLE SELECTION FOR INDEX MODELS

PubMed Central

Zhong, Wenxuan; Zhang, Tingting; Zhu, Yu; Liu, Jun S.

2012-01-01

In this article, a stepwise procedure, correlation pursuit (COP), is developed for variable selection under the sufficient dimension reduction framework, in which the response variable Y is influenced by the predictors X1, X2, …, Xp through an unknown function of a few linear combinations of them. Unlike linear stepwise regression, COP does not impose a special form of relationship (such as linear) between the response variable and the predictor variables. The COP procedure selects variables that attain the maximum correlation between the transformed response and the linear combination of the variables. Various asymptotic properties of the COP procedure are established, and in particular, its variable selection performance under diverging number of predictors and sample size has been investigated. The excellent empirical performance of the COP procedure in comparison with existing methods are demonstrated by both extensive simulation studies and a real example in functional genomics. PMID:23243388

The GISS global climate-middle atmosphere model. II - Model variability due to interactions between planetary waves, the mean circulation and gravity wave drag

NASA Technical Reports Server (NTRS)

Rind, D.; Suozzo, R.; Balachandran, N. K.

1988-01-01

The variability which arises in the GISS Global Climate-Middle Atmosphere Model on two time scales is reviewed: interannual standard deviations, derived from the five-year control run, and intraseasonal variability as exemplified by statospheric warnings. The model's extratropical variability for both mean fields and eddy statistics appears reasonable when compared with observations, while the tropical wind variability near the stratopause may be excessive possibly, due to inertial oscillations. Both wave 1 and wave 2 warmings develop, with connections to tropospheric forcing. Variability on both time scales results from a complex set of interactions among planetary waves, the mean circulation, and gravity wave drag. Specific examples of these interactions are presented, which imply that variability in gravity wave forcing and drag may be an important component of the variability of the middle atmosphere.

Determining the influence and effects of manufacturing variables on sulfur dioxide cells

NASA Technical Reports Server (NTRS)

Zajac, W. V.; Thomas, M. A.; Barnes, J. A.; Bis, R., F.; Davis, P. B.; Debold, F. C.; Gemmill, G. W.; Kowalchik, L. A.

1986-01-01

A survey of the Li/SO2 manufacturing community was conducted to determine where variability exists in processing. The upper and lower limits of these processing variables might, by themselves or by interacting with other variables, influence safety, performance, and reliability. A number of important variables were identified and a comprehensive design experiment is being proposed to make the proper determinations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cacciari, C.; Clementini, G.

Attention is given to the folowing topics: population I and II variable stars; LP variables, the sun, and mass determination; and predegenerate and degenerate variables. Particular papers are presented on alternative evolutionary approaches to the absolute magnitude of the RR Lyrae variables; the evolution of the Cepheid stars; nonradial pulsations in rapidly rotating Delta Scuti stars; dynamical models of dust shells around Mira variables; and pulsations of central stars of planetary nebulae.

Variable Star Observing in Hungary

NASA Astrophysics Data System (ADS)

Mizser, Attila

1986-12-01

Astronomy and variable star observing has a long history in Hungary, dating back to the private observatories erected by the Hungarian nobility in the late 19th Century. The first organized network of amateur variable star observers, the Variable Star Section of the new Hungarian Astronomical Association, was organized around the Urania Observatory in Budapest in 1948. Other groups, dedicated to various types of variables, have since been organized.

A conceptual framework for evaluating variable speed generator options for wind energy applications

NASA Technical Reports Server (NTRS)

Reddoch, T. W.; Lipo, T. A.; Hinrichsen, E. N.; Hudson, T. L.; Thomas, R. J.

1995-01-01

Interest in variable speed generating technology has accelerated as greater emphasis on overall efficiency and superior dynamic and control properties in wind-electric generating systems are sought. This paper reviews variable speed technology options providing advantages and disadvantages of each. Furthermore, the dynamic properties of variable speed systems are contrasted with synchronous operation. Finally, control properties of variable speed systems are examined.

Yaughan and Curriboo Plantations. Studies in Afro-American Archaeology,

DTIC Science & Technology

1983-04-01

ceramics pres- ent were produced by Indians instead of Blacks. Careful historical research was employed to control that variable. The third variable...studies without independ- ent controls over some classes of non -material variables. Historical archaeology offers the opportunity for controlling some of...these non -material variables. The non -material variables must be controlled so that attention can be focused on the archaeological data. Once models

Relative controls of external and internal variability on time-variable transit time distributions, and the importance of StorAge Selection function approaches

NASA Astrophysics Data System (ADS)

Kim, M.; Pangle, L. A.; Cardoso, C.; Lora, M.; Meira, A.; Volkmann, T. H. M.; Wang, Y.; Harman, C. J.; Troch, P. A. A.

2015-12-01

Transit time distributions (TTDs) are an efficient way of characterizing complex transport dynamics of a hydrologic system. Time-invariant TTD has been studied extensively, but TTDs are time-varying under unsteady hydrologic systems due to both external variability (e.g., time-variability in fluxes), and internal variability (e.g., time-varying flow pathways). The use of "flow-weighted time" has been suggested to account for the effect of external variability on TTDs, but neglects the role of internal variability. Recently, to account both types of variability, StorAge Selection (SAS) function approaches were developed. One of these approaches enables the transport characteristics of a system - how the different aged water in the storage is sampled by the outflow - to be parameterized by time-variable probability distribution called the rank SAS (rSAS) function, and uses it directly to determine the time-variable TTDs resulting from a given timeseries of fluxes in and out of a system. Unlike TTDs, the form of the rSAS function varies only due to changes in flow pathways, but is not affected by the timing of fluxes alone. However, the relation between physical mechanisms and the time-varying rSAS functions are not well understood. In this study, relative effects of internal and external variability on the TTDs are examined using observations from a homogeneously packed 1 m3 sloping soil lysimeter. The observations suggest the importance of internal variability on TTDs, and reinforce the need to account for this variability using time-variable rSAS functions. Furthermore, the relative usefulness of two other formulations of SAS functions and the mortality rate (which plays a similar role to SAS functions in the McKendrick-von Foerster model of age-structured population dynamics) are also discussed. Finally, numerical modeling is used to explore the role of internal and external variability for hydrologic systems with diverse geomorphic and climate characteristics. This works will give an insight that which approach (or SAS function) is preferable under different conditions.

Night-to-Night Sleep Variability in Older Adults With Chronic Insomnia: Mediators and Moderators in a Randomized Controlled Trial of Brief Behavioral Therapy (BBT-I)

PubMed Central

Chan, Wai Sze; Williams, Jacob; Dautovich, Natalie D.; McNamara, Joseph P.H.; Stripling, Ashley; Dzierzewski, Joseph M.; Berry, Richard B.; McCoy, Karin J.M.; McCrae, Christina S.

2017-01-01

Study Objectives: Sleep variability is a clinically significant variable in understanding and treating insomnia in older adults. The current study examined changes in sleep variability in the course of brief behavioral therapy for insomnia (BBT-I) in older adults who had chronic insomnia. Additionally, the current study examined the mediating mechanisms underlying reductions of sleep variability and the moderating effects of baseline sleep variability on treatment responsiveness. Methods: Sixty-two elderly participants were randomly assigned to either BBT-I or self-monitoring and attention control (SMAC). Sleep was assessed by sleep diaries and actigraphy from baseline to posttreatment and at 3-month follow-up. Mixed models were used to examine changes in sleep variability (within-person standard deviations of weekly sleep parameters) and the hypothesized mediation and moderation effects. Results: Variabilities in sleep diary-assessed sleep onset latency (SOL) and actigraphy-assessed total sleep time (TST) significantly decreased in BBT-I compared to SMAC (Pseudo R2 = .12, .27; P = .018, .008). These effects were mediated by reductions in bedtime and wake time variability and time in bed. Significant time × group × baseline sleep variability interactions on sleep outcomes indicated that participants who had higher baseline sleep variability were more responsive to BBT-I; their actigraphy-assessed TST, SOL, and sleep efficiency improved to a greater degree (Pseudo R2 = .15 to .66; P < .001 to .044). Conclusions: BBT-I is effective in reducing sleep variability in older adults who have chronic insomnia. Increased consistency in bedtime and wake time and decreased time in bed mediate reductions of sleep variability. Baseline sleep variability may serve as a marker of high treatment responsiveness to BBT-I. Clinical Trial Registration: ClinicalTrials.gov, Identifier: NCT02967185 Citation: Chan WS, Williams J, Dautovich ND, McNamara JP, Stripling A, Dzierzewski JM, Berry RB, McCoy KJ, McCrae CS. Night-to-night sleep variability in older adults with chronic insomnia: mediators and moderators in a randomized controlled trial of brief behavioral therapy (BBT-I). J Clin Sleep Med. 2017;13(11):1243–1254. PMID:28992829

The Chandra Source Catalog: Source Variability

NASA Astrophysics Data System (ADS)

Nowak, Michael; Rots, A. H.; McCollough, M. L.; Primini, F. A.; Glotfelty, K. J.; Bonaventura, N. R.; Chen, J. C.; Davis, J. E.; Doe, S. M.; Evans, J. D.; Fabbiano, G.; Galle, E.; Gibbs, D. G.; Grier, J. D.; Hain, R.; Hall, D. M.; Harbo, P. N.; He, X.; Houck, J. C.; Karovska, M.; Lauer, J.; McDowell, J. C.; Miller, J. B.; Mitschang, A. W.; Morgan, D. L.; Nichols, J. S.; Plummer, D. A.; Refsdal, B. L.; Siemiginowska, A. L.; Sundheim, B. A.; Tibbetts, M. S.; Van Stone, D. W.; Winkelman, S. L.; Zografou, P.

2009-01-01

The Chandra Source Catalog (CSC) contains fields of view that have been studied with individual, uninterrupted observations that span integration times ranging from 1 ksec to 160 ksec, and a large number of which have received (multiple) repeat observations days to years later. The CSC thus offers an unprecedented look at the variability of the X-ray sky over a broad range of time scales, and across a wide diversity of variable X-ray sources: stars in the local galactic neighborhood, galactic and extragalactic X-ray binaries, Active Galactic Nuclei, etc. Here we describe the methods used to identify and quantify source variability within a single observation, and the methods used to assess the variability of a source when detected in multiple, individual observations. Three tests are used to detect source variability within a single observation: the Kolmogorov-Smirnov test and its variant, the Kuiper test, and a Bayesian approach originally suggested by Gregory and Loredo. The latter test not only provides an indicator of variability, but is also used to create a best estimate of the variable lightcurve shape. We assess the performance of these tests via simulation of statistically stationary, variable processes with arbitrary input power spectral densities (here we concentrate on results of red noise simulations) at variety of mean count rates and fractional root mean square variabilities relevant to CSC sources. We also assess the false positive rate via simulations of constant sources whose sole source of fluctuation is Poisson noise. We compare these simulations to a preliminary assessment of the variability found in real CSC sources, and estimate the variability sensitivities of the CSC.

The Chandra Source Catalog: Source Variability

NASA Astrophysics Data System (ADS)

Nowak, Michael; Rots, A. H.; McCollough, M. L.; Primini, F. A.; Glotfelty, K. J.; Bonaventura, N. R.; Chen, J. C.; Davis, J. E.; Doe, S. M.; Evans, J. D.; Evans, I.; Fabbiano, G.; Galle, E. C.; Gibbs, D. G., II; Grier, J. D.; Hain, R.; Hall, D. M.; Harbo, P. N.; He, X.; Houck, J. C.; Karovska, M.; Lauer, J.; McDowell, J. C.; Miller, J. B.; Mitschang, A. W.; Morgan, D. L.; Nichols, J. S.; Plummer, D. A.; Refsdal, B. L.; Siemiginowska, A. L.; Sundheim, B. A.; Tibbetts, M. S.; van Stone, D. W.; Winkelman, S. L.; Zografou, P.

2009-09-01

The Chandra Source Catalog (CSC) contains fields of view that have been studied with individual, uninterrupted observations that span integration times ranging from 1 ksec to 160 ksec, and a large number of which have received (multiple) repeat observations days to years later. The CSC thus offers an unprecedented look at the variability of the X-ray sky over a broad range of time scales, and across a wide diversity of variable X-ray sources: stars in the local galactic neighborhood, galactic and extragalactic X-ray binaries, Active Galactic Nuclei, etc. Here we describe the methods used to identify and quantify source variability within a single observation, and the methods used to assess the variability of a source when detected in multiple, individual observations. Three tests are used to detect source variability within a single observation: the Kolmogorov-Smirnov test and its variant, the Kuiper test, and a Bayesian approach originally suggested by Gregory and Loredo. The latter test not only provides an indicator of variability, but is also used to create a best estimate of the variable lightcurve shape. We assess the performance of these tests via simulation of statistically stationary, variable processes with arbitrary input power spectral densities (here we concentrate on results of red noise simulations) at variety of mean count rates and fractional root mean square variabilities relevant to CSC sources. We also assess the false positive rate via simulations of constant sources whose sole source of fluctuation is Poisson noise. We compare these simulations to an assessment of the variability found in real CSC sources, and estimate the variability sensitivities of the CSC.

Daily affect variability and context-specific alcohol consumption.

PubMed

Mohr, Cynthia D; Arpin, Sarah; McCabe, Cameron T

2015-11-01

Research explored the effects of variability in negative and positive affect on alcohol consumption, specifying daily fluctuation in affect as a critical form of emotion dysregulation. Using daily process methodology allows for a more objective calculation of affect variability relative to traditional self-reports. The present study models within-person negative and positive affect variabilities as predictors of context-specific consumption (i.e. solitary vs. social drinking), controlling for mean levels of affect. A community sample of moderate-to-heavy drinkers (n = 47; 49% women) from a US metropolitan area reported on affect and alcohol consumption thrice daily for 30 days via a handheld electronic interviewer. Within-person affect variability was calculated using daily standard deviations in positive and negative affect. Within person, greater negative and positive variabilities are related to greater daily solitary and social consumption. Across study days, mean levels of negative and positive affect variabilities related to greater social consumption between persons; yet, aggregated negative affect variability was related to less solitary consumption. Results affirm affect variability as a unique predictor of alcohol consumption, independent of mean affect levels. Yet, it is important to differentiate social context of consumption, as well as type of affect variability, particularly at the between-person level. These distinctions help clarify inconsistencies in the self-medication literature regarding associations between average levels of affect and consumption. Importantly, consistent within-person relationships for both variabilities support arguments that both negative and positive affect variabilities are detrimental and reflect an inability to regulate emotional experience. © 2015 Australasian Professional Society on Alcohol and other Drugs.

Dyadic variability in mother-adolescent interactions: developmental trajectories and associations with psychosocial functioning.

PubMed

Van der Giessen, Daniёlle; Branje, Susan J T; Frijns, Tom; Meeus, Wim H J

2013-01-01

Dyadic variability is considered to be a key mechanism in the development of mother-adolescent relationships, and low levels of dyadic flexibility are thought to be associated with behavior and relationship problems. The present observational study examined heterogeneity in the development of dyadic variability in mother-adolescent interactions and associations with psychosocial functioning. Dyadic variability refers to the range of emotional states during interactions of mother-adolescent dyads. During five annual home visits, 92 mother-adolescent dyads (M age T1 = 13; 65.2 % boys) were videotaped while discussing a conflict, and they completed several questionnaires on adolescents' aggressive behavior and adolescents' and mothers' perceived relationship quality. Two types of dyads were distinguished: low variability dyads (52 %) and high decreasing variability dyads (48 %). Over time, high decreasing variability dyads were characterized by a broader emotional repertoire than low variability dyads. Moreover, these two dyad types had distinct developmental patterns of psychosocial adjustment. Over time, high decreasing variability dyads showed lower levels of adolescents' aggressive behavior, and higher levels of perceived relationship quality than low variability dyads. These findings suggest that over time more dyadic variability is associated with less adjustment problems and a more constructive development of the mother-adolescent relationship. Adaptive interactions seem to be characterized by a wider range of emotional states and mothers should guide adolescents during interactions to express both positive and negative affect. Observing the dyadic variability during mother-adolescent interactions can help clinicians to distinguish adaptive from maladaptive mother-adolescent dyads.

Estimating an area-level socioeconomic status index and its association with colonoscopy screening adherence.

PubMed

Wheeler, David C; Czarnota, Jenna; Jones, Resa M

2017-01-01

Socioeconomic status (SES) is often considered a risk factor for health outcomes. SES is typically measured using individual variables of educational attainment, income, housing, and employment variables or a composite of these variables. Approaches to building the composite variable include using equal weights for each variable or estimating the weights with principal components analysis or factor analysis. However, these methods do not consider the relationship between the outcome and the SES variables when constructing the index. In this project, we used weighted quantile sum (WQS) regression to estimate an area-level SES index and its effect in a model of colonoscopy screening adherence in the Minnesota-Wisconsin Metropolitan Statistical Area. We considered several specifications of the SES index including using different spatial scales (e.g., census block group-level, tract-level) for the SES variables. We found a significant positive association (odds ratio = 1.17, 95% CI: 1.15-1.19) between the SES index and colonoscopy adherence in the best fitting model. The model with the best goodness-of-fit included a multi-scale SES index with 10 variables at the block group-level and one at the tract-level, with home ownership, race, and income among the most important variables. Contrary to previous index construction, our results were not consistent with an assumption of equal importance of variables in the SES index when explaining colonoscopy screening adherence. Our approach is applicable in any study where an SES index is considered as a variable in a regression model and the weights for the SES variables are not known in advance.

Dosimetric impact of contouring and image registration variability on dynamic 125I prostate brachytherapy.

PubMed

Westendorp, Hendrik; Surmann, Kathrin; van de Pol, Sandrine M G; Hoekstra, Carel J; Kattevilder, Robert A J; Nuver, Tonnis T; Moerland, Marinus A; Slump, Cornelis H; Minken, André W

The quality of permanent prostate brachytherapy can be increased by addition of imaging modalities in the intraoperative procedure. This addition involves image registration, which inherently has inter- and intraobserver variabilities. We sought to quantify the inter- and intraobserver variabilities in geometry and dosimetry for contouring and image registration and analyze the results for our dynamic 125 I brachytherapy procedure. Five observers contoured 11 transrectal ultrasound (TRUS) data sets three times and 11 CT data sets one time. The observers registered 11 TRUS and MRI data sets to cone beam CT (CBCT) using fiducial gold markers. Geometrical and dosimetrical inter- and intraobserver variabilities were assessed. For the contouring study, structures were subdivided into three parts along the craniocaudal axis. We analyzed 165 observations. Interobserver geometrical variability for prostate was 1.1 mm, resulting in a dosimetric variability of 1.6% for V 100 and 9.3% for D 90 . The geometric intraobserver variability was 0.6 mm with a V 100 of 0.7% and D 90 of 1.1%. TRUS-CBCT registration showed an interobserver variability in V 100 of 2.0% and D 90 of 3.1%. Intraobserver variabilities were 0.9% and 1.6%, respectively. For MRI-CBCT registration, V 100 and D 90 were 1.3% and 2.1%. Intraobserver variabilities were 0.7% and 1.1% for the same. Prostate dosimetry is affected by interobserver contouring and registration variability. The observed variability is smaller than underdosages that are adapted during our dynamic brachytherapy procedure. Copyright © 2017 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Linking environmental variability to population and community dynamics: Chapter 7

USGS Publications Warehouse

Pantel, Jelena H.; Pendleton, Daniel E.; Walters, Annika W.; Rogers, Lauren A.

2014-01-01

Linking population and community responses to environmental variability lies at the heart of ecology, yet methodological approaches vary and existence of broad patterns spanning taxonomic groups remains unclear. We review the characteristics of environmental and biological variability. Classic approaches to link environmental variability to population and community variability are discussed as are the importance of biotic factors such as life history and community interactions. In addition to classic approaches, newer techniques such as information theory and artificial neural networks are reviewed. The establishment and expansion of observing networks will provide new long-term ecological time-series data, and with it, opportunities to incorporate environmental variability into research. This review can help guide future research in the field of ecological and environmental variability.

Study of process variables associated with manufacturing hermetically-sealed nickel-cadmium cells

NASA Technical Reports Server (NTRS)

Miller, L.

1974-01-01

A two year study of the major process variables associated with the manufacturing process for sealed, nickel-cadmium, areospace cells is summarized. Effort was directed toward identifying the major process variables associated with a manufacturing process, experimentally assessing each variable's effect, and imposing the necessary changes (optimization) and controls for the critical process variables to improve results and uniformity. A critical process variable associated with the sintered nickel plaque manufacturing process was identified as the manual forming operation. Critical process variables identified with the positive electrode impregnation/polarization process were impregnation solution temperature, free acid content, vacuum impregnation, and sintered plaque strength. Positive and negative electrodes were identified as a major source of carbonate contamination in sealed cells.

Choice of Control Variables in Variational Data Assimilation and Its Analysis and Forecast Impact

NASA Astrophysics Data System (ADS)

Xie, Yuanfu; Sun, Jenny; Fang, Wei-ting

2014-05-01

Choice of control variables directly impacts the analysis qualify of a variational data assimilation and its forecasts. A theory on selecting control variables for wind and moisture field is introduced for 3DVAR or 4DVAR. For a good control variable selection, Parseval's theory is applied to 3-4DVAR and the behavior of different control variables is illustrated in physical and Fourier space in terms of minimization condition, meteorological dynamic scales and practical implementation. The computational and meteorological benefits will be discussed. Numerical experiments have been performed using WRF-DA for wind control variables and CRTM for moisture control variables. It is evident of the WRF forecast improvement and faster convergence of CRTM satellite data assimilation.

Mapping Variables.

ERIC Educational Resources Information Center

Stone, Mark H.; Wright, Benjamin D.; Stenner, A. Jackson

1999-01-01

Describes mapping variables, the principal technique for planning and constructing a test or rating instrument. A variable map is also useful for interpreting results. Provides several maps to show the importance and value of mapping a variable by person and item data. (Author/SLD)

Modelling the co-evolution of indirect genetic effects and inherited variability.

PubMed

Marjanovic, Jovana; Mulder, Han A; Rönnegård, Lars; Bijma, Piter

2018-03-28

When individuals interact, their phenotypes may be affected not only by their own genes but also by genes in their social partners. This phenomenon is known as Indirect Genetic Effects (IGEs). In aquaculture species and some plants, however, competition not only affects trait levels of individuals, but also inflates variability of trait values among individuals. In the field of quantitative genetics, the variability of trait values has been studied as a quantitative trait in itself, and is often referred to as inherited variability. Such studies, however, consider only the genetic effect of the focal individual on trait variability and do not make a connection to competition. Although the observed phenotypic relationship between competition and variability suggests an underlying genetic relationship, the current quantitative genetic models of IGE and inherited variability do not allow for such a relationship. The lack of quantitative genetic models that connect IGEs to inherited variability limits our understanding of the potential of variability to respond to selection, both in nature and agriculture. Models of trait levels, for example, show that IGEs may considerably change heritable variation in trait values. Currently, we lack the tools to investigate whether this result extends to variability of trait values. Here we present a model that integrates IGEs and inherited variability. In this model, the target phenotype, say growth rate, is a function of the genetic and environmental effects of the focal individual and of the difference in trait value between the social partner and the focal individual, multiplied by a regression coefficient. The regression coefficient is a genetic trait, which is a measure of cooperation; a negative value indicates competition, a positive value cooperation, and an increasing value due to selection indicates the evolution of cooperation. In contrast to the existing quantitative genetic models, our model allows for co-evolution of IGEs and variability, as the regression coefficient can respond to selection. Our simulations show that the model results in increased variability of body weight with increasing competition. When competition decreases, i.e., cooperation evolves, variability becomes significantly smaller. Hence, our model facilitates quantitative genetic studies on the relationship between IGEs and inherited variability. Moreover, our findings suggest that we may have been overlooking an entire level of genetic variation in variability, the one due to IGEs.

Temperature Variability Associated with the Middle Atmosphere Electrodynamics (MAE-1) Campaign

NASA Technical Reports Server (NTRS)

Schmidlin, F. J.

1999-01-01

Meteorological rockets launched during the Middle Atmosphere Electrodynamics (MAE-1) Campaign in October 1980 from Andoya Rocket Range (ARR), Norway, exhibited large and unexpected temperature variability. Temperatures were found to vary as much as 20 C within a few hours and demonstrated a similar type of variability from one day to the next. Following examination of the reduced rocketsonde profiles the question was raised whether the observed variability was due to natural atmospheric variability or instrument malfunction. Small-scale variability, as observed, may result from one or multiple sources, e.g., intense storms upstream from the observing site, orography such as mountain waves off of the Greenland Plateau, convective activity, gravity waves, etc. Arranging the observations spaced over time showed that the perturbations moved downward. Prior to MAE-1 very few small rocketsonde measurements had been launched from ARR, thus the quality of the initial measurements in early October caused concern when the large variability was noted. We discuss the errors of the rocketsonde measurements, graphically review the nature of the variability observed, compare the data with other measurements, and postulate a possible cause for the variability.

Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fyke, Jeremy; Lenaerts, Jan T. M.; Wang, Hailong

Annually averaged precipitation in the form of snow, the dominant term of the Antarctic Ice Sheet surface mass balance, displays large spatial and temporal variability. Here we present an analysis of spatial patterns of regional Antarctic precipitation variability and their impact on integrated Antarctic surface mass balance variability simulated as part of a preindustrial 1800-year global, fully coupled Community Earth System Model simulation. Correlation and composite analyses based on this output allow for a robust exploration of Antarctic precipitation variability. We identify statistically significant relationships between precipitation patterns across Antarctica that are corroborated by climate reanalyses, regional modeling and icemore » core records. These patterns are driven by variability in large-scale atmospheric moisture transport, which itself is characterized by decadal- to centennial-scale oscillations around the long-term mean. We suggest that this heterogeneity in Antarctic precipitation variability has a dampening effect on overall Antarctic surface mass balance variability, with implications for regulation of Antarctic-sourced sea level variability, detection of an emergent anthropogenic signal in Antarctic mass trends and identification of Antarctic mass loss accelerations.« less

Correlation and agreement: overview and clarification of competing concepts and measures.

PubMed

Liu, Jinyuan; Tang, Wan; Chen, Guanqin; Lu, Yin; Feng, Changyong; Tu, Xin M

2016-04-25

Agreement and correlation are widely-used concepts that assess the association between variables. Although similar and related, they represent completely different notions of association. Assessing agreement between variables assumes that the variables measure the same construct, while correlation of variables can be assessed for variables that measure completely different constructs. This conceptual difference requires the use of different statistical methods, and when assessing agreement or correlation, the statistical method may vary depending on the distribution of the data and the interest of the investigator. For example, the Pearson correlation, a popular measure of correlation between continuous variables, is only informative when applied to variables that have linear relationships; it may be non-informative or even misleading when applied to variables that are not linearly related. Likewise, the intraclass correlation, a popular measure of agreement between continuous variables, may not provide sufficient information for investigators if the nature of poor agreement is of interest. This report reviews the concepts of agreement and correlation and discusses differences in the application of several commonly used measures.

Dynamics and spatio-temporal variability of environmental factors in Eastern Australia using functional principal component analysis

USGS Publications Warehouse

Szabo, J.K.; Fedriani, E.M.; Segovia-Gonzalez, M. M.; Astheimer, L.B.; Hooper, M.J.

2010-01-01

This paper introduces a new technique in ecology to analyze spatial and temporal variability in environmental variables. By using simple statistics, we explore the relations between abiotic and biotic variables that influence animal distributions. However, spatial and temporal variability in rainfall, a key variable in ecological studies, can cause difficulties to any basic model including time evolution. The study was of a landscape scale (three million square kilometers in eastern Australia), mainly over the period of 19982004. We simultaneously considered qualitative spatial (soil and habitat types) and quantitative temporal (rainfall) variables in a Geographical Information System environment. In addition to some techniques commonly used in ecology, we applied a new method, Functional Principal Component Analysis, which proved to be very suitable for this case, as it explained more than 97% of the total variance of the rainfall data, providing us with substitute variables that are easier to manage and are even able to explain rainfall patterns. The main variable came from a habitat classification that showed strong correlations with rainfall values and soil types. ?? 2010 World Scientific Publishing Company.

Plausible Effect of Weather on Atlantic Meridional Overturning Circulation with a Coupled General Circulation Model

NASA Astrophysics Data System (ADS)

Liu, Zedong; Wan, Xiuquan

2018-04-01

The Atlantic meridional overturning circulation (AMOC) is a vital component of the global ocean circulation and the heat engine of the climate system. Through the use of a coupled general circulation model, this study examines the role of synoptic systems on the AMOC and presents evidence that internally generated high-frequency, synoptic-scale weather variability in the atmosphere could play a significant role in maintaining the overall strength and variability of the AMOC, thereby affecting climate variability and change. Results of a novel coupling technique show that the strength and variability of the AMOC are greatly reduced once the synoptic weather variability is suppressed in the coupled model. The strength and variability of the AMOC are closely linked to deep convection events at high latitudes, which could be strongly affected by the weather variability. Our results imply that synoptic weather systems are important in driving the AMOC and its variability. Thus, interactions between atmospheric weather variability and AMOC may be an important feedback mechanism of the global climate system and need to be taken into consideration in future climate change studies.

Suppression of chaos at slow variables by rapidly mixing fast dynamics

NASA Astrophysics Data System (ADS)

Abramov, R.

2012-04-01

One of the key questions about chaotic multiscale systems is how the fast dynamics affects chaos at the slow variables, and, therefore, impacts uncertainty and predictability of the slow dynamics. Here we demonstrate that the linear slow-fast coupling with the total energy conservation property promotes the suppression of chaos at the slow variables through the rapid mixing at the fast variables, both theoretically and through numerical simulations. A suitable mathematical framework is developed, connecting the slow dynamics on the tangent subspaces to the infinite-time linear response of the mean state to a constant external forcing at the fast variables. Additionally, it is shown that the uncoupled dynamics for the slow variables may remain chaotic while the complete multiscale system loses chaos and becomes completely predictable at the slow variables through increasing chaos and turbulence at the fast variables. This result contradicts the common sense intuition, where, naturally, one would think that coupling a slow weakly chaotic system with another much faster and much stronger mixing system would result in general increase of chaos at the slow variables.

Parenting Behaviors, Parent Heart Rate Variability, and Their Associations with Adolescent Heart Rate Variability.

PubMed

Graham, Rebecca A; Scott, Brandon G; Weems, Carl F

2017-05-01

Adolescence is a potentially important time in the development of emotion regulation and parenting behaviors may play a role. We examined associations among parenting behaviors, parent resting heart rate variability, adolescent resting heart rate variability and parenting behaviors as moderators of the association between parent and adolescent resting heart rate variability. Ninety-seven youth (11-17 years; 49.5 % female; 34 % African American, 37.1 % Euro-American, 22.6 % other/mixed ethnic background, and 7.2 % Hispanic) and their parents (n = 81) completed a physiological assessment and questionnaires assessing parenting behaviors. Inconsistent discipline and corporal punishment were negatively associated with adolescent resting heart rate variability, while positive parenting and parental involvement were positively associated. Inconsistent discipline and parental involvement moderated the relationship between parent and adolescent resting heart rate variability. The findings provide evidence for a role of parenting behaviors in shaping the development of adolescent resting heart rate variability with inconsistent discipline and parental involvement potentially influencing the entrainment of resting heart rate variability in parents and their children.

Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variability

DOE PAGES

Fyke, Jeremy; Lenaerts, Jan T. M.; Wang, Hailong

2017-11-15

Annually averaged precipitation in the form of snow, the dominant term of the Antarctic Ice Sheet surface mass balance, displays large spatial and temporal variability. Here we present an analysis of spatial patterns of regional Antarctic precipitation variability and their impact on integrated Antarctic surface mass balance variability simulated as part of a preindustrial 1800-year global, fully coupled Community Earth System Model simulation. Correlation and composite analyses based on this output allow for a robust exploration of Antarctic precipitation variability. We identify statistically significant relationships between precipitation patterns across Antarctica that are corroborated by climate reanalyses, regional modeling and icemore » core records. These patterns are driven by variability in large-scale atmospheric moisture transport, which itself is characterized by decadal- to centennial-scale oscillations around the long-term mean. We suggest that this heterogeneity in Antarctic precipitation variability has a dampening effect on overall Antarctic surface mass balance variability, with implications for regulation of Antarctic-sourced sea level variability, detection of an emergent anthropogenic signal in Antarctic mass trends and identification of Antarctic mass loss accelerations.« less

Analysis of walking variability through simultaneous evaluation of the head, lumbar, and lower-extremity acceleration in healthy youth

PubMed Central

Toda, Haruki; Nagano, Akinori; Luo, Zhiwei

2016-01-01

[Purpose] The purpose of this study was to clarify whether walking speed affects acceleration variability of the head, lumbar, and lower extremity by simultaneously evaluating of acceleration. [Subjects and Methods] Twenty young individuals recruited from among the staff at Kurashiki Heisei Hospital participated in this study. Eight accelerometers were used to measure the head, lumbar and lower extremity accelerations. The participants were instructed to walk at five walking speeds prescribed by a metronome. Acceleration variability was assessed by a cross-correlation analysis normalized using z-transform in order to evaluate stride-to-stride variability. [Results] Vertical acceleration variability was the smallest in all body parts, and walking speed effect had laterality. Antero-posterior acceleration variability was significantly associated with walking speed at sites other than the head. Medio-lateral acceleration variability of the bilateral hip alone was smaller than the antero-posterior variability. [Conclusion] The findings of this study suggest that the effect of walking speed changes on the stride-to-stride acceleration variability was individual for each body parts, and differs among directions. PMID:27390419

Variable rate irrigation (VRI)

USDA-ARS?s Scientific Manuscript database

Variable rate irrigation (VRI) technology is now offered by all major manufacturers of moving irrigation systems, mostly on center pivot irrigation systems. Variable irrigation depths may be controlled by sector only, in which case only the speed of the irrigation lateral is regulated. Or, variable ...

ENSO related sea surface salinity variability in the equatorial Pacific

NASA Astrophysics Data System (ADS)

Qu, T.

2016-12-01

Recently available satellite and Argo data have shown coherent, large-scale sea surface salinity (SSS) variability in the equatorial Pacific. Based on this variability, several SSS indices of El Nino have been introduced by previous studies. Combining results from an ocean general circulation model with available satellite and in-situ observations, this study investigates the SSS variability and its associated SSS indices in the equatorial Pacific. The ocean's role and in particular the vertical entrainment of subtropical waters in this variability are discussed, which suggests that the SSS variability in the equatorial Pacific may play some active role in ENSO evolution.

Heralded processes on continuous-variable spaces as quantum maps

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ferreyrol, Franck; Spagnolo, Nicolò; Blandino, Rémi

2014-12-04

Heralding processes, which only work when a measurement on a part of the system give the good result, are particularly interesting for continuous-variables. They permit non-Gaussian transformations that are necessary for several continuous-variable quantum information tasks. However if maps and quantum process tomography are commonly used to describe quantum transformations in discrete-variable space, they are much rarer in the continuous-variable domain. Also, no convenient tool for representing maps in a way more adapted to the particularities of continuous variables have yet been explored. In this paper we try to fill this gap by presenting such a tool.

Evaluation of solar irradiance models for climate studies

NASA Astrophysics Data System (ADS)

Ball, William; Yeo, Kok-Leng; Krivova, Natalie; Solanki, Sami; Unruh, Yvonne; Morrill, Jeff

2015-04-01

Instruments on satellites have been observing both Total Solar Irradiance (TSI) and Spectral Solar Irradiance (SSI), mainly in the ultraviolet (UV), since 1978. Models were developed to reproduce the observed variability and to compute the variability at wavelengths that were not observed or had an uncertainty too high to determine an accurate rotational or solar cycle variability. However, various models and measurements show different solar cycle SSI variability that lead to different modelled responses of ozone and temperature in the stratosphere, mainly due to the different UV variability in each model, and the global energy balance. The NRLSSI and SATIRE-S models are the most comprehensive reconstructions of solar irradiance variability for the period from 1978 to the present day. But while NRLSSI and SATIRE-S show similar solar cycle variability below 250 nm, between 250 and 400 nm SATIRE-S typically displays 50% larger variability, which is however, still significantly less then suggested by recent SORCE data. Due to large uncertainties and inconsistencies in some observational datasets, it is difficult to determine in a simple way which model is likely to be closer to the true solar variability. We review solar irradiance variability measurements and modelling and employ new analysis that sheds light on the causes of the discrepancies between the two models and with the observations.

Spatial and temporal variability of interhemispheric transport times

NASA Astrophysics Data System (ADS)

Wu, Xiaokang; Yang, Huang; Waugh, Darryn W.; Orbe, Clara; Tilmes, Simone; Lamarque, Jean-Francois

2018-05-01

The seasonal and interannual variability of transport times from the northern midlatitude surface into the Southern Hemisphere is examined using simulations of three idealized age tracers: an ideal age tracer that yields the mean transit time from northern midlatitudes and two tracers with uniform 50- and 5-day decay. For all tracers the largest seasonal and interannual variability occurs near the surface within the tropics and is generally closely coupled to movement of the Intertropical Convergence Zone (ITCZ). There are, however, notable differences in variability between the different tracers. The largest seasonal and interannual variability in the mean age is generally confined to latitudes spanning the ITCZ, with very weak variability in the southern extratropics. In contrast, for tracers subject to spatially uniform exponential loss the peak variability tends to be south of the ITCZ, and there is a smaller contrast between tropical and extratropical variability. These differences in variability occur because the distribution of transit times from northern midlatitudes is very broad and tracers with more rapid loss are more sensitive to changes in fast transit times than the mean age tracer. These simulations suggest that the seasonal-interannual variability in the southern extratropics of trace gases with predominantly NH midlatitude sources may differ depending on the gases' chemical lifetimes.

Bio-inspired online variable recruitment control of fluidic artificial muscles

NASA Astrophysics Data System (ADS)

Jenkins, Tyler E.; Chapman, Edward M.; Bryant, Matthew

2016-12-01

This paper details the creation of a hybrid variable recruitment control scheme for fluidic artificial muscle (FAM) actuators with an emphasis on maximizing system efficiency and switching control performance. Variable recruitment is the process of altering a system’s active number of actuators, allowing operation in distinct force regimes. Previously, FAM variable recruitment was only quantified with offline, manual valve switching; this study addresses the creation and characterization of novel, on-line FAM switching control algorithms. The bio-inspired algorithms are implemented in conjunction with a PID and model-based controller, and applied to a simulated plant model. Variable recruitment transition effects and chatter rejection are explored via a sensitivity analysis, allowing a system designer to weigh tradeoffs in actuator modeling, algorithm choice, and necessary hardware. Variable recruitment is further developed through simulation of a robotic arm tracking a variety of spline position inputs, requiring several levels of actuator recruitment. Switching controller performance is quantified and compared with baseline systems lacking variable recruitment. The work extends current variable recruitment knowledge by creating novel online variable recruitment control schemes, and exploring how online actuator recruitment affects system efficiency and control performance. Key topics associated with implementing a variable recruitment scheme, including the effects of modeling inaccuracies, hardware considerations, and switching transition concerns are also addressed.

How potentially predictable are midlatitude ocean currents?

PubMed Central

Nonaka, Masami; Sasai, Yoshikazu; Sasaki, Hideharu; Taguchi, Bunmei; Nakamura, Hisashi

2016-01-01

Predictability of atmospheric variability is known to be limited owing to significant uncertainty that arises from intrinsic variability generated independently of external forcing and/or boundary conditions. Observed atmospheric variability is therefore regarded as just a single realization among different dynamical states that could occur. In contrast, subject to wind, thermal and fresh-water forcing at the surface, the ocean circulation has been considered to be rather deterministic under the prescribed atmospheric forcing, and it still remains unknown how uncertain the upper-ocean circulation variability is. This study evaluates how much uncertainty the oceanic interannual variability can potentially have, through multiple simulations with an eddy-resolving ocean general circulation model driven by the observed interannually-varying atmospheric forcing under slightly different conditions. These ensemble “hindcast” experiments have revealed substantial uncertainty due to intrinsic variability in the extratropical ocean circulation that limits potential predictability of its interannual variability, especially along the strong western boundary currents (WBCs) in mid-latitudes, including the Kuroshio and its eastward extention. The intrinsic variability also greatly limits potential predictability of meso-scale oceanic eddy activity. These findings suggest that multi-member ensemble simulations are essential for understanding and predicting variability in the WBCs, which are important for weather and climate variability and marine ecosystems. PMID:26831954

Global patterns of declining temperature variability from the Last Glacial Maximum to the Holocene

NASA Astrophysics Data System (ADS)

Rehfeld, Kira; Münch, Thomas; Ho, Sze Ling; Laepple, Thomas

2018-02-01

Changes in climate variability are as important for society to address as are changes in mean climate. Contrasting temperature variability during the Last Glacial Maximum and the Holocene can provide insights into the relationship between the mean state of the climate and its variability. However, although glacial-interglacial changes in variability have been quantified for Greenland, a global view remains elusive. Here we use a network of marine and terrestrial temperature proxies to show that temperature variability decreased globally by a factor of four as the climate warmed by 3-8 degrees Celsius from the Last Glacial Maximum (around 21,000 years ago) to the Holocene epoch (the past 11,500 years). This decrease had a clear zonal pattern, with little change in the tropics (by a factor of only 1.6-2.8) and greater change in the mid-latitudes of both hemispheres (by a factor of 3.3-14). By contrast, Greenland ice-core records show a reduction in temperature variability by a factor of 73, suggesting influences beyond local temperature or a decoupling of atmospheric and global surface temperature variability for Greenland. The overall pattern of reduced variability can be explained by changes in the meridional temperature gradient, a mechanism that points to further decreases in temperature variability in a warmer future.

Hedonic price models with omitted variables and measurement errors: a constrained autoregression-structural equation modeling approach with application to urban Indonesia

NASA Astrophysics Data System (ADS)

Suparman, Yusep; Folmer, Henk; Oud, Johan H. L.

2014-01-01

Omitted variables and measurement errors in explanatory variables frequently occur in hedonic price models. Ignoring these problems leads to biased estimators. In this paper, we develop a constrained autoregression-structural equation model (ASEM) to handle both types of problems. Standard panel data models to handle omitted variables bias are based on the assumption that the omitted variables are time-invariant. ASEM allows handling of both time-varying and time-invariant omitted variables by constrained autoregression. In the case of measurement error, standard approaches require additional external information which is usually difficult to obtain. ASEM exploits the fact that panel data are repeatedly measured which allows decomposing the variance of a variable into the true variance and the variance due to measurement error. We apply ASEM to estimate a hedonic housing model for urban Indonesia. To get insight into the consequences of measurement error and omitted variables, we compare the ASEM estimates with the outcomes of (1) a standard SEM, which does not account for omitted variables, (2) a constrained autoregression model, which does not account for measurement error, and (3) a fixed effects hedonic model, which ignores measurement error and time-varying omitted variables. The differences between the ASEM estimates and the outcomes of the three alternative approaches are substantial.

Global patterns of declining temperature variability from the Last Glacial Maximum to the Holocene.

PubMed

Rehfeld, Kira; Münch, Thomas; Ho, Sze Ling; Laepple, Thomas

2018-02-15

Changes in climate variability are as important for society to address as are changes in mean climate. Contrasting temperature variability during the Last Glacial Maximum and the Holocene can provide insights into the relationship between the mean state of the climate and its variability. However, although glacial-interglacial changes in variability have been quantified for Greenland, a global view remains elusive. Here we use a network of marine and terrestrial temperature proxies to show that temperature variability decreased globally by a factor of four as the climate warmed by 3-8 degrees Celsius from the Last Glacial Maximum (around 21,000 years ago) to the Holocene epoch (the past 11,500 years). This decrease had a clear zonal pattern, with little change in the tropics (by a factor of only 1.6-2.8) and greater change in the mid-latitudes of both hemispheres (by a factor of 3.3-14). By contrast, Greenland ice-core records show a reduction in temperature variability by a factor of 73, suggesting influences beyond local temperature or a decoupling of atmospheric and global surface temperature variability for Greenland. The overall pattern of reduced variability can be explained by changes in the meridional temperature gradient, a mechanism that points to further decreases in temperature variability in a warmer future.

A Sensory Material Approach for Reducing Variability in Additively Manufactured Metal Parts.

PubMed

Franco, B E; Ma, J; Loveall, B; Tapia, G A; Karayagiz, K; Liu, J; Elwany, A; Arroyave, R; Karaman, I

2017-06-15

Despite the recent growth in interest for metal additive manufacturing (AM) in the biomedical and aerospace industries, variability in the performance, composition, and microstructure of AM parts remains a major impediment to its widespread adoption. The underlying physical mechanisms, which cause variability, as well as the scale and nature of variability are not well understood, and current methods are ineffective at capturing these details. Here, a Nickel-Titanium alloy is used as a sensory material in order to quantitatively, and rather rapidly, observe compositional and/or microstructural variability in selective laser melting manufactured parts; thereby providing a means to evaluate the role of process parameters on the variability. We perform detailed microstructural investigations using transmission electron microscopy at various locations to reveal the origins of microstructural variability in this sensory material. This approach helped reveal how reducing the distance between adjacent laser scans below a critical value greatly reduces both the in-sample and sample-to-sample variability. Microstructural investigations revealed that when the laser scan distance is wide, there is an inhomogeneity in subgrain size, precipitate distribution, and dislocation density in the microstructure, responsible for the observed variability. These results provide an important first step towards understanding the nature of variability in additively manufactured parts.

Variable Behavior and Repeated Learning in Two Mouse Strains: Developmental and Genetic Contributions.

PubMed

Arnold, Megan A; Newland, M Christopher

2018-06-16

Behavioral inflexibility is often assessed using reversal learning tasks, which require a relatively low degree of response variability. No studies have assessed sensitivity to reinforcement contingencies that specifically select highly variable response patterns in mice, let alone in models of neurodevelopmental disorders involving limited response variation. Operant variability and incremental repeated acquisition (IRA) were used to assess unique aspects of behavioral variability of two mouse strains: BALB/c, a model of some deficits in ASD, and C57Bl/6. On the operant variability task, BALB/c mice responded more repetitively during adolescence than C57Bl/6 mice when reinforcement did not require variability but responded more variably when reinforcement required variability. During IRA testing in adulthood, both strains acquired an unchanging, performance sequence equally well. Strain differences emerged, however, after novel learning sequences began alternating with the performance sequence: BALB/c mice substantially outperformed C57Bl/6 mice. Using litter-mate controls, it was found that adolescent experience with variability did not affect either learning or performance on the IRA task in adulthood. These findings constrain the use of BALB/c mice as a model of ASD, but once again reveal this strain is highly sensitive to reinforcement contingencies and they are fast and robust learners. Copyright © 2018. Published by Elsevier B.V.

Interannual Variability of the Patagonian Shelf Circulation and Cross-Shelf Exchange

NASA Astrophysics Data System (ADS)

Combes, V.; Matano, R. P.

2016-02-01

Observational studies have already established the general mean circulation and hydrographic characteristics of the Patagonian shelf waters using data from in situ observation, altimetry and more recently from the Aquarius satellite sea surface salinity, but the paucity of those data in time or below the surface leave us with an incomplete picture of the shelf circulation and of its variability. This study discusses the variability of the Patagonian central shelf circulation and off-shelf transport using a high-resolution model experiment for the period 1979-2012. The model solution shows high skill in reproducing the best-known aspects of the shelf and deep-ocean circulations. This study links the variability of the central shelf circulation and off-shelf transport to the wind variability, southern shelf transport variability and large-scale current variability. We find that while the inner and central shelf circulation are principally wind driven, the contribution of the Brazil/Malvinas Confluence (BMC) variability becomes important in the outer shelf and along the shelf break. The model also indicates that whereas the location of the off-shelf transport is controlled by the BMC, its variability is modulated by the southern shelf transport. The variability of the subtropical shelf front, where the fresh southern shelf waters encounters the saline northern shelf waters, is also presented in this study.

Analysis of trends and dominant periodicities in drought variables in India: A wavelet transform based approach

NASA Astrophysics Data System (ADS)

Joshi, Nitin; Gupta, Divya; Suryavanshi, Shakti; Adamowski, Jan; Madramootoo, Chandra A.

