Iterative Strain-Gage Balance Calibration Data Analysis for Extended Independent Variable Sets

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred

2011-01-01

A new method was developed that makes it possible to use an extended set of independent calibration variables for an iterative analysis of wind tunnel strain gage balance calibration data. The new method permits the application of the iterative analysis method whenever the total number of balance loads and other independent calibration variables is greater than the total number of measured strain gage outputs. Iteration equations used by the iterative analysis method have the limitation that the number of independent and dependent variables must match. The new method circumvents this limitation. It simply adds a missing dependent variable to the original data set by using an additional independent variable also as an additional dependent variable. Then, the desired solution of the regression analysis problem can be obtained that fits each gage output as a function of both the original and additional independent calibration variables. The final regression coefficients can be converted to data reduction matrix coefficients because the missing dependent variables were added to the data set without changing the regression analysis result for each gage output. Therefore, the new method still supports the application of the two load iteration equation choices that the iterative method traditionally uses for the prediction of balance loads during a wind tunnel test. An example is discussed in the paper that illustrates the application of the new method to a realistic simulation of temperature dependent calibration data set of a six component balance.

Analysis of the labor productivity of enterprises via quantile regression

NASA Astrophysics Data System (ADS)

Türkan, Semra

2017-07-01

In this study, we have analyzed the factors that affect the performance of Turkey's Top 500 Industrial Enterprises using quantile regression. The variable about labor productivity of enterprises is considered as dependent variable, the variableabout assets is considered as independent variable. The distribution of labor productivity of enterprises is right-skewed. If the dependent distribution is skewed, linear regression could not catch important aspects of the relationships between the dependent variable and its predictors due to modeling only the conditional mean. Hence, the quantile regression, which allows modelingany quantilesof the dependent distribution, including the median,appears to be useful. It examines whether relationships between dependent and independent variables are different for low, medium, and high percentiles. As a result of analyzing data, the effect of total assets is relatively constant over the entire distribution, except the upper tail. It hasa moderately stronger effect in the upper tail.

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.

The relationship between species richness and ecosystem variability is shaped by the mechanism of coexistence.

PubMed

Tredennick, Andrew T; Adler, Peter B; Adler, Frederick R

2017-08-01

Theory relating species richness to ecosystem variability typically ignores the potential for environmental variability to promote species coexistence. Failure to account for fluctuation-dependent coexistence may explain deviations from the expected negative diversity-ecosystem variability relationship, and limits our ability to predict the consequences of increases in environmental variability. We use a consumer-resource model to explore how coexistence via the temporal storage effect and relative nonlinearity affects ecosystem variability. We show that a positive, rather than negative, diversity-ecosystem variability relationship is possible when ecosystem function is sampled across a natural gradient in environmental variability and diversity. We also show how fluctuation-dependent coexistence can buffer ecosystem functioning against increasing environmental variability by promoting species richness and portfolio effects. Our work provides a general explanation for variation in observed diversity-ecosystem variability relationships and highlights the importance of conserving regional species pools to help buffer ecosystems against predicted increases in environmental variability. © 2017 John Wiley & Sons Ltd/CNRS.

Patterns in the species-environment relationship depend on both scale and choice of response variables

Treesearch

Samuel A. Cushman; Kevin McGarigal

2004-01-01

Multi-scale investigations of species/environment relationships are an important tool in ecological research. The scale at which independent and dependent variables are measured, and how they are coded for analysis, can strongly influence the relationships that are discovered. However, little is known about how the coding of the dependent variable set influences...

Censored Hurdle Negative Binomial Regression (Case Study: Neonatorum Tetanus Case in Indonesia)

NASA Astrophysics Data System (ADS)

Yuli Rusdiana, Riza; Zain, Ismaini; Wulan Purnami, Santi

2017-06-01

Hurdle negative binomial model regression is a method that can be used for discreate dependent variable, excess zero and under- and overdispersion. It uses two parts approach. The first part estimates zero elements from dependent variable is zero hurdle model and the second part estimates not zero elements (non-negative integer) from dependent variable is called truncated negative binomial models. The discrete dependent variable in such cases is censored for some values. The type of censor that will be studied in this research is right censored. This study aims to obtain the parameter estimator hurdle negative binomial regression for right censored dependent variable. In the assessment of parameter estimation methods used Maximum Likelihood Estimator (MLE). Hurdle negative binomial model regression for right censored dependent variable is applied on the number of neonatorum tetanus cases in Indonesia. The type data is count data which contains zero values in some observations and other variety value. This study also aims to obtain the parameter estimator and test statistic censored hurdle negative binomial model. Based on the regression results, the factors that influence neonatorum tetanus case in Indonesia is the percentage of baby health care coverage and neonatal visits.