2016-12-01

In this study, seasonal trends as well as dominant and significant periods of variability of drought variables were analyzed for 30 rainfall subdivisions in India over 141 years (1871-2012). Standardized precipitation index (SPI) was used as a meteorological drought indicator, and various drought variables (monsoon SPI, non-monsoon SPI, yearly SPI, annual drought duration, annual drought severity and annual drought peak) were analyzed. Discrete wavelet transform was used in conjunction with the Mann-Kendall test to analyze trends and dominant periodicities associated with the drought variables. Furthermore, continuous wavelet transform (CWT) based global wavelet spectrum was used to analyze significant periods of variability associated with the drought variables. From the trend analysis, we observed that over the second half of the 20th century, drought occurrences increased significantly in subdivisions of Northeast and Central India. In both short-term (2-8 years) and decadal (16-32 years) periodicities, the drought variables were found to influence the trend. However, CWT analysis indicated that the dominant periodic components were not significant for most of the geographical subdivisions. Although inter-annual and inter-decadal periodic components play an important role, they may not completely explain the variability associated with the drought variables across the country.

The mortality burden of hourly temperature variability in five capital cities, Australia: Time-series and meta-regression analysis.

PubMed

Cheng, Jian; Xu, Zhiwei; Bambrick, Hilary; Su, Hong; Tong, Shilu; Hu, Wenbiao

2017-12-01

Unstable weather, such as intra- and inter-day temperature variability, can impair the health and shorten the survival time of population around the world. Climate change will cause Earth's surface temperature rise, but has unclear effects on temperature variability, making it urgent to understand the characteristics of the burden of temperature variability on mortality, regionally and nationally. This paper aims to quantify the mortality risk of exposure to short-term temperature variability, estimate the resulting death toll and explore how the strength of temperature variability effects will vary as a function of city-level characteristics. Ten-year (2000-2009) time-series data on temperature and mortality were collected for five largest Australia's cities (Sydney, Melbourne, Brisbane, Perth and Adelaide), collectively registering 708,751 deaths in different climates. Short-term temperature variability was captured and represented as the hourly temperature standard deviation within two days. Three-stage analyses were used to assess the burden of temperature variability on mortality. First, we modelled temperature variability-mortality relation and estimated the relative risk of death for each city, using a time-series quasi-Poisson regression model. Second, we used meta-analysis to pool the city-specific estimates, and meta-regression to explore if some city-level factors will modify the population vulnerability to temperature variability. Finally, we calculated the city-specific deaths attributable to temperature variability, and applied such estimates to the whole of Australia as a reflection of the nation-wide death burden associated with temperature variability. We found evidence of significant associations between temperature variability and mortality in all cities assessed. Deaths associated with each 1°C rise in temperature variability elevated by 0.28% (95% confidence interval (CI): 0.05%, 0.52%) in Melbourne to 1.00% (95%CI: 0.52%, 1.48%) in Brisbane, with a pooled estimate of 0.51% (95%CI: 0.33%, 0.69%) for Australia. Subtropical and temperate regions showed no apparent difference in temperature variability impacts. Meta-regression analyses indicated that the mortality risk could be influenced by city-specific factors: latitude, mean temperature, population density and the prevalence of several chronic diseases. Taking account of contributions from the entire time-series, temperature variability was estimated to account for 0.99% to 3.24% of deaths across cities, with a nation-wide attributable fraction of 1.67% (9.59 deaths per 100, 000 population per year). Hourly temperature variability may be an important risk factor of weather-related deaths and led to a sizeable mortality burden. This study underscores the need for developing specific and effective interventions in Australia to lessen the health consequences of temperature variability. Copyright © 2017. Published by Elsevier Ltd.

Coping and back problems: analysis of multiple data sources on an entire cross-sectional cohort of Swedish military recruits.

PubMed

Leboeuf-Yde, Charlotte; Larsen, Kristian; Ahlstrand, Ingvar; Volinn, Ernest

2006-05-03

As the literature now stands, a bewildering number and variety of biological, psychological and social factors are, apparently, implicated in back problems. However, if and how these have a direct influence on back problems is not clear. Obesity, for example, has in many studies been shown to be associated with back problems but there is no evidence for a causal link. This could be explained by a dearth of suitably designed studies but also because obesity may be but a proxy for some other, truly explanatory variable. Coping has been linked with, particularly, persistent back problems as well as with health in general. The question is, whether coping could be the explanatory link between, for example, these two variables. A cross-sectional study was undertaken using data from the Swedish Army, consisting of the entire cohort of males (N = 48,502) summoned in 1998 to serve in the military. The purpose of the study was to investigate the relation between five independent variables and two dependent variables ("outcome variables"). The independent variables were two anthropomorphic variables (height and body mass index), two psychological variables (intellectual capacity and coping in relation to stress), and one social variable (type of education). The two outcome variables were back problems and ill health. In particular, we wanted to determine whether controlling for coping would affect the associations between the other four independent variables and the two outcome variables. Data for the analysis come from a battery of standardized examinations, including medical examinations, a test of intellectual capacity, and a test of coping in relation to stress. Each of these examinations was conducted independently of the others. Unadjusted and adjusted odds ratios were calculated for the outcome variables of back problems and ill health. The associations between height, body mass index, intellectual capacity, type of education and the two outcome variables (back problems and ill health) were weak to moderate. Additionally, there were strong associations between coping and the two outcome variables and when controlling for coping the previously noted associations diminished or disappeared, whereas none of the other variables had a large effect on the association between coping and the two outcome variables. Coping emerged as strongly associated with both back problem and ill health and coping had a leveling effect on the associations between the other independent variables and the two outcome variables. This study is noteworthy particularly because the association with coping is so robust. It is a retrospective, cross-sectional study, however, and, as such it raises questions of causality; which - if any - came first, inability to cope or back pain? The results of this study call attention to the need for a prospective study, in which coping is clearly defined. Such a study has been undertaken and will be presented separately. Index terms: back pain, coping, education, height, BMI, intellectual capacity, bio-psycho-social model, epidemiology, cohort, cross-sectional study.

A CCD Search for Variable Stars of Spectral Type B in the Northern Hemisphere Open Clusters. VII. NGC 1502

NASA Astrophysics Data System (ADS)

Michalska, G.; Pigulski, A.; Stęlicki, M.; Narwid, A.

2009-12-01

We present results of variability search in the field of the young open cluster NGC 1502. Eight variable stars were discovered. Of six other stars in the observed field that were suspected for variability, we confirm variability of two, including one β Cep star, NGC 1502-26. The remaining four suspects were found to be constant in our photometry. In addition, UBVIC photometry of the well-known massive eclipsing binary SZ Cam was obtained. The new variable stars include: two eclipsing binaries of which one is a relatively bright detached system with an EA-type light curve, an α2 CVn-type variable, an SPB candidate, a field RR Lyr star and three other variables showing variability of unknown origin. The variability of two of them is probably related to their emission in Hα, which has been measured by means of the α index obtained for 57 stars brighter than V≍16 mag in the central part of the observed field. Four other non-variable stars with emission in Hα were also found. Additionally, we provide VIC photometry for stars down to V=17 mag and UB photometry for about 50 brightest stars in the observed field. We also show that the 10 Myr isochrone fits very well the observed color-magnitude diagram if a distance of 1 kpc and mean reddening, E(V-IC)=0.9 mag are adopted.

Impact of Subsurface Temperature Variability on Meteorological Variability: An AGCM Study

NASA Astrophysics Data System (ADS)

Mahanama, S. P.; Koster, R. D.; Liu, P.

2006-05-01

Anomalous atmospheric conditions can lead to surface temperature anomalies, which in turn can lead to temperature anomalies deep in the soil. The deep soil temperature (and the associated ground heat content) has significant memory -- the dissipation of a temperature anomaly may take weeks to months -- and thus deep soil temperature may contribute to the low frequency variability of energy and water variables elsewhere in the system. The memory may even provide some skill to subseasonal and seasonal forecasts. This study uses two long-term AGCM experiments to isolate the contribution of deep soil temperature variability to variability elsewhere in the climate system. The first experiment consists of a standard ensemble of AMIP-type simulations, simulations in which the deep soil temperature variable is allowed to interact with the rest of the system. In the second experiment, the coupling of the deep soil temperature to the rest of the climate system is disabled -- at each grid cell, the local climatological seasonal cycle of deep soil temperature (as determined from the first experiment) is prescribed. By comparing the variability of various atmospheric quantities as generated in the two experiments, we isolate the contribution of interactive deep soil temperature to that variability. The results show that interactive deep soil temperature contributes significantly to surface temperature variability. Interactive deep soil temperature, however, reduces the variability of the hydrological cycle (evaporation and precipitation), largely because it allows for a negative feedback between evaporation and temperature.

Movement variability in the golf swing of male and female skilled golfers.

PubMed

Horan, Sean A; Evans, Kerrie; Kavanagh, Justin J

2011-08-01

Despite the complexity of movement, the swings of skilled golfers are considered to be highly consistent. Interestingly, no direct investigation of movement variability or coupling variability during the swings of skilled golfers has occurred. To determine whether differences in movement variability exist between male and female skilled golfers during the downswing of the full golf swing. Three-dimensional thorax, pelvis, hand, and clubhead data were collected from 19 male (mean ± SD: age = 26 ± 7 yr) and 19 female (age = 25 ± 7 yr) skilled golfers. Variability of segmental movement and clubhead trajectory were examined at three phases of the downswing using discrete (SD) and continuous analyses (spanning set), whereas variability of intersegment coupling was examined using average coefficient of correspondence. Compared with males, females exhibited higher thorax and pelvis variability for axial rotation at the midpoint of the downswing and ball contact (BC). Similarly, thorax-pelvis coupling variability was higher for females than males at both the midpoint of the downswing and BC. Regardless of thorax and pelvis motion, the variability of hand and clubhead trajectory sequentially decreased from the top of the backswing to BC for both males and females. Male and female skilled golfers use different upper body movement strategies during the downswing while achieving similarly low levels of clubhead trajectory variability at BC. It is apparent that the priority of skilled golfers is to progressively minimize hand and clubhead trajectory variability toward BC, despite the individual motion or coupling of the thorax and pelvis.

Predicting change over time in career planning and career exploration for high school students.

PubMed

Creed, Peter A; Patton, Wendy; Prideaux, Lee-Ann

2007-06-01

This study assessed 166 high school students in Grade 8 and again in Grade 10. Four models were tested: (a) whether the T1 predictor variables (career knowledge, indecision, decision-making self efficacy, self-esteem, demographics) predicted the outcome variable (career planning/exploration) at T1; (b) whether the T1 predictor variables predicted the outcome variable at T2; (c) whether the T1 predictor variables predicted change in the outcome variable from T1-T2; and (d) whether changes in the predictor variables from T1-T2 predicted change in the outcome variable from T1-T2. Strong associations (R(2)=34%) were identified for the T1 analysis (confidence, ability and paid work experience were positively associated with career planning/exploration). T1 variables were less useful predictors of career planning/exploration at T2 (R(2)=9%; having more confidence at T1 was associated with more career planning/exploration at T2) and change in career planning/exploration from T1-T2 (R(2)=11%; less confidence and no work experience were associated with change in career planning/exploration from T1-T2). When testing effect of changes in predictor variables predicting changes in outcome variable (R(2)=22%), three important predictors, indecision, work experience and confidence, were identified. Overall, results indicated important roles for self-efficacy and early work experiences in current and future career planning/exploration of high school students.

Perturbing engine performance measurements to determine optimal engine control settings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Li; Lee, Donghoon; Yilmaz, Hakan

Methods and systems for optimizing a performance of a vehicle engine are provided. The method includes determining an initial value for a first engine control parameter based on one or more detected operating conditions of the vehicle engine, determining a value of an engine performance variable, and artificially perturbing the determined value of the engine performance variable. The initial value for the first engine control parameter is then adjusted based on the perturbed engine performance variable causing the engine performance variable to approach a target engine performance variable. Operation of the vehicle engine is controlled based on the adjusted initialmore » value for the first engine control parameter. These acts are repeated until the engine performance variable approaches the target engine performance variable.« less

Variable Stars in the Draco Dwarf Spheroidal Galaxy

NASA Astrophysics Data System (ADS)

Harris, H. C.; Silberman, N. A.; Smith, H. A.

A new survey of the variable stars in the Draco dwarf spheroidal galaxy updates the pioneering study of this galaxy by Baade and Swope (1961). Our improved data, taken in BVI filters with CCD cameras on three telescopes at more than 80 epochs, allow us to investigate the known variables and to discover new, mostly low-amplitude variables. Approximately 300 variables are found and classified, more than double the number of variables analyzed previously. Most are RR Lyraes, with a small fraction of Anomalous Cepheids. This large sample of variables provides a unique opportunity to study the properties of these stars in a single system. This paper discusses the census of RR Lyraes, including RRc-type, double-mode, and Blazhko-effect RR Lyraes, as well as Anomalous Cepheids, and Type II Cepheids in Draco.

Variability in seeds: biological, ecological, and agricultural implications.

PubMed

Mitchell, Jack; Johnston, Iain G; Bassel, George W

2017-02-01

Variability is observed in biology across multiple scales, ranging from populations, individuals, and cells to the molecular components within cells. This review explores the sources and roles of this variability across these scales, focusing on seeds. From a biological perspective, the role and the impact this variability has on seed behaviour and adaptation to the environment is discussed. The consequences of seed variability on agricultural production systems, which demand uniformity, are also examined. We suggest that by understanding the basis and underlying mechanisms of variability in seeds, strategies to increase seed population uniformity can be developed, leading to enhanced agricultural production across variable climatic conditions. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Enhancing the Remote Variable Operations in NPSS/CCDK

NASA Technical Reports Server (NTRS)

Sang, Janche; Follen, Gregory; Kim, Chan; Lopez, Isaac; Townsend, Scott

2001-01-01

Many scientific applications in aerodynamics and solid mechanics are written in Fortran. Refitting these legacy Fortran codes with distributed objects can increase the code reusability. The remote variable scheme provided in NPSS/CCDK helps programmers easily migrate the Fortran codes towards a client-server platform. This scheme gives the client the capability of accessing the variables at the server site. In this paper, we review and enhance the remote variable scheme by using the operator overloading features in C++. The enhancement enables NPSS programmers to use remote variables in much the same way as traditional variables. The remote variable scheme adopts the lazy update approach and the prefetch method. The design strategies and implementation techniques are described in details. Preliminary performance evaluation shows that communication overhead can be greatly reduced.

Prediction of thoracic injury severity in frontal impacts by selected anatomical morphomic variables through model-averaged logistic regression approach.

PubMed

Zhang, Peng; Parenteau, Chantal; Wang, Lu; Holcombe, Sven; Kohoyda-Inglis, Carla; Sullivan, June; Wang, Stewart

2013-11-01

This study resulted in a model-averaging methodology that predicts crash injury risk using vehicle, demographic, and morphomic variables and assesses the importance of individual predictors. The effectiveness of this methodology was illustrated through analysis of occupant chest injuries in frontal vehicle crashes. The crash data were obtained from the International Center for Automotive Medicine (ICAM) database for calendar year 1996 to 2012. The morphomic data are quantitative measurements of variations in human body 3-dimensional anatomy. Morphomics are obtained from imaging records. In this study, morphomics were obtained from chest, abdomen, and spine CT using novel patented algorithms. A NASS-trained crash investigator with over thirty years of experience collected the in-depth crash data. There were 226 cases available with occupants involved in frontal crashes and morphomic measurements. Only cases with complete recorded data were retained for statistical analysis. Logistic regression models were fitted using all possible configurations of vehicle, demographic, and morphomic variables. Different models were ranked by the Akaike Information Criteria (AIC). An averaged logistic regression model approach was used due to the limited sample size relative to the number of variables. This approach is helpful when addressing variable selection, building prediction models, and assessing the importance of individual variables. The final predictive results were developed using this approach, based on the top 100 models in the AIC ranking. Model-averaging minimized model uncertainty, decreased the overall prediction variance, and provided an approach to evaluating the importance of individual variables. There were 17 variables investigated: four vehicle, four demographic, and nine morphomic. More than 130,000 logistic models were investigated in total. The models were characterized into four scenarios to assess individual variable contribution to injury risk. Scenario 1 used vehicle variables; Scenario 2, vehicle and demographic variables; Scenario 3, vehicle and morphomic variables; and Scenario 4 used all variables. AIC was used to rank the models and to address over-fitting. In each scenario, the results based on the top three models and the averages of the top 100 models were presented. The AIC and the area under the receiver operating characteristic curve (AUC) were reported in each model. The models were re-fitted after removing each variable one at a time. The increases of AIC and the decreases of AUC were then assessed to measure the contribution and importance of the individual variables in each model. The importance of the individual variables was also determined by their weighted frequencies of appearance in the top 100 selected models. Overall, the AUC was 0.58 in Scenario 1, 0.78 in Scenario 2, 0.76 in Scenario 3 and 0.82 in Scenario 4. The results showed that morphomic variables are as accurate at predicting injury risk as demographic variables. The results of this study emphasize the importance of including morphomic variables when assessing injury risk. The results also highlight the need for morphomic data in the development of human mathematical models when assessing restraint performance in frontal crashes, since morphomic variables are more "tangible" measurements compared to demographic variables such as age and gender. Copyright © 2013 Elsevier Ltd. All rights reserved.

Biologically-variable rhythmic auditory cues are superior to isochronous cues in fostering natural gait variability in Parkinson's disease.

PubMed

Dotov, D G; Bayard, S; Cochen de Cock, V; Geny, C; Driss, V; Garrigue, G; Bardy, B; Dalla Bella, S

2017-01-01

Rhythmic auditory cueing improves certain gait symptoms of Parkinson's disease (PD). Cues are typically stimuli or beats with a fixed inter-beat interval. We show that isochronous cueing has an unwanted side-effect in that it exacerbates one of the motor symptoms characteristic of advanced PD. Whereas the parameters of the stride cycle of healthy walkers and early patients possess a persistent correlation in time, or long-range correlation (LRC), isochronous cueing renders stride-to-stride variability random. Random stride cycle variability is also associated with reduced gait stability and lack of flexibility. To investigate how to prevent patients from acquiring a random stride cycle pattern, we tested rhythmic cueing which mimics the properties of variability found in healthy gait (biological variability). PD patients (n=19) and age-matched healthy participants (n=19) walked with three rhythmic cueing stimuli: isochronous, with random variability, and with biological variability (LRC). Synchronization was not instructed. The persistent correlation in gait was preserved only with stimuli with biological variability, equally for patients and controls (p's<0.05). In contrast, cueing with isochronous or randomly varying inter-stimulus/beat intervals removed the LRC in the stride cycle. Notably, the individual's tendency to synchronize steps with beats determined the amount of negative effects of isochronous and random cues (p's<0.05) but not the positive effect of biological variability. Stimulus variability and patients' propensity to synchronize play a critical role in fostering healthier gait dynamics during cueing. The beneficial effects of biological variability provide useful guidelines for improving existing cueing treatments. Copyright © 2016 Elsevier B.V. All rights reserved.

Visit-to-visit and 24-h blood pressure variability: association with endothelial and smooth muscle function in African Americans.

PubMed

Diaz, K M; Veerabhadrappa, P; Kashem, M A; Thakkar, S R; Feairheller, D L; Sturgeon, K M; Ling, C; Williamson, S T; Kretzschmar, J; Lee, H; Grimm, H; Babbitt, D M; Vin, C; Fan, X; Crabbe, D L; Brown, M D

2013-11-01

The purpose of this study was to investigate the association of visit-to-visit and 24-h blood pressure (BP) variability with markers of endothelial injury and vascular function. We recruited 72 African Americans who were non-diabetic, non-smoking and free of cardiovascular (CV) and renal disease. Office BP was measured at three visits and 24-h ambulatory BP monitoring was conducted to measure visit-to-visit and 24-h BP variability, respectively. The 5-min time-course of brachial artery flow-mediated dilation and nitroglycerin-mediated dilation were assessed as measures of endothelial and smooth muscle function. Fasted blood samples were analyzed for circulating endothelial microparticles (EMPs). Significantly lower CD31+CD42- EMPs were found in participants with high visit-to-visit systolic blood pressure (SBP) variability or high 24-h diastolic blood pressure (DBP) variability. Participants with high visit-to-visit DBP variability had significantly lower flow-mediated dilation and higher nitroglycerin-mediated dilation at multiple time-points. When analyzed as continuous variables, 24-h mean arterial pressure variability was inversely associated with CD62+ EMPs; visit-to-visit DBP variability was inversely associated with flow-mediated dilation normalized by smooth muscle function and was positively associated with nitroglycerin-mediated dilation; and 24-h DBP variability was positively associated with nitroglycerin-mediated dilation. All associations were independent of age, gender, body mass index and mean BP. In conclusion, in this cohort of African Americans visit-to-visit and 24-h BP variability were associated with measures of endothelial injury, endothelial function and smooth muscle function. These results suggest that BP variability may influence the pathogenesis of CV disease, in part, through influences on vascular health.

A global perspective on Glacial- to Interglacial variability change

NASA Astrophysics Data System (ADS)

Rehfeld, Kira; Münch, Thomas; Ho, Sze Ling; Laepple, Thomas

2017-04-01

Changes in climate variability are more important for society than changes in the mean state alone. While we will be facing a large-scale shift of the mean climate in the future, its implications for climate variability are not well constrained. Here we quantify changes in temperature variability as climate shifted from the Last Glacial cold to the Holocene warm period. Greenland ice core oxygen isotope records provide evidence of this climatic shift, and are used as reference datasets in many palaeoclimate studies worldwide. A striking feature in these records is pronounced millennial variability in the Glacial, and a distinct reduction in variance in the Holocene. We present quantitative estimates of the change in variability on 500- to 1500-year timescales based on a global compilation of high-resolution proxy records for temperature which span both the Glacial and the Holocene. The estimates are derived based on power spectral analysis, and corrected using estimates of the proxy signal-to-noise ratios. We show that, on a global scale, variability at the Glacial maximum is five times higher than during the Holocene, with a possible range of 3-10 times. The spatial pattern of the variability change is latitude-dependent. While the tropics show no changes in variability, mid-latitude changes are higher. A slight overall reduction in variability in the centennial to millennial range is found in Antarctica. The variability decrease in the Greenland ice core oxygen isotope records is larger than in any other proxy dataset. These results therefore contradict the view of a globally quiescent Holocene following the instable Glacial, and imply that, in terms of centennial to millennial temperature variability, the two states may be more similar than previously thought.

Local-scale models reveal ecological niche variability in amphibian and reptile communities from two contrasting biogeographic regions

PubMed Central

Santos, Xavier; Felicísimo, Ángel M.

2016-01-01

Ecological Niche Models (ENMs) are widely used to describe how environmental factors influence species distribution. Modelling at a local scale, compared to a large scale within a high environmental gradient, can improve our understanding of ecological species niches. The main goal of this study is to assess and compare the contribution of environmental variables to amphibian and reptile ENMs in two Spanish national parks located in contrasting biogeographic regions, i.e., the Mediterranean and the Atlantic area. The ENMs were built with maximum entropy modelling using 11 environmental variables in each territory. The contributions of these variables to the models were analysed and classified using various statistical procedures (Mann–Whitney U tests, Principal Components Analysis and General Linear Models). Distance to the hydrological network was consistently the most relevant variable for both parks and taxonomic classes. Topographic variables (i.e., slope and altitude) were the second most predictive variables, followed by climatic variables. Differences in variable contribution were observed between parks and taxonomic classes. Variables related to water availability had the larger contribution to the models in the Mediterranean park, while topography variables were decisive in the Atlantic park. Specific response curves to environmental variables were in accordance with the biogeographic affinity of species (Mediterranean and non-Mediterranean species) and taxonomy (amphibians and reptiles). Interestingly, these results were observed for species located in both parks, particularly those situated at their range limits. Our findings show that ecological niche models built at local scale reveal differences in habitat preferences within a wide environmental gradient. Therefore, modelling at local scales rather than assuming large-scale models could be preferable for the establishment of conservation strategies for herptile species in natural parks. PMID:27761304

[Blood pressure variability: clinical interest or simple curiosity?].

PubMed

Ciaroni, Stefano

2007-03-14

Blood pressure variability is a physiological phenomenon influenced by many internal and external factors. This variability could be also influenced by pathological conditions such as arterial hypertension. Two forms must be mainly distinguished: the blood pressure variability at long and short-term. The latter could only be studied by continuous recordings. In this article will be analysed the interest of measuring blood pressure variability, its cardiovascular prognosis and the therapeutic tools when it is increased.

Environmental variability and population dynamics: Do European and North American ducks play by the same rules?

USGS Publications Warehouse

Pöysä, Hannu; Rintala, Jukka; Johnson, Douglas H.; Kauppinen, Jukka; Lammi, Esa; Nudds, Thomas D.; Väänänen, Veli-Matti

2016-01-01

Density dependence, population regulation, and variability in population size are fundamental population processes, the manifestation and interrelationships of which are affected by environmental variability. However, there are surprisingly few empirical studies that distinguish the effect of environmental variability from the effects of population processes. We took advantage of a unique system, in which populations of the same duck species or close ecological counterparts live in highly variable (north American prairies) and in stable (north European lakes) environments, to distinguish the relative contributions of environmental variability (measured as between-year fluctuations in wetland numbers) and intraspecific interactions (density dependence) in driving population dynamics. We tested whether populations living in stable environments (in northern Europe) were more strongly governed by density dependence than populations living in variable environments (in North America). We also addressed whether relative population dynamical responses to environmental variability versus density corresponded to differences in life history strategies between dabbling (relatively “fast species” and governed by environmental variability) and diving (relatively “slow species” and governed by density) ducks. As expected, the variance component of population fluctuations caused by changes in breeding environments was greater in North America than in Europe. Contrary to expectations, however, populations in more stable environments were not less variable nor clearly more strongly density dependent than populations in highly variable environments. Also, contrary to expectations, populations of diving ducks were neither more stable nor stronger density dependent than populations of dabbling ducks, and the effect of environmental variability on population dynamics was greater in diving than in dabbling ducks. In general, irrespective of continent and species life history, environmental variability contributed more to variation in species abundances than did density. Our findings underscore the need for more studies on populations of the same species in different environments to verify the generality of current explanations about population dynamics and its association with species life history.

Relative spatial soil geochemical variability along two transects across the United States and Canada

USGS Publications Warehouse

Garrett, Robert G.

2009-01-01

The patterns of relative variability differ by transect and horizon. The N–S transect A-horizon soils show significant between-40-km scale variability for 29 elements, with only 4 elements (Ca, Mg, Pb and Sr) showing in excess of 50% of their variability at the within-40-km and ‘at-site’ scales. In contrast, the C-horizon data demonstrate significant between-40-km scale variability for 26 elements, with 21 having in excess of 50% of their variability at the within-40-km and ‘at-site’ scales. In 36 instances, the ‘at-site’ variability is statistically significant in terms of the sample preparation and analysis variability. It is postulated that this contrast between the A- and C- horizons along the N–S transect, that is dominated by agricultural land uses, is due to the local homogenization of Ap-horizon soils by tillage reducing the ‘at-site’ variability. The spatial variability is distributed similarly between scales for the A- and C-horizon soils of the E–W transect. For all elements, there is significant variability at the within-40-km scale. Notwithstanding this, there is significant between-40-km variability for 28 and 20 of the elements in the A- and C-horizon data, respectively. The differences between the two transects are attributed to (1) geology, the N–S transect runs generally parallel to regional strikes, whereas the E–W transect runs across regional structures and lithologies; and (2) land use, with agricultural tillage dominating along the N–S transect. The spatial analysis of the transect data indicates that continental-scale maps demonstrating statistically significant patterns of geochemical variability may be prepared for many elements from data on soil samples collected on a 40 x 40 km grid or similar sampling designs resulting in a sample density of 1 site per 1600 km2.

Effects of visual feedback-induced variability on motor learning of handrim wheelchair propulsion.

PubMed

Leving, Marika T; Vegter, Riemer J K; Hartog, Johanneke; Lamoth, Claudine J C; de Groot, Sonja; van der Woude, Lucas H V

2015-01-01

It has been suggested that a higher intra-individual variability benefits the motor learning of wheelchair propulsion. The present study evaluated whether feedback-induced variability on wheelchair propulsion technique variables would also enhance the motor learning process. Learning was operationalized as an improvement in mechanical efficiency and propulsion technique, which are thought to be closely related during the learning process. 17 Participants received visual feedback-based practice (feedback group) and 15 participants received regular practice (natural learning group). Both groups received equal practice dose of 80 min, over 3 weeks, at 0.24 W/kg at a treadmill speed of 1.11 m/s. To compare both groups the pre- and post-test were performed without feedback. The feedback group received real-time visual feedback on seven propulsion variables with instruction to manipulate the presented variable to achieve the highest possible variability (1st 4-min block) and optimize it in the prescribed direction (2nd 4-min block). To increase motor exploration the participants were unaware of the exact variable they received feedback on. Energy consumption and the propulsion technique variables with their respective coefficient of variation were calculated to evaluate the amount of intra-individual variability. The feedback group, which practiced with higher intra-individual variability, improved the propulsion technique between pre- and post-test to the same extent as the natural learning group. Mechanical efficiency improved between pre- and post-test in the natural learning group but remained unchanged in the feedback group. These results suggest that feedback-induced variability inhibited the improvement in mechanical efficiency. Moreover, since both groups improved propulsion technique but only the natural learning group improved mechanical efficiency, it can be concluded that the improvement in mechanical efficiency and propulsion technique do not always appear simultaneously during the motor learning process. Their relationship is most likely modified by other factors such as the amount of the intra-individual variability.

Effects of Visual Feedback-Induced Variability on Motor Learning of Handrim Wheelchair Propulsion

PubMed Central

Leving, Marika T.; Vegter, Riemer J. K.; Hartog, Johanneke; Lamoth, Claudine J. C.; de Groot, Sonja; van der Woude, Lucas H. V.

2015-01-01

Background It has been suggested that a higher intra-individual variability benefits the motor learning of wheelchair propulsion. The present study evaluated whether feedback-induced variability on wheelchair propulsion technique variables would also enhance the motor learning process. Learning was operationalized as an improvement in mechanical efficiency and propulsion technique, which are thought to be closely related during the learning process. Methods 17 Participants received visual feedback-based practice (feedback group) and 15 participants received regular practice (natural learning group). Both groups received equal practice dose of 80 min, over 3 weeks, at 0.24 W/kg at a treadmill speed of 1.11 m/s. To compare both groups the pre- and post-test were performed without feedback. The feedback group received real-time visual feedback on seven propulsion variables with instruction to manipulate the presented variable to achieve the highest possible variability (1st 4-min block) and optimize it in the prescribed direction (2nd 4-min block). To increase motor exploration the participants were unaware of the exact variable they received feedback on. Energy consumption and the propulsion technique variables with their respective coefficient of variation were calculated to evaluate the amount of intra-individual variability. Results The feedback group, which practiced with higher intra-individual variability, improved the propulsion technique between pre- and post-test to the same extent as the natural learning group. Mechanical efficiency improved between pre- and post-test in the natural learning group but remained unchanged in the feedback group. Conclusion These results suggest that feedback-induced variability inhibited the improvement in mechanical efficiency. Moreover, since both groups improved propulsion technique but only the natural learning group improved mechanical efficiency, it can be concluded that the improvement in mechanical efficiency and propulsion technique do not always appear simultaneously during the motor learning process. Their relationship is most likely modified by other factors such as the amount of the intra-individual variability. PMID:25992626

Combined model of intrinsic and extrinsic variability for computational network design with application to synthetic biology.

PubMed

Toni, Tina; Tidor, Bruce

2013-01-01

Biological systems are inherently variable, with their dynamics influenced by intrinsic and extrinsic sources. These systems are often only partially characterized, with large uncertainties about specific sources of extrinsic variability and biochemical properties. Moreover, it is not yet well understood how different sources of variability combine and affect biological systems in concert. To successfully design biomedical therapies or synthetic circuits with robust performance, it is crucial to account for uncertainty and effects of variability. Here we introduce an efficient modeling and simulation framework to study systems that are simultaneously subject to multiple sources of variability, and apply it to make design decisions on small genetic networks that play a role of basic design elements of synthetic circuits. Specifically, the framework was used to explore the effect of transcriptional and post-transcriptional autoregulation on fluctuations in protein expression in simple genetic networks. We found that autoregulation could either suppress or increase the output variability, depending on specific noise sources and network parameters. We showed that transcriptional autoregulation was more successful than post-transcriptional in suppressing variability across a wide range of intrinsic and extrinsic magnitudes and sources. We derived the following design principles to guide the design of circuits that best suppress variability: (i) high protein cooperativity and low miRNA cooperativity, (ii) imperfect complementarity between miRNA and mRNA was preferred to perfect complementarity, and (iii) correlated expression of mRNA and miRNA--for example, on the same transcript--was best for suppression of protein variability. Results further showed that correlations in kinetic parameters between cells affected the ability to suppress variability, and that variability in transient states did not necessarily follow the same principles as variability in the steady state. Our model and findings provide a general framework to guide design principles in synthetic biology.

Combined Model of Intrinsic and Extrinsic Variability for Computational Network Design with Application to Synthetic Biology

PubMed Central

Toni, Tina; Tidor, Bruce

2013-01-01

Biological systems are inherently variable, with their dynamics influenced by intrinsic and extrinsic sources. These systems are often only partially characterized, with large uncertainties about specific sources of extrinsic variability and biochemical properties. Moreover, it is not yet well understood how different sources of variability combine and affect biological systems in concert. To successfully design biomedical therapies or synthetic circuits with robust performance, it is crucial to account for uncertainty and effects of variability. Here we introduce an efficient modeling and simulation framework to study systems that are simultaneously subject to multiple sources of variability, and apply it to make design decisions on small genetic networks that play a role of basic design elements of synthetic circuits. Specifically, the framework was used to explore the effect of transcriptional and post-transcriptional autoregulation on fluctuations in protein expression in simple genetic networks. We found that autoregulation could either suppress or increase the output variability, depending on specific noise sources and network parameters. We showed that transcriptional autoregulation was more successful than post-transcriptional in suppressing variability across a wide range of intrinsic and extrinsic magnitudes and sources. We derived the following design principles to guide the design of circuits that best suppress variability: (i) high protein cooperativity and low miRNA cooperativity, (ii) imperfect complementarity between miRNA and mRNA was preferred to perfect complementarity, and (iii) correlated expression of mRNA and miRNA – for example, on the same transcript – was best for suppression of protein variability. Results further showed that correlations in kinetic parameters between cells affected the ability to suppress variability, and that variability in transient states did not necessarily follow the same principles as variability in the steady state. Our model and findings provide a general framework to guide design principles in synthetic biology. PMID:23555205

Mechanism of blood pressure and R-R variability: insights from ganglion blockade in humans

NASA Technical Reports Server (NTRS)

Zhang, Rong; Iwasaki, Kenichi; Zuckerman, Julie H.; Behbehani, Khosrow; Crandall, Craig G.; Levine, Benjamin D.; Blomqvist, C. G. (Principal Investigator)

2002-01-01

Spontaneous blood pressure (BP) and R-R variability are used frequently as 'windows' into cardiovascular control mechanisms. However, the origin of these rhythmic fluctuations is not completely understood. In this study, with ganglion blockade, we evaluated the role of autonomic neural activity versus other 'non-neural' factors in the origin of BP and R-R variability in humans. Beat-to-beat BP, R-R interval and respiratory excursions were recorded in ten healthy subjects (aged 30 +/- 6 years) before and after ganglion blockade with trimethaphan. The spectral power of these variables was calculated in the very low (0.0078-0.05 Hz), low (0.05-0.15 Hz) and high (0.15-0.35 Hz) frequency ranges. The relationship between systolic BP and R-R variability was examined by cross-spectral analysis. After blockade, R-R variability was virtually abolished at all frequencies; however, respiration and high frequency BP variability remained unchanged. Very low and low frequency BP variability was reduced substantially by 84 and 69 %, respectively, but still persisted. Transfer function gain between systolic BP and R-R interval variability decreased by 92 and 88 % at low and high frequencies, respectively, while the phase changed from negative to positive values at the high frequencies. These data suggest that under supine resting conditions with spontaneous breathing: (1) R-R variability at all measured frequencies is predominantly controlled by autonomic neural activity; (2) BP variability at high frequencies (> 0.15 Hz) is mediated largely, if not exclusively, by mechanical effects of respiration on intrathoracic pressure and/or cardiac filling; (3) BP variability at very low and low frequencies (< 0.15 Hz) is probably mediated by both sympathetic nerve activity and intrinsic vasomotor rhythmicity; and (4) the dynamic relationship between BP and R-R variability as quantified by transfer function analysis is determined predominantly by autonomic neural activity rather than other, non-neural factors.

Physiologically Based Pharmacokinetic (PBPK) Modeling of Interstrain Variability in Trichloroethylene Metabolism in the Mouse

PubMed Central

Campbell, Jerry L.; Clewell, Harvey J.; Zhou, Yi-Hui; Wright, Fred A.; Guyton, Kathryn Z.

2014-01-01

Background: Quantitative estimation of toxicokinetic variability in the human population is a persistent challenge in risk assessment of environmental chemicals. Traditionally, interindividual differences in the population are accounted for by default assumptions or, in rare cases, are based on human toxicokinetic data. Objectives: We evaluated the utility of genetically diverse mouse strains for estimating toxicokinetic population variability for risk assessment, using trichloroethylene (TCE) metabolism as a case study. Methods: We used data on oxidative and glutathione conjugation metabolism of TCE in 16 inbred and 1 hybrid mouse strains to calibrate and extend existing physiologically based pharmacokinetic (PBPK) models. We added one-compartment models for glutathione metabolites and a two-compartment model for dichloroacetic acid (DCA). We used a Bayesian population analysis of interstrain variability to quantify variability in TCE metabolism. Results: Concentration–time profiles for TCE metabolism to oxidative and glutathione conjugation metabolites varied across strains. Median predictions for the metabolic flux through oxidation were less variable (5-fold range) than that through glutathione conjugation (10-fold range). For oxidative metabolites, median predictions of trichloroacetic acid production were less variable (2-fold range) than DCA production (5-fold range), although the uncertainty bounds for DCA exceeded the predicted variability. Conclusions: Population PBPK modeling of genetically diverse mouse strains can provide useful quantitative estimates of toxicokinetic population variability. When extrapolated to lower doses more relevant to environmental exposures, mouse population-derived variability estimates for TCE metabolism closely matched population variability estimates previously derived from human toxicokinetic studies with TCE, highlighting the utility of mouse interstrain metabolism studies for addressing toxicokinetic variability. Citation: Chiu WA, Campbell JL Jr, Clewell HJ III, Zhou YH, Wright FA, Guyton KZ, Rusyn I. 2014. Physiologically based pharmacokinetic (PBPK) modeling of interstrain variability in trichloroethylene metabolism in the mouse. Environ Health Perspect 122:456–463; http://dx.doi.org/10.1289/ehp.1307623 PMID:24518055

Validation of China-wide interpolated daily climate variables from 1960 to 2011

NASA Astrophysics Data System (ADS)

Yuan, Wenping; Xu, Bing; Chen, Zhuoqi; Xia, Jiangzhou; Xu, Wenfang; Chen, Yang; Wu, Xiaoxu; Fu, Yang

2015-02-01

Temporally and spatially continuous meteorological variables are increasingly in demand to support many different types of applications related to climate studies. Using measurements from 600 climate stations, a thin-plate spline method was applied to generate daily gridded climate datasets for mean air temperature, maximum temperature, minimum temperature, relative humidity, sunshine duration, wind speed, atmospheric pressure, and precipitation over China for the period 1961-2011. A comprehensive evaluation of interpolated climate was conducted at 150 independent validation sites. The results showed superior performance for most of the estimated variables. Except for wind speed, determination coefficients ( R 2) varied from 0.65 to 0.90, and interpolations showed high consistency with observations. Most of the estimated climate variables showed relatively consistent accuracy among all seasons according to the root mean square error, R 2, and relative predictive error. The interpolated data correctly predicted the occurrence of daily precipitation at validation sites with an accuracy of 83 %. Moreover, the interpolation data successfully explained the interannual variability trend for the eight meteorological variables at most validation sites. Consistent interannual variability trends were observed at 66-95 % of the sites for the eight meteorological variables. Accuracy in distinguishing extreme weather events differed substantially among the meteorological variables. The interpolated data identified extreme events for the three temperature variables, relative humidity, and sunshine duration with an accuracy ranging from 63 to 77 %. However, for wind speed, air pressure, and precipitation, the interpolation model correctly identified only 41, 48, and 58 % of extreme events, respectively. The validation indicates that the interpolations can be applied with high confidence for the three temperatures variables, as well as relative humidity and sunshine duration based on the performance of these variables in estimating daily variations, interannual variability, and extreme events. Although longitude, latitude, and elevation data are included in the model, additional information, such as topography and cloud cover, should be integrated into the interpolation algorithm to improve performance in estimating wind speed, atmospheric pressure, and precipitation.

Selection of key ambient particulate variables for epidemiological studies - applying cluster and heatmap analyses as tools for data reduction.

PubMed

Gu, Jianwei; Pitz, Mike; Breitner, Susanne; Birmili, Wolfram; von Klot, Stephanie; Schneider, Alexandra; Soentgen, Jens; Reller, Armin; Peters, Annette; Cyrys, Josef

2012-10-01

The success of epidemiological studies depends on the use of appropriate exposure variables. The purpose of this study is to extract a relatively small selection of variables characterizing ambient particulate matter from a large measurement data set. The original data set comprised a total of 96 particulate matter variables that have been continuously measured since 2004 at an urban background aerosol monitoring site in the city of Augsburg, Germany. Many of the original variables were derived from measured particle size distribution (PSD) across the particle diameter range 3 nm to 10 μm, including size-segregated particle number concentration, particle length concentration, particle surface concentration and particle mass concentration. The data set was complemented by integral aerosol variables. These variables were measured by independent instruments, including black carbon, sulfate, particle active surface concentration and particle length concentration. It is obvious that such a large number of measured variables cannot be used in health effect analyses simultaneously. The aim of this study is a pre-screening and a selection of the key variables that will be used as input in forthcoming epidemiological studies. In this study, we present two methods of parameter selection and apply them to data from a two-year period from 2007 to 2008. We used the agglomerative hierarchical cluster method to find groups of similar variables. In total, we selected 15 key variables from 9 clusters which are recommended for epidemiological analyses. We also applied a two-dimensional visualization technique called "heatmap" analysis to the Spearman correlation matrix. 12 key variables were selected using this method. Moreover, the positive matrix factorization (PMF) method was applied to the PSD data to characterize the possible particle sources. Correlations between the variables and PMF factors were used to interpret the meaning of the cluster and the heatmap analyses. Copyright © 2012 Elsevier B.V. All rights reserved.

Environmental variability and population dynamics: do European and North American ducks play by the same rules?

PubMed

Pöysä, Hannu; Rintala, Jukka; Johnson, Douglas H; Kauppinen, Jukka; Lammi, Esa; Nudds, Thomas D; Väänänen, Veli-Matti

2016-10-01

Density dependence, population regulation, and variability in population size are fundamental population processes, the manifestation and interrelationships of which are affected by environmental variability. However, there are surprisingly few empirical studies that distinguish the effect of environmental variability from the effects of population processes. We took advantage of a unique system, in which populations of the same duck species or close ecological counterparts live in highly variable (north American prairies) and in stable (north European lakes) environments, to distinguish the relative contributions of environmental variability (measured as between-year fluctuations in wetland numbers) and intraspecific interactions (density dependence) in driving population dynamics. We tested whether populations living in stable environments (in northern Europe) were more strongly governed by density dependence than populations living in variable environments (in North America). We also addressed whether relative population dynamical responses to environmental variability versus density corresponded to differences in life history strategies between dabbling (relatively "fast species" and governed by environmental variability) and diving (relatively "slow species" and governed by density) ducks. As expected, the variance component of population fluctuations caused by changes in breeding environments was greater in North America than in Europe. Contrary to expectations, however, populations in more stable environments were not less variable nor clearly more strongly density dependent than populations in highly variable environments. Also, contrary to expectations, populations of diving ducks were neither more stable nor stronger density dependent than populations of dabbling ducks, and the effect of environmental variability on population dynamics was greater in diving than in dabbling ducks. In general, irrespective of continent and species life history, environmental variability contributed more to variation in species abundances than did density. Our findings underscore the need for more studies on populations of the same species in different environments to verify the generality of current explanations about population dynamics and its association with species life history.

Variable Selection for Regression Models of Percentile Flows

NASA Astrophysics Data System (ADS)

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 degree of multicollinearity, possibly illustrating the co-evolution of climatic and physiographic conditions. Given the ineffectiveness of many variables used here, future work should develop new variables that target specific processes associated with percentile flows.

A preliminary investigation of daily variability of stuttering in adults.

PubMed

Constantino, Christopher D; Leslie, Paula; Quesal, Robert W; Yaruss, J Scott

2016-01-01

Variability in frequency of stuttering has made the results of treatment outcome studies difficult to interpret. Many factors that affect variability have been investigated; yet the typical range of variability experienced by speakers remains unknown. This study examined the day-to-day variability in the percentage of syllables containing stuttered and nonstuttered disfluencies in the speech of six adult speakers in three spontaneous speaking situations and two reading tasks. The frequency of moments stuttering during the tasks were compared within and between speakers and days to document the degree of variability in stuttering frequency and explore whether there were any consistent patterns. The Stuttering Severity Instrument-Fourth Edition (SSI-4) and Overall Assessment of the Speaker's Experience of Stuttering for Adults (OASES-A) were also tested for day-to-day variability. Correlations between frequency, severity, and life impact were made. The primary result of this study was the large range over which frequency of stuttering varied from day to day for the same individual. This variability did not correlate with any measures of stuttering severity but did correlate with life impact as measured by the OASES-A. No global pattern was detected in variability from day to day within or between participants. However, there were significantly more nonstuttered disfluencies present during the spontaneous speaking tasks than during the reading tasks. The day-to-day variability in the life impact of the disorder (OASES-A) was less than the day-to-day variability in observable stuttering behavior (percentage of syllables stuttered and SSI-4). Frequency of stuttering varies significantly from situation to situation and day to day, with observed variability exceeding the degree of change often reported in treatment outcomes studies from before to after treatment. This variability must be accounted for in future clinical and scientific work. Copyright © 2016 Elsevier Inc. All rights reserved.

26 CFR 1.801-7 - Variable annuities.

Code of Federal Regulations, 2013 CFR

2013-04-01

...) INCOME TAXES (CONTINUED) Life Insurance Companies § 1.801-7 Variable annuities. (a) In general. (1... variable annuity contract vary with the insurance company's investment experience with respect to such.... Accordingly, a company issuing variable annuity contracts shall qualify as a life insurance company for...

26 CFR 1.801-7 - Variable annuities.

Code of Federal Regulations, 2012 CFR

2012-04-01

...) INCOME TAXES (CONTINUED) Life Insurance Companies § 1.801-7 Variable annuities. (a) In general. (1... variable annuity contract vary with the insurance company's investment experience with respect to such.... Accordingly, a company issuing variable annuity contracts shall qualify as a life insurance company for...

26 CFR 1.801-7 - Variable annuities.

Code of Federal Regulations, 2014 CFR

2014-04-01

...) INCOME TAXES (CONTINUED) Life Insurance Companies § 1.801-7 Variable annuities. (a) In general. (1... variable annuity contract vary with the insurance company's investment experience with respect to such.... Accordingly, a company issuing variable annuity contracts shall qualify as a life insurance company for...

26 CFR 1.801-7 - Variable annuities.

Code of Federal Regulations, 2011 CFR

2011-04-01

...) INCOME TAXES (CONTINUED) Life Insurance Companies § 1.801-7 Variable annuities. (a) In general. (1... variable annuity contract vary with the insurance company's investment experience with respect to such.... Accordingly, a company issuing variable annuity contracts shall qualify as a life insurance company for...

Client Personality Variables Associated with Counselor Perceptions.

ERIC Educational Resources Information Center

Livneh, Hanoch

1979-01-01

Studies the relationship between clients' personality variables and rehabilitation counselors' perception of these variables. Four client groups were created along two dimensions of personality variables: emotional security need and sexual problems. A significant relationship was found between the client's group membership and his evaluation with…

Preservice Teachers' Understanding of Variable

ERIC Educational Resources Information Center

Brown, Sue; Bergman, Judy

2013-01-01

This study examines the research on middle school students' understanding of variables and explores preservice elementary and middle school teachers' knowledge of variables. According to research studies, middle school students have limited understanding of variables. Many studies have examined the performance of middle school students and offered…

Is Reaction Time Variability in ADHD Mainly at Low Frequencies?

ERIC Educational Resources Information Center

Karalunas, Sarah L.; Huang-Pollock, Cynthia L.; Nigg, Joel T.

2013-01-01

Background: Intraindividual variability in reaction times (RT variability) has garnered increasing interest as an indicator of cognitive and neurobiological dysfunction in children with attention deficit hyperactivity disorder (ADHD). Recent theory and research has emphasized specific low-frequency patterns of RT variability. However, whether…

Variable Screening for Cluster Analysis.

ERIC Educational Resources Information Center

Donoghue, John R.

Inclusion of irrelevant variables in a cluster analysis adversely affects subgroup recovery. This paper examines using moment-based statistics to screen variables; only variables that pass the screening are then used in clustering. Normal mixtures are analytically shown often to possess negative kurtosis. Two related measures, "m" and…

The effect of organisational context variables on employer attitudes toward employability of ex-offenders.

PubMed

Lukies, John; Graffam, Joseph; Shinkfield, Alison J

2011-05-01

The authors tested the premise that organisational context variables (i.e., size of organisation, industry type, location, and respondent's position in organisation) had significant effects on employer (N = 596) attitudes toward employability of ex-offenders. They also examined whether organisational context variables had an equivalent effect on employer attitudes to that of job-seeker criminal history and employer personal characteristics (e.g., respondent age and gender). Using linear regression (HLM 6.02a), organisational context variables were shown to have a significant effect on employer attitudes. In addition, organisational context variables had a significantly greater effect on employer attitudes than did employer personal characteristics. However, job-seeker criminal history contributed more to respondent ratings of ex-offender employability than did organisational context variables. The finding that judgements of employability are influenced by organisational context variables has implications for future research relevant to reintegration. Stakeholder attitudes toward the reintegration success of ex-offenders may be generally influenced by context variables.

Variability common to first leaf dates and snowpack in the western conterminous United States

USGS Publications Warehouse

McCabe, Gregory J.; Betancourt, Julio L.; Pederson, Gregory T.; Schwartz, Mark D.

2013-01-01

Singular value decomposition is used to identify the common variability in first leaf dates (FLDs) and 1 April snow water equivalent (SWE) for the western United States during the period 1900–2012. Results indicate two modes of joint variability that explain 57% of the variability in FLD and 69% of the variability in SWE. The first mode of joint variability is related to widespread late winter–spring warming or cooling across the entire west. The second mode can be described as a north–south dipole in temperature for FLD, as well as in cool season temperature and precipitation for SWE, that is closely correlated to the El Niño–Southern Oscillation. Additionally, both modes of variability indicate a relation with the Pacific–North American atmospheric pattern. These results indicate that there is a substantial amount of common variance in FLD and SWE that is related to large-scale modes of climate variability.

Do bioclimate variables improve performance of climate envelope models?

USGS Publications Warehouse

Watling, James I.; Romañach, Stephanie S.; Bucklin, David N.; Speroterra, Carolina; Brandt, Laura A.; Pearlstine, Leonard G.; Mazzotti, Frank J.

2012-01-01

Climate envelope models are widely used to forecast potential effects of climate change on species distributions. A key issue in climate envelope modeling is the selection of predictor variables that most directly influence species. To determine whether model performance and spatial predictions were related to the selection of predictor variables, we compared models using bioclimate variables with models constructed from monthly climate data for twelve terrestrial vertebrate species in the southeastern USA using two different algorithms (random forests or generalized linear models), and two model selection techniques (using uncorrelated predictors or a subset of user-defined biologically relevant predictor variables). There were no differences in performance between models created with bioclimate or monthly variables, but one metric of model performance was significantly greater using the random forest algorithm compared with generalized linear models. Spatial predictions between maps using bioclimate and monthly variables were very consistent using the random forest algorithm with uncorrelated predictors, whereas we observed greater variability in predictions using generalized linear models.

Future hotspots of increasing temperature variability in tropical countries

NASA Astrophysics Data System (ADS)

Bathiany, S.; Dakos, V.; Scheffer, M.; Lenton, T. M.

2017-12-01

Resolving how climate variability will change in future is crucial to determining how challenging it will be for societies and ecosystems to adapt to climate change. We show that the largest increases in temperature variability - that are robust between state-of-the art climate models - are concentrated in tropical countries. On average, temperature variability increases by 15% per degree of global warming in Amazonia and Southern Africa during austral summer, and by up to 10% °C-1 in the Sahel, India and South East Asia. Southern hemisphere changes can be explained by drying soils, whereas shifts in atmospheric structure play a more important role in the Northern hemisphere. These robust regional changes in variability are associated with monthly timescale events, whereas uncertain changes in inter-annual modes of variability make the response of global temperature variability uncertain. Our results suggest that regional changes in temperature variability will create new inequalities in climate change impacts between rich and poor nations.

Investigating Factorial Invariance of Latent Variables Across Populations When Manifest Variables Are Missing Completely

PubMed Central

Widaman, Keith F.; Grimm, Kevin J.; Early, Dawnté R.; Robins, Richard W.; Conger, Rand D.

2013-01-01

Difficulties arise in multiple-group evaluations of factorial invariance if particular manifest variables are missing completely in certain groups. Ad hoc analytic alternatives can be used in such situations (e.g., deleting manifest variables), but some common approaches, such as multiple imputation, are not viable. At least 3 solutions to this problem are viable: analyzing differing sets of variables across groups, using pattern mixture approaches, and a new method using random number generation. The latter solution, proposed in this article, is to generate pseudo-random normal deviates for all observations for manifest variables that are missing completely in a given sample and then to specify multiple-group models in a way that respects the random nature of these values. An empirical example is presented in detail comparing the 3 approaches. The proposed solution can enable quantitative comparisons at the latent variable level between groups using programs that require the same number of manifest variables in each group. PMID:24019738

Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas - a review

NASA Astrophysics Data System (ADS)

Cristiano, Elena; ten Veldhuis, Marie-claire; van de Giesen, Nick

2017-07-01

In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on small-scale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.

Effects of ice shelf basal melt variability on evolution of Thwaites Glacier

NASA Astrophysics Data System (ADS)

Hoffman, M. J.; Fyke, J. G.; Price, S. F.; Asay-Davis, X.; Perego, M.

2017-12-01

Theory, modeling, and observations indicate that marine ice sheets on a retrograde bed, including Thwaites Glacier, Antarctica, are only conditionally stable. Previous modeling studies have shown that rapid, unstable retreat can occur when steady ice-shelf basal melting causes the grounding line to retreat past restraining bedrock bumps. Here we explore the initiation and evolution of unstable retreat of Thwaites Glacier when the ice-shelf basal melt forcing includes temporal variability mimicking realistic climate variability. We use the three-dimensional, higher-order Model for Prediction Across Scales-Land Ice (MPASLI) model forced with an ice shelf basal melt parameterization derived from previous coupled ice sheet/ocean simulations. We add sinusoidal temporal variability to the melt parameterization that represents shoaling and deepening of Circumpolar Deep Water. We perform an ensemble of 250 year duration simulations with different values for the amplitude, period, and phase of the variability. Preliminary results suggest that, overall, variability leads to slower grounding line retreat and less mass loss than steady simulations. Short period (2 yr) variability leads to similar results as steady forcing, whereas decadal variability can result in up to one-third less mass loss. Differences in phase lead to a large range in mass loss/grounding line retreat, but it is always less than the steady forcing. The timing of ungrounding from each restraining bedrock bump, which is strongly affected by the melt variability, is the rate limiting factor, and variability-driven delays in ungrounding at each bump accumulate. Grounding line retreat in the regions between bedrock bumps is relatively unaffected by ice shelf melt variability. While the results are sensitive to the form of the melt parameterization and its variability, we conclude that decadal period ice shelf melt variability could potentially delay marine ice sheet instability by up to many decades. However, it does not alter the eventual mass loss and sea level rise at centennial scales. The potential differences are significant enough to highlight the need for further observations to constrain the amplitude and period of the modes of climate and ocean variability relevant to Antarctic ice shelf melting.

Integrating models that depend on variable data

NASA Astrophysics Data System (ADS)

Banks, A. T.; Hill, M. C.

2016-12-01

Models of human-Earth systems are often developed with the goal of predicting the behavior of one or more dependent variables from multiple independent variables, processes, and parameters. Often dependent variable values range over many orders of magnitude, which complicates evaluation of the fit of the dependent variable values to observations. Many metrics and optimization methods have been proposed to address dependent variable variability, with little consensus being achieved. In this work, we evaluate two such methods: log transformation (based on the dependent variable being log-normally distributed with a constant variance) and error-based weighting (based on a multi-normal distribution with variances that tend to increase as the dependent variable value increases). Error-based weighting has the advantage of encouraging model users to carefully consider data errors, such as measurement and epistemic errors, while log-transformations can be a black box for typical users. Placing the log-transformation into the statistical perspective of error-based weighting has not formerly been considered, to the best of our knowledge. To make the evaluation as clear and reproducible as possible, we use multiple linear regression (MLR). Simulations are conducted with MatLab. The example represents stream transport of nitrogen with up to eight independent variables. The single dependent variable in our example has values that range over 4 orders of magnitude. Results are applicable to any problem for which individual or multiple data types produce a large range of dependent variable values. For this problem, the log transformation produced good model fit, while some formulations of error-based weighting worked poorly. Results support previous suggestions fthat error-based weighting derived from a constant coefficient of variation overemphasizes low values and degrades model fit to high values. Applying larger weights to the high values is inconsistent with the log-transformation. Greater consistency is obtained by imposing smaller (by up to a factor of 1/35) weights on the smaller dependent-variable values. From an error-based perspective, the small weights are consistent with large standard deviations. This work considers the consequences of these two common ways of addressing variable data.

Assessment of Social Vulnerability Identification at Local Level around Merapi Volcano - A Self Organizing Map Approach

NASA Astrophysics Data System (ADS)

Lee, S.; Maharani, Y. N.; Ki, S. J.

2015-12-01

The application of Self-Organizing Map (SOM) to analyze social vulnerability to recognize the resilience within sites is a challenging tasks. The aim of this study is to propose a computational method to identify the sites according to their similarity and to determine the most relevant variables to characterize the social vulnerability in each cluster. For this purposes, SOM is considered as an effective platform for analysis of high dimensional data. By considering the cluster structure, the characteristic of social vulnerability of the sites identification can be fully understand. In this study, the social vulnerability variable is constructed from 17 variables, i.e. 12 independent variables which represent the socio-economic concepts and 5 dependent variables which represent the damage and losses due to Merapi eruption in 2010. These variables collectively represent the local situation of the study area, based on conducted fieldwork on September 2013. By using both independent and dependent variables, we can identify if the social vulnerability is reflected onto the actual situation, in this case, Merapi eruption 2010. However, social vulnerability analysis in the local communities consists of a number of variables that represent their socio-economic condition. Some of variables employed in this study might be more or less redundant. Therefore, SOM is used to reduce the redundant variable(s) by selecting the representative variables using the component planes and correlation coefficient between variables in order to find the effective sample size. Then, the selected dataset was effectively clustered according to their similarities. Finally, this approach can produce reliable estimates of clustering, recognize the most significant variables and could be useful for social vulnerability assessment, especially for the stakeholder as decision maker. This research was supported by a grant 'Development of Advanced Volcanic Disaster Response System considering Potential Volcanic Risk around Korea' [MPSS-NH-2015-81] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of Korea. Keywords: Self-organizing map, Component Planes, Correlation coefficient, Cluster analysis, Sites identification, Social vulnerability, Merapi eruption 2010

The dynamic relationship between Bursa Malaysia composite index and macroeconomic variables

NASA Astrophysics Data System (ADS)

Ismail, Mohd Tahir; Rose, Farid Zamani Che; Rahman, Rosmanjawati Abd.

2017-08-01

This study investigates and analyzes the long run and short run relationships between Bursa Malaysia Composite index (KLCI) and nine macroeconomic variables in a VAR/VECM framework. After regression analysis seven out the nine macroeconomic variables are chosen for further analysis. The use of Johansen-Juselius Cointegration and Vector Error Correction Model (VECM) technique indicate that there are long run relationships between the seven macroeconomic variables and KLCI. Meanwhile, Granger causality test shows that bidirectional relationship between KLCI and oil price. Furthermore, after 12 months the shock on KLCI are explained by innovations of the seven macroeconomic variables. This indicate the close relationship between macroeconomic variables and KLCI.

The education of attention as explanation of variability of practice effects: learning the final approach phase in a flight simulator.

PubMed

Huet, Michaël; Jacobs, David M; Camachon, Cyril; Missenard, Olivier; Gray, Rob; Montagne, Gilles

2011-12-01

The present study reports two experiments in which a total of 20 participants without prior flight experience practiced the final approach phase in a fixed-base simulator. All participants received self-controlled concurrent feedback during 180 practice trials. Experiment 1 shows that participants learn more quickly under variable practice conditions than under constant practice conditions. This finding is attributed to the education of attention to the more useful informational variables: Variability of practice reduces the usefulness of initially used informational variables, which leads to a quicker change in variable use, and hence to a larger improvement in performance. In the practice phase of Experiment 2 variability was selectively applied to some experimental factors but not to others. Participants tended to converge toward the variables that were useful in the specific conditions that they encountered during practice. This indicates that an explanation for variability of practice effects in terms of the education of attention is a useful alternative to traditional explanations based on the notion of the generalized motor program and to explanations based on the notions of noise and local minima.

The origin of Total Solar Irradiance variability on timescales less than a day

NASA Astrophysics Data System (ADS)

Shapiro, Alexander; Krivova, Natalie; Schmutz, Werner; Solanki, Sami K.; Leng Yeo, Kok; Cameron, Robert; Beeck, Benjamin

2016-07-01

Total Solar Irradiance (TSI) varies on timescales from minutes to decades. It is generally accepted that variability on timescales of a day and longer is dominated by solar surface magnetic fields. For shorter time scales, several additional sources of variability have been proposed, including convection and oscillation. However, available simplified and highly parameterised models could not accurately explain the observed variability in high-cadence TSI records. We employed the high-cadence solar imagery from the Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory and the SATIRE (Spectral And Total Irradiance Reconstruction) model of solar irradiance variability to recreate the magnetic component of TSI variability. The recent 3D simulations of solar near-surface convection with MURAM code have been used to calculate the TSI variability caused by convection. This allowed us to determine the threshold timescale between TSI variability caused by the magnetic field and convection. Our model successfully replicates the TSI measurements by the PICARD/PREMOS radiometer which span the period of July 2010 to February 2014 at 2-minute cadence. Hence, we demonstrate that solar magnetism and convection can account for TSI variability at all timescale it has ever been measured (sans the 5-minute component from p-modes).

Environmental variables measured at multiple spatial scales exert uneven influence on fish assemblages of floodplain lakes

USGS Publications Warehouse

Dembkowski, Daniel J.; Miranda, Leandro E.

2014-01-01

We examined the interaction between environmental variables measured at three different scales (i.e., landscape, lake, and in-lake) and fish assemblage descriptors across a range of over 50 floodplain lakes in the Mississippi Alluvial Valley of Mississippi and Arkansas. Our goal was to identify important local- and landscape-level determinants of fish assemblage structure. Relationships between fish assemblage structure and variables measured at broader scales (i.e., landscape-level and lake-level) were hypothesized to be stronger than relationships with variables measured at finer scales (i.e., in-lake variables). Results suggest that fish assemblage structure in floodplain lakes was influenced by variables operating on three different scales. However, and contrary to expectations, canonical correlations between in-lake environmental characteristics and fish assemblage structure were generally stronger than correlations between landscape-level and lake-level variables and fish assemblage structure, suggesting a hierarchy of influence. From a resource management perspective, our study suggests that landscape-level and lake-level variables may be manipulated for conservation or restoration purposes, and in-lake variables and fish assemblage structure may be used to monitor the success of such efforts.

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

PubMed

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

2015-01-01

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. Copyright © 2015 Elsevier B.V. All rights reserved.

The use of functional data analysis to study variability in childrens speech: Further data

NASA Astrophysics Data System (ADS)

Koenig, Laura L.; Lucero, Jorge C.

2002-05-01

Much previous research has reported increased token-to-token variability in children relative to adults, but the sources and implications of this variability remain matters of debate. Recently, functional data analysis has been used as a tool to gain greater insight into the nature of variability in children's and adults' speech data. In FDA, signals are time-normalized using a smooth function of time. The magnitude of the time-warping function provides an index of phasing (temporal) variability, and a separate index of amplitude variability is calculated from the time-normalized signal. Here, oral airflow data are analyzed from 5-year-olds, 10-year-olds, and adult women producing laryngeal and oral fricatives (/h, s, z/). The preliminary FDA results show that children generally have higher temporal and amplitude indices than adults, suggesting greater variability both in gestural timing and magnitude. However, individual patterns are evident in the relative magnitude of the two indices, and in which consonants show the highest values. The time-varying patterns of flow variability over time in /s/ are also explored as a method of inferring relative variability among laryngeal and oral gestures. [Work supported by NIH and CNPq, Brazil.

The Magnitude of Trial-By-Trial Neural Variability Is Reproducible over Time and across Tasks in Humans.

PubMed

Arazi, Ayelet; Gonen-Yaacovi, Gil; Dinstein, Ilan

2017-01-01

Numerous studies have shown that neural activity in sensory cortices is remarkably variable over time and across trials even when subjects are presented with an identical repeating stimulus or task. This trial-by-trial neural variability is relatively large in the prestimulus period and considerably smaller (quenched) following stimulus presentation. Previous studies have suggested that the magnitude of neural variability affects behavior such that perceptual performance is better on trials and in individuals where variability quenching is larger. To what degree are neural variability magnitudes of individual subjects flexible or static? Here, we used EEG recordings from adult humans to demonstrate that neural variability magnitudes in visual cortex are remarkably consistent across different tasks and recording sessions. While magnitudes of neural variability differed dramatically across individual subjects, they were surprisingly stable across four tasks with different stimuli, temporal structures, and attentional/cognitive demands as well as across experimental sessions separated by one year. These experiments reveal that, in adults, neural variability magnitudes are mostly solidified individual characteristics that change little with task or time, and are likely to predispose individual subjects to exhibit distinct behavioral capabilities.

Predicting national suicide numbers with social media data.

PubMed

Won, Hong-Hee; Myung, Woojae; Song, Gil-Young; Lee, Won-Hee; Kim, Jong-Won; Carroll, Bernard J; Kim, Doh Kwan

2013-01-01

Suicide is not only an individual phenomenon, but it is also influenced by social and environmental factors. With the high suicide rate and the abundance of social media data in South Korea, we have studied the potential of this new medium for predicting completed suicide at the population level. We tested two social media variables (suicide-related and dysphoria-related weblog entries) along with classical social, economic and meteorological variables as predictors of suicide over 3 years (2008 through 2010). Both social media variables were powerfully associated with suicide frequency. The suicide variable displayed high variability and was reactive to celebrity suicide events, while the dysphoria variable showed longer secular trends, with lower variability. We interpret these as reflections of social affect and social mood, respectively. In the final multivariate model, the two social media variables, especially the dysphoria variable, displaced two classical economic predictors - consumer price index and unemployment rate. The prediction model developed with the 2-year training data set (2008 through 2009) was validated in the data for 2010 and was robust in a sensitivity analysis controlling for celebrity suicide effects. These results indicate that social media data may be of value in national suicide forecasting and prevention.

Analysis of the semi-permanent house in Merauke city in terms of aesthetic value in architecture

NASA Astrophysics Data System (ADS)

Topan, Anton; Octavia, Sari; Soleman, Henry

2018-05-01

Semi permanent houses are also used called “Rumah Kancingan” is the houses that generally exist in the Merauke city. Called semi permanent because the main structure use is woods even if the walls uses bricks. This research tries to analyze more about Semi permanent house in terms of aesthethics value. This research is a qualitative research with data collection techniques using questionnaire method and direct observation field and study of literature. The result of questionnaire data collection then processed using SPSS to get the influence of independent variable against the dependent variable and found that color, ornament, shape of the door-window and shape of roof (independent) gives 97,1% influence to the aesthetics of the Semi permanent house and based on the output coefficient SPSS obtained that the dependent variable has p-value < 0.05 which means independent variables have an effect on significant to aesthetic variable. For variables of semi permanent and wooden structure gives an effect of 98,6% to aesthetics and based on the result of SPSS coefficient it is found that free variable has p-value < 0.05 which means independent variables have an effect on significant to aesthetic variable.

Brain Signal Variability is Parametrically Modifiable

PubMed Central

Garrett, Douglas D.; McIntosh, Anthony R.; Grady, Cheryl L.

2014-01-01

Moment-to-moment brain signal variability is a ubiquitous neural characteristic, yet remains poorly understood. Evidence indicates that heightened signal variability can index and aid efficient neural function, but it is not known whether signal variability responds to precise levels of environmental demand, or instead whether variability is relatively static. Using multivariate modeling of functional magnetic resonance imaging-based parametric face processing data, we show here that within-person signal variability level responds to incremental adjustments in task difficulty, in a manner entirely distinct from results produced by examining mean brain signals. Using mixed modeling, we also linked parametric modulations in signal variability with modulations in task performance. We found that difficulty-related reductions in signal variability predicted reduced accuracy and longer reaction times within-person; mean signal changes were not predictive. We further probed the various differences between signal variance and signal means by examining all voxels, subjects, and conditions; this analysis of over 2 million data points failed to reveal any notable relations between voxel variances and means. Our results suggest that brain signal variability provides a systematic task-driven signal of interest from which we can understand the dynamic function of the human brain, and in a way that mean signals cannot capture. PMID:23749875

Climate variability has a stabilizing effect on the coexistence of prairie grasses

PubMed Central

Adler, Peter B.; HilleRisLambers, Janneke; Kyriakidis, Phaedon C.; Guan, Qingfeng; Levine, Jonathan M.

2006-01-01

How expected increases in climate variability will affect species diversity depends on the role of such variability in regulating the coexistence of competing species. Despite theory linking temporal environmental fluctuations with the maintenance of diversity, the importance of climate variability for stabilizing coexistence remains unknown because of a lack of appropriate long-term observations. Here, we analyze three decades of demographic data from a Kansas prairie to demonstrate that interannual climate variability promotes the coexistence of three common grass species. Specifically, we show that (i) the dynamics of the three species satisfy all requirements of “storage effect” theory based on recruitment variability with overlapping generations, (ii) climate variables are correlated with interannual variation in species performance, and (iii) temporal variability increases low-density growth rates, buffering these species against competitive exclusion. Given that environmental fluctuations are ubiquitous in natural systems, our results suggest that coexistence based on the storage effect may be underappreciated and could provide an important alternative to recent neutral theories of diversity. Field evidence for positive effects of variability on coexistence also emphasizes the need to consider changes in both climate means and variances when forecasting the effects of global change on species diversity. PMID:16908862

Variable Stars in M13. II.The Red Variables and the Globular Cluster Period-Luminosity Relation

NASA Astrophysics Data System (ADS)

Osborn, W.; Layden, A.; Kopacki, G.; Smith, H.; Anderson, M.; Kelly, A.; McBride, K.; Pritzl, B.

2017-06-01

New CCD observations have been combined with archival data to investigate the nature of the red variables in the globular cluster M13. Mean magnitudes, colors and variation ranges on the UBVIC system have been determined for the 17 cataloged red variables. 15 of the stars are irregular or semi-regular variables that lie at the top of the red giant branch in the color-magnitude diagram. Two stars are not, including one with a well-defined period and a light curve shape indicating it is an ellipsoidal or eclipsing variable. All stars redder than (V-IC)0=1.38 mag vary, with the amplitudes being larger with increased stellar luminosity and with bluer filter passband. Searches of the data for periodicities yielded typical variability cycle times ranging from 30 d up to 92 d for the most luminous star. Several stars have evidence of multiple periods. The stars' period-luminosity diagram compared to those from microlensing survey data shows that most M13 red variables are overtone pulsators. Comparison with the diagrams for other globular clusters shows a correlation between red variable luminosity and cluster metallicity.

Variability of Massive Young Stellar Objects in Cygnus-X

NASA Astrophysics Data System (ADS)

Thomas, Nancy H.; Hora, J. L.; Smith, H. A.

2013-01-01

Young stellar objects (YSOs) are stars in the process of formation. Several recent investigations have shown a high rate of photometric variability in YSOs at near- and mid-infrared wavelengths. Theoretical models for the formation of massive stars (1-10 solar masses) remain highly idealized, and little is known about the mechanisms that produce the variability. An ongoing Spitzer Space Telescope program is studying massive star formation in the Cygnus-X region. In conjunction with the Spitzer observations, we have conducted a ground-based near-infrared observing program of the Cygnus-X DR21 field using PAIRITEL, the automated infrared telescope at Whipple Observatory. Using the Stetson index for variability, we identified variable objects and a number of variable YSOs in our time-series PAIRITEL data of DR21. We have searched for periodicity among our variable objects using the Lomb-Scargle algorithm, and identified periodic variable objects with an average period of 8.07 days. Characterization of these variable and periodic objects will help constrain models of star formation present. This work is supported in part by the NSF REU and DOD ASSURE programs under NSF grant no. 0754568 and by the Smithsonian Institution.

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

NASA Astrophysics Data System (ADS)

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.

Gait variability in community dwelling adults with Alzheimer disease.

PubMed

Webster, Kate E; Merory, John R; Wittwer, Joanne E

2006-01-01

Studies have shown that measures of gait variability are associated with falling in older adults. However, few studies have measured gait variability in people with Alzheimer disease, despite the high incidence of falls in Alzheimer disease. The purpose of this study was to compare gait variability of community-dwelling older adults with Alzheimer disease and control subjects at various walking speeds. Ten subjects with mild-moderate Alzheimer disease and ten matched control subjects underwent gait analysis using an electronic walkway. Participants were required to walk at self-selected slow, preferred, and fast speeds. Stride length and step width variability were determined using the coefficient of variation. Results showed that stride length variability was significantly greater in the Alzheimer disease group compared with the control group at all speeds. In both groups, increases in walking speed were significantly correlated with decreases in stride length variability. Step width variability was significantly reduced in the Alzheimer disease group compared with the control group at slow speed only. In conclusion, there is an increase in stride length variability in Alzheimer disease at all walking speeds that may contribute to the increased incidence of falls in Alzheimer disease.

Predicting National Suicide Numbers with Social Media Data

PubMed Central

Won, Hong-Hee; Song, Gil-Young; Lee, Won-Hee; Kim, Jong-Won; Carroll, Bernard J.

2013-01-01

Suicide is not only an individual phenomenon, but it is also influenced by social and environmental factors. With the high suicide rate and the abundance of social media data in South Korea, we have studied the potential of this new medium for predicting completed suicide at the population level. We tested two social media variables (suicide-related and dysphoria-related weblog entries) along with classical social, economic and meteorological variables as predictors of suicide over 3 years (2008 through 2010). Both social media variables were powerfully associated with suicide frequency. The suicide variable displayed high variability and was reactive to celebrity suicide events, while the dysphoria variable showed longer secular trends, with lower variability. We interpret these as reflections of social affect and social mood, respectively. In the final multivariate model, the two social media variables, especially the dysphoria variable, displaced two classical economic predictors – consumer price index and unemployment rate. The prediction model developed with the 2-year training data set (2008 through 2009) was validated in the data for 2010 and was robust in a sensitivity analysis controlling for celebrity suicide effects. These results indicate that social media data may be of value in national suicide forecasting and prevention. PMID:23630615

Understanding the context of healthcare utilization: assessing environmental and provider-related variables in the behavioral model of utilization.

PubMed Central

Phillips, K A; Morrison, K R; Andersen, R; Aday, L A

1998-01-01

OBJECTIVE: The behavioral model of utilization, developed by Andersen, Aday, and others, is one of the most frequently used frameworks for analyzing the factors that are associated with patient utilization of healthcare services. However, the use of the model for examining the context within which utilization occurs-the role of the environment and provider-related factors-has been largely neglected. OBJECTIVE: To conduct a systematic review and analysis to determine if studies of medical care utilization that have used the behavioral model during the last 20 years have included environmental and provider-related variables and the methods used to analyze these variables. We discuss barriers to the use of these contextual variables and potential solutions. DATA SOURCES: The Social Science Citation Index and Science Citation Index. We included all articles from 1975-1995 that cited any of three key articles on the behavioral model, that included all articles that were empirical analyses and studies of formal medical care utilization, and articles that specifically stated their use of the behavioral model (n = 139). STUDY DESIGN: Design was a systematic literature review. DATA ANALYSIS: We used a structured review process to code articles on whether they included contextual variables: (1) environmental variables (characteristics of the healthcare delivery system, external environment, and community-level enabling factors); and (2) provider-related variables (patient factors that may be influenced by providers and provider characteristics that interact with patient characteristics to influence utilization). We also examined the methods used in studies that included contextual variables. PRINCIPAL FINDINGS: Forty-five percent of the studies included environmental variables and 51 percent included provider-related variables. Few studies examined specific measures of the healthcare system or provider characteristics or used methods other than simple regression analysis with hierarchical entry of variables. Only 14 percent of studies analyzed the context of healthcare by including both environmental and provider-related variables as well as using relevant methods. CONCLUSIONS: By assessing whether and how contextual variables are used, we are able to highlight the contributions made by studies using these approaches, to identify variables and methods that have been relatively underused, and to suggest solutions to barriers in using contextual variables. PMID:9685123

a Latent Variable Path Analysis Model of Secondary Physics Enrollments in New York State.

NASA Astrophysics Data System (ADS)

Sobolewski, Stanley John

The Percentage of Enrollment in Physics (PEP) at the secondary level nationally has been approximately 20% for the past few decades. For a more scientifically literate citizenry as well as specialists to continue scientific research and development, it is desirable that more students enroll in physics. Some of the predictor variables for physics enrollment and physics achievement that have been identified previously includes a community's socioeconomic status, the availability of physics, the sex of the student, the curriculum, as well as teacher and student data. This study isolated and identified predictor variables for PEP of secondary schools in New York. Data gathered by the State Education Department for the 1990-1991 school year was used. The source of this data included surveys completed by teachers and administrators on student characteristics and school facilities. A data analysis similar to that done by Bryant (1974) was conducted to determine if the relationships between a set of predictor variables related to physics enrollment had changed in the past 20 years. Variables which were isolated included: community, facilities, teacher experience, number of type of science courses, school size and school science facilities. When these variables were isolated, latent variable path diagrams were proposed and verified by the Linear Structural Relations computer modeling program (LISREL). These diagrams differed from those developed by Bryant in that there were more manifest variables used which included achievement scores in the form of Regents exam results. Two criterion variables were used, percentage of students enrolled in physics (PEP) and percent of students enrolled passing the Regents physics exam (PPP). The first model treated school and community level variables as exogenous while the second model treated only the community level variables as exogenous. The goodness of fit indices for the models was 0.77 for the first model and 0.83 for the second model. No dramatic differences were found between the relationship of predictor variables to physics enrollment in 1972 and 1991. New models indicated that smaller school size, enrollment in previous science and math courses and other school variables were more related to high enrollment rather than achievement. Exogenous variables such as community size were related to achievement. It was shown that achievement and enrollment were related to a different set of predictor variables.

Construct Relevant and Irrelevant Variables in Math Problem Solving Assessment

ERIC Educational Resources Information Center

Birk, Lisa E.

2013-01-01

In this study, I examined the relation between various construct relevant and irrelevant variables and a math problem solving assessment. I used independent performance measures representing the variables of mathematics content knowledge, general ability, and reading fluency. Non-performance variables included gender, socioeconomic status,…

Place, Poverty, and Algebra: A Statewide Comparative Spatial Analysis of Variable Relationships

ERIC Educational Resources Information Center

Hogrebe, Mark C.; Tate, William F.

2012-01-01

Place matters in moderating variable relationships between algebra performance and educational variables because there are differences on the socioeconomic (SES) poverty-affluence continuum that shape local contexts. This article examines relationships between variables for school district demographic composition, teaching and financial contexts,…

Integrating Mediators and Moderators in Research Design

ERIC Educational Resources Information Center

MacKinnon, David P.

2011-01-01

The purpose of this article is to describe mediating variables and moderating variables and provide reasons for integrating them in outcome studies. Separate sections describe examples of moderating and mediating variables and the simplest statistical model for investigating each variable. The strengths and limitations of incorporating mediating…

Bayesian Semiparametric Structural Equation Models with Latent Variables

ERIC Educational Resources Information Center

Yang, Mingan; Dunson, David B.

2010-01-01

Structural equation models (SEMs) with latent variables are widely useful for sparse covariance structure modeling and for inferring relationships among latent variables. Bayesian SEMs are appealing in allowing for the incorporation of prior information and in providing exact posterior distributions of unknowns, including the latent variables. In…

Factors associated with NO2 and NOX concentration gradients near a highway

NASA Astrophysics Data System (ADS)

Richmond-Bryant, J.; Snyder, M. G.; Owen, R. C.; Kimbrough, S.

2018-02-01

The objective of this research is to learn how the near-road gradient, in which NO2 and NOX (NO + NO2) concentrations are elevated, varies with changes in meteorological and traffic variables. Measurements of NO2 and NOX were obtained east of I-15 in Las Vegas and fit to functions whose slopes (dCNO2/dx and dCNOX/dx, respectively) characterize the size of the near-road zone where NO2 and NOX concentrations from mobile sources on the highway are elevated. These metrics were used to learn about the near-road gradient by modeling dCNO2/dx and dCNOX/dx as functions of meteorological variables (e.g., wind direction, wind speed), traffic (vehicle count), NOX concentration upwind of the road, and O3 concentration at two fixed-site ambient monitors. Generalized additive models (GAM) were used to model dCNO2/dx and dCNOX/dx versus the independent variables because they allowed for nonlinearity of the variables being compared. When data from all wind directions were included in the analysis, variability in O3 concentration comprised the largest proportion of variability in dCNO2/dx, followed by variability in wind direction. In a second analysis constrained to winds from the west, variability in O3 concentration remained the largest contributor to variability in dCNO2/dx, but the relative contribution of variability in wind speed to variability in dCNO2/dx increased relative to its contribution for the all-wind analysis. When data from all wind directions were analyzed, variability in wind direction was by far the largest contributor to variability in dCNOX/dx, with smaller contributions from hour of day and upwind NOX concentration. When only winds from the west were analyzed, variability in upwind NOX concentration, wind speed, hour of day, and traffic count all were associated with variability in dCNOX/dx. Increases in O3 concentration were associated with increased magnitude near-road dCNO2/dx, possibly shrinking the zone of elevated concentrations occurring near roads. Wind direction parallel to the highway was also related to an increased magnitude of both dCNO2/dx and dCNOX/dx, again likely shrinking the zone of elevated concentrations occurring near roads. Wind direction perpendicular to the road decreased the magnitude of dCNO2/dx and dCNOX/dx and likely contributed to growth of the zone of elevated concentrations occurring near roads. Thus, variability in near-road concentrations is influenced by local meteorology and ambient O3 concentration.

Interannual to Decadal Variability of Ocean Evaporation as Viewed from Climate Reanalyses

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Bosilovich, Michael G.; Roberts, Jason B.; Wang, Hailan

2015-01-01

Questions we'll address: Given the uncoupled framework of "AMIP" (Atmosphere Model Inter-comparison Project) experiments, what can they tell us regarding evaporation variability? Do Reduced Observations Reanalyses (RedObs) using Surface Fluxes and Clouds (SFC) pressure (and wind) provide a more realistic picture of evaporation variability? What signals of interannual variability (e.g. El Nino/Southern Oscillation (ENSO)) and decadal variability (Interdecadal Pacific Oscillation (IPO)) are detectable with this hierarchy of evaporation estimates?

Spin, Unit Climate, and Aggression: Near Term, Long Term, and Reciprocal Predictors of Violence Among Workers in Military Settings

DTIC Science & Technology

2016-08-01

differences in within-person variability in emotional state, known as “spin”) and group level variables (e.g., unit climate) hypothesized to impact...effort includes both individual level variables (e.g., differences in within-person variability in emotional state, known as “spin”) and group level...and unit level factors across time. At the individual level, we will examine within-person variability in emotion and interpersonal behaviors

Discontinuity of the annuity curves. III. Two types of vital variability in Drosophila melanogaster.

PubMed

Bychkovskaia, I B; Mylnikov, S V; Mozhaev, G A

2016-01-01

We confirm five-phased construction of Drosophila annuity curves established earlier. Annuity curves were composed of stable five-phase component and variable one. Variable component was due to differences in phase durations. As stable, so variable components were apparent for 60 generations. Stochastic component was described as well. Viability variance which characterize «reaction norm» was apparent for all generation as well. Thus, both types of variability seem to be inherited.

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.

PubMed

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.

Climate, soil or both? Which variables are better predictors of the distributions of Australian shrub species?

PubMed Central

Esperón-Rodríguez, Manuel; Baumgartner, John B.; Beaumont, Linda J.

2017-01-01

Background Shrubs play a key role in biogeochemical cycles, prevent soil and water erosion, provide forage for livestock, and are a source of food, wood and non-wood products. However, despite their ecological and societal importance, the influence of different environmental variables on shrub distributions remains unclear. We evaluated the influence of climate and soil characteristics, and whether including soil variables improved the performance of a species distribution model (SDM), Maxent. Methods This study assessed variation in predictions of environmental suitability for 29 Australian shrub species (representing dominant members of six shrubland classes) due to the use of alternative sets of predictor variables. Models were calibrated with (1) climate variables only, (2) climate and soil variables, and (3) soil variables only. Results The predictive power of SDMs differed substantially across species, but generally models calibrated with both climate and soil data performed better than those calibrated only with climate variables. Models calibrated solely with soil variables were the least accurate. We found regional differences in potential shrub species richness across Australia due to the use of different sets of variables. Conclusions Our study provides evidence that predicted patterns of species richness may be sensitive to the choice of predictor set when multiple, plausible alternatives exist, and demonstrates the importance of considering soil properties when modeling availability of habitat for plants. PMID:28652933

Short-term to seasonal variability in factors driving primary productivity in a shallow estuary: Implications for modeling production

NASA Astrophysics Data System (ADS)

Canion, Andy; MacIntyre, Hugh L.; Phipps, Scott

2013-10-01

The inputs of primary productivity models may be highly variable on short timescales (hourly to daily) in turbid estuaries, but modeling of productivity in these environments is often implemented with data collected over longer timescales. Daily, seasonal, and spatial variability in primary productivity model parameters: chlorophyll a concentration (Chla), the downwelling light attenuation coefficient (kd), and photosynthesis-irradiance response parameters (Pmchl, αChl) were characterized in Weeks Bay, a nitrogen-impacted shallow estuary in the northern Gulf of Mexico. Variability in primary productivity model parameters in response to environmental forcing, nutrients, and microalgal taxonomic marker pigments were analysed in monthly and short-term datasets. Microalgal biomass (as Chla) was strongly related to total phosphorus concentration on seasonal scales. Hourly data support wind-driven resuspension as a major source of short-term variability in Chla and light attenuation (kd). The empirical relationship between areal primary productivity and a combined variable of biomass and light attenuation showed that variability in the photosynthesis-irradiance response contributed little to the overall variability in primary productivity, and Chla alone could account for 53-86% of the variability in primary productivity. Efforts to model productivity in similar shallow systems with highly variable microalgal biomass may benefit the most by investing resources in improving spatial and temporal resolution of chlorophyll a measurements before increasing the complexity of models used in productivity modeling.

Evaluation of alternative model selection criteria in the analysis of unimodal response curves using CART

USGS Publications Warehouse

Ribic, C.A.; Miller, T.W.

1998-01-01

We investigated CART performance with a unimodal response curve for one continuous response and four continuous explanatory variables, where two variables were important (ie directly related to the response) and the other two were not. We explored performance under three relationship strengths and two explanatory variable conditions: equal importance and one variable four times as important as the other. We compared CART variable selection performance using three tree-selection rules ('minimum risk', 'minimum risk complexity', 'one standard error') to stepwise polynomial ordinary least squares (OLS) under four sample size conditions. The one-standard-error and minimum-risk-complexity methods performed about as well as stepwise OLS with large sample sizes when the relationship was strong. With weaker relationships, equally important explanatory variables and larger sample sizes, the one-standard-error and minimum-risk-complexity rules performed better than stepwise OLS. With weaker relationships and explanatory variables of unequal importance, tree-structured methods did not perform as well as stepwise OLS. Comparing performance within tree-structured methods, with a strong relationship and equally important explanatory variables, the one-standard-error-rule was more likely to choose the correct model than were the other tree-selection rules 1) with weaker relationships and equally important explanatory variables; and 2) under all relationship strengths when explanatory variables were of unequal importance and sample sizes were lower.

The Oceanic Contribution to Atlantic Multi-Decadal Variability

NASA Astrophysics Data System (ADS)

Wills, R. C.; Armour, K.; Battisti, D. S.; Hartmann, D. L.

2017-12-01

Atlantic multi-decadal variability (AMV) is typically associated with variability in ocean heat transport (OHT) by the Atlantic Meridional Overturning Circulation (AMOC). However, recent work has cast doubt on this connection by showing that slab-ocean climate models, in which OHT cannot vary, exhibit similar variability. Here, we apply low-frequency component analysis to isolate the variability of Atlantic sea-surface temperatures (SSTs) that occurs on decadal and longer time scales. In observations and in pre-industrial control simulations of comprehensive climate models, we find that AMV is confined to the extratropics, with the strongest temperature anomalies in the North Atlantic subpolar gyre. We show that warm subpolar temperatures are associated with a strengthened AMOC, increased poleward OHT, and local heat fluxes from the ocean into the atmosphere. In contrast, the traditional index of AMV based on the basin-averaged SST anomaly shows warm temperatures preceded by heat fluxes from the atmosphere into the ocean, consistent with the atmosphere driving this variability, and shows a weak relationship with AMOC. The autocorrelation time of the basin-averaged SST index is 1 year compared to an autocorrelation time of 5 years for the variability of subpolar temperatures. This shows that multi-decadal variability of Atlantic SSTs is sustained by OHT variability associated with AMOC, while atmosphere-driven SST variability, such as exists in slab-ocean models, contributes primarily on interannual time scales.

Potential Impact of North Atlantic Climate Variability on Ocean Biogeochemical Processes

NASA Astrophysics Data System (ADS)

Liu, Y.; Muhling, B.; Lee, S. K.; Muller-Karger, F. E.; Enfield, D. B.; Lamkin, J. T.; Roffer, M. A.

2016-02-01

Previous studies have shown that upper ocean circulations largely determine primary production in the euphotic layers, here the global ocean model with biogeochemistry (GFDL's Modular Ocean Model with TOPAZ biogeochemistry) forced with the ERA-Interim is used to simulate the natural variability of biogeochemical processes in global ocean during 1979-present. Preliminary results show that the surface chlorophyll is overall underestimated in MOM-TOPAZ, but its spatial pattern is fairly realistic. Relatively high chlorophyll variability is shown in the subpolar North Atlantic, northeastern tropical Atlantic, and equatorial Atlantic. Further analysis suggests that the chlorophyll variability in the North Atlantic Ocean is affected by long-term climate variability. For the subpolar North Atlantic region, the chlorophyll variability is light-limited and is significantly correlated with North Atlantic Oscillation. A dipole pattern of chlorophyll variability is found between the northeastern tropical Atlantic and equatorial Atlantic. For the northeastern North Atlantic, the chlorophyll variability is significantly correlated with Atlantic Meridional Mode (AMM) and Atlantic Multidecadal Oscillation (AMO). During the negative phase of AMM and AMO, the increased trade wind in the northeast North Atlantic can lead to increased upwelling of nutrients. In the equatorial Atlantic region, the chlorophyll variability is largely link to Atlantic-Niño and associated equatorial upwelling of nutrients. The potential impact of climate variability on the distribution of pelagic fishes (i.e. yellowfin tuna) are discussed.

Characterization of the spatial variability of channel morphology

USGS Publications Warehouse

Moody, J.A.; Troutman, B.M.

2002-01-01

The spatial variability of two fundamental morphological variables is investigated for rivers having a wide range of discharge (five orders of magnitude). The variables, water-surface width and average depth, were measured at 58 to 888 equally spaced cross-sections in channel links (river reaches between major tributaries). These measurements provide data to characterize the two-dimensional structure of a channel link which is the fundamental unit of a channel network. The morphological variables have nearly log-normal probability distributions. A general relation was determined which relates the means of the log-transformed variables to the logarithm of discharge similar to previously published downstream hydraulic geometry relations. The spatial variability of the variables is described by two properties: (1) the coefficient of variation which was nearly constant (0.13-0.42) over a wide range of discharge; and (2) the integral length scale in the downstream direction which was approximately equal to one to two mean channel widths. The joint probability distribution of the morphological variables in the downstream direction was modelled as a first-order, bivariate autoregressive process. This model accounted for up to 76 per cent of the total variance. The two-dimensional morphological variables can be scaled such that the channel width-depth process is independent of discharge. The scaling properties will be valuable to modellers of both basin and channel dynamics. Published in 2002 John Wiley and Sons, Ltd.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Radigan, Jacqueline, E-mail: radigan@stsci.edu

Observations of variability can provide valuable information about the processes of cloud formation and dissipation in brown dwarf atmospheres. Here we report the results of an independent analysis of archival data from the Brown dwarf Atmosphere Monitoring (BAM) program. Time series data for 14 L and T dwarfs reported to be significantly variable over timescales of hours were analyzed. We confirm large-amplitude variability (amplitudes >2%) for 4 out of 13 targets and place upper limits of 0.7%-1.6% on variability in the remaining sample. For two targets we find evidence of weak variability at amplitudes of 1.3% and 1.6%. Based onmore » our revised classification of variable objects in the BAM study, we find strong variability outside the L/T transition to be rare at near infrared wavelengths. From a combined sample of 81 L0-T9 dwarfs from the revised BAM sample and the variability survey of Radigan et al., we infer an overall observed frequency for large-amplitude variability outside the L/T transition of 3.2{sub −1.8}{sup +2.8}%, in contrast to 24{sub −9}{sup +11}% for L9-T3.5 spectral types. We conclude that while strong variability is not limited to the L/T transition, it occurs more frequently in this spectral type range, indicative of larger or more highly contrasting cloud features at these spectral types.« less

[Modelling the effect of local climatic variability on dengue transmission in Medellin (Colombia) by means of time series analysis].

PubMed

Rúa-Uribe, Guillermo L; Suárez-Acosta, Carolina; Chauca, José; Ventosilla, Palmira; Almanza, Rita

2013-09-01

Dengue fever is a major impact on public health vector-borne disease, and its transmission is influenced by entomological, sociocultural and economic factors. Additionally, climate variability plays an important role in the transmission dynamics. A large scientific consensus has indicated that the strong association between climatic variables and disease could be used to develop models to explain the incidence of the disease. To develop a model that provides a better understanding of dengue transmission dynamics in Medellin and predicts increases in the incidence of the disease. The incidence of dengue fever was used as dependent variable, and weekly climatic factors (maximum, mean and minimum temperature, relative humidity and precipitation) as independent variables. Expert Modeler was used to develop a model to better explain the behavior of the disease. Climatic variables with significant association to the dependent variable were selected through ARIMA models. The model explains 34% of observed variability. Precipitation was the climatic variable showing statistically significant association with the incidence of dengue fever, but with a 20 weeks delay. In Medellin, the transmission of dengue fever was influenced by climate variability, especially precipitation. The strong association dengue fever/precipitation allowed the construction of a model to help understand dengue transmission dynamics. This information will be useful to develop appropriate and timely strategies for dengue control.