A Computer Program for Preliminary Data Analysis

Treesearch

Dennis L. Schweitzer

1967-01-01

ABSTRACT. -- A computer program written in FORTRAN has been designed to summarize data. Class frequencies, means, and standard deviations are printed for as many as 100 independent variables. Cross-classifications of an observed dependent variable and of a dependent variable predicted by a multiple regression equation can also be generated.

Modified Regression Correlation Coefficient for Poisson Regression Model

NASA Astrophysics Data System (ADS)

Kaengthong, Nattacha; Domthong, Uthumporn

2017-09-01

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

The turbulent mean-flow, Reynolds-stress, and heat flux equations in mass-averaged dependent variables

NASA Technical Reports Server (NTRS)

Rubesin, M. W.; Rose, W. C.

1973-01-01

The time-dependent, turbulent mean-flow, Reynolds stress, and heat flux equations in mass-averaged dependent variables are presented. These equations are given in conservative form for both generalized orthogonal and axisymmetric coordinates. For the case of small viscosity and thermal conductivity fluctuations, these equations are considerably simpler than the general Reynolds system of dependent variables for a compressible fluid and permit a more direct extension of low speed turbulence modeling to computer codes describing high speed turbulence fields.

The nature and use of prediction skills in a biological computer simulation

NASA Astrophysics Data System (ADS)

Lavoie, Derrick R.; Good, Ron

The primary goal of this study was to examine the science process skill of prediction using qualitative research methodology. The think-aloud interview, modeled after Ericsson and Simon (1984), let to the identification of 63 program exploration and prediction behaviors.The performance of seven formal and seven concrete operational high-school biology students were videotaped during a three-phase learning sequence on water pollution. Subjects explored the effects of five independent variables on two dependent variables over time using a computer-simulation program. Predictions were made concerning the effect of the independent variables upon dependent variables through time. Subjects were identified according to initial knowledge of the subject matter and success at solving three selected prediction problems.Successful predictors generally had high initial knowledge of the subject matter and were formal operational. Unsuccessful predictors generally had low initial knowledge and were concrete operational. High initial knowledge seemed to be more important to predictive success than stage of Piagetian cognitive development.Successful prediction behaviors involved systematic manipulation of the independent variables, note taking, identification and use of appropriate independent-dependent variable relationships, high interest and motivation, and in general, higher-level thinking skills. Behaviors characteristic of unsuccessful predictors were nonsystematic manipulation of independent variables, lack of motivation and persistence, misconceptions, and the identification and use of inappropriate independent-dependent variable relationships.

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…

A Primer on Logistic Regression.

ERIC Educational Resources Information Center

Woldbeck, Tanya

This paper introduces logistic regression as a viable alternative when the researcher is faced with variables that are not continuous. If one is to use simple regression, the dependent variable must be measured on a continuous scale. In the behavioral sciences, it may not always be appropriate or possible to have a measured dependent variable on a…

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

Comparing Public and Private Institutions That Have and Have Not Implemented Enterprise Resource Planning (ERP) Systems: A Resource Dependence Perspective

ERIC Educational Resources Information Center

Sendhil, Geetha R.

2012-01-01

The purpose of this national study was to utilize quantitative methods to examine institutional characteristics, financial resource variables, personnel variables, and customer variables of public and private institutions that have and have not implemented enterprise resource planning (ERP) systems, from a resource dependence perspective.…

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

A computer graphics display and data compression technique

NASA Technical Reports Server (NTRS)

Teague, M. J.; Meyer, H. G.; Levenson, L. (Editor)

1974-01-01

The computer program discussed is intended for the graphical presentation of a general dependent variable X that is a function of two independent variables, U and V. The required input to the program is the variation of the dependent variable with one of the independent variables for various fixed values of the other. The computer program is named CRP, and the output is provided by the SD 4060 plotter. Program CRP is an extremely flexible program that offers the user a wide variety of options. The dependent variable may be presented in either a linear or a logarithmic manner. Automatic centering of the plot is provided in the ordinate direction, and the abscissa is scaled automatically for a logarithmic plot. A description of the carpet plot technique is given along with the coordinates system used in the program. Various aspects of the program logic are discussed and detailed documentation of the data card format is presented.