A Call to Standardize Preanalytic Data Elements for Biospecimens, Part II.

PubMed

Robb, James A; Bry, Lynn; Sluss, Patrick M; Wagar, Elizabeth A; Kennedy, Mary F

2015-09-01

Biospecimens must have appropriate clinical annotation (data) to ensure optimal quality for both patient care and research. Additional clinical preanalytic variables are the focus of this continuing study. To complete the identification of the essential preanalytic variables (data fields) that can, and in some instances should, be attached to every collected biospecimen by adding the additional specific variables for clinical chemistry and microbiology to our original 170 variables. The College of American Pathologists Diagnostic Intelligence and Health Information Technology Committee sponsored a second Biorepository Working Group to complete the list of preanalytic variables for annotating biospecimens. Members of the second Biorepository Working Group are experts in clinical pathology and microbiology. Additional preanalytic area-specific variables were identified and ranked along with definitions and potential negative impacts if the variable is not attached to the biospecimen. The draft manuscript was reviewed by additional national and international stakeholders. Four additional required preanalytic variables were identified specifically for clinical chemistry and microbiology biospecimens that can be used as a guide for site-specific implementation into patient care and research biorepository processes. In our collective experience, selecting which of the many preanalytic variables to attach to any specific set of biospecimens used for patient care and/or research is often difficult. The additional ranked list should be of practical benefit when selecting preanalytic variables for a given biospecimen collection.

Time-Integral Correlations of Multiple Variables With the Relativistic-Electron Flux at Geosynchronous Orbit: The Strong Roles of Substorm-Injected Electrons and the Ion Plasma Sheet

NASA Astrophysics Data System (ADS)

Borovsky, Joseph E.

2017-12-01

Time-integral correlations are examined between the geosynchronous relativistic electron flux index Fe1.2 and 31 variables of the solar wind and magnetosphere. An "evolutionary algorithm" is used to maximize correlations. Time integrations (into the past) of the variables are found to be superior to time-lagged variables for maximizing correlations with the radiation belt. Physical arguments are given as to why. Dominant correlations are found for the substorm-injected electron flux at geosynchronous orbit and for the pressure of the ion plasma sheet. Different sets of variables are constructed and correlated with Fe1.2: some sets maximize the correlations, and some sets are based on purely solar wind variables. Examining known physical mechanisms that act on the radiation belt, sets of correlations are constructed (1) using magnetospheric variables that control those physical mechanisms and (2) using the solar wind variables that control those magnetospheric variables. Fe1.2-increasing intervals are correlated separately from Fe1.2-decreasing intervals, and the introduction of autoregression into the time-integral correlations is explored. A great impediment to discerning physical cause and effect from the correlations is the fact that all solar wind variables are intercorrelated and carry much of the same information about the time sequence of the solar wind that drives the time sequence of the magnetosphere.

Variability of a "force signature" during windmill softball pitching and relationship between discrete force variables and pitch velocity.

PubMed

Nimphius, Sophia; McGuigan, Michael R; Suchomel, Timothy J; Newton, Robert U

2016-06-01

This study assessed reliability of discrete ground reaction force (GRF) variables over multiple pitching trials, investigated the relationships between discrete GRF variables and pitch velocity (PV) and assessed the variability of the "force signature" or continuous force-time curve during the pitching motion of windmill softball pitchers. Intraclass correlation coefficient (ICC) for all discrete variables was high (0.86-0.99) while the coefficient of variance (CV) was low (1.4-5.2%). Two discrete variables were significantly correlated to PV; second vertical peak force (r(5)=0.81, p=0.03) and time between peak forces (r(5)=-0.79; p=0.03). High ICCs and low CVs support the reliability of discrete GRF and PV variables over multiple trials and significant correlations indicate there is a relationship between the ability to produce force and the timing of this force production with PV. The mean of all pitchers' curve-average standard deviation of their continuous force-time curves demonstrated low variability (CV=4.4%) indicating a repeatable and identifiable "force signature" pattern during this motion. As such, the continuous force-time curve in addition to discrete GRF variables should be examined in future research as a potential method to monitor or explain changes in pitching performance. Copyright © 2016 Elsevier B.V. All rights reserved.

Risk models for post-endoscopic retrograde cholangiopancreatography pancreatitis (PEP): smoking and chronic liver disease are predictors of protection against PEP.

PubMed

DiMagno, Matthew J; Spaete, Joshua P; Ballard, Darren D; Wamsteker, Erik-Jan; Saini, Sameer D

2013-08-01

We investigated which variables independently associated with protection against or development of postendoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) and severity of PEP. Subsequently, we derived predictive risk models for PEP. In a case-control design, 6505 patients had 8264 ERCPs, 211 patients had PEP, and 22 patients had severe PEP. We randomly selected 348 non-PEP controls. We examined 7 established- and 9 investigational variables. In univariate analysis, 7 variables predicted PEP: younger age, female sex, suspected sphincter of Oddi dysfunction (SOD), pancreatic sphincterotomy, moderate-difficult cannulation (MDC), pancreatic stent placement, and lower Charlson score. Protective variables were current smoking, former drinking, diabetes, and chronic liver disease (CLD, biliary/transplant complications). Multivariate analysis identified seven independent variables for PEP, three protective (current smoking, CLD-biliary, CLD-transplant/hepatectomy complications) and 4 predictive (younger age, suspected SOD, pancreatic sphincterotomy, MDC). Pre- and post-ERCP risk models of 7 variables have a C-statistic of 0.74. Removing age (seventh variable) did not significantly affect the predictive value (C-statistic of 0.73) and reduced model complexity. Severity of PEP did not associate with any variables by multivariate analysis. By using the newly identified protective variables with 3 predictive variables, we derived 2 risk models with a higher predictive value for PEP compared to prior studies.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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.

Hierarchy in factors affecting fish biodiversity in floodplain lakes of the Mississippi Alluvial Valley

USGS Publications Warehouse

Dembkowski, D.J.; Miranda, L.E.

2012-01-01

River-floodplain ecosystems offer some of the most diverse and dynamic environments in the world. Accordingly, floodplain habitats harbor diverse fish assemblages. Fish biodiversity in floodplain lakes may be influenced by multiple variables operating on disparate scales, and these variables may exhibit a hierarchical organization depending on whether one variable governs another. In this study, we examined the interaction between primary variables descriptive of floodplain lake large-scale features, suites of secondary variables descriptive of water quality and primary productivity, and a set of tertiary variables descriptive of fish biodiversity across a range of floodplain lakes in the Mississippi Alluvial Valley of Mississippi and Arkansas (USA). Lakes varied considerably in their representation of primary, secondary, and tertiary variables. Multivariate direct gradient analyses indicated that lake maximum depth and the percentage of agricultural land surrounding a lake were the most important factors controlling variation in suites of secondary and tertiary variables, followed to a lesser extent by lake surface area. Fish biodiversity was generally greatest in large, deep lakes with lower proportions of watershed agricultural land. Our results may help foster a holistic approach to floodplain lake management and suggest the framework for a feedback model wherein primary variables can be manipulated for conservation and restoration purposes and secondary and tertiary variables can be used to monitor the success of such efforts. ?? 2011 Springer Science+Business Media B.V.

Factors affecting fish biodiversity in floodplain lakes of the Mississippi Alluvial Valley

USGS Publications Warehouse

Miranda, Leandro E.; Dembkowski, Daniel J.

2012-01-01

River-floodplain ecosystems offer some of the most diverse and dynamic environments in the world. Accordingly, floodplain habitats harbor diverse fish assemblages. Fish biodiversity in floodplain lakes may be influenced by multiple variables operating on disparate scales, and these variables may exhibit a hierarchical organization depending on whether one variable governs another. In this study, we examined the interaction between primary variables descriptive of floodplain lake large-scale features, suites of secondary variables descriptive of water quality and primary productivity, and a set of tertiary variables descriptive of fish biodiversity across a range of floodplain lakes in the Mississippi Alluvial Valley of Mississippi and Arkansas (USA). Lakes varied considerably in their representation of primary, secondary, and tertiary variables. Multivariate direct gradient analyses indicated that lake maximum depth and the percentage of agricultural land surrounding a lake were the most important factors controlling variation in suites of secondary and tertiary variables, followed to a lesser extent by lake surface area. Fish biodiversity was generally greatest in large, deep lakes with lower proportions of watershed agricultural land. Our results may help foster a holistic approach to floodplain lake management and suggest the framework for a feedback model wherein primary variables can be manipulated for conservation and restoration purposes and secondary and tertiary variables can be used to monitor the success of such efforts.

Behavioral variability in SHR and WKY rats as a function of rearing environment and reinforcement contingency.

PubMed Central

Hunziker, M H; Saldana, R L; Neuringer, A

1996-01-01

The spontaneously hypertensive rat (SHR) may model aspects of human attention deficit hyperactivity disorder (ADHD). For example, just as responses by children with ADHD tend to be variable, so too SHRs often respond more variably than do Wistar-Kyoto (WKY) control rats. The present study asked whether behavioral variability in the SHR strain is influenced by rearing environment, a question related to hypotheses concerning the etiology of human ADHD. Some rats from each strain were reared in an enriched environment (housed socially), and others were reared in an impoverished environment (housed in isolation). Four groups--enriched SHR, impoverished SHR, enriched WKY, and impoverished WKY--were studied under two reinforcement contingencies, one in which reinforcement was independent of response variability and the other in which reinforcement depended upon high variability. The main finding was that rearing environment did not influence response variability (enriched and impoverished subjects responded similarly throughout). However, rearing environment affected body weight (enriched subjects weighted more than impoverished subjects) and response rate (impoverished subjects generally responded faster than enriched subjects). In addition, SHRs tended to respond variably throughout the experiment, whereas WKYs were more sensitive to the variability contingencies. Thus, behavioral variability was affected by genetic strain and by reinforcement contingency but not by the environment in which the subjects were reared. PMID:8583193

Robust best linear estimator for Cox regression with instrumental variables in whole cohort and surrogates with additive measurement error in calibration sample

PubMed Central

Wang, Ching-Yun; Song, Xiao

2017-01-01

SUMMARY Biomedical researchers are often interested in estimating the effect of an environmental exposure in relation to a chronic disease endpoint. However, the exposure variable of interest may be measured with errors. In a subset of the whole cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies an additive measurement error model, but it may not have repeated measurements. The subset in which the surrogate variables are available is called a calibration sample. In addition to the surrogate variables that are available among the subjects in the calibration sample, we consider the situation when there is an instrumental variable available for all study subjects. An instrumental variable is correlated with the unobserved true exposure variable, and hence can be useful in the estimation of the regression coefficients. In this paper, we propose a nonparametric method for Cox regression using the observed data from the whole cohort. The nonparametric estimator is the best linear combination of a nonparametric correction estimator from the calibration sample and the difference of the naive estimators from the calibration sample and the whole cohort. The asymptotic distribution is derived, and the finite sample performance of the proposed estimator is examined via intensive simulation studies. The methods are applied to the Nutritional Biomarkers Study of the Women’s Health Initiative. PMID:27546625

Variable-spot ion beam figuring

NASA Astrophysics Data System (ADS)

Wu, Lixiang; Qiu, Keqiang; Fu, Shaojun

2016-03-01

This paper introduces a new scheme of ion beam figuring (IBF), or rather variable-spot IBF, which is conducted at a constant scanning velocity with variable-spot ion beam collimated by a variable diaphragm. It aims at improving the reachability and adaptation of the figuring process within the limits of machine dynamics by varying the ion beam spot size instead of the scanning velocity. In contrast to the dwell time algorithm in the conventional IBF, the variable-spot IBF adopts a new algorithm, which consists of the scan path programming and the trajectory optimization using pattern search. In this algorithm, instead of the dwell time, a new concept, integral etching time, is proposed to interpret the process of variable-spot IBF. We conducted simulations to verify its feasibility and practicality. The simulation results indicate the variable-spot IBF is a promising alternative to the conventional approach.

Sigh rate and respiratory variability during mental load and sustained attention.

PubMed

Vlemincx, Elke; Taelman, Joachim; De Peuter, Steven; Van Diest, Ilse; Van den Bergh, Omer

2011-01-01

Spontaneous breathing consists of substantial correlated variability: Parameters characterizing a breath are correlated with parameters characterizing previous and future breaths. On the basis of dynamic system theory, negative emotion states are predicted to reduce correlated variability whereas sustained attention is expected to reduce total respiratory variability. Both are predicted to evoke sighing. To test this, respiratory variability and sighing were assessed during a baseline, stressful mental arithmetic task, nonstressful sustained attention task, and recovery in between tasks. For respiration rate (excluding sighs), reduced total variability was found during the attention task, whereas correlated variation was reduced during mental load. Sigh rate increased during mental load and during recovery from the attention task. It is concluded that mental load and task-related attention show specific patterns in respiratory variability and sigh rate. Copyright © 2010 Society for Psychophysiological Research.

Cataclysmic Variable Stars

NASA Astrophysics Data System (ADS)

Hellier, Coel

2001-01-01

Cataclysmic variable stars are the most variable stars in the night sky, fluctuating in brightness continually on timescales from seconds to hours to weeks to years. The changes can be recorded using amateur telescopes, yet are also the subject of intensive study by professional astronomers. That study has led to an understanding of cataclysmic variables as binary stars, orbiting so closely that material transfers from one star to the other. The resulting process of accretion is one of the most important in astrophysics. This book presents the first account of cataclysmic variables at an introductory level. Assuming no previous knowledge of the field, it explains the basic principles underlying the variability, while providing an extensive compilation of cataclysmic variable light curves. Aimed at amateur astronomers, undergraduates, and researchers, the main text is accessible to those with no mathematical background, while supplementary boxes present technical details and equations.

[Application of regression tree in analyzing the effects of climate factors on NDVI in loess hilly area of Shaanxi Province].

PubMed

Liu, Yang; Lü, Yi-he; Zheng, Hai-feng; Chen, Li-ding

2010-05-01

Based on the 10-day SPOT VEGETATION NDVI data and the daily meteorological data from 1998 to 2007 in Yan' an City, the main meteorological variables affecting the annual and interannual variations of NDVI were determined by using regression tree. It was found that the effects of test meteorological variables on the variability of NDVI differed with seasons and time lags. Temperature and precipitation were the most important meteorological variables affecting the annual variation of NDVI, and the average highest temperature was the most important meteorological variable affecting the inter-annual variation of NDVI. Regression tree was very powerful in determining the key meteorological variables affecting NDVI variation, but could not build quantitative relations between NDVI and meteorological variables, which limited its further and wider application.

The Association between Tax Structure and Cigarette Price Variability: Findings from the International Tobacco Control Policy Evaluation (ITC) Project

PubMed Central

Shang, Ce; Chaloupka, Frank J.; Fong, Geoffrey T; Thompson, Mary; O’Connor, Richard J

2015-01-01

Background Recent studies have shown that more opportunities exist for tax avoidance when cigarette excise tax structure departs from a uniform specific structure. However, the association between tax structure and cigarette price variability has not been thoroughly studied in the existing literature. Objective To examine how cigarette tax structure is associated with price variability. The variability of self-reported prices is measured using the ratios of differences between higher and lower prices to the median price such as the IQR-to-median ratio. Methods We used survey data taken from the International Tobacco Control Policy Evaluation (ITC) Project in 17 countries to conduct the analysis. Cigarette prices were derived using individual purchase information and aggregated to price variability measures for each surveyed country and wave. The effect of tax structures on price variability was estimated using Generalised Estimating Equations after adjusting for year and country attributes. Findings Our study provides empirical evidence of a relationship between tax structure and cigarette price variability. We find that, compared to the specific uniform tax structure, mixed uniform and tiered (specific, ad valorem or mixed) structures are associated with greater price variability (p≤0.01). Moreover, while a greater share of the specific component in total excise taxes is associated with lower price variability (p≤0.05), a tiered tax structure is associated with greater price variability (p≤0.01). The results suggest that a uniform and specific tax structure is the most effective tax structure for reducing tobacco consumption and prevalence by limiting price variability and decreasing opportunities for tax avoidance. PMID:25855641

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

PubMed Central

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

WEATHER ON OTHER WORLDS. III. A SURVEY FOR T DWARFS WITH HIGH-AMPLITUDE OPTICAL VARIABILITY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heinze, Aren N.; Metchev, Stanimir; Kellogg, Kendra, E-mail: aren.heinze@stonybrook.edu, E-mail: smetchev@uwo.ca

2015-03-10

We have monitored 12 T dwarfs with the Kitt Peak 2.1 m telescope using an F814W filter (0.7-0.95 μm) to place in context the remarkable 10%-20% variability exhibited by the nearby T dwarf Luhman 16B in this wavelength regime. The motivation was the poorly known red optical behavior of T dwarfs, which have been monitored almost exclusively at infrared wavelengths, where variability amplitudes greater than 10% have been found to be very rare. We detect highly significant variability in two T dwarfs. The T2.5 dwarf 2MASS 13243559+6358284 shows consistent ∼17% variability on two consecutive nights. The T2 dwarf 2MASS J16291840+0335371 exhibits ∼10% variability thatmore » may evolve from night to night, similarly to Luhman 16B. Both objects were previously known to be variable in the infrared, but with considerably lower amplitudes. We also find evidence for variability in the T6 dwarf J162414.37+002915.6, but since it has lower significance, we conservatively refrain from claiming this object as a variable. We explore and rule out various telluric effects, demonstrating that the variations we detect are astrophysically real. We suggest that high-amplitude photometric variability for T dwarfs is likely more common in the red optical than at longer wavelengths. The two new members of the growing class of high-amplitude variable T dwarfs offer excellent prospects for further study of cloud structures and their evolution.« less

A review of covariate selection for non-experimental comparative effectiveness research.

PubMed

Sauer, Brian C; Brookhart, M Alan; Roy, Jason; VanderWeele, Tyler

2013-11-01

This paper addresses strategies for selecting variables for adjustment in non-experimental comparative effectiveness research and uses causal graphs to illustrate the causal network that relates treatment to outcome. Variables in the causal network take on multiple structural forms. Adjustment for a common cause pathway between treatment and outcome can remove confounding, whereas adjustment for other structural types may increase bias. For this reason, variable selection would ideally be based on an understanding of the causal network; however, the true causal network is rarely known. Therefore, we describe more practical variable selection approaches based on background knowledge when the causal structure is only partially known. These approaches include adjustment for all observed pretreatment variables thought to have some connection to the outcome, all known risk factors for the outcome, and all direct causes of the treatment or the outcome. Empirical approaches, such as forward and backward selection and automatic high-dimensional proxy adjustment, are also discussed. As there is a continuum between knowing and not knowing the causal, structural relations of variables, we recommend addressing variable selection in a practical way that involves a combination of background knowledge and empirical selection and that uses high-dimensional approaches. This empirical approach can be used to select from a set of a priori variables based on the researcher's knowledge to be included in the final analysis or to identify additional variables for consideration. This more limited use of empirically derived variables may reduce confounding while simultaneously reducing the risk of including variables that may increase bias. Copyright © 2013 John Wiley & Sons, Ltd.

A novel device to stretch multiple tissue samples with variable patterns: application for mRNA regulation in tissue-engineered constructs.

PubMed

Imsirovic, Jasmin; Derricks, Kelsey; Buczek-Thomas, Jo Ann; Rich, Celeste B; Nugent, Matthew A; Suki, Béla

2013-01-01

A broad range of cells are subjected to irregular time varying mechanical stimuli within the body, particularly in the respiratory and circulatory systems. Mechanical stretch is an important factor in determining cell function; however, the effects of variable stretch remain unexplored. In order to investigate the effects of variable stretch, we designed, built and tested a uniaxial stretching device that can stretch three-dimensional tissue constructs while varying the strain amplitude from cycle to cycle. The device is the first to apply variable stretching signals to cells in tissues or three dimensional tissue constructs. Following device validation, we applied 20% uniaxial strain to Gelfoam samples seeded with neonatal rat lung fibroblasts with different levels of variability (0%, 25%, 50% and 75%). RT-PCR was then performed to measure the effects of variable stretch on key molecules involved in cell-matrix interactions including: collagen 1α, lysyl oxidase, α-actin, β1 integrin, β3 integrin, syndecan-4, and vascular endothelial growth factor-A. Adding variability to the stretching signal upregulated, downregulated or had no effect on mRNA production depending on the molecule and the amount of variability. In particular, syndecan-4 showed a statistically significant peak at 25% variability, suggesting that an optimal variability of strain may exist for production of this molecule. We conclude that cycle-by-cycle variability in strain influences the expression of molecules related to cell-matrix interactions and hence may be used to selectively tune the composition of tissue constructs.

A new approach used to explore associations of current Ambrosia pollen levels with current and past meteorological elements

NASA Astrophysics Data System (ADS)

Matyasovszky, István; Makra, László; Csépe, Zoltán; Deák, Áron József; Pál-Molnár, Elemér; Fülöp, Andrea; Tusnády, Gábor

2015-09-01

The paper examines the sensitivity of daily airborne Ambrosia (ragweed) pollen levels of a current pollen season not only on daily values of meteorological variables during this season but also on the past meteorological conditions. The results obtained from a 19-year data set including daily ragweed pollen counts and ten daily meteorological variables are evaluated with special focus on the interactions between the phyto-physiological processes and the meteorological elements. Instead of a Pearson correlation measuring the strength of the linear relationship between two random variables, a generalised correlation that measures every kind of relationship between random vectors was used. These latter correlations between arrays of daily values of the ten meteorological elements and the array of daily ragweed pollen concentrations during the current pollen season were calculated. For the current pollen season, the six most important variables are two temperature variables (mean and minimum temperatures), two humidity variables (dew point depression and rainfall) and two variables characterising the mixing of the air (wind speed and the height of the planetary boundary layer). The six most important meteorological variables before the current pollen season contain four temperature variables (mean, maximum, minimum temperatures and soil temperature) and two variables that characterise large-scale weather patterns (sea level pressure and the height of the planetary boundary layer). Key periods of the past meteorological variables before the current pollen season have been identified. The importance of this kind of analysis is that a knowledge of the past meteorological conditions may contribute to a better prediction of the upcoming pollen season.

A Review of Covariate Selection for Nonexperimental Comparative Effectiveness Research

PubMed Central

Sauer, Brian C.; Brookhart, Alan; Roy, Jason; Vanderweele, Tyler

2014-01-01

This paper addresses strategies for selecting variables for adjustment in non-experimental comparative effectiveness research (CER), and uses causal graphs to illustrate the causal network that relates treatment to outcome. Variables in the causal network take on multiple structural forms. Adjustment for on a common cause pathway between treatment and outcome can remove confounding, while adjustment for other structural types may increase bias. For this reason variable selection would ideally be based on an understanding of the causal network; however, the true causal network is rarely know. Therefore, we describe more practical variable selection approaches based on background knowledge when the causal structure is only partially known. These approaches include adjustment for all observed pretreatment variables thought to have some connection to the outcome, all known risk factors for the outcome, and all direct causes of the treatment or the outcome. Empirical approaches, such as forward and backward selection and automatic high-dimensional proxy adjustment, are also discussed. As there is a continuum between knowing and not knowing the causal, structural relations of variables, we recommend addressing variable selection in a practical way that involves a combination of background knowledge and empirical selection and that uses the high-dimensional approaches. This empirical approach can be used to select from a set of a priori variables based on the researcher’s knowledge to be included in the final analysis or to identify additional variables for consideration. This more limited use of empirically-derived variables may reduce confounding while simultaneously reducing the risk of including variables that may increase bias. PMID:24006330

Evaluating the underlying factors behind variable rate debt.

PubMed

McCue, Michael J; Kim, Tae Hyun Tanny

2007-01-01

Recent trends show a greater usage of variable rate debt among health care bond issues. In 2004, 63.4% of the total health care bonds issued were variable rate compared with 30.6% in 1995 (Fitch Ratings, 2005). The purpose of this study is to gain a better understanding of the underlying factors, credit spread, issue characteristics, and issuer factors behind why hospitals and health system borrowers select variable rate debt compared with fixed rate debt. From 2000 to 2004, this study sampled 230 newly issued tax-exempt bonds issued by acute care hospitals and health care systems that included both variable and fixed rate debt issues. Using a logistic regression model, hospitals with variable rate debt issues were assigned a value of 1, whereas hospitals with fixed rate debt issues were assigned a value of 0. This study found a positive association between bond insurance and variable rate debt and a negative association between callable feature and variable rate debt. Facilities located in certificate-of-need states that possessed higher case mix acuity, earned higher profit margins, generated higher debt service coverage, and held less debt were more likely to issue variable rate debt. Overall, hospital managers and board members of hospitals possessing a strong financial performance have an interest in utilizing variable rate debt to lower their cost of capital. In addition, this outcome may also reflect that investment bankers are doing a better job in educating senior hospital management about the interest rate savings benefit of variable rate compared with fixed rate debt.

A new approach used to explore associations of current Ambrosia pollen levels with current and past meteorological elements.

PubMed

Matyasovszky, István; Makra, László; Csépe, Zoltán; Deák, Áron József; Pál-Molnár, Elemér; Fülöp, Andrea; Tusnády, Gábor

2015-09-01

The paper examines the sensitivity of daily airborne Ambrosia (ragweed) pollen levels of a current pollen season not only on daily values of meteorological variables during this season but also on the past meteorological conditions. The results obtained from a 19-year data set including daily ragweed pollen counts and ten daily meteorological variables are evaluated with special focus on the interactions between the phyto-physiological processes and the meteorological elements. Instead of a Pearson correlation measuring the strength of the linear relationship between two random variables, a generalised correlation that measures every kind of relationship between random vectors was used. These latter correlations between arrays of daily values of the ten meteorological elements and the array of daily ragweed pollen concentrations during the current pollen season were calculated. For the current pollen season, the six most important variables are two temperature variables (mean and minimum temperatures), two humidity variables (dew point depression and rainfall) and two variables characterising the mixing of the air (wind speed and the height of the planetary boundary layer). The six most important meteorological variables before the current pollen season contain four temperature variables (mean, maximum, minimum temperatures and soil temperature) and two variables that characterise large-scale weather patterns (sea level pressure and the height of the planetary boundary layer). Key periods of the past meteorological variables before the current pollen season have been identified. The importance of this kind of analysis is that a knowledge of the past meteorological conditions may contribute to a better prediction of the upcoming pollen season.

Solar variability: Implications for global change

NASA Technical Reports Server (NTRS)

Lean, Judith; Rind, David

1994-01-01

Solar variability is examined in search of implications for global change. The topics covered include the following: solar variation modification of global surface temperature; the significance of solar variability with respect to future climate change; and methods of reducing the uncertainty of the potential amplitude of solar variability on longer time scales.

Can APEX Represent In-Field Spatial Variability and Simulate Its Effects On Crop Yields?

USDA-ARS?s Scientific Manuscript database

Precision agriculture, from variable rate nitrogen application to precision irrigation, promises improved management of resources by considering the spatial variability of topography and soil properties. Hydrologic models need to simulate the effects of this variability if they are to inform about t...

A provisional effective evaluation when errors are present in independent variables

NASA Technical Reports Server (NTRS)

Gurin, L. S.

1983-01-01

Algorithms are examined for evaluating the parameters of a regression model when there are errors in the independent variables. The algorithms are fast and the estimates they yield are stable with respect to the correlation of errors and measurements of both the dependent variable and the independent variables.

Distribution, abundance, and diversity of stream fishes under variable environmental conditions

Treesearch

Christopher M. Taylor; Thomas L. Holder; Richard A. Fiorillo; Lance R. Williams; R. Brent Thomas; Melvin L. Warren

2006-01-01

The effects of stream size and flow regime on spatial and temporal variability of stream fish distribution, abundance, and diversity patterns were investigated. Assemblage variability and species richness were each significantly associated with a complex environmental gradient contrasting smaller, hydrologically variable stream localities with larger localities...

The Effects of Model Misspecification and Sample Size on LISREL Maximum Likelihood Estimates.

ERIC Educational Resources Information Center

Baldwin, Beatrice

The robustness of LISREL computer program maximum likelihood estimates under specific conditions of model misspecification and sample size was examined. The population model used in this study contains one exogenous variable; three endogenous variables; and eight indicator variables, two for each latent variable. Conditions of model…

A Multifactor Approach to Research in Instructional Technology.

ERIC Educational Resources Information Center

Ragan, Tillman J.

In a field such as instructional design, explanations of educational outcomes must necessarily consider multiple input variables. To adequately understand the contribution made by the independent variables, it is helpful to have a visual conception of how the input variables interrelate. Two variable models are adequately represented by a two…

Clustering "N" Objects into "K" Groups under Optimal Scaling of Variables.

ERIC Educational Resources Information Center

van Buuren, Stef; Heiser, Willem J.

1989-01-01

A method based on homogeneity analysis (multiple correspondence analysis or multiple scaling) is proposed to reduce many categorical variables to one variable with "k" categories. The method is a generalization of the sum of squared distances cluster analysis problem to the case of mixed measurement level variables. (SLD)

Romanticism and Self-Esteem among Teen Mothers.

ERIC Educational Resources Information Center

Medora, Nilufer P.; von der Hellen, Cheryl

1997-01-01

Examined teen mothers' (N=94) romanticism and self-esteem so as to investigate these variables' relationships among ten independent variables, (e.g., age and sexual activity). Results indicate that five variables were significantly related to romanticism (previous abortion, etc.), whereas two variables were connected to self-esteem (age and birth…

89. 22'X34' original vellum, VariableAngle Launcher 'ELEVATION OF LAUNCHER BRIDGE ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

89. 22'X34' original vellum, Variable-Angle Launcher 'ELEVATION OF LAUNCHER BRIDGE ON TEMPORARY SUPPORT' drawn at 1'=20'. (BUORD Sketch # 209786, PAPW 1932). - Variable Angle Launcher Complex, Variable Angle Launcher, CA State Highway 39 at Morris Reservior, Azusa, Los Angeles County, CA

90. 22'X34' original blueprint, VariableAngle Launcher, 'FRONT ELEVATION OF LAUNCHER ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

90. 22'X34' original blueprint, Variable-Angle Launcher, 'FRONT ELEVATION OF LAUNCHER BRIDGE, CONNECTING BRIDGE AND BARGES' drawn at 1/4'=1'0'. (BUROD Sketch # 208247). - Variable Angle Launcher Complex, Variable Angle Launcher, CA State Highway 39 at Morris Reservior, Azusa, Los Angeles County, CA

Examining the Causes of Memory Strength Variability: Recollection, Attention Failure, or Encoding Variability?

ERIC Educational Resources Information Center

Koen, Joshua D.; Aly, Mariam; Wang, Wei-Chun; Yonelinas, Andrew P.

2013-01-01

A prominent finding in recognition memory is that studied items are associated with more variability in memory strength than new items. Here, we test 3 competing theories for why this occurs--the "encoding variability," "attention failure", and "recollection" accounts. Distinguishing among these theories is critical…

A Geometrical Framework for Covariance Matrices of Continuous and Categorical Variables

ERIC Educational Resources Information Center

Vernizzi, Graziano; Nakai, Miki

2015-01-01

It is well known that a categorical random variable can be represented geometrically by a simplex. Accordingly, several measures of association between categorical variables have been proposed and discussed in the literature. Moreover, the standard definitions of covariance and correlation coefficient for continuous random variables have been…

Individual animal variability in ruminal bacterial communities and ruminal acidosis in primiparous Holstein cows during the periparturient period

USDA-ARS?s Scientific Manuscript database

The purpose of this study was to investigate variability among individual cows for their susceptibility to ruminal acidosis (RA) pre- and postpartum, and determine whether this variability was related to differences in their ruminal bacterial community composition (BCC). Variability in susceptibilit...

A Systems Approach to Explaining Teachers' Leadership Behavior.

ERIC Educational Resources Information Center

Peterson, Mark F.; Cooke, Robert A.

This paper focuses on identifying the way that individual and organizational variables affect the classroom leadership behavior of teachers. Measured are the effects of one individual-level variable and six organizational variables--three at the organization system level and three at the classroom subsystem level. The individual-level variable is…

Climate variability drives population cycling and synchrony

Treesearch

Lars Y. Pomara; Benjamin Zuckerberg

2017-01-01

Aim There is mounting concern that climate change will lead to the collapse of cyclic population dynamics, yet the influence of climate variability on population cycling remains poorly understood. We hypothesized that variability in survival and fecundity, driven by climate variability at different points in the life cycle, scales up from...

Developmental Differences in Intra-Individual Variability in Children with ADHD and ASD

ERIC Educational Resources Information Center

Belle, Janna; van Hulst, Branko M.; Durston, Sarah

2015-01-01

Background: Intra-individual variability reflects temporal variation within an individual's performance on a cognitive task. Children with developmental disorders, such as ADHD and ASD show increased levels of intra-individual variability. In typical development, intra-individual variability decreases sharply between the ages 6 and 20. The tight…

Current performance of planter technology to support variable-rate seeding in the Southern US

USDA-ARS?s Scientific Manuscript database

Advances in planting technology are expanding opportunities to vary seeding rates on–the-go. Variable-rate seeding can help maximize overall profits by matching optimal planting rates to field production variability. An important aspect of variable-rate seeding is ensuring peak performance of the pl...

Neuroanatomical Substrates of Age-Related Cognitive Decline

ERIC Educational Resources Information Center

Salthouse, Timothy A.

2011-01-01

There are many reports of relations between age and cognitive variables and of relations between age and variables representing different aspects of brain structure and a few reports of relations between brain structure variables and cognitive variables. These findings have sometimes led to inferences that the age-related brain changes cause the…

Econometrics in outcomes research: the use of instrumental variables.

PubMed

Newhouse, J P; McClellan, M

1998-01-01

We describe an econometric technique, instrumental variables, that can be useful in estimating the effectiveness of clinical treatments in situations when a controlled trial has not or cannot be done. This technique relies upon the existence of one or more variables that induce substantial variation in the treatment variable but have no direct effect on the outcome variable of interest. We illustrate the use of the technique with an application to aggressive treatment of acute myocardial infarction in the elderly.

Variable Star and Exoplanet Section of the Czech Astronomical Society

NASA Astrophysics Data System (ADS)

Brát, L.; Zejda, M.

2010-12-01

We present activities of Czech variable star observers organized in the Variable Star and Exoplanet Section of the Czech Astronomical Society. We work in four observing projects: B.R.N.O. - eclipsing binaries, MEDUZA - intrinsic variable stars, TRESCA - transiting exoplanets and candidates, HERO - objects of high energy astrophysics. Detailed information together with O-C gate (database of eclipsing binaries minima timings) and OEJV (Open European Journal on Variable stars) are available on our internet portal http://var.astro.cz.

Intelligent Tutoring for Programming Tasks: Using Plan Analysis to Generate Better Hints.

DTIC Science & Technology

1982-03-01

construction and execution of a BASIC proqram that assiqns an integer value to a variable and then prints the value of that integer. - ARTICHOKE : assign...the string " ARTICHOKE " to a string variable, assiqn the value of that variable to a second variable, and print the second variable. -SINOP: qet two...the first five tasks: GREENFLAG, ARTICHOKE , SINOP, NINOP, and TWOS. Because the protocols are very lonq, it was necessary to condense them into a

CDC6600 subroutine for normal random variables. [RVNORM (RMU, SIG)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Amos, D.E.

1977-04-01

A value y for a uniform variable on (0,1) is generated and a table of 96-percent points for the (0,1) normal distribution is interpolated for a value of the normal variable x(0,1) on 0.02 less than or equal to y less than or equal to 0.98. For the tails, the inverse normal is computed by a rational Chebyshev approximation in an appropriate variable. Then X = x sigma + ..mu.. gives the X(..mu..,sigma) variable.

[Visit-to-visit blood pressure variability: clinical and prognostic significance].

PubMed

Kotovskaia, Iu V; Troitskaia, E A; Kobalava, Zh D

2014-01-01

The phenomenon of variability of blood pressure (BP) was studied for a long time, but recently it has received increased attention, with the focus shifted from short-term BP variability, estimated at daily monitoring for clinical blood pressure variability from visit to visit, which can be regarded as one of the indicators quality control of blood pressure with prolonged treatment. In light of the recent years of clinical data from visit to visit BP variability seems a promising new target for antihypertensive therapy.

Impact of Turbine Modulation on Variable-Cycle Engine Performance. Phase 4. Additional Hardware Design and Fabrication, Engine Modification, and Altitude Test. Part 3 B

DTIC Science & Technology

1974-12-01

urbofan engine performance. An AiKesearch Model TFE731 -2 Turbofan Engine was modified to incorporate production-type variable-geometry hardware...reliability was shown for the variable- geometry components. The TFE731 , modified to include variable geometry, proved to be an inexpensive...Atm at a Met Thrust of 3300 LBF 929 85 Variable-Cycle Engine TFE731 Exhaust-Nozzle Performance 948 86 Analytical Model Comparisons, Aerodynamic

Analysis and modeling of wafer-level process variability in 28 nm FD-SOI using split C-V measurements

NASA Astrophysics Data System (ADS)

Pradeep, Krishna; Poiroux, Thierry; Scheer, Patrick; Juge, André; Gouget, Gilles; Ghibaudo, Gérard

2018-07-01

This work details the analysis of wafer level global process variability in 28 nm FD-SOI using split C-V measurements. The proposed approach initially evaluates the native on wafer process variability using efficient extraction methods on split C-V measurements. The on-wafer threshold voltage (VT) variability is first studied and modeled using a simple analytical model. Then, a statistical model based on the Leti-UTSOI compact model is proposed to describe the total C-V variability in different bias conditions. This statistical model is finally used to study the contribution of each process parameter to the total C-V variability.

Continuous-variable quantum homomorphic signature

NASA Astrophysics Data System (ADS)

Li, Ke; Shang, Tao; Liu, Jian-wei

2017-10-01

Quantum cryptography is believed to be unconditionally secure because its security is ensured by physical laws rather than computational complexity. According to spectrum characteristic, quantum information can be classified into two categories, namely discrete variables and continuous variables. Continuous-variable quantum protocols have gained much attention for their ability to transmit more information with lower cost. To verify the identities of different data sources in a quantum network, we propose a continuous-variable quantum homomorphic signature scheme. It is based on continuous-variable entanglement swapping and provides additive and subtractive homomorphism. Security analysis shows the proposed scheme is secure against replay, forgery and repudiation. Even under nonideal conditions, it supports effective verification within a certain verification threshold.

Estrellas variables en campos de cúmulos abiertos galácticos detectadas en el relevamiento VVV

NASA Astrophysics Data System (ADS)

Palma, T.; Dékany, I.; Clariá, J. J.; Minniti, D.; Alonso-García, J. A.; Ramírez Alegría, S.; Bonatto, C.

2016-08-01

The present project constitutes a massive search for variable stars in the field of open clusters projected on highly reddened regions of the galactic disk and bulge. This search is being performed using -, - and -band observations of the near-infrared variability Survey Vista variables in the Via Lactea. We present the first results obtained in four open clusters projected on the Galactic bulge. The new variables discovered in the current work, 182 in total, are classified on the basis of their light curves and their locations in the corresponding color-magnitude diagrams. Among the newly discovered variable stars, Cepheids, RR Lyrae, Scuti, eclipsing binaries and other types have been found.

Spatio-temporal error growth in the multi-scale Lorenz'96 model

NASA Astrophysics Data System (ADS)

Herrera, S.; Fernández, J.; Rodríguez, M. A.; Gutiérrez, J. M.

2010-07-01

The influence of multiple spatio-temporal scales on the error growth and predictability of atmospheric flows is analyzed throughout the paper. To this aim, we consider the two-scale Lorenz'96 model and study the interplay of the slow and fast variables on the error growth dynamics. It is shown that when the coupling between slow and fast variables is weak the slow variables dominate the evolution of fluctuations whereas in the case of strong coupling the fast variables impose a non-trivial complex error growth pattern on the slow variables with two different regimes, before and after saturation of fast variables. This complex behavior is analyzed using the recently introduced Mean-Variance Logarithmic (MVL) diagram.

Mythical Maia, ultrashort and 53 PSC variables. Lecture 4

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cox, A.N.

1983-03-14

Moving down the main sequence from the ..beta.. Cephei variables, we come to later B-type stars. The suspicion of variability for these stars goes back to Vogel in 1891 who studied the radial velocities of Vega. Since that time there have been numerous studies of Vega (Wisniewski and Johnson 1979, Fernie 1981) and other B and early A stars which hint at variability in both radial velocity and light. Since Struve (1955) discussed these stars 28 years ago, they have been called the Maia stars after the Pleiades star that he thought was the prototype. The uncertainty in their actualmore » variability has led Breger (1980) to call them the mythical Maia variables.« less

Linear solvation energy relationships: "rule of thumb" for estimation of variable values

USGS Publications Warehouse

Hickey, James P.; Passino-Reader, Dora R.

1991-01-01

For the linear solvation energy relationship (LSER), values are listed for each of the variables (Vi/100, π*, &betam, αm) for fundamental organic structures and functional groups. We give the guidelines to estimate LSER variable values quickly for a vast array of possible organic compounds such as those found in the environment. The difficulty in generating these variables has greatly discouraged the application of this quantitative structure-activity relationship (QSAR) method. This paper present the first compilation of molecular functional group values together with a utilitarian set of the LSER variable estimation rules. The availability of these variable values and rules should facilitate widespread application of LSER for hazard evaluation of environmental contaminants.

Perspectives for short timescale variability studies with Gaia

NASA Astrophysics Data System (ADS)

Roelens, M.; Eyer, L.; Mowlavi, N.; Lecoeur-Taïbi, I.; Rimoldini, L.; Blanco-Cuaresma, S.; Palaversa, L.; Süveges, M.; Charnas, J.; Wevers, T.

2017-12-01

We assess the potential of Gaia for detecting and characterizing short timescale variables, i.e. at timescale from a few seconds to a dozen hours, through extensive light-curve simulations for various short timescale variable types, including both periodic and non-periodic variability. We evidence that the variogram analysis applied to Gaia photometry should enable to detect such fast variability phenomena, down to amplitudes of a few millimagnitudes, with limited contamination from longer timescale variables or constant sources. This approach also gives valuable information on the typical timescale(s) of the considered variation, which could complement results of classical period search methods, and help prepare ground-based follow-up of the Gaia short timescale candidates.

How Well Has Global Ocean Heat Content Variability Been Measured?

NASA Astrophysics Data System (ADS)

Nelson, A.; Weiss, J.; Fox-Kemper, B.; Fabienne, G.

2016-12-01

We introduce a new strategy that uses synthetic observations of an ensemble of model simulations to test the fidelity of an observational strategy, quantifying how well it captures the statistics of variability. We apply this test to the 0-700m global ocean heat content anomaly (OHCA) as observed with in-situ measurements by the Coriolis Dataset for Reanalysis (CORA), using the Community Climate System Model (CCSM) version 3.5. One-year running mean OHCAs for the years 2005 onward are found to faithfully capture the variability. During these years, synthetic observations of the model are strongly correlated at 0.94±0.06 with the actual state of the model. Overall, sub-annual variability and data before 2005 are significantly affected by the variability of the observing system. In contrast, the sometimes-used weighted integral of observations is not a good indicator of OHCA as variability in the observing system contaminates dynamical variability.

Metacognitive judgments of repetition and variability effects in natural concept learning: evidence for variability neglect.

PubMed

Wahlheim, Christopher N; Finn, Bridgid; Jacoby, Larry L

2012-07-01

In four experiments, we examined the effects of repetitions and variability on the learning of bird families and metacognitive awareness of such effects. Of particular interest was the accuracy of, and bases for, predictions regarding classification of novel bird species, referred to as category learning judgments (CLJs). Participants studied birds in high repetitions and high variability conditions. These conditions differed in the number of presentations of each bird (repetitions) and the number of unique species from each family (variability). After study, participants made CLJs for each family and were then tested. Results from a classification test revealed repetition benefits for studied species and variability benefits for novel species. In contrast with performance, CLJs did not reflect the benefits of variability. Results showed that CLJs were susceptible to accessibility-based metacognitive illusions produced by additional repetitions of studied items.

Revealing the ultrafast outflow in IRAS 13224-3809 through spectral variability

NASA Astrophysics Data System (ADS)

Parker, M. L.; Alston, W. N.; Buisson, D. J. K.; Fabian, A. C.; Jiang, J.; Kara, E.; Lohfink, A.; Pinto, C.; Reynolds, C. S.

2017-08-01

We present an analysis of the long-term X-ray variability of the extreme narrow-line Seyfert 1 galaxy IRAS 13224-3809 using principal component analysis (PCA) and fractional excess variability (Fvar) spectra to identify model-independent spectral components. We identify a series of variability peaks in both the first PCA component and Fvar spectrum which correspond to the strongest predicted absorption lines from the ultrafast outflow (UFO) discovered by Parker et al. (2017). We also find higher order PCA components, which correspond to variability of the soft excess and reflection features. The subtle differences between RMS and PCA results argue that the observed flux-dependence of the absorption is due to increased ionization of the gas, rather than changes in column density or covering fraction. This result demonstrates that we can detect outflows from variability alone and that variability studies of UFOs are an extremely promising avenue for future research.

Variability modifies life satisfaction's association with mortality risk in older adults

PubMed Central

Boehm, Julia K.; Winning, Ashley; Segerstrom, Suzanne; Kubzansky, Laura D.

2015-01-01

Life satisfaction is associated with greater longevity, but its variability across time has not been examined relative to longevity. We investigated whether mean levels of life satisfaction across time, variability in life satisfaction across time, and their interaction were associated with mortality over 9 years of follow-up. Participants were 4,458 Australians initially ≥50 years old. During the follow-up, 546 people died. Adjusting for age, greater mean life satisfaction was associated with reduced risk and greater variability in life satisfaction was associated with increased risk of mortality. These findings were qualified by a significant interaction such that individuals with low mean satisfaction and high variability in satisfaction had the greatest risk of mortality over the follow-up period. In combination with mean levels of life satisfaction, variability in life satisfaction is relevant for mortality risk among older adults. Considering intraindividual variability provides additional insight into associations between psychological characteristics and health. PMID:26048888

Effects of demographic and health variables on Rasch scaled cognitive scores.

PubMed

Zelinski, Elizabeth M; Gilewski, Michael J

2003-08-01

To determine whether demographic and health variables interact to predict cognitive scores in Asset and Health Dynamics of the Oldest-Old (AHEAD), a representative survey of older Americans, as a test of the developmental discontinuity hypothesis. Rasch modeling procedures were used to rescale cognitive measures into interval scores, equating scales across measures, making it possible to compare predictor effects directly. Rasch scaling also reduces the likelihood of obtaining spurious interactions. Tasks included combined immediate and delayed recall, the Telephone Interview for Cognitive Status (TICS), Series 7, and an overall cognitive score. Demographic variables most strongly predicted performance on all scores, with health variables having smaller effects. Age interacted with both demographic and health variables, but patterns of effects varied. Demographic variables have strong effects on cognition. The developmental discontinuity hypothesis that health variables have stronger effects than demographic ones on cognition in older adults was not supported.

GANP regulates recruitment of AID to immunoglobulin variable regions by modulating transcription and nucleosome occupancy

PubMed Central

Singh, Shailendra Kumar; Maeda, Kazuhiko; Eid, Mohammed Mansour Abbas; Almofty, Sarah Ameen; Ono, Masaya; Pham, Phuong; Goodman, Myron F.; Sakaguchi, Nobuo

2013-01-01

Somatic hypermutation in B cells is initiated by activation-induced cytidine deaminase-catalyzed C→U deamination at immunoglobulin variable regions. Here we investigate the role of the germinal centre-associated nuclear protein (GANP) in enhancing the access of activation-induced cytidine deaminase (AID) to immunoglobulin variable regions. We show that the nuclear export factor GANP is involved in chromatin modification at rearranged immunoglobulin variable loci, and its activity requires a histone acetyltransferase domain. GANP interacts with the transcription stalling protein Spt5 and facilitates RNA Pol-II recruitment to immunoglobulin variable regions. Germinal centre B cells from ganp-transgenic mice showed a higher AID occupancy at the immunoglobulin variable region, whereas B cells from conditional ganp-knockout mice exhibit a lower AID accessibility. These findings suggest that GANP-mediated chromatin modification promotes transcription complex recruitment and positioning at immunoglobulin variable loci to favour AID targeting. PMID:23652018

VARIABLE TIME-INTERVAL GENERATOR

DOEpatents

Gross, J.E.

1959-10-31

This patent relates to a pulse generator and more particularly to a time interval generator wherein the time interval between pulses is precisely determined. The variable time generator comprises two oscillators with one having a variable frequency output and the other a fixed frequency output. A frequency divider is connected to the variable oscillator for dividing its frequency by a selected factor and a counter is used for counting the periods of the fixed oscillator occurring during a cycle of the divided frequency of the variable oscillator. This defines the period of the variable oscillator in terms of that of the fixed oscillator. A circuit is provided for selecting as a time interval a predetermined number of periods of the variable oscillator. The output of the generator consists of a first pulse produced by a trigger circuit at the start of the time interval and a second pulse marking the end of the time interval produced by the same trigger circuit.

Atypical Reactivity of Heart Rate Variability to Stress and Depression: Systematic Review of the Literature and Directions for Future Research

PubMed Central

Hamilton, Jessica L.; Alloy, Lauren B.

2017-01-01

Heart rate variability has received growing attention in the depression literature, with several recent meta-analyses indicating that lower resting heart rate variability is associated with depression. However, the role of fluctuations in heart rate variability (or reactivity) in response to stress in depression remains less clear. The present review provides a systematic examination of the literature on heart rate variability reactivity to a laboratory-induced stressor task and depression, including 26 studies of reactivity in heart rate variability and clinical depression, remitted (or history of) depression, and subthreshold depression (or symptom-level depression) among adults, adolescents, and children. In addition to reviewing the findings of these studies, methodological considerations and conceptual gaps in the literature are addressed. We conclude by highlighting the importance of investigating the potential transactional relationship between heart rate variability reactivity and depression and possible mechanisms underlying this relationship. PMID:27697746

Statistical optics

NASA Astrophysics Data System (ADS)

Goodman, J. W.

This book is based on the thesis that some training in the area of statistical optics should be included as a standard part of any advanced optics curriculum. Random variables are discussed, taking into account definitions of probability and random variables, distribution functions and density functions, an extension to two or more random variables, statistical averages, transformations of random variables, sums of real random variables, Gaussian random variables, complex-valued random variables, and random phasor sums. Other subjects examined are related to random processes, some first-order properties of light waves, the coherence of optical waves, some problems involving high-order coherence, effects of partial coherence on imaging systems, imaging in the presence of randomly inhomogeneous media, and fundamental limits in photoelectric detection of light. Attention is given to deterministic versus statistical phenomena and models, the Fourier transform, and the fourth-order moment of the spectrum of a detected speckle image.

Effect of age on variability in the production of text-based global inferences.

PubMed

Williams, Lynne J; Dunlop, Joseph P; Abdi, Hervé

2012-01-01

As we age, our differences in cognitive skills become more visible, an effect especially true for memory and problem solving skills (i.e., fluid intelligence). However, by contrast with fluid intelligence, few studies have examined variability in measures that rely on one's world knowledge (i.e., crystallized intelligence). The current study investigated whether age increased the variability in text based global inference generation--a measure of crystallized intelligence. Global inference generation requires the integration of textual information and world knowledge and can be expressed as a gist or lesson. Variability in generating two global inferences for a single text was examined in young-old (62 to 69 years), middle-old (70 to 76 years) and old-old (77 to 94 years) adults. The older two groups showed greater variability, with the middle elderly group being most variable. These findings suggest that variability may be a characteristic of both fluid and crystallized intelligence in aging.

Optimal allocation of testing resources for statistical simulations

NASA Astrophysics Data System (ADS)

Quintana, Carolina; Millwater, Harry R.; Singh, Gulshan; Golden, Patrick

2015-07-01

Statistical estimates from simulation involve uncertainty caused by the variability in the input random variables due to limited data. Allocating resources to obtain more experimental data of the input variables to better characterize their probability distributions can reduce the variance of statistical estimates. The methodology proposed determines the optimal number of additional experiments required to minimize the variance of the output moments given single or multiple constraints. The method uses multivariate t-distribution and Wishart distribution to generate realizations of the population mean and covariance of the input variables, respectively, given an amount of available data. This method handles independent and correlated random variables. A particle swarm method is used for the optimization. The optimal number of additional experiments per variable depends on the number and variance of the initial data, the influence of the variable in the output function and the cost of each additional experiment. The methodology is demonstrated using a fretting fatigue example.

Replicates in high dimensions, with applications to latent variable graphical models.

PubMed

Tan, Kean Ming; Ning, Yang; Witten, Daniela M; Liu, Han

2016-12-01

In classical statistics, much thought has been put into experimental design and data collection. In the high-dimensional setting, however, experimental design has been less of a focus. In this paper, we stress the importance of collecting multiple replicates for each subject in this setting. We consider learning the structure of a graphical model with latent variables, under the assumption that these variables take a constant value across replicates within each subject. By collecting multiple replicates for each subject, we are able to estimate the conditional dependence relationships among the observed variables given the latent variables. To test the null hypothesis of conditional independence between two observed variables, we propose a pairwise decorrelated score test. Theoretical guarantees are established for parameter estimation and for this test. We show that our proposal is able to estimate latent variable graphical models more accurately than some existing proposals, and apply the proposed method to a brain imaging dataset.

A National Reassessment: Exploring Variables that Predispose People with Disabilities to Vocational Rehabilitation Acceptance

ERIC Educational Resources Information Center

Wilson, Keith B.; Gines, Jason E.

2009-01-01

Vocational rehabilitation (VR) acceptance has been explored by many research teams over the last 30 years. However, none of the prior studies explored the multitude of demographic variables that may influence VR acceptance and the possible interactions of those variables with VR acceptance. Extrapolating demographic variables from the national…

The Perceived Success of Tutoring Students with Learning Disabilities: Relations to Tutee and Tutoring Variables

ERIC Educational Resources Information Center

Michael, Rinat

2016-01-01

The current study examined the contribution of two types of variables to the perceived success of a tutoring project for college students with learning disabilities (LD): tutoring-related variables (the degree of engagement in different tutoring activities and difficulties encountered during tutoring), and tutee-related variables (learning…

Children's and Adults' Interpretation of Covariation Data: Does Symmetry of Variables Matter?

ERIC Educational Resources Information Center

Saffran, Andrea; Barchfeld, Petra; Sodian, Beate; Alibali, Martha W.

2016-01-01

In a series of 3 experiments, the authors investigated the influence of symmetry of variables on children's and adults' data interpretation. They hypothesized that symmetrical (i.e., present/present) variables would support correct interpretations more than asymmetrical (i.e., present/absent) variables. Participants were asked to judge covariation…

Individual Variables, Literacy History, and ESL Progress Among Kurdish and Bosnian Immigrants.

ERIC Educational Resources Information Center

Gardner, Sheena; And Others

1996-01-01

Examines the relationship between individual variables and the progress in English as a Second Language (ESL) among Kurdish and Bosnian adult immigrants living in Canada. Findings reveal significant correlations between the dependent variables of oral and written progress and the independent variables of literacy level, years of schooling, and…

How Robust Is Linear Regression with Dummy Variables?

ERIC Educational Resources Information Center

Blankmeyer, Eric

2006-01-01

Researchers in education and the social sciences make extensive use of linear regression models in which the dependent variable is continuous-valued while the explanatory variables are a combination of continuous-valued regressors and dummy variables. The dummies partition the sample into groups, some of which may contain only a few observations.…

Unitary Response Regression Models

ERIC Educational Resources Information Center

Lipovetsky, S.

2007-01-01

The dependent variable in a regular linear regression is a numerical variable, and in a logistic regression it is a binary or categorical variable. In these models the dependent variable has varying values. However, there are problems yielding an identity output of a constant value which can also be modelled in a linear or logistic regression with…

Discrimination of Variable Schedules Is Controlled by Interresponse Times Proximal to Reinforcement

ERIC Educational Resources Information Center

Tanno, Takayuki; Silberberg, Alan; Sakagami, Takayuki

2012-01-01

In Experiment 1, food-deprived rats responded to one of two schedules that were, with equal probability, associated with a sample lever. One schedule was always variable ratio, while the other schedule, depending on the trial within a session, was: (a) a variable-interval schedule; (b) a tandem variable-interval,…

Schedule-Induced and Operant Mechanisms that Influence Response Variability: A Review and Implications for Future Investigations

ERIC Educational Resources Information Center

Lee, Ronald; Sturmey, Peter; Fields, Lanny

2007-01-01

Response variability, a fundamental characteristic of behavior, may be in some cases an induced effect of reinforcement schedules. Research on schedule-induced response variability has shown that continuous reinforcement results in less variability than intermittent reinforcement schedules. Studies on the effects of intermittency of reinforcement,…

Parametric Cost Models for Space Telescopes

NASA Technical Reports Server (NTRS)

Stahl, H. Philip

2010-01-01

A study is in-process to develop a multivariable parametric cost model for space telescopes. Cost and engineering parametric data has been collected on 30 different space telescopes. Statistical correlations have been developed between 19 variables of 59 variables sampled. Single Variable and Multi-Variable Cost Estimating Relationships have been developed. Results are being published.

Preliminary Multi-Variable Parametric Cost Model for Space Telescopes

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Hendrichs, Todd

2010-01-01

This slide presentation reviews creating a preliminary multi-variable cost model for the contract costs of making a space telescope. There is discussion of the methodology for collecting the data, definition of the statistical analysis methodology, single variable model results, testing of historical models and an introduction of the multi variable models.

Air velocity distributions inside tree canopies from a variable-rate air-assisted sprayer

USDA-ARS?s Scientific Manuscript database

A variable-rate, air assisted, five-port sprayer had been in development to achieve variable discharge rates of both liquid and air. To verify the variable air rate capability by changing the fan inlet diameter of the sprayer, air jet velocities impeded by plant canopies were measured at various loc...

Estimating and Interpreting Latent Variable Interactions: A Tutorial for Applying the Latent Moderated Structural Equations Method

ERIC Educational Resources Information Center

Maslowsky, Julie; Jager, Justin; Hemken, Douglas

2015-01-01

Latent variables are common in psychological research. Research questions involving the interaction of two variables are likewise quite common. Methods for estimating and interpreting interactions between latent variables within a structural equation modeling framework have recently become available. The latent moderated structural equations (LMS)…

A Note on McDonald's Generalization of Principal Components Analysis

ERIC Educational Resources Information Center

Shine, Lester C., II

1972-01-01

It is shown that McDonald's generalization of Classical Principal Components Analysis to groups of variables maximally channels the totalvariance of the original variables through the groups of variables acting as groups. An equation is obtained for determining the vectors of correlations of the L2 components with the original variables.…

Within-Students Variability in Learning Experiences, and Teachers' Perceptions of Students' Task-Focus

ERIC Educational Resources Information Center

Malmberg, Lars-Erik; Lim, Wee H. T.; Tolvanen, Asko; Nurmi, Jari-Erik

2016-01-01

In order to advance our understanding of educational processes, we present a tutorial of intraindividual variability. An adaptive educational process is characterised by stable (less variability), and a maladaptive process is characterised by instable (more variability) learning experiences from one learning situation to the next. We outline step…

An Observation on the Role of Context Variability in Free Recall

ERIC Educational Resources Information Center

Hicks, Jason L.; Marsh, Richard L.; Cook, Gabriel I.

2005-01-01

The authors conducted 3 experiments investigating the effect of context variability and word frequency on free recall. Context variability refers to the number of preexperimental contexts in which a given word is experienced. Both between-subjects and within-subjects manipulations of context variability demonstrated a distinct advantage for low…

The Non-Effect of Process-Product Variables in Resource Classrooms.

ERIC Educational Resources Information Center

Skiba, Russell; And Others

To test the efficacy of variables found effective in regular classrooms (in previous process-product research), variables were observed for 126 elementary school children in 17 resource classrooms. Measurement of teacher structure and student achievement was performed. Results indicated that, although most of the variables were used to at least a…

Exploring the Impact of Early Decisions in Variable Ordering for Constraint Satisfaction Problems.

PubMed

Ortiz-Bayliss, José Carlos; Amaya, Ivan; Conant-Pablos, Santiago Enrique; Terashima-Marín, Hugo

2018-01-01

When solving constraint satisfaction problems (CSPs), it is a common practice to rely on heuristics to decide which variable should be instantiated at each stage of the search. But, this ordering influences the search cost. Even so, and to the best of our knowledge, no earlier work has dealt with how first variable orderings affect the overall cost. In this paper, we explore the cost of finding high-quality orderings of variables within constraint satisfaction problems. We also study differences among the orderings produced by some commonly used heuristics and the way bad first decisions affect the search cost. One of the most important findings of this work confirms the paramount importance of first decisions. Another one is the evidence that many of the existing variable ordering heuristics fail to appropriately select the first variable to instantiate. Another one is the evidence that many of the existing variable ordering heuristics fail to appropriately select the first variable to instantiate. We propose a simple method to improve early decisions of heuristics. By using it, performance of heuristics increases.

Determining Directional Dependency in Causal Associations

PubMed Central

Pornprasertmanit, Sunthud; Little, Todd D.

2014-01-01

Directional dependency is a method to determine the likely causal direction of effect between two variables. This article aims to critique and improve upon the use of directional dependency as a technique to infer causal associations. We comment on several issues raised by von Eye and DeShon (2012), including: encouraging the use of the signs of skewness and excessive kurtosis of both variables, discouraging the use of D’Agostino’s K2, and encouraging the use of directional dependency to compare variables only within time points. We offer improved steps for determining directional dependency that fix the problems we note. Next, we discuss how to integrate directional dependency into longitudinal data analysis with two variables. We also examine the accuracy of directional dependency evaluations when several regression assumptions are violated. Directional dependency can suggest the direction of a relation if (a) the regression error in population is normal, (b) an unobserved explanatory variable correlates with any variables equal to or less than .2, (c) a curvilinear relation between both variables is not strong (standardized regression coefficient ≤ .2), (d) there are no bivariate outliers, and (e) both variables are continuous. PMID:24683282

Variability of Neuronal Responses: Types and Functional Significance in Neuroplasticity and Neural Darwinism

PubMed Central

Chervyakov, Alexander V.; Sinitsyn, Dmitry O.; Piradov, Michael A.

2016-01-01

HIGHLIGHTS We suggest classifying variability of neuronal responses as follows: false (associated with a lack of knowledge about the influential factors), “genuine harmful” (noise), “genuine neutral” (synonyms, repeats), and “genuine useful” (the basis of neuroplasticity and learning).The genuine neutral variability is considered in terms of the phenomenon of degeneracy.Of particular importance is the genuine useful variability that is considered as a potential basis for neuroplasticity and learning. This type of variability is considered in terms of the neural Darwinism theory. In many cases, neural signals detected under the same external experimental conditions significantly change from trial to trial. The variability phenomenon, which complicates extraction of reproducible results and is ignored in many studies by averaging, has attracted attention of researchers in recent years. In this paper, we classify possible types of variability based on its functional significance and describe features of each type. We describe the key adaptive significance of variability at the neural network level and the degeneracy phenomenon that may be important for learning processes in connection with the principle of neuronal group selection. PMID:27932969

Variability of Neuronal Responses: Types and Functional Significance in Neuroplasticity and Neural Darwinism.

PubMed

Chervyakov, Alexander V; Sinitsyn, Dmitry O; Piradov, Michael A

2016-01-01

HIGHLIGHTS We suggest classifying variability of neuronal responses as follows: false (associated with a lack of knowledge about the influential factors), "genuine harmful" (noise), "genuine neutral" (synonyms, repeats), and "genuine useful" (the basis of neuroplasticity and learning).The genuine neutral variability is considered in terms of the phenomenon of degeneracy.Of particular importance is the genuine useful variability that is considered as a potential basis for neuroplasticity and learning. This type of variability is considered in terms of the neural Darwinism theory. In many cases, neural signals detected under the same external experimental conditions significantly change from trial to trial. The variability phenomenon, which complicates extraction of reproducible results and is ignored in many studies by averaging, has attracted attention of researchers in recent years. In this paper, we classify possible types of variability based on its functional significance and describe features of each type. We describe the key adaptive significance of variability at the neural network level and the degeneracy phenomenon that may be important for learning processes in connection with the principle of neuronal group selection.

Variables that Predict Serve Efficacy in Elite Men’s Volleyball with Different Quality of Opposition Sets

PubMed Central

Valhondo, Álvaro; Fernández-Echeverría, Carmen; González-Silva, Jara; Claver, Fernando; Moreno, M. Perla

2018-01-01

Abstract The objective of this study was to determine the variables that predicted serve efficacy in elite men’s volleyball, in sets with different quality of opposition. 3292 serve actions were analysed, of which 2254 were carried out in high quality of opposition sets and 1038 actions were in low quality of opposition sets, corresponding to a total of 24 matches played during the Men’s European Volleyball Championships held in 2011. The independent variables considered in this study were the serve zone, serve type, serving player, serve direction, reception zone, receiving player and reception type; the dependent variable was serve efficacy and the situational variable was quality of opposition sets. The variables that acted as predictors in both high and low quality of opposition sets were the serving player, reception zone and reception type. The serve type variable only acted as a predictor in high quality of opposition sets, while the serve zone variable only acted as a predictor in low quality of opposition sets. These results may provide important guidance in men’s volleyball training processes. PMID:29599869

Exploring the Impact of Early Decisions in Variable Ordering for Constraint Satisfaction Problems

PubMed Central

Amaya, Ivan

2018-01-01

When solving constraint satisfaction problems (CSPs), it is a common practice to rely on heuristics to decide which variable should be instantiated at each stage of the search. But, this ordering influences the search cost. Even so, and to the best of our knowledge, no earlier work has dealt with how first variable orderings affect the overall cost. In this paper, we explore the cost of finding high-quality orderings of variables within constraint satisfaction problems. We also study differences among the orderings produced by some commonly used heuristics and the way bad first decisions affect the search cost. One of the most important findings of this work confirms the paramount importance of first decisions. Another one is the evidence that many of the existing variable ordering heuristics fail to appropriately select the first variable to instantiate. Another one is the evidence that many of the existing variable ordering heuristics fail to appropriately select the first variable to instantiate. We propose a simple method to improve early decisions of heuristics. By using it, performance of heuristics increases. PMID:29681923

Deciphering Sources of Variability in Clinical Pathology.

PubMed

Tripathi, Niraj K; Everds, Nancy E; Schultze, A Eric; Irizarry, Armando R; Hall, Robert L; Provencher, Anne; Aulbach, Adam

2017-01-01

The objectives of this session were to explore causes of variability in clinical pathology data due to preanalytical and analytical variables as well as study design and other procedures that occur in toxicity testing studies. The presenters highlighted challenges associated with such variability in differentiating test article-related effects from the effects of experimental procedures and its impact on overall data interpretation. These presentations focused on preanalytical and analytical variables and study design-related factors and their influence on clinical pathology data, and the importance of various factors that influence data interpretation including statistical analysis and reference intervals. Overall, these presentations touched upon potential effect of many variables on clinical pathology parameters, including animal physiology, sample collection process, specimen handling and analysis, study design, and some discussion points on how to manage those variables to ensure accurate interpretation of clinical pathology data in toxicity studies. This article is a brief synopsis of presentations given in a session entitled "Deciphering Sources of Variability in Clinical Pathology-It's Not Just about the Numbers" that occurred at the 35th Annual Symposium of the Society of Toxicologic Pathology in San Diego, California.

Review and classification of variability analysis techniques with clinical applications.

PubMed

Bravi, Andrea; Longtin, André; Seely, Andrew J E

2011-10-10

Analysis of patterns of variation of time-series, termed variability analysis, represents a rapidly evolving discipline with increasing applications in different fields of science. In medicine and in particular critical care, efforts have focussed on evaluating the clinical utility of variability. However, the growth and complexity of techniques applicable to this field have made interpretation and understanding of variability more challenging. Our objective is to provide an updated review of variability analysis techniques suitable for clinical applications. We review more than 70 variability techniques, providing for each technique a brief description of the underlying theory and assumptions, together with a summary of clinical applications. We propose a revised classification for the domains of variability techniques, which include statistical, geometric, energetic, informational, and invariant. We discuss the process of calculation, often necessitating a mathematical transform of the time-series. Our aims are to summarize a broad literature, promote a shared vocabulary that would improve the exchange of ideas, and the analyses of the results between different studies. We conclude with challenges for the evolving science of variability analysis.

Calibration of multivariate scatter plots for exploratory analysis of relations within and between sets of variables in genomic research.

PubMed

Graffelman, Jan; van Eeuwijk, Fred

2005-12-01

The scatter plot is a well known and easily applicable graphical tool to explore relationships between two quantitative variables. For the exploration of relations between multiple variables, generalisations of the scatter plot are useful. We present an overview of multivariate scatter plots focussing on the following situations. Firstly, we look at a scatter plot for portraying relations between quantitative variables within one data matrix. Secondly, we discuss a similar plot for the case of qualitative variables. Thirdly, we describe scatter plots for the relationships between two sets of variables where we focus on correlations. Finally, we treat plots of the relationships between multiple response and predictor variables, focussing on the matrix of regression coefficients. We will present both known and new results, where an important original contribution concerns a procedure for the inclusion of scales for the variables in multivariate scatter plots. We provide software for drawing such scales. We illustrate the construction and interpretation of the plots by means of examples on data collected in a genomic research program on taste in tomato.

ROTSE All-Sky Surveys for Variable Stars. I. Test Fields

NASA Astrophysics Data System (ADS)

Akerlof, C.; Amrose, S.; Balsano, R.; Bloch, J.; Casperson, D.; Fletcher, S.; Gisler, G.; Hills, J.; Kehoe, R.; Lee, B.; Marshall, S.; McKay, T.; Pawl, A.; Schaefer, J.; Szymanski, J.; Wren, J.

2000-04-01

The Robotic Optical Transient Search Experiment I (ROTSE-I) experiment has generated CCD photometry for the entire northern sky in two epochs nightly since 1998 March. These sky patrol data are a powerful resource for studies of astrophysical transients. As a demonstration project, we present first results of a search for periodic variable stars derived from ROTSE-I observations. Variable identification, period determination, and type classification are conducted via automatic algorithms. In a set of nine ROTSE-I sky patrol fields covering roughly 2000 deg2, we identify 1781 periodic variable stars with mean magnitudes between mv=10.0 and mv=15.5. About 90% of these objects are newly identified as variable. Examples of many familiar types are presented. All classifications for this study have been manually confirmed. The selection criteria for this analysis have been conservatively defined and are known to be biased against some variable classes. This preliminary study includes only 5.6% of the total ROTSE-I sky coverage, suggesting that the full ROTSE-I variable catalog will include more than 32,000 periodic variable stars.

A comparison of sea surface salinity in the equatorial Pacific Ocean during the 1997-1998, 2012-2013, and 2014-2015 ENSO events

NASA Astrophysics Data System (ADS)

Corbett, Caroline M.; Subrahmanyam, Bulusu; Giese, Benjamin S.

2017-11-01

Sea surface salinity (SSS) variability during the 1997-1998 El Niño event and the failed 2012-2013 and 2014-2015 El Niño events is explored using a combination of observations and ocean reanalyses. Previously, studies have mainly focused on the sea surface temperature (SST) and sea surface height (SSH) variability. This analysis utilizes salinity data from Argo and the Simple Ocean Data Assimilation (SODA) reanalysis to examine the SSS variability. Advective processes and evaporation minus precipitation (E-P) variability is understood to influence SSS variability. Using surface wind, surface current, evaporation, and precipitation data, we analyze the causes for the observed SSS variability during each event. Barrier layer thickness and upper level salt content are also examined in connection to subsurface salinity variability. Both advective processes and E-P variability are important during the generation and onset of a successful El Niño, while a lack of one or both of these processes leads to a failed ENSO event.

Movement Variability Increases With Shoulder Pain When Compensatory Strategies of the Upper Body Are Constrained.

PubMed

López-Pascual, Juan; Page, Álvaro; Serra-Añó, Pilar

2017-10-13

This cross-sectional study analyzed the influence of chronic shoulder pain (CSP) on movement variability/kinematics during humeral elevation, with the trunk and elbow motions constrained to avoid compensatory strategies. For this purpose, 37 volunteers with CSP as the injured group (IG) and 58 participants with asymptomatic shoulders as the control group (CG) participated in the study. Maximum humeral elevation (Emax), maximum angular velocity (Velmax), variability of the maximum angle (CVEmax), functional variability (Func_var), and approximate entropy (ApEn) were calculated from the kinematic data. Patients' pain was measured on the visual analogue scale (VAS). Compared with the CG, the IG presented lower Emax and Velmax and higher variability (i.e., CVEmax, Func_var, and ApEn). Moderate correlations were achieved for the VAS score and the kinematic variables Emax, Velmax and variability of curve analysis, Func_varm, and ApEn. No significant correlation was found for CVEmax. In conclusion, CSP results in a decrease of angle and velocity and an increased shoulder movement variability when the neuromuscular system cannot use compensatory strategies to avoid painful positions.

Distribution of Reynolds stress carried by mesoscale variability in the Antarctic Circumpolar Current

NASA Technical Reports Server (NTRS)

Johnson, Thomas J.; Stewart, Robert H.; Shum, C. K.; Tapley, Byron D.

1992-01-01

Satellite altimeter data collected by the Geosat Exact Repeat Mission were used to investigate turbulent stress resulting from the variability of surface geostrophic currents in the Antarctic Circumpolar Current. The altimeter measured sea level along the subsatellite track. The variability of the along-track slope of sea level is directly proportional to the variability of surface geostrophic currents in the cross-track direction. Because the grid of crossover points is dense at high latitudes, the satellite data could be used for mapping the temporal and spatial variability of the current. Two and a half years of data were used to compute the statistical structure of the variability. The statistics included the probability distribution functions for each component of the current, the time-lagged autocorrelation functions of the variability, and the Reynolds stress produced by the variability. The results demonstrate that stress is correlated with bathymetry. In some areas the distribution of negative stress indicate that eddies contribute to an acceleration of the mean flow, strengthening the hypothesis that baroclinic instability makes important contributions to strong oceanic currents.

Multi-scale streamflow variability responses to precipitation over the headwater catchments in southern China

NASA Astrophysics Data System (ADS)

Niu, Jun; Chen, Ji; Wang, Keyi; Sivakumar, Bellie

2017-08-01

This paper examines the multi-scale streamflow variability responses to precipitation over 16 headwater catchments in the Pearl River basin, South China. The long-term daily streamflow data (1952-2000), obtained using a macro-scale hydrological model, the Variable Infiltration Capacity (VIC) model, and a routing scheme, are studied. Temporal features of streamflow variability at 10 different timescales, ranging from 6 days to 8.4 years, are revealed with the Haar wavelet transform. The principal component analysis (PCA) is performed to categorize the headwater catchments with the coherent modes of multi-scale wavelet spectra. The results indicate that three distinct modes, with different variability distributions at small timescales and seasonal scales, can explain 95% of the streamflow variability. A large majority of the catchments (i.e. 12 out of 16) exhibit consistent mode feature on multi-scale variability throughout three sub-periods (1952-1968, 1969-1984, and 1985-2000). The multi-scale streamflow variability responses to precipitation are identified to be associated with the regional flood and drought tendency over the headwater catchments in southern China.

Review and classification of variability analysis techniques with clinical applications

PubMed Central

2011-01-01

Analysis of patterns of variation of time-series, termed variability analysis, represents a rapidly evolving discipline with increasing applications in different fields of science. In medicine and in particular critical care, efforts have focussed on evaluating the clinical utility of variability. However, the growth and complexity of techniques applicable to this field have made interpretation and understanding of variability more challenging. Our objective is to provide an updated review of variability analysis techniques suitable for clinical applications. We review more than 70 variability techniques, providing for each technique a brief description of the underlying theory and assumptions, together with a summary of clinical applications. We propose a revised classification for the domains of variability techniques, which include statistical, geometric, energetic, informational, and invariant. We discuss the process of calculation, often necessitating a mathematical transform of the time-series. Our aims are to summarize a broad literature, promote a shared vocabulary that would improve the exchange of ideas, and the analyses of the results between different studies. We conclude with challenges for the evolving science of variability analysis. PMID:21985357

Conventional heart rate variability analysis of ambulatory electrocardiographic recordings fails to predict imminent ventricular fibrillation

NASA Technical Reports Server (NTRS)

Vybiral, T.; Glaeser, D. H.; Goldberger, A. L.; Rigney, D. R.; Hess, K. R.; Mietus, J.; Skinner, J. E.; Francis, M.; Pratt, C. M.

1993-01-01

OBJECTIVES. The purpose of this report was to study heart rate variability in Holter recordings of patients who experienced ventricular fibrillation during the recording. BACKGROUND. Decreased heart rate variability is recognized as a long-term predictor of overall and arrhythmic death after myocardial infarction. It was therefore postulated that heart rate variability would be lowest when measured immediately before ventricular fibrillation. METHODS. Conventional indexes of heart rate variability were calculated from Holter recordings of 24 patients with structural heart disease who had ventricular fibrillation during monitoring. The control group consisted of 19 patients with coronary artery disease, of comparable age and left ventricular ejection fraction, who had nonsustained ventricular tachycardia but no ventricular fibrillation. RESULTS. Heart rate variability did not differ between the two groups, and no consistent trends in heart rate variability were observed before ventricular fibrillation occurred. CONCLUSIONS. Although conventional heart rate variability is an independent long-term predictor of adverse outcome after myocardial infarction, its clinical utility as a short-term predictor of life-threatening arrhythmias remains to be elucidated.

Manufacturing challenge: An employee perception of the impact of BEM variables on motivation

NASA Astrophysics Data System (ADS)

Nyaude, Alaster

The study examines the impact of Thomas F. Gilbert's Behavior Engineering Model (BEM) variables on employee perception of motivation at an aerospace equipment manufacturing plant in Georgia. The research process involved literature review, and determination of an appropriate survey instrument for the study. The Hersey-Chevalier modified PROBE instrument (Appendix C) was used with Dr Roger Chevalier's validation. The participants' responses were further examined to determine the influence of demographic control variables of age, gender, length of service with the company and education on employee perception of motivation. The results indicated that the top three highly motivating variables were knowledge and skills, capacity and resources. Knowledge and skills was perceived to be highly motivating, capacity as second highly motivating and resources as the third highly motivating variable. Interestingly, the fourth highly motivating variable was information, the fifth was motives and the sixth was incentives. The results also showed that demographic control variables had no influence on employee perception of motivation. Further research may be required to understand to what extend these BEM variables impact employee perceptions of motivation.

Tutorial in Biostatistics: Instrumental Variable Methods for Causal Inference*

PubMed Central

Baiocchi, Michael; Cheng, Jing; Small, Dylan S.

2014-01-01

A goal of many health studies is to determine the causal effect of a treatment or intervention on health outcomes. Often, it is not ethically or practically possible to conduct a perfectly randomized experiment and instead an observational study must be used. A major challenge to the validity of observational studies is the possibility of unmeasured confounding (i.e., unmeasured ways in which the treatment and control groups differ before treatment administration which also affect the outcome). Instrumental variables analysis is a method for controlling for unmeasured confounding. This type of analysis requires the measurement of a valid instrumental variable, which is a variable that (i) is independent of the unmeasured confounding; (ii) affects the treatment; and (iii) affects the outcome only indirectly through its effect on the treatment. This tutorial discusses the types of causal effects that can be estimated by instrumental variables analysis; the assumptions needed for instrumental variables analysis to provide valid estimates of causal effects and sensitivity analysis for those assumptions; methods of estimation of causal effects using instrumental variables; and sources of instrumental variables in health studies. PMID:24599889

Performance Variability as a Predictor of Response to Aphasia Treatment.

PubMed

Duncan, E Susan; Schmah, Tanya; Small, Steven L

2016-10-01

Performance variability in individuals with aphasia is typically regarded as a nuisance factor complicating assessment and treatment. We present the alternative hypothesis that intraindividual variability represents a fundamental characteristic of an individual's functioning and an important biomarker for therapeutic selection and prognosis. A total of 19 individuals with chronic aphasia participated in a 6-week trial of imitation-based speech therapy. We assessed improvement both on overall language functioning and repetition ability. Furthermore, we determined which pretreatment variables best predicted improvement on the repetition test. Significant gains were made on the Western Aphasia Battery-Revised (WAB) Aphasia Quotient, Cortical Quotient, and 2 subtests as well as on a separate repetition test. Using stepwise regression, we found that pretreatment intraindividual variability was the only predictor of improvement in performance on the repetition test, with greater pretreatment variability predicting greater improvement. Furthermore, the degree of reduction in this variability over the course of treatment was positively correlated with the degree of improvement. Intraindividual variability may be indicative of potential for improvement on a given task, with more uniform performance suggesting functioning at or near peak potential. © The Author(s) 2016.

Mechanisms of the 40-70 Day Variability in the Yucatan Channel Volume Transport

NASA Astrophysics Data System (ADS)

van Westen, René M.; Dijkstra, Henk A.; Klees, Roland; Riva, Riccardo E. M.; Slobbe, D. Cornelis; van der Boog, Carine G.; Katsman, Caroline A.; Candy, Adam S.; Pietrzak, Julie D.; Zijlema, Marcel; James, Rebecca K.; Bouma, Tjeerd J.

2018-02-01

The Yucatan Channel connects the Caribbean Sea with the Gulf of Mexico and is the main outflow region of the Caribbean Sea. Moorings in the Yucatan Channel show high-frequent variability in kinetic energy (50-100 days) and transport (20-40 days), but the physical mechanisms controlling this variability are poorly understood. In this study, we show that the short-term variability in the Yucatan Channel transport has an upstream origin and arises from processes in the North Brazil Current. To establish this connection, we use data from altimetry and model output from several high resolution global models. A significant 40-70 day variability is found in the sea surface height in the North Brazil Current retroflection region with a propagation toward the Lesser Antilles. The frequency of variability is generated by intrinsic processes associated with the shedding of eddies, rather than by atmospheric forcing. This sea surface height variability is able to pass the Lesser Antilles, it propagates westward with the background ocean flow in the Caribbean Sea and finally affects the variability in the Yucatan Channel volume transport.

Two Cepheid variables in the Fornax dwarf galaxy

NASA Technical Reports Server (NTRS)

Light, R. M.; Armandroff, T. E.; Zinn, R.

1986-01-01

Two fields surrounding globular clusters 2 and 3 in the Fornax dwarf spheroidal galaxy have been searched for short-period variable stars that are brighter than the horizontal branch. This survey confirmed as variable the two suspected suprahorizontal-branch variables discovered by Buonanno et al. (1985) in their photometry of the clusters. The observations show that the star in cluster 2 is a W Virginis variable of 14.4 day period. It is the first W Vir variable to be found in a dwarf spheroidal galaxy, and its proximity to the center of cluster 2 suggests that it is a cluster member. The other star appears to be an anomalous Cephpeid of 0.78 day period. It lies outside or very near the boundary of cluster 3, and is therefore probably a member of the field population of Fornax. Although no other suprahorizontal-branch variables were discovered in the survey, it did confirm as variable two of the RR Lyrae candidates of Buonanno et al., which appeared at the survey limit. The implications of these observations for the understanding of the stellar content at Fornax are discussed.

Comparing demographic, health status and psychosocial strategies of audience segmentation to promote physical activity.

PubMed

Boslaugh, Sarah E; Kreuter, Matthew W; Nicholson, Robert A; Naleid, Kimberly

2005-08-01

The goal of audience segmentation is to identify population subgroups that are homogeneous with respect to certain variables associated with a given outcome or behavior. When such groups are identified and understood, targeted intervention strategies can be developed to address their unique characteristics and needs. This study compares the results of audience segmentation for physical activity that is based on either demographic, health status or psychosocial variables alone, or a combination of all three types of variables. Participants were 1090 African-American and White adults from two public health centers in St Louis, MO. Using a classification-tree algorithm to form homogeneous groups, analyses showed that more segments with greater variability in physical activity were created using psychosocial versus health status or demographic variables and that a combination of the three outperformed any individual set of variables. Simple segmentation strategies such as those relying on demographic variables alone provided little improvement over no segmentation at all. Audience segmentation appears to yield more homogeneous subgroups when psychosocial and health status factors are combined with demographic variables.

X-ray spectra and time variability of active galactic nuclei

NASA Technical Reports Server (NTRS)

Mushotzky, R. F.

1984-01-01

The X-ray spectra of broad line active galactic nuclei (AGN) of all types (Seyfert I's, NELG's, broadline radio galaxies) are well fit by a power law in the .5 to 100 keV band of man energy slope alpha = .68 + or - .15. There is, as yet, no strong evidence for time variability of this slope in a given object. The constraints that this places on simple models of the central energy source are discussed. BL Lac objects have quite different X-ray spectral properties and show pronounced X-ray spectral variability. On time scales longer than 12 hours most radio quiet AGN do not show strong, delta I/I .5, variability. The probability of variability of these AGN seems to be inversely related to their luminosity. However characteristics timescales for variability have not been measured for many objects. This general lack of variability may imply that most AGN are well below the Eddington limit. Radio bright AGN tend to be more variable than radio quiet AGN on long, tau approx 6 month, timescales.

Variability common to global sea surface temperatures and runoff in the conterminous United States

USGS Publications Warehouse

McCabe, Gregory J.; Wolock, David M.

2014-01-01

Singular value decomposition (SVD) is used to identify the variability common to global sea surface temperatures (SSTs) and water-balance-modeled water-year (WY) runoff in the conterminous United States (CONUS) for the 1900–2012 period. Two modes were identified from the SVD analysis; the two modes explain 25% of the variability in WY runoff and 33% of the variability in WY SSTs. The first SVD mode reflects the variability of the El Niño–Southern Oscillation (ENSO) in the SST data and the hydroclimatic effects of ENSO on WY runoff in the CONUS. The second SVD mode is related to variability of the Atlantic multidecadal oscillation (AMO). An interesting aspect of these results is that both ENSO and AMO appear to have nearly equivalent effects on runoff variability in the CONUS. However, the relatively small amount of variance explained by the SVD analysis indicates that there is little covariation between runoff and SSTs, suggesting that SSTs may not be a viable predictor of runoff variability for most of the conterminous United States.

Increased variability of stimulus-driven cortical responses is associated with genetic variability in children with and without dyslexia.

PubMed

Centanni, T M; Pantazis, D; Truong, D T; Gruen, J R; Gabrieli, J D E; Hogan, T P

2018-05-26

Individuals with dyslexia exhibit increased brainstem variability in response to sound. It is unknown as to whether increased variability extends to neocortical regions associated with audition and reading, extends to visual stimuli, and whether increased variability characterizes all children with dyslexia or, instead, a specific subset of children. We evaluated the consistency of stimulus-evoked neural responses in children with (N = 20) or without dyslexia (N = 12) as measured by magnetoencephalography (MEG). Approximately half of the children with dyslexia had significantly higher levels of variability in cortical responses to both auditory and visual stimuli in multiple nodes of the reading network. There was a significant and positive relationship between the number of risk alleles at rs6935076 in the dyslexia-susceptibility gene KIAA0319 and the degree of neural variability in primary auditory cortex across all participants. This gene has been linked with neural variability in rodents and in typical readers. These findings indicate that unstable representations of auditory and visual stimuli in auditory and other reading-related neocortical regions are present in a subset of children with dyslexia and support the link between the gene KIAA0319 and the auditory neural variability across children with or without dyslexia. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Tropical cloud feedbacks and natural variability of climate

NASA Technical Reports Server (NTRS)

Miller, R. L.; Del Genio, A. D.

1994-01-01

Simulations of natural variability by two general circulation models (GCMs) are examined. One GCM is a sector model, allowing relatively rapid integration without simplification of the model physics, which would potentially exclude mechanisms of variability. Two mechanisms are found in which tropical surface temperature and sea surface temperature (SST) vary on interannual and longer timescales. Both are related to changes in cloud cover that modulate SST through the surface radiative flux. Over the equatorial ocean, SST and surface temperature vary on an interannual timescale, which is determined by the magnitude of the associated cloud cover anomalies. Over the subtropical ocean, variations in low cloud cover drive SST variations. In the sector model, the variability has no preferred timescale, but instead is characterized by a 'red' spectrum with increasing power at longer periods. In the terrestrial GCM, SST variability associated with low cloud anomalies has a decadal timescale and is the dominant form of global temperature variability. Both GCMs are coupled to a mixed layer ocean model, where dynamical heat transports are prescribed, thus filtering out El Nino-Southern Oscillation (ENSO) and thermohaline circulation variability. The occurrence of variability in the absence of dynamical ocean feedbacks suggests that climatic variability on long timescales can arise from atmospheric processes alone.

Interannual to decadal variability of circulation in the northern Japan/East Sea, 1958-2006

NASA Astrophysics Data System (ADS)

Stepanov, Dmitry; Stepanova, Victoriia; Gusev, Anatoly

2015-04-01

We use a numerical ocean model INMOM (Institute of Numerical Mathematics Ocean Model) and atmospheric forcing data extracted from the CORE (Coordinated Ocean Reference Experiments) dataset and reconstruct a circulation in the Japan/East Sea (JES) from 1958 to 2006 and its interannual and decadal variability in the intermediate and abyssal layers in the northern JES. It is founded that the circulation is cyclonic over the course of a climatological year. The circulation increases in spring and decreases in autumn. We analyzes the relative vorticity (RV) averaged over the Japan Basin (JB) and show that the variability is characterized by the interannual oscillations (2.3, 3.7 and 4.7 years) and decadal variability (9.5 and 14.3 years). The spectrum structure of the average RV variability does not change with depth; however, the energy of the decadal oscillations decreases in contrast to that of the interannual oscillations. We analyze monthly anomalies of the wind stress curl and sensible heat flux and reveal that interannual variability (3-4 years) of the circulation over the JB result from 4-year variability of the wind stress curl. In contrast, the decadal variability (period of 9.5 years) of the circulation over the JB is generated by both the wind stress curl and the decadal variability in deep convection.

Climate variability decreases species richness and community stability in a temperate grassland.

PubMed

Zhang, Yunhai; Loreau, Michel; He, Nianpeng; Wang, Junbang; Pan, Qingmin; Bai, Yongfei; Han, Xingguo

2018-06-26

Climate change involves modifications in both the mean and the variability of temperature and precipitation. According to global warming projections, both the magnitude and the frequency of extreme weather events are increasing, thereby increasing climate variability. The previous studies have reported that climate warming tends to decrease biodiversity and the temporal stability of community primary productivity (i.e., community stability), but the effects of the variability of temperature and precipitation on biodiversity, community stability, and their relationship have not been clearly explored. We used a long-term (from 1982 to 2014) field data set from a temperate grassland in northern China to explore the effects of the variability of mean temperature and total precipitation on species richness, community stability, and their relationship. Results showed that species richness promoted community stability through increases in asynchronous dynamics across species (i.e., species asynchrony). Both species richness and species asynchrony were positively associated with the residuals of community stability after controlling for its dependence on the variability of mean temperature and total precipitation. Furthermore, the variability of mean temperature reduced species richness, while the variability of total precipitation decreased species asynchrony and community stability. Overall, the present study revealed that species richness and species asynchrony promoted community stability, but increased climate variability may erode these positive effects and thereby threaten community stability.

Comparisons of estimates of annual exceedance-probability discharges for small drainage basins in Iowa, based on data through water year 2013

USGS Publications Warehouse

Eash, David A.

2015-01-01

An examination was conducted to understand why the 1987 single-variable RREs seem to provide better accuracy and less bias than either of the 2013 multi- or single-variable RREs. A comparison of 1-percent annual exceedance-probability regression lines for hydrologic regions 1-4 from the 1987 single-variable RREs and for flood regions 1-3 from the 2013 single-variable RREs indicates that the 1987 single-variable regional-regression lines generally have steeper slopes and lower discharges when compared to 2013 single-variable regional-regression lines for corresponding areas of Iowa. The combination of the definition of hydrologic regions, the lower discharges, and the steeper slopes of regression lines associated with the 1987 single-variable RREs seem to provide better accuracy and less bias when compared to the 2013 multi- or single-variable RREs; better accuracy and less bias was determined particularly for drainage areas less than 2 mi2, and also for some drainage areas between 2 and 20 mi2. The 2013 multi- and single-variable RREs are considered to provide better accuracy and less bias for larger drainage areas. Results of this study indicate that additional research is needed to address the curvilinear relation between drainage area and AEPDs for areas of Iowa.

How adolescents construct their future: the effect of loneliness on future orientation.

PubMed

Seginer, Rachel; Lilach, Efrat

2004-12-01

This study examined the effect of loneliness, gender, and two dimensions of prospective life domains on adolescent future orientation. Future orientation was studied in four prospective domains: social relations, marriage and family, higher education and work and career. These domains are described in terms of two dimensions: theme (relational vs. instrumental) and distance (near vs. distant future). Data collected from Israeli Jewish adolescents (11th graders) were analysed by repeated measures ANOVAs and ANCOVAs (covariate: depressive experiences) for seven future orientation variables: value, expectance, control (motivational variables), hopes, fears (cognitive representation variables), exploration, commitment (behavioural variables). As predicted, lonely adolescents scored lower than socially embedded adolescents on future orientation variables applied to the relational and near future domains and lonely boys scored lower than lonely girls. However, effects were found only on the three future orientation motivational variables and not on the cognitive representation and behavioural variables. Contrary to prediction controlling for the effect of depressive experiences did not reduce the effect of loneliness on the future orientation variables, but reduced the tendency of adolescents to score higher on all future orientation variables in the instrumental than in the relational prospective domains. The contribution of these findings to the understanding of adolescent loneliness and future orientation was discussed and directions for future research were suggested.

Speech production variability in fricatives of children and adults: Results of functional data analysis

PubMed Central

Koenig, Laura L.; Lucero, Jorge C.; Perlman, Elizabeth

2008-01-01

This study investigates token-to-token variability in fricative production of 5 year olds, 10 year olds, and adults. Previous studies have reported higher intrasubject variability in children than adults, in speech as well as nonspeech tasks, but authors have disagreed on the causes and implications of this finding. The current work assessed the characteristics of age-related variability across articulators (larynx and tongue) as well as in temporal versus spatial domains. Oral airflow signals, which reflect changes in both laryngeal and supralaryngeal apertures, were obtained for multiple productions of ∕h s z∕. The data were processed using functional data analysis, which provides a means of obtaining relatively independent indices of amplitude and temporal (phasing) variability. Consistent with past work, both temporal and amplitude variabilities were higher in children than adults, but the temporal indices were generally less adultlike than the amplitude indices for both groups of children. Quantitative and qualitative analyses showed considerable speaker- and consonant-specific patterns of variability. The data indicate that variability in ∕s∕ may represent laryngeal as well as supralaryngeal control and further that a simple random noise factor, higher in children than in adults, is insufficient to explain developmental differences in speech production variability. PMID:19045800

Evaluating shrub-associated spatial patterns of soil properties in a shrub-steppe ecosystem using multiple-variable geostatistics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Halvorson, J.J.; Smith, J.L.; Bolton, H. Jr.

1995-09-01

Geostatistics are often calculated for a single variable at a time, even though many natural phenomena are functions of several variables. The objective of this work was to demonstrate a nonparametric approach for assessing the spatial characteristics of multiple-variable phenomena. Specifically, we analyzed the spatial characteristics of resource islands in the soil under big sagebrush (Artemisia tridentala Nutt.), a dominant shrub in the intermountain western USA. For our example, we defined resource islands as a function of six soil variables representing concentrations of soil resources, populations of microorganisms, and soil microbial physiological variables. By collectively evaluating the indicator transformations ofmore » these individual variables, we created a new data set, termed a multiple-variable indicator transform or MVIT. Alternate MVITs were obtained by varying the selection criteria. Each MVIT was analyzed with variography to characterize spatial continuity, and with indicator kriging to predict the combined probability of their occurrence at unsampled locations in the landscape. Simple graphical analysis and variography demonstrated spatial dependence for all individual soil variables. Maps derived from ordinary kriging of MVITs suggested that the combined probabilities for encountering zones of above-median resources were greatest near big sagebrush. 51 refs., 5 figs., 1 tab.« less

Baseline-dependent effect of noise-enhanced insoles on gait variability in healthy elderly walkers.

PubMed

Stephen, Damian G; Wilcox, Bethany J; Niemi, James B; Franz, Jason R; Franz, Jason; Kerrigan, Dr; Kerrigan, D Casey; D'Andrea, Susan E

2012-07-01

The purpose of this study was to determine whether providing subsensory stochastic-resonance mechanical vibration to the foot soles of elderly walkers could decrease gait variability. In a randomized double-blind controlled trial, 29 subjects engaged in treadmill walking while wearing sandals customized with three actuators capable of producing stochastic-resonance mechanical vibration embedded in each sole. For each subject, we determined a subsensory level of vibration stimulation. After a 5-min acclimation period of walking with the footwear, subjects were asked to walk on the treadmill for six trials, each 30s long. Trials were pair-wise random: in three trials, actuators provided subsensory vibration; in the other trials, they did not. Subjects wore reflective markers to track body motion. Stochastic-resonance mechanical stimulation exhibited baseline-dependent effects on spatial stride-to-stride variability in gait, slightly increasing variability in subjects with least baseline variability and providing greater reductions in variability for subjects with greater baseline variability (p<.001). Thus, applying stochastic-resonance mechanical vibrations on the plantar surface of the foot reduces gait variability for subjects with more variable gait. Stochastic-resonance mechanical vibrations may provide an effective intervention for preventing falls in healthy elderly walkers. Published by Elsevier B.V.

Effects of Parkinson's Disease on Fundamental Frequency Variability in Running Speech.

PubMed

Bowen, Leah K; Hands, Gabrielle L; Pradhan, Sujata; Stepp, Cara E

2013-09-01

In Parkinson's Disease (PD), qualitative speech changes such as decreased variation in pitch and loudness are common, but quantitative vocal changes are not well documented. The variability of fundamental frequency (F0) in 32 individuals (23 male) with PD both ON and OFF levodopa medication was compared with 32 age-matched healthy controls (23 male). Participants read a single paragraph and estimates of fundamental frequency (F0) variability were determined for the entire reading passage as well as for the first and last sentences of the passage separately. F0 variability was significantly increased in controls relative to both PD groups and PD patients showed significantly higher F0 variability while ON medication relative to OFF. No significant effect of group was seen in the change in F0 variability from the beginning to the end of the reading passage. Female speakers were found to have higher F0 variability than males. F0 variability was both significantly reduced in PD relative to controls and significantly increased in patients with PD during use of dopaminergic medications. F0 variability changes over the course of reading a paragraph may not be indicative of PD but rather dependent on non-disease factors such as the linguistic characteristics of the text.

Quantifying Grain-Size Variability of Metal Pollutants in Road-Deposited Sediments Using the Coefficient of Variation

PubMed Central

Wang, Xiaoxue; Li, Xuyong

2017-01-01

Particle grain size is an important indicator for the variability in physical characteristics and pollutants composition of road-deposited sediments (RDS). Quantitative assessment of the grain-size variability in RDS amount, metal concentration, metal load and GSFLoad is essential to elimination of the uncertainty it causes in estimation of RDS emission load and formulation of control strategies. In this study, grain-size variability was explored and quantified using the coefficient of variation (Cv) of the particle size compositions, metal concentrations, metal loads, and GSFLoad values in RDS. Several trends in grain-size variability of RDS were identified: (i) the medium class (105–450 µm) variability in terms of particle size composition, metal loads, and GSFLoad values in RDS was smaller than the fine (<105 µm) and coarse (450–2000 µm) class; (ii) The grain-size variability in terms of metal concentrations increased as the particle size increased, while the metal concentrations decreased; (iii) When compared to the Lorenz coefficient (Lc), the Cv was similarly effective at describing the grain-size variability, whereas it is simpler to calculate because it did not require the data to be pre-processed. The results of this study will facilitate identification of the uncertainty in modelling RDS caused by grain-size class variability. PMID:28788078

A model for AGN variability on multiple time-scales

NASA Astrophysics Data System (ADS)

Sartori, Lia F.; Schawinski, Kevin; Trakhtenbrot, Benny; Caplar, Neven; Treister, Ezequiel; Koss, Michael J.; Urry, C. Megan; Zhang, C. E.

2018-05-01

We present a framework to link and describe active galactic nuclei (AGN) variability on a wide range of time-scales, from days to billions of years. In particular, we concentrate on the AGN variability features related to changes in black hole fuelling and accretion rate. In our framework, the variability features observed in different AGN at different time-scales may be explained as realisations of the same underlying statistical properties. In this context, we propose a model to simulate the evolution of AGN light curves with time based on the probability density function (PDF) and power spectral density (PSD) of the Eddington ratio (L/LEdd) distribution. Motivated by general galaxy population properties, we propose that the PDF may be inspired by the L/LEdd distribution function (ERDF), and that a single (or limited number of) ERDF+PSD set may explain all observed variability features. After outlining the framework and the model, we compile a set of variability measurements in terms of structure function (SF) and magnitude difference. We then combine the variability measurements on a SF plot ranging from days to Gyr. The proposed framework enables constraints on the underlying PSD and the ability to link AGN variability on different time-scales, therefore providing new insights into AGN variability and black hole growth phenomena.

The role of personal self-regulation and regulatory teaching to predict motivational-affective variables, achievement, and satisfaction: a structural model

PubMed Central

De la Fuente, Jesus; Zapata, Lucía; Martínez-Vicente, Jose M.; Sander, Paul; Cardelle-Elawar, María

2014-01-01

The present investigation examines how personal self-regulation (presage variable) and regulatory teaching (process variable of teaching) relate to learning approaches, strategies for coping with stress, and self-regulated learning (process variables of learning) and, finally, how they relate to performance and satisfaction with the learning process (product variables). The objective was to clarify the associative and predictive relations between these variables, as contextualized in two different models that use the presage-process-product paradigm (the Biggs and DEDEPRO models). A total of 1101 university students participated in the study. The design was cross-sectional and retrospective with attributional (or selection) variables, using correlations and structural analysis. The results provide consistent and significant empirical evidence for the relationships hypothesized, incorporating variables that are part of and influence the teaching–learning process in Higher Education. Findings confirm the importance of interactive relationships within the teaching–learning process, where personal self-regulation is assumed to take place in connection with regulatory teaching. Variables that are involved in the relationships validated here reinforce the idea that both personal factors and teaching and learning factors should be taken into consideration when dealing with a formal teaching–learning context at university. PMID:25964764

[Meta analysis of variables related to attention deficit hyperactivity disorder in school-age children].

PubMed

Park, Wan Ju; Seo, Ji Yeong; Kim, Mi Ye

2011-04-01

The purpose of this study was to use meta-analysis to examine recent domestic articles related to attention deficit hyperactivity disorder (ADHD) in school-age children. After reviewing 213 articles published between 1990 and 2009 from and cited in RISS, KISS, and DBpia, the researchers identified 24 studies with 440 research variables that had appropriate data for methodological study. SPSS 17.0 program was used. The outcome variables were divided into five types: Inattention, hyperactive impulsive, intrinsic, extrinsic, and academic ability variables. Effects size of overall core symptoms was 0.47 which is moderate level in terms of Cohen criteria and effects size of overall negative variables related ADHD was 0.27 which is small level. The most dominant variable related to ADHD was obtained from hyperactive-impulsive (0.70). Also academic ability (0.45), inattention (0.37), and intrinsic variables (0.29) had a small effect whereas extrinsic variables (0.13) had little effect on descriptive ADHD study. The results reveal that ADHD core symptoms have moderate effect size and peripheral negative variables related ADHD have small effect size. To improve the reliability of the meta-analysis results by minimizing publication bias, more intervention studies using appropriate study designs should be done.

Movement variability and skill level of various throwing techniques.

PubMed

Wagner, Herbert; Pfusterschmied, Jürgen; Klous, Miriam; von Duvillard, Serge P; Müller, Erich

2012-02-01

In team-handball, skilled athletes are able to adapt to different game situations that may lead to differences in movement variability. Whether movement variability affects the performance of a team-handball throw and is affected by different skill levels or throwing techniques has not yet been demonstrated. Consequently, the aims of the study were to determine differences in performance and movement variability for several throwing techniques in different phases of the throwing movement, and of different skill levels. Twenty-four team-handball players of different skill levels (n=8) performed 30 throws using various throwing techniques. Upper body kinematics was measured via an 8 camera Vicon motion capture system and movement variability was calculated. Results indicated an increase in movement variability in the distal joint movements during the acceleration phase. In addition, there was a decrease in movement variability in highly skilled and skilled players in the standing throw with run-up, which indicated an increase in the ball release speed, which was highest when using this throwing technique. We assert that team-handball players had the ability to compensate an increase in movement variability in the acceleration phase to throw accurately, and skilled players were able to control the movement, although movement variability decreased in the standing throw with run-up. Copyright © 2011 Elsevier B.V. All rights reserved.

YSOVAR: MID-INFRARED VARIABILITY OF YOUNG STELLAR OBJECTS AND THEIR DISKS IN THE CLUSTER IRAS 20050+2720

DOE Office of Scientific and Technical Information (OSTI.GOV)

Poppenhaeger, K.; Wolk, S. J.; Hora, J. L.

2015-10-15

We present a time-variability study of young stellar objects (YSOs) in the cluster IRAS 20050+2720, performed at 3.6 and 4.5 μm with the Spitzer Space Telescope; this study is part of the Young Stellar Object VARiability (YSOVAR) project. We have collected light curves for 181 cluster members over 60 days. We find a high variability fraction among embedded cluster members of ca. 70%, whereas young stars without a detectable disk display variability less often (in ca. 50% of the cases) and with lower amplitudes. We detect periodic variability for 33 sources with periods primarily in the range of 2–6 days.more » Practically all embedded periodic sources display additional variability on top of their periodicity. Furthermore, we analyze the slopes of the tracks that our sources span in the color–magnitude diagram (CMD). We find that sources with long variability time scales tend to display CMD slopes that are at least partially influenced by accretion processes, while sources with short variability timescales tend to display extinction-dominated slopes. We find a tentative trend of X-ray detected cluster members to vary on longer timescales than the X-ray undetected members.« less

Enhanced blood pressure variability in a high cardiovascular risk group of African Americans: FIT4Life Study.

PubMed

Veerabhadrappa, Praveen; Diaz, Keith M; Feairheller, Deborah L; Sturgeon, Kathleen M; Williamson, Sheara; Crabbe, Deborah L; Kashem, Abul; Ahrensfield, Debra; Brown, Michael D

2010-01-01

High blood pressure (BP) levels in African Americans elicit vascular inflammation resulting in vascular remodeling. BP variability (BPV) correlates with target organ damage. We aimed to investigate the relationship between inflammatory markers and BPV in African Americans. Thirty-six African Americans underwent 24-hour ambulatory BP monitoring (ABPM). BPV was calculated using the average real variability index. Fasting blood samples were assayed for high-sensitivity C-reactive protein (hs-CRP), tumor necrosis factor-alpha (TNF-alpha), and white blood cell (WBC) count. Significant associations between hs-CRP and 24-hour systolic variability (r=0.50; P=.012) and awake systolic variability (r=0.45; P=.02) were identified after adjusting for age, body mass index, and 24-hour mean BP. ABPM variables were compared between the hs-CRP tertile groups. In post-hoc analysis, there was a significant difference in 24-hour and awake periods for both systolic and diastolic variability among the groups. TNF-alpha and WBC count showed no associations with ABPM variables. hs-CRP was associated with systolic variability, and higher levels of hs-CRP were related with greater BPV. Higher inflammatory status influences wider fluctuations in systolic BP, which in turn could facilitate early progression to target organ damage independent of absolute BP levels in African Americans.

Propagation of variability in railway dynamic simulations: application to virtual homologation

NASA Astrophysics Data System (ADS)

Funfschilling, Christine; Perrin, Guillaume; Kraft, Sönke

2012-01-01

Railway dynamic simulations are increasingly used to predict and analyse the behaviour of the vehicle and of the track during their whole life cycle. Up to now however, no simulation has been used in the certification procedure even if the expected benefits are important: cheaper and shorter procedures, more objectivity, better knowledge of the behaviour around critical situations. Deterministic simulations are nevertheless too poor to represent the whole physical of the track/vehicle system which contains several sources of variability: variability of the mechanical parameters of a train among a class of vehicles (mass, stiffness and damping of different suspensions), variability of the contact parameters (friction coefficient, wheel and rail profiles) and variability of the track design and quality. This variability plays an important role on the safety, on the ride quality, and thus on the certification criteria. When using the simulation for certification purposes, it seems therefore crucial to take into account the variability of the different inputs. The main goal of this article is thus to propose a method to introduce the variability in railway dynamics. A four-step method is described namely the definition of the stochastic problem, the modelling of the inputs variability, the propagation and the analysis of the output. Each step is illustrated with railway examples.

Suppression of chaos at slow variables by rapidly mixing fast dynamics through linear energy-preserving coupling

NASA Astrophysics Data System (ADS)

Abramov, R. V.

2011-12-01

Chaotic multiscale dynamical systems are common in many areas of science, one of the examples being the interaction of the low-frequency dynamics in the atmosphere with the fast turbulent weather dynamics. One of the key questions about chaotic multiscale systems is how the fast dynamics affects chaos at the slow variables, and, therefore, impacts uncertainty and predictability of the slow dynamics. Here we demonstrate that the linear slow-fast coupling with the total energy conservation property promotes the suppression of chaos at the slow variables through the rapid mixing at the fast variables, both theoretically and through numerical simulations. A suitable mathematical framework is developed, connecting the slow dynamics on the tangent subspaces to the infinite-time linear response of the mean state to a constant external forcing at the fast variables. Additionally, it is shown that the uncoupled dynamics for the slow variables may remain chaotic while the complete multiscale system loses chaos and becomes completely predictable at the slow variables through increasing chaos and turbulence at the fast variables. This result contradicts the common sense intuition, where, naturally, one would think that coupling a slow weakly chaotic system with another much faster and much stronger chaotic system would result in general increase of chaos at the slow variables.

Predicting word-recognition performance in noise by young listeners with normal hearing using acoustic, phonetic, and lexical variables.

PubMed

McArdle, Rachel; Wilson, Richard H

2008-06-01

To analyze the 50% correct recognition data that were from the Wilson et al (this issue) study and that were obtained from 24 listeners with normal hearing; also to examine whether acoustic, phonetic, or lexical variables can predict recognition performance for monosyllabic words presented in speech-spectrum noise. The specific variables are as follows: (a) acoustic variables (i.e., effective root-mean-square sound pressure level, duration), (b) phonetic variables (i.e., consonant features such as manner, place, and voicing for initial and final phonemes; vowel phonemes), and (c) lexical variables (i.e., word frequency, word familiarity, neighborhood density, neighborhood frequency). The descriptive, correlational study will examine the influence of acoustic, phonetic, and lexical variables on speech recognition in noise performance. Regression analysis demonstrated that 45% of the variance in the 50% point was accounted for by acoustic and phonetic variables whereas only 3% of the variance was accounted for by lexical variables. These findings suggest that monosyllabic word-recognition-in-noise is more dependent on bottom-up processing than on top-down processing. The results suggest that when speech-in-noise testing is used in a pre- and post-hearing-aid-fitting format, the use of monosyllabic words may be sensitive to changes in audibility resulting from amplification.

Effects of a cognitive dual task on variability and local dynamic stability in sustained repetitive arm movements using principal component analysis: a pilot study.

PubMed

Longo, Alessia; Federolf, Peter; Haid, Thomas; Meulenbroek, Ruud

2018-06-01

In many daily jobs, repetitive arm movements are performed for extended periods of time under continuous cognitive demands. Even highly monotonous tasks exhibit an inherent motor variability and subtle fluctuations in movement stability. Variability and stability are different aspects of system dynamics, whose magnitude may be further affected by a cognitive load. Thus, the aim of the study was to explore and compare the effects of a cognitive dual task on the variability and local dynamic stability in a repetitive bimanual task. Thirteen healthy volunteers performed the repetitive motor task with and without a concurrent cognitive task of counting aloud backwards in multiples of three. Upper-body 3D kinematics were collected and postural reconfigurations-the variability related to the volunteer's postural change-were determined through a principal component analysis-based procedure. Subsequently, the most salient component was selected for the analysis of (1) cycle-to-cycle spatial and temporal variability, and (2) local dynamic stability as reflected by the largest Lyapunov exponent. Finally, end-point variability was evaluated as a control measure. The dual cognitive task proved to increase the temporal variability and reduce the local dynamic stability, marginally decrease endpoint variability, and substantially lower the incidence of postural reconfigurations. Particularly, the latter effect is considered to be relevant for the prevention of work-related musculoskeletal disorders since reduced variability in sustained repetitive tasks might increase the risk of overuse injuries.

A New Catalog of Variable Stars in the Field of the Open Cluster M37

NASA Astrophysics Data System (ADS)

Chang, S.-W.; Byun, Y.-I.; Hartman, J. D.

2015-07-01

We present a comprehensive re-analysis of stellar photometric variability in the field of the open cluster M37 following the application of a new photometry and de-trending method to the MMT/Megacam image archive. This new analysis allows a rare opportunity to explore photometric variability over a broad range of timescales, from minutes to a month. The intent of this work is to examine the entire sample of more than 30,000 objects for periodic, aperiodic, and sporadic behaviors in their light curves. We show a modified version of the fast χ2 periodogram algorithm (Fχ2) and change-point analysis as tools for detecting and assessing the significance of periodic and non-periodic variations. The benefits of our new photometry and analysis methods are evident. A total of 2,306 stars exhibit convincing variations that are induced by flares, pulsations, eclipses, starspots, and unknown causes in some cases. This represents a 60% increase in the number of variables known in this field. Moreover, 30 of the previously identified variables are found to be false positives resulting from time-dependent systematic effects. The new catalog includes 61 eclipsing binary systems, 92 multiperiodic variable stars, 132 aperiodic variables, and 436 flare stars, as well as several hundreds of rotating variables. Based on extended and improved catalog of variables, we investigate the basic properties (e.g., period, amplitude, type) of all variables. The catalog can be accessed through the web interface (http://stardb.yonsei.ac.kr/).

Dependence of Halo Bias and Kinematics on Assembly Variables

NASA Astrophysics Data System (ADS)

Xu, Xiaoju; Zheng, Zheng

2018-06-01

Using dark matter haloes identified in a large N-body simulation, we study halo assembly bias, with halo formation time, peak maximum circular velocity, concentration, and spin as the assembly variables. Instead of grouping haloes at fixed mass into different percentiles of each assembly variable, we present the joint dependence of halo bias on the values of halo mass and each assembly variable. In the plane of halo mass and one assembly variable, the joint dependence can be largely described as halo bias increasing outward from a global minimum. We find it unlikely to have a combination of halo variables to absorb all assembly bias effects. We then present the joint dependence of halo bias on two assembly variables at fixed halo mass. The gradient of halo bias does not necessarily follow the correlation direction of the two assembly variables and it varies with halo mass. Therefore in general for two correlated assembly variables one cannot be used as a proxy for the other in predicting halo assembly bias trend. Finally, halo assembly is found to affect the kinematics of haloes. Low-mass haloes formed earlier can have much higher pairwise velocity dispersion than those of massive haloes. In general, halo assembly leads to a correlation between halo bias and halo pairwise velocity distribution, with more strongly clustered haloes having higher pairwise velocity and velocity dispersion. However, the correlation is not tight, and the kinematics of haloes at fixed halo bias still depends on halo mass and assembly variables.

When is affect variability bad for health? The association between affect variability and immune response to the influenza vaccination.

PubMed

Jenkins, Brooke N; Hunter, John F; Cross, Marie P; Acevedo, Amanda M; Pressman, Sarah D

2018-01-01

This study addresses methodological and theoretical questions about the association between affect and physical health. Specifically, we examine the role of affect variability and its interaction with mean levels of affect to predict antibody (Ab) levels in response to an influenza vaccination. Participants (N=83) received the vaccination and completed daily diary measures of affect four times a day for 13days. At one and four months post-vaccination, blood was collected from the participants to assess Ab levels. Findings indicate that affect variability and its interaction with mean levels of affect predict an individual's immune response. Those high in mean positive affect (PA) who had more PA variability were more likely to have a lower Ab response in comparison to those who had high mean PA and less PA variability. Although it did not interact with mean negative affect (NA), NA variability on its own was associated with Ab response, whereby those with less NA variability mounted a more robust immune response. Affect variability is related to immune response to an influenza vaccination and, in some cases, interacts with mean levels of affect. These oscillations in affective experiences are critical to consider in order to unpack the intricacies of how affect influences health. These findings suggest that future researchers should consider the important role of affect variability on physical health-relevant outcomes as well as examine the moderating effect of mean affect levels. Copyright © 2017 Elsevier Inc. All rights reserved.

Modeling climate effects on hip fracture rate by the multivariate GARCH model in Montreal region, Canada.

PubMed

Modarres, Reza; Ouarda, Taha B M J; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre

2014-07-01

Changes in extreme meteorological variables and the demographic shift towards an older population have made it important to investigate the association of climate variables and hip fracture by advanced methods in order to determine the climate variables that most affect hip fracture incidence. The nonlinear autoregressive moving average with exogenous variable-generalized autoregressive conditional heteroscedasticity (ARMAX-GARCH) and multivariate GARCH (MGARCH) time series approaches were applied to investigate the nonlinear association between hip fracture rate in female and male patients aged 40-74 and 75+ years and climate variables in the period of 1993-2004, in Montreal, Canada. The models describe 50-56% of daily variation in hip fracture rate and identify snow depth, air temperature, day length and air pressure as the influencing variables on the time-varying mean and variance of the hip fracture rate. The conditional covariance between climate variables and hip fracture rate is increasing exponentially, showing that the effect of climate variables on hip fracture rate is most acute when rates are high and climate conditions are at their worst. In Montreal, climate variables, particularly snow depth and air temperature, appear to be important predictors of hip fracture incidence. The association of climate variables and hip fracture does not seem to change linearly with time, but increases exponentially under harsh climate conditions. The results of this study can be used to provide an adaptive climate-related public health program and ti guide allocation of services for avoiding hip fracture risk.

Modeling climate effects on hip fracture rate by the multivariate GARCH model in Montreal region, Canada

NASA Astrophysics Data System (ADS)

Modarres, Reza; Ouarda, Taha B. M. J.; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre

2014-07-01

Changes in extreme meteorological variables and the demographic shift towards an older population have made it important to investigate the association of climate variables and hip fracture by advanced methods in order to determine the climate variables that most affect hip fracture incidence. The nonlinear autoregressive moving average with exogenous variable-generalized autoregressive conditional heteroscedasticity (ARMA X-GARCH) and multivariate GARCH (MGARCH) time series approaches were applied to investigate the nonlinear association between hip fracture rate in female and male patients aged 40-74 and 75+ years and climate variables in the period of 1993-2004, in Montreal, Canada. The models describe 50-56 % of daily variation in hip fracture rate and identify snow depth, air temperature, day length and air pressure as the influencing variables on the time-varying mean and variance of the hip fracture rate. The conditional covariance between climate variables and hip fracture rate is increasing exponentially, showing that the effect of climate variables on hip fracture rate is most acute when rates are high and climate conditions are at their worst. In Montreal, climate variables, particularly snow depth and air temperature, appear to be important predictors of hip fracture incidence. The association of climate variables and hip fracture does not seem to change linearly with time, but increases exponentially under harsh climate conditions. The results of this study can be used to provide an adaptive climate-related public health program and ti guide allocation of services for avoiding hip fracture risk.

Optical Variability of Narrow-line and Broad-line Seyfert 1 Galaxies

NASA Astrophysics Data System (ADS)

Rakshit, Suvendu; Stalin, C. S.

2017-06-01

We studied the optical variability (OV) of a large sample of narrow-line Seyfert 1 (NLSy1) and broad-line Seyfert 1 (BLSy1) galaxies with z < 0.8 to investigate any differences in their OV properties. Using archival optical V-band light curves from the Catalina Real Time Transient Survey that span 5-9 years and modeling them using damped random walk, we estimated the amplitude of variability. We found that NLSy1 galaxies as a class show lower amplitude of variability than their broad-line counterparts. In the sample of both NLSy1 and BLSy1 galaxies, radio-loud sources are found to have higher variability amplitude than radio-quiet sources. Considering only sources that are detected in the X-ray band, NLSy1 galaxies are less optically variable than BLSy1 galaxies. The amplitude of variability in the sample of both NLSy1 and BLSy1 galaxies is found to be anti-correlated with Fe II strength but correlated with the width of the Hβ line. The well-known anti-correlation of variability-luminosity and the variability-Eddington ratio is present in our data. Among the radio-loud sample, variability amplitude is found to be correlated with radio-loudness and radio-power, suggesting that jets also play an important role in the OV in radio-loud objects, in addition to the Eddington ratio, which is the main driving factor of OV in radio-quiet sources.

Motion makes sense: an adaptive motor-sensory strategy underlies the perception of object location in rats.

PubMed

Saraf-Sinik, Inbar; Assa, Eldad; Ahissar, Ehud

2015-06-10

Tactile perception is obtained by coordinated motor-sensory processes. We studied the processes underlying the perception of object location in freely moving rats. We trained rats to identify the relative location of two vertical poles placed in front of them and measured at high resolution the motor and sensory variables (19 and 2 variables, respectively) associated with this whiskers-based perceptual process. We found that the rats developed stereotypic head and whisker movements to solve this task, in a manner that can be described by several distinct behavioral phases. During two of these phases, the rats' whiskers coded object position by first temporal and then angular coding schemes. We then introduced wind (in two opposite directions) and remeasured their perceptual performance and motor-sensory variables. Our rats continued to perceive object location in a consistent manner under wind perturbations while maintaining all behavioral phases and relatively constant sensory coding. Constant sensory coding was achieved by keeping one group of motor variables (the "controlled variables") constant, despite the perturbing wind, at the cost of strongly modulating another group of motor variables (the "modulated variables"). The controlled variables included coding-relevant variables, such as head azimuth and whisker velocity. These results indicate that consistent perception of location in the rat is obtained actively, via a selective control of perception-relevant motor variables. Copyright © 2015 the authors 0270-6474/15/358777-13$15.00/0.

The role of family planning communications--an agent of reinforcement or change.

PubMed

Chen, E C

1981-12-01

Results are presented of a multiple classification analysis of responses to a 1972 KAP survey in Taiwan of 2013 married women aged 18-34 designed to determine whether family planning communication is primarily a reinforcement agent or a change agent. 2 types of independent variables, social demographic variables including age, number of children, residence, education, employment status, and duration of marriage; and social climate variables including ever receiving family planning information from mass media and ever discussing family planning with others, were used. KAP levels, the dependent variables, were measured by 2 variables each: awareness of effective methods and awareness of government supply of contraceptives for knowledge, wish for additional children and approve of 2-child family for attitude, and never use contraception and neither want children nor use contraception for practice. Social demographic and attitudinal variables were found to be the critical ones, while social climate and knowledge variables had only negligible effects on various stages of family planning adoption, indicating that family planning communications functioned primarily as a reinforcement agent. The effects of social demographic variables were prominent in all stages of contraceptive adoption. Examination of effects of individual variables on various stages of family planning adoption still supported the argument that family planning communications played a reinforcement role. Family planning communications functioned well in diffusing family planning knowledge and accessibility, but social demographic variables and desire for additional children were the most decisive influences on use of contraception.

The gait standard deviation, a single measure of kinematic variability.

PubMed

Sangeux, Morgan; Passmore, Elyse; Graham, H Kerr; Tirosh, Oren

2016-05-01

Measurement of gait kinematic variability provides relevant clinical information in certain conditions affecting the neuromotor control of movement. In this article, we present a measure of overall gait kinematic variability, GaitSD, based on combination of waveforms' standard deviation. The waveform standard deviation is the common numerator in established indices of variability such as Kadaba's coefficient of multiple correlation or Winter's waveform coefficient of variation. Gait data were collected on typically developing children aged 6-17 years. Large number of strides was captured for each child, average 45 (SD: 11) for kinematics and 19 (SD: 5) for kinetics. We used a bootstrap procedure to determine the precision of GaitSD as a function of the number of strides processed. We compared the within-subject, stride-to-stride, variability with the, between-subject, variability of the normative pattern. Finally, we investigated the correlation between age and gait kinematic, kinetic and spatio-temporal variability. In typically developing children, the relative precision of GaitSD was 10% as soon as 6 strides were captured. As a comparison, spatio-temporal parameters required 30 strides to reach the same relative precision. The ratio stride-to-stride divided by normative pattern variability was smaller in kinematic variables (the smallest for pelvic tilt, 28%) than in kinetic and spatio-temporal variables (the largest for normalised stride length, 95%). GaitSD had a strong, negative correlation with age. We show that gait consistency may stabilise only at, or after, skeletal maturity. Copyright © 2016 Elsevier B.V. All rights reserved.

The variability of the rainfall rate as a function of area

NASA Astrophysics Data System (ADS)

Jameson, A. R.; Larsen, M. L.

2016-01-01

Distributions of drop sizes can be expressed as DSD = Nt × PSD, where Nt is the total number of drops in a sample and PSD is the frequency distribution of drop diameters (D). Their discovery permitted remote sensing techniques for rainfall estimation using radars and satellites measuring over large domains of several kilometers. Because these techniques depend heavily on higher moments of the PSD, there has been a bias toward attributing the variability of the intrinsic rainfall rates R over areas (σR) to the variability of the PSDs. While this variability does increase up to a point with increasing domain dimension L, the variability of the rainfall rate R also depends upon the variability in the total number of drops Nt. We show that while the importance of PSDs looms large for small domains used in past studies, it is the variability of Nt that dominates the variability of R as L increases to 1 km and beyond. The PSDs contribute to the variability of R through the relative dispersion of χ = D3Vt, where Vt is the terminal fall speed of drops of diameter D. However, the variability of χ is inherently limited because drop sizes and fall speeds are physically limited. In contrast, it is shown that the variance of Nt continuously increases as the domain expands for physical reasons explained below. Over domains larger than around 1 km, it is shown that Nt dominates the variance of the rainfall rate with increasing L regardless of the PSD.

Working memory and intraindividual variability as neurocognitive indicators in ADHD: examining competing model predictions.

PubMed

Kofler, Michael J; Alderson, R Matt; Raiker, Joseph S; Bolden, Jennifer; Sarver, Dustin E; Rapport, Mark D

2014-05-01

The current study examined competing predictions of the default mode, cognitive neuroenergetic, and functional working memory models of attention-deficit/hyperactivity disorder (ADHD) regarding the relation between neurocognitive impairments in working memory and intraindividual variability. Twenty-two children with ADHD and 15 typically developing children were assessed on multiple tasks measuring intraindividual reaction time (RT) variability (ex-Gaussian: tau, sigma) and central executive (CE) working memory. Latent factor scores based on multiple, counterbalanced tasks were created for each construct of interest (CE, tau, sigma) to reflect reliable variance associated with each construct and remove task-specific, test-retest, and random error. Bias-corrected, bootstrapped mediation analyses revealed that CE working memory accounted for 88% to 100% of ADHD-related RT variability across models, and between-group differences in RT variability were no longer detectable after accounting for the mediating role of CE working memory. In contrast, RT variability accounted for 10% to 29% of between-group differences in CE working memory, and large magnitude CE working memory deficits remained after accounting for this partial mediation. Statistical comparison of effect size estimates across models suggests directionality of effects, such that the mediation effects of CE working memory on RT variability were significantly greater than the mediation effects of RT variability on CE working memory. The current findings question the role of RT variability as a primary neurocognitive indicator in ADHD and suggest that ADHD-related RT variability may be secondary to underlying deficits in CE working memory.

Emotional variability in mother-adolescent conflict interactions and internalizing problems of mothers and adolescents: dyadic and individual processes.

PubMed

Van der Giessen, Daniëlle; Hollenstein, Tom; Hale, William W; Koot, Hans M; Meeus, Wim; Branje, Susan

2015-02-01

Emotional variability reflects the ability to flexibly switch among a broad range of positive and negative emotions from moment-to-moment during interactions. Emotional variability during mother-adolescent conflict interactions is considered to be important for healthy socio-emotional functioning of mothers and adolescents. The current observational study examined whether dyadic emotional variability, maternal emotional variability, and adolescent emotional variability during conflict interactions in early adolescence predicted mothers' and adolescents' internalizing problems five years later. We used data from 92 mother-adolescent dyads (Mage T1 = 13.05; 65.20 % boys) who were videotaped at T1 while discussing a conflict. Emotional variability was derived from these conflict interactions and it was observed for mother-adolescent dyads, mothers and adolescents separately. Mothers and adolescents also completed questionnaires in early adolescence (T1) and five years later in late adolescence (T6) on mothers' internalizing problems, and adolescents' anxiety and depressive symptoms. Hierarchical regression analyses showed that less dyadic emotional variability in early adolescence predicted relative increases in mothers' internalizing problems, adolescents' depressive symptoms, and adolescents' anxiety symptoms from early to late adolescence. Less maternal emotional variability only predicted relative increases in adolescents' anxiety symptoms over time. The emotional valence (e.g., types of emotions expressed) of conflict interactions did not moderate the results. Taken together, findings highlighted the importance of considering limited emotional variability during conflict interactions in the development, prevention, and treatment of internalizing problems of mothers and adolescents.

Robust best linear estimator for Cox regression with instrumental variables in whole cohort and surrogates with additive measurement error in calibration sample.

PubMed

Wang, Ching-Yun; Song, Xiao

2016-11-01

Biomedical researchers are often interested in estimating the effect of an environmental exposure in relation to a chronic disease endpoint. However, the exposure variable of interest may be measured with errors. In a subset of the whole cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies an additive measurement error model, but it may not have repeated measurements. The subset in which the surrogate variables are available is called a calibration sample. In addition to the surrogate variables that are available among the subjects in the calibration sample, we consider the situation when there is an instrumental variable available for all study subjects. An instrumental variable is correlated with the unobserved true exposure variable, and hence can be useful in the estimation of the regression coefficients. In this paper, we propose a nonparametric method for Cox regression using the observed data from the whole cohort. The nonparametric estimator is the best linear combination of a nonparametric correction estimator from the calibration sample and the difference of the naive estimators from the calibration sample and the whole cohort. The asymptotic distribution is derived, and the finite sample performance of the proposed estimator is examined via intensive simulation studies. The methods are applied to the Nutritional Biomarkers Study of the Women's Health Initiative. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Combining information from 3 anatomic regions in the diagnosis of glaucoma with time-domain optical coherence tomography.

PubMed

Wang, Mingwu; Lu, Ake Tzu-Hui; Varma, Rohit; Schuman, Joel S; Greenfield, David S; Huang, David

2014-03-01

To improve the diagnosis of glaucoma by combining time-domain optical coherence tomography (TD-OCT) measurements of the optic disc, circumpapillary retinal nerve fiber layer (RNFL), and macular retinal thickness. Ninety-six age-matched normal and 96 perimetric glaucoma participants were included in this observational, cross-sectional study. Or-logic, support vector machine, relevance vector machine, and linear discrimination function were used to analyze the performances of combined TD-OCT diagnostic variables. The area under the receiver-operating curve (AROC) was used to evaluate the diagnostic accuracy and to compare the diagnostic performance of single and combined anatomic variables. The best RNFL thickness variables were the inferior (AROC=0.900), overall (AROC=0.892), and superior quadrants (AROC=0.850). The best optic disc variables were horizontal integrated rim width (AROC=0.909), vertical integrated rim area (AROC=0.908), and cup/disc vertical ratio (AROC=0.890). All macular retinal thickness variables had AROCs of 0.829 or less. Combining the top 3 RNFL and optic disc variables in optimizing glaucoma diagnosis, support vector machine had the highest AROC, 0.954, followed by or-logic (AROC=0.946), linear discrimination function (AROC=0.946), and relevance vector machine (AROC=0.943). All combination diagnostic variables had significantly larger AROCs than any single diagnostic variable. There are no significant differences among the combination diagnostic indices. With TD-OCT, RNFL and optic disc variables had better diagnostic accuracy than macular retinal variables. Combining top RNFL and optic disc variables significantly improved diagnostic performance. Clinically, or-logic classification was the most practical analytical tool with sufficient accuracy to diagnose early glaucoma.

Selecting predictors for discriminant analysis of species performance: an example from an amphibious softwater plant.

PubMed

Vanderhaeghe, F; Smolders, A J P; Roelofs, J G M; Hoffmann, M

2012-03-01

Selecting an appropriate variable subset in linear multivariate methods is an important methodological issue for ecologists. Interest often exists in obtaining general predictive capacity or in finding causal inferences from predictor variables. Because of a lack of solid knowledge on a studied phenomenon, scientists explore predictor variables in order to find the most meaningful (i.e. discriminating) ones. As an example, we modelled the response of the amphibious softwater plant Eleocharis multicaulis using canonical discriminant function analysis. We asked how variables can be selected through comparison of several methods: univariate Pearson chi-square screening, principal components analysis (PCA) and step-wise analysis, as well as combinations of some methods. We expected PCA to perform best. The selected methods were evaluated through fit and stability of the resulting discriminant functions and through correlations between these functions and the predictor variables. The chi-square subset, at P < 0.05, followed by a step-wise sub-selection, gave the best results. In contrast to expectations, PCA performed poorly, as so did step-wise analysis. The different chi-square subset methods all yielded ecologically meaningful variables, while probable noise variables were also selected by PCA and step-wise analysis. We advise against the simple use of PCA or step-wise discriminant analysis to obtain an ecologically meaningful variable subset; the former because it does not take into account the response variable, the latter because noise variables are likely to be selected. We suggest that univariate screening techniques are a worthwhile alternative for variable selection in ecology. © 2011 German Botanical Society and The Royal Botanical Society of the Netherlands.

Vagal-dependent nonlinear variability in the respiratory pattern of anesthetized, spontaneously breathing rats

PubMed Central

Dhingra, R. R.; Jacono, F. J.; Fishman, M.; Loparo, K. A.; Rybak, I. A.

2011-01-01

Physiological rhythms, including respiration, exhibit endogenous variability associated with health, and deviations from this are associated with disease. Specific changes in the linear and nonlinear sources of breathing variability have not been investigated. In this study, we used information theory-based techniques, combined with surrogate data testing, to quantify and characterize the vagal-dependent nonlinear pattern variability in urethane-anesthetized, spontaneously breathing adult rats. Surrogate data sets preserved the amplitude distribution and linear correlations of the original data set, but nonlinear correlation structure in the data was removed. Differences in mutual information and sample entropy between original and surrogate data sets indicated the presence of deterministic nonlinear or stochastic non-Gaussian variability. With vagi intact (n = 11), the respiratory cycle exhibited significant nonlinear behavior in templates of points separated by time delays ranging from one sample to one cycle length. After vagotomy (n = 6), even though nonlinear variability was reduced significantly, nonlinear properties were still evident at various time delays. Nonlinear deterministic variability did not change further after subsequent bilateral microinjection of MK-801, an N-methyl-d-aspartate receptor antagonist, in the Kölliker-Fuse nuclei. Reversing the sequence (n = 5), blocking N-methyl-d-aspartate receptors bilaterally in the dorsolateral pons significantly decreased nonlinear variability in the respiratory pattern, even with the vagi intact, and subsequent vagotomy did not change nonlinear variability. Thus both vagal and dorsolateral pontine influences contribute to nonlinear respiratory pattern variability. Furthermore, breathing dynamics of the intact system are mutually dependent on vagal and pontine sources of nonlinear complexity. Understanding the structure and modulation of variability provides insight into disease effects on respiratory patterning. PMID:21527661

Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes

DOE PAGES

Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.; ...

2015-08-07

While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less

EUV brightness variations in the quiet Sun

NASA Astrophysics Data System (ADS)

Brković, A.; Rüedi, I.; Solanki, S. K.; Fludra, A.; Harrison, R. A.; Huber, M. C. E.; Stenflo, J. O.; Stucki, K.

2000-01-01

The Coronal Diagnostic Spectrometer (CDS) onboard the SOHO satellite has been used to obtain movies of quiet Sun regions at disc centre. These movies were used to study brightness variations of solar features at three different temperatures sampled simultaneously in the chromospheric He I 584.3 Ä (2 * 104 K), the transition region O V 629.7 Ä (2.5 * 105 K) and coronal Mg IX 368.1 Ä (106 K) lines. In all parts of the quiet Sun, from darkest intranetwork to brightest network, we find significant variability in the He I and O V line, while the variability in the Mg IX line is more marginal. The relative variability, defined by rms of intensity normalised to the local intensity, is independent of brightness and strongest in the transition region line. Thus the relative variability is the same in the network and the intranetwork. More than half of the points on the solar surface show a relative variability, determined over a period of 4 hours, greater than 15.5% for the O V line, but only 5% of the points exhibit a variability above 25%. Most of the variability appears to take place on time-scales between 5 and 80 minutes for the He I and O V lines. Clear signs of ``high variability'' events are found. For these events the variability as a function of time seen in the different lines shows a good correlation. The correlation is higher for more variable events. These events coincide with the (time averaged) brightest points on the solar surface, i.e. they occur in the network. The spatial positions of the most variable points are identical in all the lines.

Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.

While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less

Brown dwarf photospheres are patchy: A Hubble space telescope near-infrared spectroscopic survey finds frequent low-level variability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buenzli, Esther; Apai, Dániel; Radigan, Jacqueline

2014-02-20

Condensate clouds strongly impact the spectra of brown dwarfs and exoplanets. Recent discoveries of variable L/T transition dwarfs argued for patchy clouds in at least some ultracool atmospheres. This study aims to measure the frequency and level of spectral variability in brown dwarfs and to search for correlations with spectral type. We used Hubble Space Telescope/Wide Field Camera 3 to obtain spectroscopic time series for 22 brown dwarfs of spectral types ranging from L5 to T6 at 1.1-1.7 μm for ≈40 minutes per object. Using Bayesian analysis, we find six brown dwarfs with confident (p > 95%) variability in themore » relative flux in at least one wavelength region at sub-percent precision, and five brown dwarfs with tentative (p > 68%) variability. We derive a minimum variability fraction f{sub min}=27{sub −7}{sup +11}% over all covered spectral types. The fraction of variables is equal within errors for mid-L, late-L, and mid-T spectral types; for early-T dwarfs we do not find any confident variable but the sample is too small to derive meaningful limits. For some objects, the variability occurs primarily in the flux peak in the J or H band, others are variable throughout the spectrum or only in specific absorption regions. Four sources may have broadband peak-to-peak amplitudes exceeding 1%. Our measurements are not sensitive to very long periods, inclinations near pole-on and rotationally symmetric heterogeneity. The detection statistics are consistent with most brown dwarf photospheres being patchy. While multiple-percent near-infrared variability may be rare and confined to the L/T transition, low-level heterogeneities are a frequent characteristic of brown dwarf atmospheres.« less

An Expanded RXTE Survey of Long-Term X-ray Variability in Seyfert 1 Galaxies

NASA Technical Reports Server (NTRS)

Markowitz, A.; Edelson, R.

2004-01-01

The first seven years of RXTE monitoring of Seyfert 1 active galactic nuclei have been systematically analyzed to yield five homogenous samples of 2-12 keV light curves, probing hard X-ray variability on successively longer durations from approx. 1 day to approx. 3.5 years. 2-10 keV variability on time scales of approx. 1 day, as probed by ASCA, are included. All sources exhibit stronger X-ray variability towards longer time scales, with variability amplitudes saturating at the longest time scales, but the increase is greater for relatively higher luminosity sources. The well-documented anticorrelation between variability amplitude and luminosity is confirmed on all time scales. However, anticorrelations between variability amplitude and black hole mass estimate are evident on only the shortest time scales probed. The data are consistent with the models of power spectral density (PSD) movement described in Markowitz et al. (2003) and McHardy et al. (2004), whereby Seyfert 1 galaxies variability can be described by a single, universal PSD shape whose cutoff frequency scales with black hole mass. The best-fitting scaling relations between variability time scale, black hole mass and X-ray luminosity support an average accretion rate of 2% of the Eddington limit for the sample. Nearly all sources exhibit stronger variability in the relatively soft 2-4 keV band compared to the 7-12 keV band on all time scales. Color-flux diagrams support also Seyfert 1s' softening as they brighten. There are indications that relatively less luminous or less massive sources exhibit a greater degree of spectral variability for a given increase in overall flux.

A plant’s perspective of extremes: Terrestrial plant responses to changing climatic variability

PubMed Central

Reyer, C.; Leuzinger, S.; Rammig, A.; Wolf, A.; Bartholomeus, R. P.; Bonfante, A.; de Lorenzi, F.; Dury, M.; Gloning, P.; Abou Jaoudé, R.; Klein, T.; Kuster, T. M.; Martins, M.; Niedrist, G.; Riccardi, M.; Wohlfahrt, G.; de Angelis, P.; de Dato, G.; François, L.; Menzel, A.; Pereira, M.

2013-01-01

We review observational, experimental and model results on how plants respond to extreme climatic conditions induced by changing climatic variability. Distinguishing between impacts of changing mean climatic conditions and changing climatic variability on terrestrial ecosystems is generally underrated in current studies. The goals of our review are thus (1) to identify plant processes that are vulnerable to changes in the variability of climatic variables rather than to changes in their mean, and (2) to depict/evaluate available study designs to quantify responses of plants to changing climatic variability. We find that phenology is largely affected by changing mean climate but also that impacts of climatic variability are much less studied but potentially damaging. We note that plant water relations seem to be very vulnerable to extremes driven by changes in temperature and precipitation and that heatwaves and flooding have stronger impacts on physiological processes than changing mean climate. Moreover, interacting phenological and physiological processes are likely to further complicate plant responses to changing climatic variability. Phenological and physiological processes and their interactions culminate in even more sophisticated responses to changing mean climate and climatic variability at the species and community level. Generally, observational studies are well suited to study plant responses to changing mean climate, but less suitable to gain a mechanistic understanding of plant responses to climatic variability. Experiments seem best suited to simulate extreme events. In models, temporal resolution and model structure are crucial to capture plant responses to changing climatic variability. We highlight that a combination of experimental, observational and /or modeling studies have the potential to overcome important caveats of the respective individual approaches. PMID:23504722

Variability survey of brightest stars in selected OB associations

NASA Astrophysics Data System (ADS)

Laur, Jaan; Kolka, Indrek; Eenmäe, Tõnis; Tuvikene, Taavi; Leedjärv, Laurits

2017-02-01

Context. The stellar evolution theory of massive stars remains uncalibrated with high-precision photometric observational data mainly due to a small number of luminous stars that are monitored from space. Automated all-sky surveys have revealed numerous variable stars but most of the luminous stars are often overexposed. Targeted campaigns can improve the time base of photometric data for those objects. Aims: The aim of this investigation is to study the variability of luminous stars at different timescales in young open clusters and OB associations. Methods: We monitored 22 open clusters and associations from 2011 to 2013 using a 0.25-m telescope. Variable stars were detected by comparing the overall light-curve scatter with measurement uncertainties. Variability was analysed by the light curve feature extraction tool FATS. Periods of pulsating stars were determined using the discrete Fourier transform code SigSpec. We then classified the variable stars based on their pulsation periods and available spectral information. Results: We obtained light curves for more than 20 000 sources of which 354 were found to be variable. Amongst them we find 80 eclipsing binaries, 31 α Cyg, 13 β Cep, 62 Be, 16 slowly pulsating B, 7 Cepheid, 1 γ Doradus, 3 Wolf-Rayet and 63 late-type variable stars. Up to 55% of these stars are potential new discoveries as they are not present in the Variable Star Index (VSX) database. We find the cluster membership fraction for variable stars to be 13% with an upper limit of 35%. Variable star catalogue (Tables A.1-A.10) and light curves are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/598/A108

Optimal traits of plant hydraulic capacitance as an adaptation to hydroclimatic variability

NASA Astrophysics Data System (ADS)

Hartzell, S. R.; Bartlett, M. S., Jr.; Porporato, A. M.

2016-12-01

Hydraulic capacitance allows plants to uptake and store water when it is abundant. This stored water is utilized during periods of water stress, decreasing tissue damage and increasing carbon assimilation. By providing a more consistent and readily accessible water supply, it buffers water stress variability across daily and seasonal timescales. The rate of plant water storage and withdrawal varies widely between plant species and is principally governed by several plant hydraulic parameters, principally the hydraulic capacitance, the total water storage capacity, and the conductance between xylem and water storage tissue. The timescale of the plant response to changes in environmental conditions may be related to the timescale of relevant environmental variability. For example, the Baobab tree (Adansonia), which grows in an environment with very strong seasonal rainfall variability, has a relatively long timescale of hydraulic response, while an evergreen tree such as Pinus taeda, which mainly contends with daily and inter-rainfall moisture variability, has a much shorter timescale of hydraulic response. Here a model of hydraulic capacitance is coupled to a resistance model of soil-plant-atmosphere continuum. We force this model with stochastic rainfall and examine plant responses to moisture variability at various timescales. Optimal plant hydraulic properties are examined as a function of mean soil moisture (daily variability), mean period between rainfall events (inter-rainfall variability), and seasonal rainfall variability, and the relative importance of each type of variability in shaping plant water use strategies is assessed. Results are compared to typical hydraulic parameters of plants growing under specific environmental conditions. Values of hydraulic traits which optimize carbon assimilation and water use efficiency are found; these values are dependent on mean environmental conditions as well as the timescale of environmental variability.

Response variables for evaluation of the effectiveness of conservation corridors.

PubMed

Gregory, Andrew J; Beier, Paul

2014-06-01

Many studies have evaluated effectiveness of corridors by measuring species presence in and movement through small structural corridors. However, few studies have assessed whether these response variables are adequate for assessing whether the conservation goals of the corridors have been achieved or considered the costs or lag times involved in measuring the response variables. We examined 4 response variables-presence of the focal species in the corridor, interpatch movement via the corridor, gene flow, and patch occupancy--with respect to 3 criteria--relevance to conservation goals, lag time (fewest generations at which a positive response to the corridor might be evident with a particular variable), and the cost of a study when applying a particular variable. The presence variable had the least relevance to conservation goals, no lag time advantage compared with interpatch movement, and only a moderate cost advantage over interpatch movement or gene flow. Movement of individual animals between patches was the most appropriate response variable for a corridor intended to provide seasonal migration, but it was not an appropriate response variable for corridor dwellers, and for passage species it was only moderately relevant to the goals of gene flow, demographic rescue, and recolonization. Response variables related to gene flow provided a good trade-off among cost, relevance to conservation goals, and lag time. Nonetheless, the lag time of 10-20 generations means that evaluation of conservation corridors cannot occur until a few decades after a corridor has been established. Response variables related to occupancy were most relevant to conservation goals, but the lag time and costs to detect corridor effects on occupancy were much greater than the lag time and costs to detect corridor effects on gene flow. © 2014 Society for Conservation Biology.

When to trust our learners? Clinical teachers' perceptions of decision variables in the entrustment process.

PubMed

Duijn, Chantal C M A; Welink, Lisanne S; Bok, Harold G J; Ten Cate, Olle T J

2018-06-01

Clinical training programs increasingly use entrustable professional activities (EPAs) as focus of assessment. However, questions remain about which information should ground decisions to trust learners. This qualitative study aimed to identify decision variables in the workplace that clinical teachers find relevant in the elaboration of the entrustment decision processes. The findings can substantiate entrustment decision-making in the clinical workplace. Focus groups were conducted with medical and veterinary clinical teachers, using the structured consensus method of the Nominal Group Technique to generate decision variables. A ranking was made based on a relevance score assigned by the clinical teachers to the different decision variables. Field notes, audio recordings and flip chart lists were analyzed and subsequently translated and, as a form of axial coding, merged into one list, combining the decision variables that were similar in their meaning. A list of 11 and 17 decision variables were acknowledged as relevant by the medical and veterinary teacher groups, respectively. The focus groups yielded 21 unique decision variables that were considered relevant to inform readiness to perform a clinical task on a designated level of supervision. The decision variables consisted of skills, generic qualities, characteristics, previous performance or other information. We were able to group the decision variables into five categories: ability, humility, integrity, reliability and adequate exposure. To entrust a learner to perform a task at a specific level of supervision, a supervisor needs information to support such a judgement. This trust cannot be credited on a single case at a single moment of assessment, but requires different variables and multiple sources of information. This study provides an overview of decision variables giving evidence to justify the multifactorial process of making an entrustment decision.

The association between tax structure and cigarette price variability: findings from the ITC Project.

PubMed

Shang, Ce; Chaloupka, Frank J; Fong, Geoffrey T; Thompson, Mary; O'Connor, Richard J

2015-07-01

Recent studies have shown that more opportunities exist for tax avoidance when cigarette excise tax structure departs from a uniform specific structure. However, the association between tax structure and cigarette price variability has not been thoroughly studied in the existing literature. To examine how cigarette tax structure is associated with price variability. The variability of self-reported prices is measured using the ratios of differences between higher and lower prices to the median price such as the IQR-to-median ratio. We used survey data taken from the International Tobacco Control Policy Evaluation (ITC) Project in 17 countries to conduct the analysis. Cigarette prices were derived using individual purchase information and aggregated to price variability measures for each surveyed country and wave. The effect of tax structures on price variability was estimated using Generalised Estimating Equations after adjusting for year and country attributes. Our study provides empirical evidence of a relationship between tax structure and cigarette price variability. We find that, compared to the specific uniform tax structure, mixed uniform and tiered (specific, ad valorem or mixed) structures are associated with greater price variability (p≤0.01). Moreover, while a greater share of the specific component in total excise taxes is associated with lower price variability (p≤0.05), a tiered tax structure is associated with greater price variability (p≤0.01). The results suggest that a uniform and specific tax structure is the most effective tax structure for reducing tobacco consumption and prevalence by limiting price variability and decreasing opportunities for tax avoidance. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Capturing the dynamics of response variability in the brain in ADHD.

PubMed

van Belle, Janna; van Raalten, Tamar; Bos, Dienke J; Zandbelt, Bram B; Oranje, Bob; Durston, Sarah

2015-01-01

ADHD is characterized by increased intra-individual variability in response times during the performance of cognitive tasks. However, little is known about developmental changes in intra-individual variability, and how these changes relate to cognitive performance. Twenty subjects with ADHD aged 7-24 years and 20 age-matched, typically developing controls participated in an fMRI-scan while they performed a go-no-go task. We fit an ex-Gaussian distribution on the response distribution to objectively separate extremely slow responses, related to lapses of attention, from variability on fast responses. We assessed developmental changes in these intra-individual variability measures, and investigated their relation to no-go performance. Results show that the ex-Gaussian measures were better predictors of no-go performance than traditional measures of reaction time. Furthermore, we found between-group differences in the change in ex-Gaussian parameters with age, and their relation to task performance: subjects with ADHD showed age-related decreases in their variability on fast responses (sigma), but not in lapses of attention (tau), whereas control subjects showed a decrease in both measures of variability. For control subjects, but not subjects with ADHD, this age-related reduction in variability was predictive of task performance. This group difference was reflected in neural activation: for typically developing subjects, the age-related decrease in intra-individual variability on fast responses (sigma) predicted activity in the dorsal anterior cingulate gyrus (dACG), whereas for subjects with ADHD, activity in this region was related to improved no-go performance with age, but not to intra-individual variability. These data show that using more sophisticated measures of intra-individual variability allows the capturing of the dynamics of task performance and associated neural changes not permitted by more traditional measures.

Capturing the dynamics of response variability in the brain in ADHD

PubMed Central

van Belle, Janna; van Raalten, Tamar; Bos, Dienke J.; Zandbelt, Bram B.; Oranje, Bob; Durston, Sarah

2014-01-01

ADHD is characterized by increased intra-individual variability in response times during the performance of cognitive tasks. However, little is known about developmental changes in intra-individual variability, and how these changes relate to cognitive performance. Twenty subjects with ADHD aged 7–24 years and 20 age-matched, typically developing controls participated in an fMRI-scan while they performed a go-no-go task. We fit an ex-Gaussian distribution on the response distribution to objectively separate extremely slow responses, related to lapses of attention, from variability on fast responses. We assessed developmental changes in these intra-individual variability measures, and investigated their relation to no-go performance. Results show that the ex-Gaussian measures were better predictors of no-go performance than traditional measures of reaction time. Furthermore, we found between-group differences in the change in ex-Gaussian parameters with age, and their relation to task performance: subjects with ADHD showed age-related decreases in their variability on fast responses (sigma), but not in lapses of attention (tau), whereas control subjects showed a decrease in both measures of variability. For control subjects, but not subjects with ADHD, this age-related reduction in variability was predictive of task performance. This group difference was reflected in neural activation: for typically developing subjects, the age-related decrease in intra-individual variability on fast responses (sigma) predicted activity in the dorsal anterior cingulate gyrus (dACG), whereas for subjects with ADHD, activity in this region was related to improved no-go performance with age, but not to intra-individual variability. These data show that using more sophisticated measures of intra-individual variability allows the capturing of the dynamics of task performance and associated neural changes not permitted by more traditional measures. PMID:25610775

Reproducibility of 3D kinematics and surface electromyography measurements of mastication.

PubMed

Remijn, Lianne; Groen, Brenda E; Speyer, Renée; van Limbeek, Jacques; Nijhuis-van der Sanden, Maria W G

2016-03-01

The aim of this study was to determine the measurement reproducibility for a procedure evaluating the mastication process and to estimate the smallest detectable differences of 3D kinematic and surface electromyography (sEMG) variables. Kinematics of mandible movements and sEMG activity of the masticatory muscles were obtained over two sessions with four conditions: two food textures (biscuit and bread) of two sizes (small and large). Twelve healthy adults (mean age 29.1 years) completed the study. The second to the fifth chewing cycle of 5 bites were used for analyses. The reproducibility per outcome variable was calculated with an intraclass correlation coefficient (ICC) and a Bland-Altman analysis was applied to determine the standard error of measurement relative error of measurement and smallest detectable differences of all variables. ICCs ranged from 0.71 to 0.98 for all outcome variables. The outcome variables consisted of four bite and fourteen chewing cycle variables. The relative standard error of measurement of the bite variables was up to 17.3% for 'time-to-swallow', 'time-to-transport' and 'number of chewing cycles', but ranged from 31.5% to 57.0% for 'change of chewing side'. The relative standard error of measurement ranged from 4.1% to 24.7% for chewing cycle variables and was smaller for kinematic variables than sEMG variables. In general, measurements obtained with 3D kinematics and sEMG are reproducible techniques to assess the mastication process. The duration of the chewing cycle and frequency of chewing were the best reproducible measurements. Change of chewing side could not be reproduced. The published measurement error and smallest detectable differences will aid the interpretation of the results of future clinical studies using the same study variables. Copyright © 2015 Elsevier Inc. All rights reserved.

Variability Selected Low-Luminosity Active Galactic Nuclei in the 4 Ms Chandra Deep Field-South

NASA Technical Reports Server (NTRS)

Young, M.; Brandt, W. N.; Xue, Y. Q.; Paolillo, D. M.; Alexander, F. E.; Bauer, F. E.; Lehmer, B. D.; Luo, B.; Shemmer, O.; Schneider, D. P.;

The effect of virtual reality on gait variability.

PubMed

Katsavelis, Dimitrios; Mukherjee, Mukul; Decker, Leslie; Stergiou, Nicholas

2010-07-01

Optic Flow (OF) plays an important role in human locomotion and manipulation of OF characteristics can cause changes in locomotion patterns. The purpose of the study was to investigate the effect of the velocity of optic flow on the amount and structure of gait variability. Each subject underwent four conditions of treadmill walking at their self-selected pace. In three conditions the subjects walked in an endless virtual corridor, while a fourth control condition was also included. The three virtual conditions differed in the speed of the optic flow displayed as follows--same speed (OFn), faster (OFf), and slower (OFs) than that of the treadmill. Gait kinematics were tracked with an optical motion capture system. Gait variability measures of the hip, knee and ankle range of motion and stride interval were analyzed. Amount of variability was evaluated with linear measures of variability--coefficient of variation, while structure of variability i.e., its organization over time, were measured with nonlinear measures--approximate entropy and detrended fluctuation analysis. The linear measures of variability, CV, did not show significant differences between Non-VR and VR conditions while nonlinear measures of variability identified significant differences at the hip, ankle, and in stride interval. In response to manipulation of the optic flow, significant differences were observed between the three virtual conditions in the following order: OFn greater than OFf greater than OFs. Measures of structure of variability are more sensitive to changes in gait due to manipulation of visual cues, whereas measures of the amount of variability may be concealed by adaptive mechanisms. Visual cues increase the complexity of gait variability and may increase the degrees of freedom available to the subject. Further exploration of the effects of optic flow manipulation on locomotion may provide us with an effective tool for rehabilitation of subjects with sensorimotor issues.

Regression: The Apple Does Not Fall Far From the Tree.

PubMed

Vetter, Thomas R; Schober, Patrick

2018-05-15

Researchers and clinicians are frequently interested in either: (1) assessing whether there is a relationship or association between 2 or more variables and quantifying this association; or (2) determining whether 1 or more variables can predict another variable. The strength of such an association is mainly described by the correlation. However, regression analysis and regression models can be used not only to identify whether there is a significant relationship or association between variables but also to generate estimations of such a predictive relationship between variables. This basic statistical tutorial discusses the fundamental concepts and techniques related to the most common types of regression analysis and modeling, including simple linear regression, multiple regression, logistic regression, ordinal regression, and Poisson regression, as well as the common yet often underrecognized phenomenon of regression toward the mean. The various types of regression analysis are powerful statistical techniques, which when appropriately applied, can allow for the valid interpretation of complex, multifactorial data. Regression analysis and models can assess whether there is a relationship or association between 2 or more observed variables and estimate the strength of this association, as well as determine whether 1 or more variables can predict another variable. Regression is thus being applied more commonly in anesthesia, perioperative, critical care, and pain research. However, it is crucial to note that regression can identify plausible risk factors; it does not prove causation (a definitive cause and effect relationship). The results of a regression analysis instead identify independent (predictor) variable(s) associated with the dependent (outcome) variable. As with other statistical methods, applying regression requires that certain assumptions be met, which can be tested with specific diagnostics.

Step-by-step variability of swing phase trajectory area during steady state walking at a range of speeds

PubMed Central

Hurt, Christopher P.; Brown, David A.

2018-01-01

Background Step kinematic variability has been characterized during gait using spatial and temporal kinematic characteristics. However, people can adopt different trajectory paths both between individuals and even within individuals at different speeds. Single point measures such as minimum toe clearance (MTC) and step length (SL) do not necessarily account for the multiple paths that the foot may take during the swing phase to reach the same foot fall endpoint. The purpose of this study was to test a step-by-step foot trajectory area (SBS-FTA) variability measure that is able to characterize sagittal plane foot trajectories of varying areas, and compare this measure against MTC and SL variability at different speeds. We hypothesize that the SBS-FTA variability would demonstrate increased variability with speed. Second, we hypothesize that SBS-FTA would have a stronger curvilinear fit compared with the CV and SD of SL and MTC. Third, we hypothesize SBS-FTA would be more responsive to change in the foot trajectory at a given speed compared to SL and MTC. Fourth, SBS-FTA variability would not strongly co-vary with SL and MTC variability measures since it represents a different construct related to foot trajectory area variability. Methods We studied 15 nonimpaired individuals during walking at progressively faster speeds. We calculated SL, MTC, and SBS-FTA area. Results SBS-FTA variability increased with speed, had a stronger curvilinear fit compared with the CV and SD of SL and MTC, was more responsive at a given speed, and did not strongly co-vary with SL and MTC variability measures. Conclusion SBS foot trajectory area variability was sensitive to change with faster speeds, captured a relationship that the majority of the other measures did not demonstrate, and did not co-vary strongly with other measures that are also components of the trajectory. PMID:29370202

The vertical dependence in the horizontal variability of salinity and temperature at the ocean surface

NASA Astrophysics Data System (ADS)

Asher, W.; Drushka, K.; Jessup, A. T.; Clark, D.

2016-02-01

Satellite-mounted microwave radiometers measure sea surface salinity (SSS) as an area-averaged quantity in the top centimeter of the ocean over the footprint of the instrument. If the horizontal variability in SSS is large inside this footprint, sub-grid-scale variability in SSS can affect comparison of the satellite-retrieved SSS with in situ measurements. Understanding the magnitude of horizontal variability in SSS over spatial scales that are relevant to the satellite measurements is therefore important. Horizontal variability of SSS at the ocean surface can be studied in situ using data recorded by thermosalinographs (TSGs) that sample water from a depth of a few meters. However, it is possible measurements made at this depth might underestimate the horizontal variability at the surface because salinity and temperature can become vertically stratified in a very near surface layer due to the effects of rain, solar heating, and evaporation. This vertical stratification could prevent horizontal gradients from propagating to the sampling depths of ship-mounted TSGs. This presentation will discuss measurements made using an underway salinity profiling system installed on the R/V Thomas Thompson that made continuous measurements of SSS and SST in the Pacific Ocean. The system samples at nominal depths of 2-m, 3-m, and 5-m, allowing the depth dependence of the horizontal variability in SSS and SST to be measured. Horizontal variability in SST is largest at low wind speeds during daytime, when a diurnal warm layer forms. In contrast, the diurnal signal in the variability of SSS was smaller with variability being slightly larger at night. When studied as a function of depth, the results show that over 100-km scales, the horizontal variability in both SSS and SST at a depth of 2 m is approximately a factor of 4 higher than the variability at 5 m.

Long-term variability in sugarcane bagasse feedstock compositional methods: Sources and magnitude of analytical variability

DOE PAGES

Templeton, David W.; Sluiter, Justin B.; Sluiter, Amie; ...

2016-10-18

In an effort to find economical, carbon-neutral transportation fuels, biomass feedstock compositional analysis methods are used to monitor, compare, and improve biofuel conversion processes. These methods are empirical, and the analytical variability seen in the feedstock compositional data propagates into variability in the conversion yields, component balances, mass balances, and ultimately the minimum ethanol selling price (MESP). We report the average composition and standard deviations of 119 individually extracted National Institute of Standards and Technology (NIST) bagasse [Reference Material (RM) 8491] run by seven analysts over 7 years. Two additional datasets, using bulk-extracted bagasse (containing 58 and 291 replicates each),more » were examined to separate out the effects of batch, analyst, sugar recovery standard calculation method, and extractions from the total analytical variability seen in the individually extracted dataset. We believe this is the world's largest NIST bagasse compositional analysis dataset and it provides unique insight into the long-term analytical variability. Understanding the long-term variability of the feedstock analysis will help determine the minimum difference that can be detected in yield, mass balance, and efficiency calculations. The long-term data show consistent bagasse component values through time and by different analysts. This suggests that the standard compositional analysis methods were performed consistently and that the bagasse RM itself remained unchanged during this time period. The long-term variability seen here is generally higher than short-term variabilities. It is worth noting that the effect of short-term or long-term feedstock compositional variability on MESP is small, about $0.03 per gallon. The long-term analysis variabilities reported here are plausible minimum values for these methods, though not necessarily average or expected variabilities. We must emphasize the importance of training and good analytical procedures needed to generate this data. As a result, when combined with a robust QA/QC oversight protocol, these empirical methods can be relied upon to generate high-quality data over a long period of time.« less

Interannual rainfall variability and SOM-based circulation classification

NASA Astrophysics Data System (ADS)

Wolski, Piotr; Jack, Christopher; Tadross, Mark; van Aardenne, Lisa; Lennard, Christopher

2018-01-01

Self-Organizing Maps (SOM) based classifications of synoptic circulation patterns are increasingly being used to interpret large-scale drivers of local climate variability, and as part of statistical downscaling methodologies. These applications rely on a basic premise of synoptic climatology, i.e. that local weather is conditioned by the large-scale circulation. While it is clear that this relationship holds in principle, the implications of its implementation through SOM-based classification, particularly at interannual and longer time scales, are not well recognized. Here we use a SOM to understand the interannual synoptic drivers of climate variability at two locations in the winter and summer rainfall regimes of South Africa. We quantify the portion of variance in seasonal rainfall totals that is explained by year to year differences in the synoptic circulation, as schematized by a SOM. We furthermore test how different spatial domain sizes and synoptic variables affect the ability of the SOM to capture the dominant synoptic drivers of interannual rainfall variability. Additionally, we identify systematic synoptic forcing that is not captured by the SOM classification. The results indicate that the frequency of synoptic states, as schematized by a relatively disaggregated SOM (7 × 9) of prognostic atmospheric variables, including specific humidity, air temperature and geostrophic winds, captures only 20-45% of interannual local rainfall variability, and that the residual variance contains a strong systematic component. Utilising a multivariate linear regression framework demonstrates that this residual variance can largely be explained using synoptic variables over a particular location; even though they are used in the development of the SOM their influence, however, diminishes with the size of the SOM spatial domain. The influence of the SOM domain size, the choice of SOM atmospheric variables and grid-point explanatory variables on the levels of explained variance, is consistent with the general understanding of the dominant processes and atmospheric variables that affect rainfall variability at a particular location.

Does internal variability change in response to global warming? A large ensemble modelling study of tropical rainfall

NASA Astrophysics Data System (ADS)

Milinski, S.; Bader, J.; Jungclaus, J. H.; Marotzke, J.

2017-12-01

There is some consensus on mean state changes of rainfall under global warming; changes of the internal variability, on the other hand, are more difficult to analyse and have not been discussed as much despite their importance for understanding changes in extreme events, such as droughts or floodings. We analyse changes in the rainfall variability in the tropical Atlantic region. We use a 100-member ensemble of historical (1850-2005) model simulations with the Max Planck Institute for Meteorology Earth System Model (MPI-ESM1) to identify changes of internal rainfall variability. To investigate the effects of global warming on the internal variability, we employ an additional ensemble of model simulations with stronger external forcing (1% CO2-increase per year, same integration length as the historical simulations) with 68 ensemble members. The focus of our study is on the oceanic Atlantic ITCZ. We find that the internal variability of rainfall over the tropical Atlantic does change due to global warming and that these changes in variability are larger than changes in the mean state in some regions. From splitting the total variance into patterns of variability, we see that the variability on the southern flank of the ITCZ becomes more dominant, i.e. explaining a larger fraction of the total variance in a warmer climate. In agreement with previous studies, we find that changes in the mean state show an increase and narrowing of the ITCZ. The large ensembles allow us to do a statistically robust differentiation between the changes in variability that can be explained by internal variability and those that can be attributed to the external forcing. Furthermore, we argue that internal variability in a transient climate is only well defined in the ensemble domain and not in the temporal domain, which requires the use of a large ensemble.

Selected questions on biomechanical exposures for surveillance of upper-limb work-related musculoskeletal disorders

PubMed Central

Descatha, Alexis; Roquelaure, Yves; Evanoff, Bradley; Niedhammer, Isabelle; Chastang, Jean François; Mariot, Camille; Ha, Catherine; Imbernon, Ellen; Goldberg, Marcel; Leclerc, Annette

2007-01-01

Objective Questionnaires for assessment of biomechanical exposure are frequently used in surveillance programs, though few studies have evaluated which key questions are needed. We sought to reduce the number of variables on a surveillance questionnaire by identifying which variables best summarized biomechanical exposure in a survey of the French working population. Methods We used data from the 2002–2003 French experimental network of Upper-limb work-related musculoskeletal disorders (UWMSD), performed on 2685 subjects in which 37 variables assessing biomechanical exposures were available (divided into four ordinal categories, according to the task frequency or duration). Principal Component Analysis (PCA) with orthogonal rotation was performed on these variables. Variables closely associated with factors issued from PCA were retained, except those highly correlated to another variable (rho>0.70). In order to study the relevance of the final list of variables, correlations between a score based on retained variables (PCA score) and the exposure score suggested by the SALTSA group were calculated. The associations between the PCA score and the prevalence of UWMSD were also studied. In a final step, we added back to the list a few variables not retained by PCA, because of their established recognition as risk factors. Results According to the results of the PCA, seven interpretable factors were identified: posture exposures, repetitiveness, handling of heavy loads, distal biomechanical exposures, computer use, forklift operator specific task, and recovery time. Twenty variables strongly correlated with the factors obtained from PCA were retained. The PCA score was strongly correlated both with the SALTSA score and with UWMSD prevalence (p<0.0001). In the final step, six variables were reintegrated. Conclusion Twenty-six variables out of 37 were efficiently selected according to their ability to summarize major biomechanical constraints in a working population, with an approach combining statistical analyses and existing knowledge. PMID:17476519

Flexible Strategies for Coping with Rainfall Variability: Seasonal Adjustments in Cropped Area in the Ganges Basin

PubMed Central

Siderius, Christian; Biemans, Hester; van Walsum, Paul E. V.; van Ierland, Ekko C.; Kabat, Pavel; Hellegers, Petra J. G. J.

2016-01-01

One of the main manifestations of climate change will be increased rainfall variability. How to deal with this in agriculture will be a major societal challenge. In this paper we explore flexibility in land use, through deliberate seasonal adjustments in cropped area, as a specific strategy for coping with rainfall variability. Such adjustments are not incorporated in hydro-meteorological crop models commonly used for food security analyses. Our paper contributes to the literature by making a comprehensive model assessment of inter-annual variability in crop production, including both variations in crop yield and cropped area. The Ganges basin is used as a case study. First, we assessed the contribution of cropped area variability to overall variability in rice and wheat production by applying hierarchical partitioning on time-series of agricultural statistics. We then introduced cropped area as an endogenous decision variable in a hydro-economic optimization model (WaterWise), coupled to a hydrology-vegetation model (LPJmL), and analyzed to what extent its performance in the estimation of inter-annual variability in crop production improved. From the statistics, we found that in the period 1999–2009 seasonal adjustment in cropped area can explain almost 50% of variability in wheat production and 40% of variability in rice production in the Indian part of the Ganges basin. Our improved model was well capable of mimicking existing variability at different spatial aggregation levels, especially for wheat. The value of flexibility, i.e. the foregone costs of choosing not to crop in years when water is scarce, was quantified at 4% of gross margin of wheat in the Indian part of the Ganges basin and as high as 34% of gross margin of wheat in the drought-prone state of Rajasthan. We argue that flexibility in land use is an important coping strategy to rainfall variability in water stressed regions. PMID:26934389

Forced Atlantic Multidecadal Variability Over the Past Millennium

NASA Astrophysics Data System (ADS)

Halloran, P. R.; Reynolds, D.; Scourse, J. D.; Hall, I. R.

2016-02-01

Paul R. Halloran, David J. Reynolds, Ian R. Hall and James D. Scourse Multidecadal variability in Atlantic sea surface temperatures (SSTs) plays a first order role in determining regional atmospheric circulation and moisture transport, with major climatic consequences. These regional climate impacts range from drought in the Sahel and South America, though increased hurricane activity and temperature extremes, to modified monsoonal rainfall. Multidecadal Atlantic SST variability could arise through internal variability in the Atlantic Meridional Overturning Circulation (AMOC) (e.g., Knight et al., 2006), or through externally forced change (e.g. Booth et al., 2012). It is critical that we know whether internal or external forcing dominates if we are to provide useful near-term climate projections in the Atlantic region. A persuasive argument that internal variability plays an important role in Atlantic Multidecadal Variability is that periodic SST variability has been observed throughout much of the last millennium (Mann et al., 2009), and the hypothesized external forcing of historical Atlantic Multidecadal Variability (Booth et al., 2012) is largely anthropogenic in origin. Here we combine the first annually-resolved millennial marine reconstruction with multi-model analysis, to show that the Atlantic SST variability of the last millennium can be explained by a combination of direct volcanic forcing, and indirect, forced, AMOC variability. Our results indicate that whilst climate models capture the timing of both the directly forced SST and forced AMOC-mediated SST variability, the models fail to capture the magnitude of the forced AMOC change. Does this mean that models underestimate the 21st century reduction in AMOC strength? J. Knight, C. Folland and A. Scaife., Climate impacts of the Atlantic Multidecadal Oscillation, GRL, 2006 B.B.B Booth, N. Dunstone, P.R. Halloran et al., Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability, Nature, 2012 M.E. Mann, Z. Zhang, S. Rutherford et al., Global Signatures and Dynamical Origins of the Little Ice Age and Medieval Climate Anomaly, Science, 2009

Snow-atmosphere coupling and its impact on temperature variability and extremes over North America

NASA Astrophysics Data System (ADS)

Diro, G. T.; Sushama, L.; Huziy, O.

2018-04-01

The impact of snow-atmosphere coupling on climate variability and extremes over North America is investigated using modeling experiments with the fifth generation Canadian Regional Climate Model (CRCM5). To this end, two CRCM5 simulations driven by ERA-Interim reanalysis for the 1981-2010 period are performed, where snow cover and depth are prescribed (uncoupled) in one simulation while they evolve interactively (coupled) during model integration in the second one. Results indicate systematic influence of snow cover and snow depth variability on the inter-annual variability of soil and air temperatures during winter and spring seasons. Inter-annual variability of air temperature is larger in the coupled simulation, with snow cover and depth variability accounting for 40-60% of winter temperature variability over the Mid-west, Northern Great Plains and over the Canadian Prairies. The contribution of snow variability reaches even more than 70% during spring and the regions of high snow-temperature coupling extend north of the boreal forests. The dominant process contributing to the snow-atmosphere coupling is the albedo effect in winter, while the hydrological effect controls the coupling in spring. Snow cover/depth variability at different locations is also found to affect extremes. For instance, variability of cold-spell characteristics is sensitive to snow cover/depth variation over the Mid-west and Northern Great Plains, whereas, warm-spell variability is sensitive to snow variation primarily in regions with climatologically extensive snow cover such as northeast Canada and the Rockies. Furthermore, snow-atmosphere interactions appear to have contributed to enhancing the number of cold spell days during the 2002 spring, which is the coldest recorded during the study period, by over 50%, over western North America. Additional results also provide useful information on the importance of the interactions of snow with large-scale mode of variability in modulating temperature extreme characteristics.

A SYSTEMATIC SEARCH FOR COROTATING INTERACTION REGIONS IN APPARENTLY SINGLE GALACTIC WOLF-RAYET STARS. II. A GLOBAL VIEW OF THE WIND VARIABILITY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chene, A.-N.; St-Louis, N., E-mail: achene@astro-udec.cl, E-mail: stlouis@astro.umontreal.ca

This study is the second part of a survey searching for large-scale spectroscopic variability in apparently single Wolf-Rayet (WR) stars. In a previous paper (Paper I), we described and characterized the spectroscopic variability level of 25 WR stars observable from the northern hemisphere and found 3 new candidates presenting large-scale wind variability, potentially originating from large-scale structures named corotating interaction regions (CIRs). In this second paper, we discuss an additional 39 stars observable from the southern hemisphere. For each star in our sample, we obtained 4-5 high-resolution spectra with a signal-to-noise ratio of {approx}100 and determined its variability level usingmore » the approach described in Paper I. In total, 10 new stars are found to show large-scale spectral variability of which 7 present CIR-type changes (WR 8, WR 44, WR55, WR 58, WR 61, WR 63, WR 100). Of the remaining stars, 20 were found to show small-amplitude changes and 9 were found to show no spectral variability as far as can be concluded from the data on hand. Also, we discuss the spectroscopic variability level of all single galactic WR stars that are brighter than v {approx} 12.5, and some WR stars with 12.5 < v {<=} 13.5, i.e., all the stars presented in our two papers and four more stars for which spectra have already been published in the literature. We find that 23/68 stars (33.8%) present large-scale variability, but only 12/54 stars ({approx}22.1%) are potentially of CIR type. Also, we find that 31/68 stars (45.6%) only show small-scale variability, most likely due to clumping in the wind. Finally, no spectral variability is detected based on the data on hand for 14/68 (20.6%) stars. Interestingly, the variability with the highest amplitude also has the widest mean velocity dispersion.« less

Interpretation of tropospheric ozone variability in data with different vertical and temporal resolution

NASA Astrophysics Data System (ADS)

Petropavlovskikh, I. V.; Disterhoft, P.; Johnson, B. J.; Rieder, H. E.; Manney, G. L.; Daffer, W.

2012-12-01

This work attributes tropospheric ozone variability derived from the ground-based Dobson and Brewer Umkehr measurements and from ozone sonde data to local sources and transport. It assesses capability and limitations in both types of measurements that are often used to analyze long- and short-term variability in tropospheric ozone time series. We will address the natural and instrument-related contribution to the variability found in both Umkehr and sonde data. Validation of Umkehr methods is often done by intercomparisons against independent ozone measuring techniques such as ozone sounding. We will use ozone-sounding in its original and AK-smoothed vertical profiles for assessment of ozone inter-annual variability over Boulder, CO. We will discuss possible reasons for differences between different ozone measuring techniques and its effects on the derived ozone trends. Next to standard evaluation techniques we utilize a STL-decomposition method to address temporal variability and trends in the Boulder Umkehr data. Further, we apply a statistical modeling approach to the ozone data set to attribute ozone variability to individual driving forces associated with natural and anthropogenic causes. To this aim we follow earlier work applying a backward selection method (i.e., a stepwise elimination procedure out of a set of total 44 explanatory variables) to determine those explanatory variables which contribute most significantly to the observed variability. We will present also some results associated with completeness (sampling rate) of the existing data sets. We will also use MERRA (Modern-Era Retrospective analysis for Research and Applications) re-analysis results selected for Boulder location as a transfer function in understanding of the effects that the temporal sampling and vertical resolution bring into trend and ozone variability analysis. Analyzing intra-annual variability in ozone measurements over Boulder, CO, in relation to the upper tropospheric subtropical and polar jets, we will address the stratospheric and tropospheric intrusions in the middle latitude troposphere ozone field.

Biostatistics Series Module 10: Brief Overview of Multivariate Methods.

PubMed

Hazra, Avijit; Gogtay, Nithya

2017-01-01

Multivariate analysis refers to statistical techniques that simultaneously look at three or more variables in relation to the subjects under investigation with the aim of identifying or clarifying the relationships between them. These techniques have been broadly classified as dependence techniques, which explore the relationship between one or more dependent variables and their independent predictors, and interdependence techniques, that make no such distinction but treat all variables equally in a search for underlying relationships. Multiple linear regression models a situation where a single numerical dependent variable is to be predicted from multiple numerical independent variables. Logistic regression is used when the outcome variable is dichotomous in nature. The log-linear technique models count type of data and can be used to analyze cross-tabulations where more than two variables are included. Analysis of covariance is an extension of analysis of variance (ANOVA), in which an additional independent variable of interest, the covariate, is brought into the analysis. It tries to examine whether a difference persists after "controlling" for the effect of the covariate that can impact the numerical dependent variable of interest. Multivariate analysis of variance (MANOVA) is a multivariate extension of ANOVA used when multiple numerical dependent variables have to be incorporated in the analysis. Interdependence techniques are more commonly applied to psychometrics, social sciences and market research. Exploratory factor analysis and principal component analysis are related techniques that seek to extract from a larger number of metric variables, a smaller number of composite factors or components, which are linearly related to the original variables. Cluster analysis aims to identify, in a large number of cases, relatively homogeneous groups called clusters, without prior information about the groups. The calculation intensive nature of multivariate analysis has so far precluded most researchers from using these techniques routinely. The situation is now changing with wider availability, and increasing sophistication of statistical software and researchers should no longer shy away from exploring the applications of multivariate methods to real-life data sets.

Long-term variability in sugarcane bagasse feedstock compositional methods: Sources and magnitude of analytical variability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Templeton, David W.; Sluiter, Justin B.; Sluiter, Amie

In an effort to find economical, carbon-neutral transportation fuels, biomass feedstock compositional analysis methods are used to monitor, compare, and improve biofuel conversion processes. These methods are empirical, and the analytical variability seen in the feedstock compositional data propagates into variability in the conversion yields, component balances, mass balances, and ultimately the minimum ethanol selling price (MESP). We report the average composition and standard deviations of 119 individually extracted National Institute of Standards and Technology (NIST) bagasse [Reference Material (RM) 8491] run by seven analysts over 7 years. Two additional datasets, using bulk-extracted bagasse (containing 58 and 291 replicates each),more » were examined to separate out the effects of batch, analyst, sugar recovery standard calculation method, and extractions from the total analytical variability seen in the individually extracted dataset. We believe this is the world's largest NIST bagasse compositional analysis dataset and it provides unique insight into the long-term analytical variability. Understanding the long-term variability of the feedstock analysis will help determine the minimum difference that can be detected in yield, mass balance, and efficiency calculations. The long-term data show consistent bagasse component values through time and by different analysts. This suggests that the standard compositional analysis methods were performed consistently and that the bagasse RM itself remained unchanged during this time period. The long-term variability seen here is generally higher than short-term variabilities. It is worth noting that the effect of short-term or long-term feedstock compositional variability on MESP is small, about $0.03 per gallon. The long-term analysis variabilities reported here are plausible minimum values for these methods, though not necessarily average or expected variabilities. We must emphasize the importance of training and good analytical procedures needed to generate this data. As a result, when combined with a robust QA/QC oversight protocol, these empirical methods can be relied upon to generate high-quality data over a long period of time.« less

Relevance of anisotropy and spatial variability of gas diffusivity for soil-gas transport

NASA Astrophysics Data System (ADS)

Schack-Kirchner, Helmer; Kühne, Anke; Lang, Friederike

2017-04-01

Models of soil gas transport generally do not consider neither direction dependence of gas diffusivity, nor its small-scale variability. However, in a recent study, we could provide evidence for anisotropy favouring vertical gas diffusion in natural soils. We hypothesize that gas transport models based on gas diffusion data measured with soil rings are strongly influenced by both, anisotropy and spatial variability and the use of averaged diffusivities could be misleading. To test this we used a 2-dimensional model of soil gas transport to under compacted wheel tracks to model the soil-air oxygen distribution in the soil. The model was parametrized with data obtained from soil-ring measurements with its central tendency and variability. The model includes vertical parameter variability as well as variation perpendicular to the elongated wheel track. Different parametrization types have been tested: [i)]Averaged values for wheel track and undisturbed. em [ii)]Random distribution of soil cells with normally distributed variability within the strata. em [iii)]Random distributed soil cells with uniformly distributed variability within the strata. All three types of small-scale variability has been tested for [j)] isotropic gas diffusivity and em [jj)]reduced horizontal gas diffusivity (constant factor), yielding in total six models. As expected the different parametrizations had an important influence to the aeration state under wheel tracks with the strongest oxygen depletion in case of uniformly distributed variability and anisotropy towards higher vertical diffusivity. The simple simulation approach clearly showed the relevance of anisotropy and spatial variability in case of identical central tendency measures of gas diffusivity. However, until now it did not consider spatial dependency of variability, that could even aggravate effects. To consider anisotropy and spatial variability in gas transport models we recommend a) to measure soil-gas transport parameters spatially explicit including different directions and b) to use random-field stochastic models to assess the possible effects for gas-exchange models.

Factors related to achievement in sophomore organic chemistry at the University of Arkansas

NASA Astrophysics Data System (ADS)

Lindsay, Harriet Arlene

The purpose of this study was to identify the significant cognitive and non-cognitive variables that related to achievement in the first semester of organic chemistry at the University of Arkansas. Cognitive variables included second semester general chemistry grade, ACT composite score, ACT English, mathematics, reading, and science reasoning subscores, and spatial ability. Non-cognitive variables included anxiety, confidence, effectance motivation, and usefulness. Using a correlation research design, the individual relationships between organic chemistry achievement and each of the cognitive variables and non-cognitive variables were assessed. In addition, the relationships between organic chemistry achievement and combinations of these independent variables were explored. Finally, gender- and instructor-related differences in the relationships between organic chemistry achievement and the independent variables were investigated. The samples consisted of volunteers from the Fall 1999 and Fall 2000 sections of Organic Chemistry I at the University of Arkansas. All students in each section were asked to participate. Data for spatial ability and non-cognitive independent variables were collected using the Purdue Visualization of Rotations test and the modified Fennema-Sherman Attitude Scales. Data for other independent variables, including ACT scores and second semester general chemistry grades, were obtained from the Office of Institutional Research. The dependent variable, organic chemistry achievement, was measured by each student's accumulated points in the course and consisted of scores on quizzes and exams in the lecture section only. These totals were obtained from the lecture instructor at the end of each semester. Pearson correlation and stepwise multiple regression analyses were used to measure the relationships between organic chemistry achievement and the independent variables. Prior performance in chemistry as measured by second semester general chemistry grade was the best indicator of performance in organic chemistry. The importance of other independent variables in explaining organic chemistry achievement varied between instructors. In addition, gender differences were found in the explanations of organic chemistry achievement variance provided by this study. In general, males exhibited stronger correlations between independent variables and organic chemistry achievement than females. The report contains 19 tables detailing the statistical analyses. Suggestions for improved practice and further research are also included

An Optimization-Based Approach to Injector Element Design

NASA Technical Reports Server (NTRS)

Tucker, P. Kevin; Shyy, Wei; Vaidyanathan, Rajkumar; Turner, Jim (Technical Monitor)

2000-01-01

An injector optimization methodology, method i, is used to investigate optimal design points for gaseous oxygen/gaseous hydrogen (GO2/GH2) injector elements. A swirl coaxial element and an unlike impinging element (a fuel-oxidizer-fuel triplet) are used to facilitate the study. The elements are optimized in terms of design variables such as fuel pressure drop, APf, oxidizer pressure drop, deltaP(sub f), combustor length, L(sub comb), and full cone swirl angle, theta, (for the swirl element) or impingement half-angle, alpha, (for the impinging element) at a given mixture ratio and chamber pressure. Dependent variables such as energy release efficiency, ERE, wall heat flux, Q(sub w), injector heat flux, Q(sub inj), relative combustor weight, W(sub rel), and relative injector cost, C(sub rel), are calculated and then correlated with the design variables. An empirical design methodology is used to generate these responses for both element types. Method i is then used to generate response surfaces for each dependent variable for both types of elements. Desirability functions based on dependent variable constraints are created and used to facilitate development of composite response surfaces representing the five dependent variables in terms of the input variables. Three examples illustrating the utility and flexibility of method i are discussed in detail for each element type. First, joint response surfaces are constructed by sequentially adding dependent variables. Optimum designs are identified after addition of each variable and the effect each variable has on the element design is illustrated. This stepwise demonstration also highlights the importance of including variables such as weight and cost early in the design process. Secondly, using the composite response surface that includes all five dependent variables, unequal weights are assigned to emphasize certain variables relative to others. Here, method i is used to enable objective trade studies on design issues such as component life and thrust to weight ratio. Finally, combining results from both elements to simulate a trade study, thrust-to-weight trends are illustrated and examined in detail.

Image-Subtraction Photometry of Variable Stars in the Field of the Globular Cluster NGC 6934

NASA Astrophysics Data System (ADS)

Kaluzny, J.; Olech, A.; Stanek, K. Z.

2001-03-01

We present CCD BVI photometry of 85 variable stars from the field of the globular cluster NGC 6934. The photometry was obtained with the image subtraction package ISIS. 35 variables are new identifications: 24 RRab stars, five RRc stars, two eclipsing binaries of W UMa-type, one SX Phe star, and three variables of other types. Both detected contact binaries are foreground stars. The SX Phe variable belongs most likely to the group of cluster blue stragglers. Large number of newly found RR Lyr variables in this cluster, as well as in other clusters recently observed by us, indicates that total RR Lyr population identified up to date in nearby galactic globular clusters is significantly (>30%) incomplete. Fourier decomposition of the light curves of RR Lyr variables was used to estimate the basic properties of these stars. From the analysis of RRc variables we obtain a mean mass of M=0.63 Msolar, luminosity logL/Lsolar=1.72, effective temperature Teff=7300 and helium abundance Y=0.27. The mean values of the absolute magnitude, metallicity (on Zinn's scale) and effective temperature for RRab variables are MV=0.81, [Fe/H]=-1.53 and Teff=6450, respectively. From the B-V color at minimum light of the RRab variables we obtained the color excess to NGC 6934 equal to E(B-V)=0.09+/-0.01. Different calibrations of absolute magnitudes of RRab and RRc available in literature were used to estimate apparent distance modulus of the cluster: (m-M)V=16.09+/-0.06. We note a likely error in the zero point of the HST-based V-band photometry of NGC 6934 recently presented by Piotto et al. Among analyzed sample of RR Lyr stars we have detected a short period and low amplitude variable which possibly belongs to the group of second overtone pulsators (RRe subtype variables). The BVI photometry of all variables is available electronically via anonymous ftp. The complete set of the CCD frames is available upon request. Based on observations obtained with the 1.2 m Telescope at the F. L. Whipple Observatory of the Harvard-Smithsonian Center for Astrophysics.

Reassessing regime shifts in the North Pacific: incremental climate change and commercial fishing are necessary for explaining decadal-scale biological variability.

PubMed

Litzow, Michael A; Mueter, Franz J; Hobday, Alistair J

2014-01-01

In areas of the North Pacific that are largely free of overfishing, climate regime shifts - abrupt changes in modes of low-frequency climate variability - are seen as the dominant drivers of decadal-scale ecological variability. We assessed the ability of leading modes of climate variability [Pacific Decadal Oscillation (PDO), North Pacific Gyre Oscillation (NPGO), Arctic Oscillation (AO), Pacific-North American Pattern (PNA), North Pacific Index (NPI), El Niño-Southern Oscillation (ENSO)] to explain decadal-scale (1965-2008) patterns of climatic and biological variability across two North Pacific ecosystems (Gulf of Alaska and Bering Sea). Our response variables were the first principle component (PC1) of four regional climate parameters [sea surface temperature (SST), sea level pressure (SLP), freshwater input, ice cover], and PCs 1-2 of 36 biological time series [production or abundance for populations of salmon (Oncorhynchus spp.), groundfish, herring (Clupea pallasii), shrimp, and jellyfish]. We found that the climate modes alone could not explain ecological variability in the study region. Both linear models (for climate PC1) and generalized additive models (for biology PC1-2) invoking only the climate modes produced residuals with significant temporal trends, indicating that the models failed to capture coherent patterns of ecological variability. However, when the residual climate trend and a time series of commercial fishery catches were used as additional candidate variables, resulting models of biology PC1-2 satisfied assumptions of independent residuals and out-performed models constructed from the climate modes alone in terms of predictive power. As measured by effect size and Akaike weights, the residual climate trend was the most important variable for explaining biology PC1 variability, and commercial catch the most important variable for biology PC2. Patterns of climate sensitivity and exploitation history for taxa strongly associated with biology PC1-2 suggest plausible mechanistic explanations for these modeling results. Our findings suggest that, even in the absence of overfishing and in areas strongly influenced by internal climate variability, climate regime shift effects can only be understood in the context of other ecosystem perturbations. © 2013 John Wiley & Sons Ltd.

North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part II: Inter-annual to decadal variability

NASA Astrophysics Data System (ADS)

Danabasoglu, Gokhan; Yeager, Steve G.; Kim, Who M.; Behrens, Erik; Bentsen, Mats; Bi, Daohua; Biastoch, Arne; Bleck, Rainer; Böning, Claus; Bozec, Alexandra; Canuto, Vittorio M.; Cassou, Christophe; Chassignet, Eric; Coward, Andrew C.; Danilov, Sergey; Diansky, Nikolay; Drange, Helge; Farneti, Riccardo; Fernandez, Elodie; Fogli, Pier Giuseppe; Forget, Gael; Fujii, Yosuke; Griffies, Stephen M.; Gusev, Anatoly; Heimbach, Patrick; Howard, Armando; Ilicak, Mehmet; Jung, Thomas; Karspeck, Alicia R.; Kelley, Maxwell; Large, William G.; Leboissetier, Anthony; Lu, Jianhua; Madec, Gurvan; Marsland, Simon J.; Masina, Simona; Navarra, Antonio; Nurser, A. J. George; Pirani, Anna; Romanou, Anastasia; Salas y Mélia, David; Samuels, Bonita L.; Scheinert, Markus; Sidorenko, Dmitry; Sun, Shan; Treguier, Anne-Marie; Tsujino, Hiroyuki; Uotila, Petteri; Valcke, Sophie; Voldoire, Aurore; Wang, Qiang; Yashayaev, Igor

2016-01-01

Simulated inter-annual to decadal variability and trends in the North Atlantic for the 1958-2007 period from twenty global ocean - sea-ice coupled models are presented. These simulations are performed as contributions to the second phase of the Coordinated Ocean-ice Reference Experiments (CORE-II). The study is Part II of our companion paper (Danabasoglu et al., 2014) which documented the mean states in the North Atlantic from the same models. A major focus of the present study is the representation of Atlantic meridional overturning circulation (AMOC) variability in the participating models. Relationships between AMOC variability and those of some other related variables, such as subpolar mixed layer depths, the North Atlantic Oscillation (NAO), and the Labrador Sea upper-ocean hydrographic properties, are also investigated. In general, AMOC variability shows three distinct stages. During the first stage that lasts until the mid- to late-1970s, AMOC is relatively steady, remaining lower than its long-term (1958-2007) mean. Thereafter, AMOC intensifies with maximum transports achieved in the mid- to late-1990s. This enhancement is then followed by a weakening trend until the end of our integration period. This sequence of low frequency AMOC variability is consistent with previous studies. Regarding strengthening of AMOC between about the mid-1970s and the mid-1990s, our results support a previously identified variability mechanism where AMOC intensification is connected to increased deep water formation in the subpolar North Atlantic, driven by NAO-related surface fluxes. The simulations tend to show general agreement in their temporal representations of, for example, AMOC, sea surface temperature (SST), and subpolar mixed layer depth variabilities. In particular, the observed variability of the North Atlantic SSTs is captured well by all models. These findings indicate that simulated variability and trends are primarily dictated by the atmospheric datasets which include the influence of ocean dynamics from nature superimposed onto anthropogenic effects. Despite these general agreements, there are many differences among the model solutions, particularly in the spatial structures of variability patterns. For example, the location of the maximum AMOC variability differs among the models between Northern and Southern Hemispheres.

North Atlantic Simulations in Coordinated Ocean-Ice Reference Experiments Phase II (CORE-II) . Part II; Inter-Annual to Decadal Variability

NASA Technical Reports Server (NTRS)

Danabasoglu, Gokhan; Yeager, Steve G.; Kim, Who M.; Behrens, Erik; Bentsen, Mats; Bi, Daohua; Biastoch, Arne; Bleck, Rainer; Boening, Claus; Bozec, Alexandra;

Examining the infrared variable star population discovered in the Small Magellanic Cloud using the SAGE-SMC survey

DOE Office of Scientific and Technical Information (OSTI.GOV)

Polsdofer, Elizabeth; Marengo, M.; Seale, J.

2015-02-01

We present our study on the infrared variability of point sources in the Small Magellanic Cloud (SMC). We use the data from the Spitzer Space Telescope Legacy Program “Surveying the Agents of Galaxy Evolution in the Tidally Stripped, Low Metallicity Small Magellanic Cloud” (SAGE-SMC) and the “Spitzer Survey of the Small Magellanic Cloud” (S{sup 3}MC) survey, over three different epochs, separated by several months to 3 years. Variability in the thermal infrared is identified using a combination of Spitzer’s InfraRed Array Camera 3.6, 4.5, 5.8, and 8.0 μm bands, and the Multiband Imaging Photometer for Spitzer 24 μm band. Anmore » error-weighted flux difference between each pair of three epochs (“variability index”) is used to assess the variability of each source. A visual source inspection is used to validate the photometry and image quality. Out of ∼2 million sources in the SAGE-SMC catalog, 814 meet our variability criteria. We matched the list of variable star candidates to the catalogs of SMC sources classified with other methods, available in the literature. Carbon-rich Asymptotic Giant Branch (AGB) stars make up the majority (61%) of our variable sources, with about a third of all of our sources being classified as extreme AGB stars. We find a small, but significant population of oxygen-rich (O-rich) AGB (8.6%), Red Supergiant (2.8%), and Red Giant Branch (<1%) stars. Other matches to the literature include Cepheid variable stars (8.6%), early type stars (2.8%), Young-stellar objects (5.8%), and background galaxies (1.2%). We found a candidate OH maser star, SSTISAGE1C J005212.88-730852.8, which is a variable O-rich AGB star, and would be the first OH/IR star in the SMC, if confirmed. We measured the infrared variability of a rare RV Tau variable (a post-AGB star) that has recently left the AGB phase. 59 variable stars from our list remain unclassified.« less

Simultaneous Ultraviolet Line and Continuum Variability Studies in Seyfert 1 Galaxies and Quasars

NASA Astrophysics Data System (ADS)

Honnappa, Vijayakumar; Prabhakar, Vedavvathi

Simultaneous Ultraviolet Line and Continuum Variability Studies in Seyfert 1 Galaxies and Quasars Vijayakumar H. Doddamani*and P. Vedavathi Department of Physics, Bangalore University, Bangalore-560056, *Corresponding author:drvkdmani@gmail.com, Abstract The line and continuum flux variability is a hallmark phenomenon of Seyfert 1 galaxies and quasars. Large amplitude luminosity variability is observed in AGNs from x-rays through radio waves over a wide-ranging timescales from minutes to years. The combinations of high luminosity and short variability time scales suggests, that the power of AGN is produced by a phenomena more efficient in terms of energy release per unit mass than ordinary stellar processes. The basic structure of AGNs thus developed based on the variability studies consists of a central super massive black hole surrounded by an accretion disk or more generally optically thick plasma radiating brightly at UV and soft X-ray wavelengths. The variability studies have been important tools of understanding the physics of the central regions of AGNs, which in general cannot be resolved with the existing or planned ground and space telescopes. Therefore, we have undertaken a study of the simultaneous ultraviolet line and continuum flux variability studies in MRK501, ESOB113-IG45 (also called as Fairall 9), MRK1506, MRK1095 V*GQCOM, PG1211+143, MRK205, PG1226+023 (also known as 3C273), PG1351+640, MRK 1383, MRK876 and QSO2251-178 as these objects have been repeatedly observed by IUE satellite over several years.. It is observed that Fairall 9, MRK 1095 and 3C273 exhibit the large amplitude variability (» 30 times) over the observed timescale, which spans several years. The remaining nine objects exhibit small amplitude (» 5 times) variability over the long time scale of observations. The highest amplitude variability is observed in Lya with a least in the MgII line. The amplitude of variability decreases in the order of Lya, CIV and Mg II, lines. These results suggest that the BLR is spatially stratified into different regions from the central compact nuclear engine. Keywords: Active galaxies, Seyfert galaxies, Quasars, Line and continuum, Variability, Supermassive black hole

Effects of variable practice on the motor learning outcomes in manual wheelchair propulsion.

PubMed

Leving, Marika T; Vegter, Riemer J K; de Groot, Sonja; van der Woude, Lucas H V

2016-11-23

Handrim wheelchair propulsion is a cyclic skill that needs to be learned during rehabilitation. It has been suggested that more variability in propulsion technique benefits the motor learning process of wheelchair propulsion. The purpose of this study was to determine the influence of variable practice on the motor learning outcomes of wheelchair propulsion in able-bodied participants. Variable practice was introduced in the form of wheelchair basketball practice and wheelchair-skill practice. Motor learning was operationalized as improvements in mechanical efficiency and propulsion technique. Eleven Participants in the variable practice group and 12 participants in the control group performed an identical pre-test and a post-test. Pre- and post-test were performed in a wheelchair on a motor-driven treadmill (1.11 m/s) at a relative power output of 0.23 W/kg. Energy consumption and the propulsion technique variables with their respective coefficient of variation were calculated. Between the pre- and the post-test the variable practice group received 7 practice sessions. During the practice sessions participants performed one-hour of variable practice, consisting of five wheelchair-skill tasks and a 30 min wheelchair basketball game. The control group did not receive any practice between the pre- and the post-test. Comparison of the pre- and the post-test showed that the variable practice group significantly improved the mechanical efficiency (4.5 ± 0.6% → 5.7 ± 0.7%) in contrast to the control group (4.5 ± 0.6% → 4.4 ± 0.5%) (group x time interaction effect p < 0.001).With regard to propulsion technique, both groups significantly reduced the push frequency and increased the contact angle of the hand with the handrim (within group, time effect). No significant group × time interaction effects were found for propulsion technique. With regard to propulsion variability, the variable practice group increased variability when compared to the control group (interaction effect p < 0.001). Compared to a control, variable practice, resulted in an increase in mechanical efficiency and increased variability. Interestingly, the large relative improvement in mechanical efficiency was concomitant with only moderate improvements in the propulsion technique, which were similar in the control group, suggesting that other factors besides propulsion technique contributed to the lower energy expenditure.

Towards the Rational Design of a Candidate Vaccine against Pregnancy Associated Malaria: Conserved Sequences of the DBL6ε Domain of VAR2CSA

PubMed Central

Badaut, Cyril; Bertin, Gwladys; Rustico, Tatiana; Fievet, Nadine; Massougbodji, Achille; Gaye, Alioune; Deloron, Philippe

2010-01-01

Background Placental malaria is a disease linked to the sequestration of Plasmodium falciparum infected red blood cells (IRBC) in the placenta, leading to reduced materno-fetal exchanges and to local inflammation. One of the virulence factors of P. falciparum involved in cytoadherence to chondroitin sulfate A, its placental receptor, is the adhesive protein VAR2CSA. Its localisation on the surface of IRBC makes it accessible to the immune system. VAR2CSA contains six DBL domains. The DBL6ε domain is the most variable. High variability constitutes a means for the parasite to evade the host immune response. The DBL6ε domain could constitute a very attractive basis for a vaccine candidate but its reported variability necessitates, for antigenic characterisations, identifying and classifying commonalities across isolates. Methodology/Principal Findings Local alignment analysis of the DBL6ε domain had revealed that it is not as variable as previously described. Variability is concentrated in seven regions present on the surface of the DBL6ε domain. The main goal of our work is to classify and group variable sequences that will simplify further research to determine dominant epitopes. Firstly, variable sequences were grouped following their average percent pairwise identity (APPI). Groups comprising many variable sequences sharing low variability were found. Secondly, ELISA experiments following the IgG recognition of a recombinant DBL6ε domain, and of peptides mimicking its seven variable blocks, allowed to determine an APPI cut-off and to isolate groups represented by a single consensus sequence. Conclusions/Significance A new sequence approach is used to compare variable regions in sequences that have extensive segmental gene relationship. Using this approach, the VAR2CSA DBL6 domain is composed of 7 variable blocks with limited polymorphism. Each variable block is composed of a limited number of consensus types. Based on peptide based ELISA, variable blocks with 85% or greater sequence identity are expected to be recognized equally well by antibody and can be considered the same consensus type. Therefore, the analysis of the antibody response against the classified small number of sequences should be helpful to determine epitopes. PMID:20585655

Knee-Extension Torque Variability and Subjective Knee Function in Patients with a History of Anterior Cruciate Ligament Reconstruction.

PubMed

Goetschius, John; Hart, Joseph M

2016-01-01

When returning to physical activity, patients with a history of anterior cruciate ligament reconstruction (ACL-R) often experience limitations in knee-joint function that may be due to chronic impairments in quadriceps motor control. Assessment of knee-extension torque variability may demonstrate underlying impairments in quadriceps motor control in patients with a history of ACL-R. To identify differences in maximal isometric knee-extension torque variability between knees that have undergone ACL-R and healthy knees and to determine the relationship between knee-extension torque variability and self-reported knee function in patients with a history of ACL-R. Descriptive laboratory study. Laboratory. A total of 53 individuals with primary, unilateral ACL-R (age = 23.4 ± 4.9 years, height = 1.7 ± 0.1 m, mass = 74.6 ± 14.8 kg) and 50 individuals with no history of substantial lower extremity injury or surgery who served as controls (age = 23.3 ± 4.4 years, height = 1.7 ± 0.1 m, mass = 67.4 ± 13.2 kg). Torque variability, strength, and central activation ratio (CAR) were calculated from 3-second maximal knee-extension contraction trials (90° of flexion) with a superimposed electrical stimulus. All participants completed the International Knee Documentation Committee (IKDC) Subjective Knee Evaluation Form, and we determined the number of months after surgery. Group differences were assessed using independent-samples t tests. Correlation coefficients were calculated among torque variability, strength, CAR, months after surgery, and IKDC scores. Torque variability, strength, CAR, and months after surgery were regressed on IKDC scores using stepwise, multiple linear regression. Torque variability was greater and strength, CAR, and IKDC scores were lower in the ACL-R group than in the control group (P < .05). Torque variability and strength were correlated with IKDC scores (P < .05). Torque variability, strength, and CAR were correlated with each other (P < .05). Torque variability alone accounted for 14.3% of the variance in IKDC scores. The combination of torque variability and number of months after surgery accounted for 21% of the variance in IKDC scores. Strength and CAR were excluded from the regression model. Knee-extension torque variability was moderately associated with IKDC scores in patients with a history of ACL-R. Torque variability combined with months after surgery predicted 21% of the variance in IKDC scores in these patients.

Temporal Variability of Observed and Simulated Hyperspectral Earth Reflectance

NASA Technical Reports Server (NTRS)

Roberts, Yolanda; Pilewskie, Peter; Kindel, Bruce; Feldman, Daniel; Collins, William D.

2012-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system designed to study Earth's climate variability with unprecedented absolute radiometric accuracy and SI traceability. Observation System Simulation Experiments (OSSEs) were developed using GCM output and MODTRAN to simulate CLARREO reflectance measurements during the 21st century as a design tool for the CLARREO hyperspectral shortwave imager. With OSSE simulations of hyperspectral reflectance, Feldman et al. [2011a,b] found that shortwave reflectance is able to detect changes in climate variables during the 21st century and improve time-to-detection compared to broadband measurements. The OSSE has been a powerful tool in the design of the CLARREO imager and for understanding the effect of climate change on the spectral variability of reflectance, but it is important to evaluate how well the OSSE simulates the Earth's present-day spectral variability. For this evaluation we have used hyperspectral reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), a shortwave spectrometer that was operational between March 2002 and April 2012. To study the spectral variability of SCIAMACHY-measured and OSSE-simulated reflectance, we used principal component analysis (PCA), a spectral decomposition technique that identifies dominant modes of variability in a multivariate data set. Using quantitative comparisons of the OSSE and SCIAMACHY PCs, we have quantified how well the OSSE captures the spectral variability of Earth?s climate system at the beginning of the 21st century relative to SCIAMACHY measurements. These results showed that the OSSE and SCIAMACHY data sets share over 99% of their total variance in 2004. Using the PCs and the temporally distributed reflectance spectra projected onto the PCs (PC scores), we can study the temporal variability of the observed and simulated reflectance spectra. Multivariate time series analysis of the PC scores using techniques such as Singular Spectrum Analysis (SSA) and Multichannel SSA will provide information about the temporal variability of the dominant variables. Quantitative comparison techniques can evaluate how well the OSSE reproduces the temporal variability observed by SCIAMACHY spectral reflectance measurements during the first decade of the 21st century. PCA of OSSE-simulated reflectance can also be used to study how the dominant spectral variables change on centennial scales for forced and unforced climate change scenarios. To have confidence in OSSE predictions of the spectral variability of hyperspectral reflectance, it is first necessary for us to evaluate the degree to which the OSSE simulations are able to reproduce the Earth?s present-day spectral variability.

Validation of the Carotid Intima-Media Thickness Variability: Can Manual Segmentations Be Trusted as Ground Truth?

PubMed

Meiburger, Kristen M; Molinari, Filippo; Wong, Justin; Aguilar, Luis; Gallo, Diego; Steinman, David A; Morbiducci, Umberto

2016-07-01

The common carotid artery intima-media thickness (IMT) is widely accepted and used as an indicator of atherosclerosis. Recent studies, however, have found that the irregularity of the IMT along the carotid artery wall has a stronger correlation with atherosclerosis than the IMT itself. We set out to validate IMT variability (IMTV), a parameter defined to assess IMT irregularities along the wall. In particular, we analyzed whether or not manual segmentations of the lumen-intima and media-adventitia can be considered reliable in calculation of the IMTV parameter. To do this, we used a total of 60 simulated ultrasound images with a priori IMT and IMTV values. The images, simulated using the Fast And Mechanistic Ultrasound Simulation software, presented five different morphologies, four nominal IMT values and three different levels of variability along the carotid artery wall (no variability, small variability and large variability). Three experts traced the lumen-intima (LI) and media-adventitia (MA) profiles, and two automated algorithms were employed to obtain the LI and MA profiles. One expert also re-traced the LI and MA profiles to test intra-reader variability. The average IMTV measurements of the profiles used to simulate the longitudinal B-mode images were 0.002 ± 0.002, 0.149 ± 0.035 and 0.286 ± 0.068 mm for the cases of no variability, small variability and large variability, respectively. The IMTV measurements of one of the automated algorithms were statistically similar (p > 0.05, Wilcoxon signed rank) when considering small and large variability, but non-significant when considering no variability (p < 0.05, Wilcoxon signed rank). The second automated algorithm resulted in statistically similar values in the small variability case. Two readers' manual tracings, however, produced IMTV measurements with a statistically significant difference considering all three variability levels, whereas the third reader found a statistically significant difference in both the no variability and large variability cases. Moreover, the error range between the reader and automatic IMTV values was approximately 0.15 mm, which is on the same order of small IMTV values, indicating that manual and automatic IMTV readings should be not used interchangeably in clinical practice. On the basis of our findings, we conclude that expert manual tracings should not be considered reliable in IMTV measurement and, therefore, should not be trusted as ground truth. On the other hand, our automated algorithm was found to be more reliable, indicating how automated techniques could therefore foster analysis of the carotid artery intima-media thickness irregularity. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Factors associated with NO2 and NOX concentration gradients near a highway.

PubMed

Richmond-Bryant, J; Snyder, M G; Owen, R C; Kimbrough, S

2017-11-21

The objective of this research is to learn how the near-road gradient, in which NO 2 and NO X (NO + NO 2 ) concentrations are elevated, varies with changes in meteorological and traffic variables. Measurements of NO 2 and NO X were obtained east of I-15 in Las Vegas and fit to functions whose slopes (dC NO 2 /dx and dC NO X /dx, respectively) characterize the size of the near-road zone where NO 2 and NO X concentrations from mobile sources on the highway are elevated. These metrics were used to learn about the near-road gradient by modeling dC NO 2 /dx and dC NO X /dx as functions of meteorological variables (e.g., wind direction, wind speed), traffic (vehicle count), NO X concentration upwind of the road, and O 3 concentration at two fixed-site ambient monitors. Generalized additive models (GAM) were used to model dC NO 2 /dx and dC NO X /dx versus the independent variables because they allowed for nonlinearity of the variables being compared. When data from all wind directions were included in the analysis, variability in O 3 concentration comprised the largest proportion of variability in dC NO 2 /dx, followed by variability in wind direction. In a second analysis constrained to winds from the west, variability in O 3 concentration remained the largest contributor to variability in dC NO 2 /dx, but the relative contribution of variability in wind speed to variability in dC NO 2 /dx increased relative to its contribution for the all-wind analysis. When data from all wind directions were analyzed, variability in wind direction was by far the largest contributor to variability in dC NO X /dx, with smaller contributions from hour of day and upwind NO X concentration. When only winds from the west were analyzed, variability in upwind NO X concentration, wind speed, hour of day, and traffic count all were associated with variability in dC NO X /dx. Increases in O 3 concentration were associated with increased magnitude near-road dC NO 2 /dx, possibly shrinking the zone of elevated concentrations occurring near roads. Wind direction parallel to the highway was also related to an increased magnitude of both dC NO 2 /dx and dC NO X /dx, again likely shrinking the zone of elevated concentrations occurring near roads. Wind direction perpendicular to the road decreased the magnitude of dC NO 2 /dx and dC NO X /dx and likely contributed to growth of the zone of elevated concentrations occurring near roads. Thus, variability in near-road concentrations is influenced by local meteorology and ambient O 3 concentration.

Variability in Lotic Communities in Three Contrasting Stream Environments in the Santa Ana River Basin, California, 1999-2001

USGS Publications Warehouse

Burton, Carmen A.

2008-01-01

Biotic communities and environmental conditions can be highly variable between natural ecosystems. The variability of natural assemblages should be considered in the interpretation of any ecological study when samples are either spatially or temporally distributed. Little is known about biotic variability in the Santa Ana River Basin. In this report, the lotic community and habitat assessment data from ecological studies done as part of the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) program are used for a preliminary assessment of variability in the Santa Ana Basin. Habitat was assessed, and benthic algae, benthic macroinvertebrate, and fish samples were collected at four sites during 1999-2001. Three of these sites were sampled all three years. One of these sites is located in the San Bernardino Mountains, and the other two sites are located in the alluvial basin. Analysis of variance determined that the three sites with multiyear data were significantly different for 41 benthic algae metrics and 65 macroinvertebrate metrics and fish communities. Coefficients of variation (CVs) were calculated for the habitat measurements, metrics of benthic algae, and macroinvertebrate data as measures of variability. Annual variability of habitat data was generally greater at the mountain site than at the basin sites. The mountain site had higher CVs for water temperature, depth, velocity, canopy angle, streambed substrate, and most water-quality variables. In general, CVs of most benthic algae metrics calculated from the richest-targeted habitat (RTH) samples were greater at the mountain site. In contrast, CVs of most benthic algae metrics calculated from depositional-targeted habitat (DTH) samples were lower at the mountain site. In general, CVs of macroinvertebrate metrics calculated from qualitative multihabitat (QMH) samples were lower at the mountain site. In contrast, CVs of many metrics calculated from RTH samples were greater at the mountain site than at one of the basin sites. Fish communities were more variable at the basin sites because more species were present at these sites. Annual variability of benthic algae metrics was related to annual variability in habitat variables. The CVs of benthic algae metrics related to the most CVs of habitat variables included QMH taxon richness, the RTH percentage richness, RTH abundance of tolerant taxa, RTH percentage richness of halophilic diatoms, RTH percentage abundance of sestonic diatoms, DTH percentage richness of nitrogen heterotrophic diatoms, and DTH pollution tolerance index. The CVs of macroinvertebrate metrics related to the most CVs of habitat variables included the RTH trichoptera, RTH EPT, RTH scraper richness, RTH nonchironomid dipteran abundance (in percent), and RTH EPA (U.S. Environmental Protection Agency) tolerance, which is based on abundance. Many of the CVs of habitat variables related to CVs of macroinvertebrate metrics were the same habitat variables that were related to the CVs of benthic algae metrics. On the basis of these results, annual variability may have a role in the relationship of benthic algae and macroinvertebrates assemblages with habitat and water quality in the Santa Ana Basin. This report provides valuable baseline data on the variability of biological communities in the Santa Ana Basin.

A Progression in First-Grade Children's Thinking about Variable and Variable Notation in Functional Relationships

ERIC Educational Resources Information Center

Blanton, Maria; Brizuela, Bárbara M.; Gardiner, Angela Murphy; Sawrey, Katie; Newman-Owens, Ashley

2017-01-01

Recent research suggests that children in elementary grades have some facility with variable and variable notation in ways that warrant closer attention. We report here on an empirically developed progression in first-grade children's thinking about these concepts in functional relationships. Using learning trajectories research as a framework for…

Mutilating Data and Discarding Variance: The Dangers of Dichotomizing Continuous Variables.

ERIC Educational Resources Information Center

Kroff, Michael W.

This paper reviews issues involved in converting continuous variables to nominal variables to be used in the OVA techniques. The literature dealing with the dangers of dichotomizing continuous variables is reviewed. First, the assumptions invoked by OVA analyses are reviewed in addition to concerns regarding the loss of variance and a reduction in…

Genetic variability in krill.

PubMed

Valentine, J W; Ayala, F J

1976-02-01

We have estimated genetic variability by gel electrophoresis in three species of krill, genus Euphausia (Arthropoda: Crustacea). Genetic variability is low where trophic resources are most seasonal, and high where trophic resources are most stable. Simlar trends have been found in benthic marine invertebrates. The observed trends of genetic variability do not correlate with trends in the stability of physical environment parameters.

7 CFR 1735.33 - Variable interest rate loans.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 11 2010-01-01 2010-01-01 false Variable interest rate loans. 1735.33 Section 1735.33... § 1735.33 Variable interest rate loans. After June 10, 1991, and prior to November 1, 1993, RUS made certain variable rate loans at interest rates less than 5 percent but not less than 2 percent. For those...

The Variables of Composition: Process and Product in a Business Setting. Studies in Writing & Rhetoric Series.

ERIC Educational Resources Information Center

Broadhead, Glenn J.; Freed, Richard C.

Describing the variables of composition, offering researchers a methodology with which to investigate how the variables interact in specific writing strategies, and suggesting how teachers might make use of the variables of revision to help students learn successful writing strategies appropriate to a business setting, this book reports a research…

Exploring Relationships between Personal Variables, Programmatic Variables, and Self-Efficacy in School-Based Agricultural Education

ERIC Educational Resources Information Center

McKim, Aaron J.; Velez, Jonathan J.; Clement, Haley Q.

2017-01-01

The educational importance of teacher self-efficacy necessitates research into variables presumed to significantly influence teacher self-efficacy. In the current study, the role of personal and programmatic variables on the self-efficacy of school-based agriculture teachers was explored. Self-efficacy was measured in five aspects of the…

Short-term favorable weather conditions are an important control of interannual variability in carbon and water fluxes

Treesearch

Jakob Zscheischler; Simone Fatichi; Sebastian Wolf; Peter D. Blanken; Gil Bohrer; Ken Clark; Ankur R. Desai; David Hollinger; Trevor Keenan; Kimberly A. Novick; Sonia I. Seneviratne

2016-01-01

Ecosystem models often perform poorly in reproducing interannual variability in carbon and water fluxes, resulting in considerable uncertainty when estimating the land-carbon sink. While many aggregated variables (growing season length, seasonal precipitation, or temperature) have been suggested as predictors for interannual variability in carbon fluxes, their...

A Note on the Use of Missing Auxiliary Variables in Full Information Maximum Likelihood-Based Structural Equation Models

ERIC Educational Resources Information Center

Enders, Craig K.

2008-01-01

Recent missing data studies have argued in favor of an "inclusive analytic strategy" that incorporates auxiliary variables into the estimation routine, and Graham (2003) outlined methods for incorporating auxiliary variables into structural equation analyses. In practice, the auxiliary variables often have missing values, so it is reasonable to…

Identification of low and high frequency ranges for heart rate variability and blood pressure variability analyses using pharmacological autonomic blockade with atropine and propranolol in swine.

USDA-ARS?s Scientific Manuscript database

Understanding autonomic nervous system functioning, which mediates behavioral and physiological responses to stress, offers great potential for evaluation of farm animal stress and welfare. Evaluation of heart rate variability (HRV) and blood pressure variability (BPV), using time and frequency doma...

Variable range hopping in ZnO films

NASA Astrophysics Data System (ADS)

Ali, Nasir; Ghosh, Subhasis

2018-04-01

We report the variable range hopping in ZnO films grown by RF magnetron sputtering in different argon and oxygen partial pressure. It has been found that Mott variable range hopping dominant over Efros variable range hopping in all ZnO films. It also has been found that hopping distance and energy increases with increasing oxygen partial pressure.

Demographically Adjusted Groups for Equating Test Scores. Research Report. ETS RR-14-30

ERIC Educational Resources Information Center

Livingston, Samuel A.

2014-01-01

In this study, I investigated 2 procedures intended to create test-taker groups of equal ability by poststratifying on a composite variable created from demographic information. In one procedure, the stratifying variable was the composite variable that best predicted the test score. In the other procedure, the stratifying variable was the…

Using crown condition variables as indicators of forest health

Treesearch

Stanley J. Zarnoch; William A. Bechtold; K.W. Stolte

2004-01-01

Indicators of forest health used in previous studies have focused on crown variables analyzed individually at the tree level by summarizing over all species. This approach has the virtue of simplicity but does not account for the three-dimensional attributes of a tree crown, the multivariate nature of the crown variables, or variability among species. To alleviate...

Quantifying Forest Soil Physical Variables Potentially Important for Site Growth Analyses

Treesearch

John S. Kush; Douglas G. Pitt; Phillip J. Craul; William D. Boyer

2004-01-01

Accurate mean plot values of forest soil factors are required for use as independent variables in site-growth analyses. Adequate accuracy is often difficult to attain because soils are inherently widely variable. Estimates of the variability of appropriate soil factors influencing growth can be used to determine the sampling intensity required to secure accurate mean...

Variable stars in the Galactic center, as revealed by the VVV Survey

NASA Astrophysics Data System (ADS)

Molina, Claudio Navarro; Borissova, Jura; Catelan, Márcio; Kurtev, Radostin; Medina, Nicolás

2017-09-01

A variability search has been performed in the Galactic center, using the nearinfrared images from the Vista Variables in the Vía Láctea (VVV) Survey. Light curves contain 89 epochs in the KS band. A total of 353 variable stars were found, of which only 47 are already present in the literature.

Predictors of Performance in Introductory Finance: Variables within and beyond the Student's Control

ERIC Educational Resources Information Center

Englander, Fred; Wang, Zhaobo; Betz, Kenneth

2015-01-01

This study examined variables that are within and beyond the control of students in explaining variations in performance in an introductory finance course. Regression models were utilized to consider whether the variables within the student's control have a greater impact on course performance relative to the variables beyond the student's…

Causal Inference and Omitted Variable Bias in Financial Aid Research: Assessing Solutions

ERIC Educational Resources Information Center

Riegg, Stephanie K.

2008-01-01

This article highlights the problem of omitted variable bias in research on the causal effect of financial aid on college-going. I first describe the problem of self-selection and the resulting bias from omitted variables. I then assess and explore the strengths and weaknesses of random assignment, multivariate regression, proxy variables, fixed…

Unfinished Business in Clarifying Causal Measurement: Commentary on Bainter and Bollen

ERIC Educational Resources Information Center

Markus, Keith A.

2014-01-01

In a series of articles and comments, Kenneth Bollen and his collaborators have incrementally refined an account of structural equation models that (a) model a latent variable as the effect of several observed variables and (b) carry an interpretation of the observed variables as, in some sense, measures of the latent variable that they cause.…

In Pursuit of the Elusive Elixir: Predictors of First Grade Reading.

ERIC Educational Resources Information Center

Porter, Robin

Multivariate sets of predictor variables including both cognitive and social variables, different types of preschool experiences, and family environment variables were used to predict the first-grade reading achievement of 144 first-grade boys and girls. Measures for the predictor variables had been taken at school entry and at the end of the…

Intelligence, Creativity, and Language: An Examination of the Interrelationships of Three Variables among Preschool, Disadvantaged Negro Children.

ERIC Educational Resources Information Center

Lichtman, Marilyn Vickman

The interrelationships among the three variables of intelligence, creativity, and language in a preschool, disadvantaged Negro sample were investigated. The two main hypotheses tested were: (1) The interrelationships among the three variables are lower than the interrelationships within each variable; and (2) A factor analysis indicates a factor…

Increased Variability in Tacting under a Lag 3 Schedule of Reinforcement

ERIC Educational Resources Information Center

Heldt, Juliane; Schlinger, Henry D., Jr.

2012-01-01

Research has shown that variability may be an operant dimension of behavior. One method of reinforcing response variability is to use a lag schedule of reinforcement (Page & Neuringer, 1985). Several studies have shown that a Lag 1 schedule is effective in increasing variable responding with human participants (e.g., Esch, Esch, & Love, 2009; Lee,…

Children's Use of Variables and Variable Notation to Represent Their Algebraic Ideas

ERIC Educational Resources Information Center

Brizuela, Bárbara M.; Blanton, Maria; Sawrey, Katharine; Newman-Owens, Ashley; Murphy Gardiner, Angela

2015-01-01

In this article, we analyze a first grade classroom episode and individual interviews with students who participated in that classroom event to provide evidence of the variety of understandings about variable and variable notation held by first grade children approximately six years of age. Our findings illustrate that given the opportunity,…

Variable Neighborhood Search Heuristics for Selecting a Subset of Variables in Principal Component Analysis

ERIC Educational Resources Information Center

Brusco, Michael J.; Singh, Renu; Steinley, Douglas

2009-01-01

The selection of a subset of variables from a pool of candidates is an important problem in several areas of multivariate statistics. Within the context of principal component analysis (PCA), a number of authors have argued that subset selection is crucial for identifying those variables that are required for correct interpretation of the…

A Q-GERT Model for Determining the Maintenance Crew Size for the SAC command Post Upgrade

DTIC Science & Technology

1983-12-01

time that an equiprment fails. DAY3 A real variable corresponding to the day that an LRU is removed from the equipment. DAY4 A real variable...variable corresponding to the time that an LRU is repaired. TIM5 A real variable corresponaing to Lhe time that an equipment returns to service. TNOW...The current time . UF(IFN) User function IFN. UN(I) A sample from the uniform distri- bution defined by parameter set I. YIlN1 A real variable

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

NASA Technical Reports Server (NTRS)

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.

Violation of Bell's Inequality Using Continuous Variable Measurements

NASA Astrophysics Data System (ADS)

Thearle, Oliver; Janousek, Jiri; Armstrong, Seiji; Hosseini, Sara; Schünemann Mraz, Melanie; Assad, Syed; Symul, Thomas; James, Matthew R.; Huntington, Elanor; Ralph, Timothy C.; Lam, Ping Koy

2018-01-01

A Bell inequality is a fundamental test to rule out local hidden variable model descriptions of correlations between two physically separated systems. There have been a number of experiments in which a Bell inequality has been violated using discrete-variable systems. We demonstrate a violation of Bell's inequality using continuous variable quadrature measurements. By creating a four-mode entangled state with homodyne detection, we recorded a clear violation with a Bell value of B =2.31 ±0.02 . This opens new possibilities for using continuous variable states for device independent quantum protocols.

Gender interactions and success.

PubMed

Wiggins, Carla; Peterson, Teri

2004-01-01

Does gender by itself, or does gender's interaction with career variables, better explain the difference between women and men's careers in healthcare management? US healthcare managers were surveyed regarding career and personal experiences. Gender was statistically interacted with explanatory variables. Multiple regression with backwards selection systematically removed non-significant variables. All gender interaction variables were non-significant. Much of the literature proposes that work and career factors impact working women differently than working men. We find that while gender alone is a significant predictor of income, it does not significantly interact with other career variables.

VizieR Online Data Catalog: uvby photometry of 4 CP stars (Adelman, 1997)

NASA Astrophysics Data System (ADS)

Adelman, S. J.

1996-07-01

Differential Stroemgren uvby photometric observations from the Four College Automated Photoelectric Telescope refine the rotational periods and define the shapes of the light curves of four magnetic Chemically Peculiar stars. HD 32633 (P=6.43000d) exhibits an in-phase variability with asymmetrically shaped light curves. 25 Sex (P=4.37900d) has a complex variability with the v, b, and y light variability crudely in phase, but quite different from that of u. HR 7224 (P=1.123095d) shows in-phase variability with two nearly equal secondary minima. HD 200311 (P=26.0042d), which was previous thought to be a long period variable, is found to be a modest photometric variable. (5 data files).

Role of slack variables in quasi-Newton methods for constrained optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tapia, R.A.

In constrained optimization the technique of converting an inequality constraint into an equality constraint by the addition of a squared slack variable is well known but rarely used. In choosing an active constraint philosophy over the slack variable approach, researchers quickly justify their choice with the standard criticisms: the slack variable approach increases the dimension of the problem, is numerically unstable, and gives rise to singular systems. It is shown that these criticisms of the slack variable approach need not apply and the two seemingly distinct approaches are actually very closely related. In fact, the squared slack variable formulation canmore » be used to develop a superior and more comprehensive active constraint philosophy.« less

Near-infrared Variability in the 2MASS Calibration Fields: A Search for Planetary Transit Candidates

NASA Technical Reports Server (NTRS)

Plavchan, Peter; Jura, M.; Kirkpatrick, J. Davy; Cutri, Roc M.; Gallagher, S. C.

2008-01-01

The Two Micron All Sky Survey (2MASS) photometric calibration observations cover approximately 6 square degrees on the sky in 35 'calibration fields,' each sampled in nominal photometric conditions between 562 and 3692 times during the 4 years of the 2MASS mission. We compile a catalog of variables from the calibration observations to search for M dwarfs transited by extrasolar planets. We present our methods for measuring periodic and nonperiodic flux variability. From 7554 sources with apparent K(sub s) magnitudes between 5.6 and 16.1, we identify 247 variables, including extragalactic variables and 23 periodic variables. We have discovered three M dwarf eclipsing systems, including two candidates for transiting extrasolar planets.

Stability of uncertain impulsive complex-variable chaotic systems with time-varying delays.

PubMed

Zheng, Song

2015-09-01

In this paper, the robust exponential stabilization of uncertain impulsive complex-variable chaotic delayed systems is considered with parameters perturbation and delayed impulses. It is assumed that the considered complex-variable chaotic systems have bounded parametric uncertainties together with the state variables on the impulses related to the time-varying delays. Based on the theories of adaptive control and impulsive control, some less conservative and easily verified stability criteria are established for a class of complex-variable chaotic delayed systems with delayed impulses. Some numerical simulations are given to validate the effectiveness of the proposed criteria of impulsive stabilization for uncertain complex-variable chaotic delayed systems. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

ENSO modulation of tropical Indian Ocean subseasonal variability

NASA Astrophysics Data System (ADS)

Jung, Eunsil; Kirtman, Ben P.

2016-12-01

In this study, we use 30 years of retrospective climate model forecasts and observational estimates to show that El Niño/Southern Oscillation (ENSO) affects the amplitude of subseasonal variability of sea surface temperature (SST) in the southwest Indian Ocean, an important Tropical Intraseasonal Oscillation (TISO) onset region. The analysis shows that deeper background mixed-layer depths and warmer upper ocean conditions during El Niño reduce the amplitude of the subseasonal SST variability over Seychelles-Chagos Thermocline Ridge (SCTR), which may reduce SST-wind coupling and the amplitude of TISO variability. The opposite holds for La Niña where the shallower mixed-layer depth enhances SST variability over SCTR, which may increase SST-wind coupling and the amplitude of TISO variability.

Adaptive Variability in Skilled Human Movements

NASA Astrophysics Data System (ADS)

Kudo, Kazutoshi; Ohtsuki, Tatsuyuki

Human movements are produced in variable external/internal environments. Because of this variability, the same motor command can result in quite different movement patterns. Therefore, to produce skilled movements humans must coordinate the variability, not try to exclude it. In addition, because human movements are produced in redundant and complex systems, a combination of variability should be observed in different anatomical/physiological levels. In this paper, we introduce our research about human movement variability that shows remarkable coordination among components, and between organism and environment. We also introduce nonlinear dynamical models that can describe a variety of movements as a self-organization of a dynamical system, because the dynamical systems approach is a major candidate to understand the principle underlying organization of varying systems with huge degrees-of-freedom.

Hydrological and environmental variables outperform spatial factors in structuring species, trait composition, and beta diversity of pelagic algae.

PubMed

Wu, Naicheng; Qu, Yueming; Guse, Björn; Makarevičiūtė, Kristė; To, Szewing; Riis, Tenna; Fohrer, Nicola

2018-03-01

There has been increasing interest in algae-based bioassessment, particularly, trait-based approaches are increasingly suggested. However, the main drivers, especially the contribution of hydrological variables, of species composition, trait composition, and beta diversity of algae communities are less studied. To link species and trait composition to multiple factors (i.e., hydrological variables, local environmental variables, and spatial factors) that potentially control species occurrence/abundance and to determine their relative roles in shaping species composition, trait composition, and beta diversities of pelagic algae communities, samples were collected from a German lowland catchment, where a well-proven ecohydrological modeling enabled to predict long-term discharges at each sampling site. Both trait and species composition showed significant correlations with hydrological, environmental, and spatial variables, and variation partitioning revealed that the hydrological and local environmental variables outperformed spatial variables. A higher variation of trait composition (57.0%) than species composition (37.5%) could be explained by abiotic factors. Mantel tests showed that both species and trait-based beta diversities were mostly related to hydrological and environmental heterogeneity with hydrological contributing more than environmental variables, while purely spatial impact was less important. Our findings revealed the relative importance of hydrological variables in shaping pelagic algae community and their spatial patterns of beta diversities, emphasizing the need to include hydrological variables in long-term biomonitoring campaigns and biodiversity conservation or restoration. A key implication for biodiversity conservation was that maintaining the instream flow regime and keeping various habitats among rivers are of vital importance. However, further investigations at multispatial and temporal scales are greatly needed.

Design approaches to experimental mediation☆

PubMed Central

Pirlott, Angela G.; MacKinnon, David P.

2016-01-01

Identifying causal mechanisms has become a cornerstone of experimental social psychology, and editors in top social psychology journals champion the use of mediation methods, particularly innovative ones when possible (e.g. Halberstadt, 2010, Smith, 2012). Commonly, studies in experimental social psychology randomly assign participants to levels of the independent variable and measure the mediating and dependent variables, and the mediator is assumed to causally affect the dependent variable. However, participants are not randomly assigned to levels of the mediating variable(s), i.e., the relationship between the mediating and dependent variables is correlational. Although researchers likely know that correlational studies pose a risk of confounding, this problem seems forgotten when thinking about experimental designs randomly assigning participants to levels of the independent variable and measuring the mediator (i.e., “measurement-of-mediation” designs). Experimentally manipulating the mediator provides an approach to solving these problems, yet these methods contain their own set of challenges (e.g., Bullock, Green, & Ha, 2010). We describe types of experimental manipulations targeting the mediator (manipulations demonstrating a causal effect of the mediator on the dependent variable and manipulations targeting the strength of the causal effect of the mediator) and types of experimental designs (double randomization, concurrent double randomization, and parallel), provide published examples of the designs, and discuss the strengths and challenges of each design. Therefore, the goals of this paper include providing a practical guide to manipulation-of-mediator designs in light of their challenges and encouraging researchers to use more rigorous approaches to mediation because manipulation-of-mediator designs strengthen the ability to infer causality of the mediating variable on the dependent variable. PMID:27570259

Design approaches to experimental mediation.

PubMed

Pirlott, Angela G; MacKinnon, David P

2016-09-01

Identifying causal mechanisms has become a cornerstone of experimental social psychology, and editors in top social psychology journals champion the use of mediation methods, particularly innovative ones when possible (e.g. Halberstadt, 2010, Smith, 2012). Commonly, studies in experimental social psychology randomly assign participants to levels of the independent variable and measure the mediating and dependent variables, and the mediator is assumed to causally affect the dependent variable. However, participants are not randomly assigned to levels of the mediating variable(s), i.e., the relationship between the mediating and dependent variables is correlational. Although researchers likely know that correlational studies pose a risk of confounding, this problem seems forgotten when thinking about experimental designs randomly assigning participants to levels of the independent variable and measuring the mediator (i.e., "measurement-of-mediation" designs). Experimentally manipulating the mediator provides an approach to solving these problems, yet these methods contain their own set of challenges (e.g., Bullock, Green, & Ha, 2010). We describe types of experimental manipulations targeting the mediator (manipulations demonstrating a causal effect of the mediator on the dependent variable and manipulations targeting the strength of the causal effect of the mediator) and types of experimental designs (double randomization, concurrent double randomization, and parallel), provide published examples of the designs, and discuss the strengths and challenges of each design. Therefore, the goals of this paper include providing a practical guide to manipulation-of-mediator designs in light of their challenges and encouraging researchers to use more rigorous approaches to mediation because manipulation-of-mediator designs strengthen the ability to infer causality of the mediating variable on the dependent variable.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mitrani, J

Bayesian networks (BN) are an excellent tool for modeling uncertainties in systems with several interdependent variables. A BN is a directed acyclic graph, and consists of a structure, or the set of directional links between variables that depend on other variables, and conditional probabilities (CP) for each variable. In this project, we apply BN's to understand uncertainties in NIF ignition experiments. One can represent various physical properties of National Ignition Facility (NIF) capsule implosions as variables in a BN. A dataset containing simulations of NIF capsule implosions was provided. The dataset was generated from a radiation hydrodynamics code, and itmore » contained 120 simulations of 16 variables. Relevant knowledge about the physics of NIF capsule implosions and greedy search algorithms were used to search for hypothetical structures for a BN. Our preliminary results found 6 links between variables in the dataset. However, we thought there should have been more links between the dataset variables based on the physics of NIF capsule implosions. Important reasons for the paucity of links are the relatively small size of the dataset, and the sampling of the values for dataset variables. Another factor that might have caused the paucity of links is the fact that in the dataset, 20% of the simulations represented successful fusion, and 80% didn't, (simulations of unsuccessful fusion are useful for measuring certain diagnostics) which skewed the distributions of several variables, and possibly reduced the number of links. Nevertheless, by illustrating the interdependencies and conditional probabilities of several parameters and diagnostics, an accurate and complete BN built from an appropriate simulation set would provide uncertainty quantification for NIF capsule implosions.« less

Near-infrared Variability of Obscured and Unobscured X-Ray-selected AGNs in the COSMOS Field

NASA Astrophysics Data System (ADS)

Sánchez, P.; Lira, P.; Cartier, R.; Pérez, V.; Miranda, N.; Yovaniniz, C.; Arévalo, P.; Milvang-Jensen, B.; Fynbo, J.; Dunlop, J.; Coppi, P.; Marchesi, S.

2017-11-01

We present our statistical study of near-infrared (NIR) variability of X-ray-selected active galactic nuclei (AGNs) in the COSMOS field, using UltraVISTA data. This is the largest sample of AGN light curves in YJHKs bands, making it possible to have a global description of the nature of AGNs for a large range of redshifts and for different levels of obscuration. To characterize the variability properties of the sources, we computed the structure function. Our results show that there is an anticorrelation between the structure function A parameter (variability amplitude) and the wavelength of emission and a weak anticorrelation between A and the bolometric luminosity. We find that broad-line (BL) AGNs have a considerably larger fraction of variable sources than narrow-line (NL) AGNs and that they have different distributions of the A parameter. We find evidence that suggests that most of the low-luminosity variable NL sources correspond to BL AGNs, where the host galaxy could be damping the variability signal. For high-luminosity variable NL sources, we propose that they can be examples of “true type II” AGNs or BL AGNs with limited spectral coverage, which results in missing the BL emission. We also find that the fraction of variable sources classified as unobscured in the X-ray is smaller than the fraction of variable sources unobscured in the optical range. We present evidence that this is related to the differences in the origin of the obscuration in the optical and X-ray regimes.

Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes

PubMed Central

Ghosh, Subimal; Vittal, H.; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K. S.; Dhanesh, Y.; Sudheer, K. P.; Gunthe, S. S.

2016-01-01

India’s agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins. PMID:27463092

Variability of pesticide detections and concentrations in field replicate water samples collected for the National Water-Quality Assessment Program, 1992-97

USGS Publications Warehouse

Martin, Jeffrey D.

2002-01-01

Correlation analysis indicates that for most pesticides and concentrations, pooled estimates of relative standard deviation rather than pooled estimates of standard deviation should be used to estimate variability because pooled estimates of relative standard deviation are less affected by heteroscedasticity. The 2 Variability of Pesticide Detections and Concentrations in Field Replicate Water Samples, 1992–97 median pooled relative standard deviation was calculated for all pesticides to summarize the typical variability for pesticide data collected for the NAWQA Program. The median pooled relative standard deviation was 15 percent at concentrations less than 0.01 micrograms per liter (µg/L), 13 percent at concentrations near 0.01 µg/L, 12 percent at concentrations near 0.1 µg/L, 7.9 percent at concentrations near 1 µg/L, and 2.7 percent at concentrations greater than 5 µg/L. Pooled estimates of standard deviation or relative standard deviation presented in this report are larger than estimates based on averages, medians, smooths, or regression of the individual measurements of standard deviation or relative standard deviation from field replicates. Pooled estimates, however, are the preferred method for characterizing variability because they provide unbiased estimates of the variability of the population. Assessments of variability based on standard deviation (rather than variance) underestimate the true variability of the population. Because pooled estimates of variability are larger than estimates based on other approaches, users of estimates of variability must be cognizant of the approach used to obtain the estimate and must use caution in the comparison of estimates based on different approaches.