A hazard rate analysis of fertility using duration data from Malaysia.

PubMed

Chang, C

1988-01-01

Data from the Malaysia Fertility and Family Planning Survey (MFLS) of 1974 were used to investigate the effects of biological and socioeconomic variables on fertility based on the hazard rate model. Another study objective was to investigate the robustness of the findings of Trussell et al. (1985) by comparing the findings of this study with theirs. The hazard rate of conception for the jth fecundable spell of the ith woman, hij, is determined by duration dependence, tij, measured by the waiting time to conception; unmeasured heterogeneity (HETi; the time-invariant variables, Yi (race, cohort, education, age at marriage); and time-varying variables, Xij (age, parity, opportunity cost, income, child mortality, child sex composition). In this study, all the time-varying variables were constant over a spell. An asymptotic X2 test for the equality of constant hazard rates across birth orders, allowing time-invariant variables and heterogeneity, showed the importance of time-varying variables and duration dependence. Under the assumption of fixed effects heterogeneity and the Weibull distribution for the duration of waiting time to conception, the empirical results revealed a negative parity effect, a negative impact from male children, and a positive effect from child mortality on the hazard rate of conception. The estimates of step functions for the hazard rate of conception showed parity-dependent fertility control, evidence of heterogeneity, and the possibility of nonmonotonic duration dependence. In a hazard rate model with piecewise-linear-segment duration dependence, the socioeconomic variables such as cohort, child mortality, income, and race had significant effects, after controlling for the length of the preceding birth. The duration dependence was consistant with the common finding, i.e., first increasing and then decreasing at a slow rate. The effects of education and opportunity cost on fertility were insignificant.

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.

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

Multivariate dynamic Tobit models with lagged observed dependent variables: An effectiveness analysis of highway safety laws.

PubMed

Dong, Chunjiao; Xie, Kun; Zeng, Jin; Li, Xia

2018-04-01

Highway safety laws aim to influence driver behaviors so as to reduce the frequency and severity of crashes, and their outcomes. For one specific highway safety law, it would have different effects on the crashes across severities. Understanding such effects can help policy makers upgrade current laws and hence improve traffic safety. To investigate the effects of highway safety laws on crashes across severities, multivariate models are needed to account for the interdependency issues in crash counts across severities. Based on the characteristics of the dependent variables, multivariate dynamic Tobit (MVDT) models are proposed to analyze crash counts that are aggregated at the state level. Lagged observed dependent variables are incorporated into the MVDT models to account for potential temporal correlation issues in crash data. The state highway safety law related factors are used as the explanatory variables and socio-demographic and traffic factors are used as the control variables. Three models, a MVDT model with lagged observed dependent variables, a MVDT model with unobserved random variables, and a multivariate static Tobit (MVST) model are developed and compared. The results show that among the investigated models, the MVDT models with lagged observed dependent variables have the best goodness-of-fit. The findings indicate that, compared to the MVST, the MVDT models have better explanatory power and prediction accuracy. The MVDT model with lagged observed variables can better handle the stochasticity and dependency in the temporal evolution of the crash counts and the estimated values from the model are closer to the observed values. The results show that more lives could be saved if law enforcement agencies can make a sustained effort to educate the public about the importance of motorcyclists wearing helmets. Motor vehicle crash-related deaths, injuries, and property damages could be reduced if states enact laws for stricter text messaging rules, higher speeding fines, older licensing age, and stronger graduated licensing provisions. Injury and PDO crashes would be significantly reduced with stricter laws prohibiting the use of hand-held communication devices and higher fines for drunk driving. Copyright © 2018 Elsevier Ltd. All rights reserved.

The MASIV Survey - IV. Relationship between intra-day scintillation and intrinsic variability of radio AGNs

NASA Astrophysics Data System (ADS)

Koay, J. Y.; Macquart, J.-P.; Jauncey, D. L.; Pursimo, T.; Giroletti, M.; Bignall, H. E.; Lovell, J. E. J.; Rickett, B. J.; Kedziora-Chudczer, L.; Ojha, R.; Reynolds, C.

2018-03-01

We investigate the relationship between 5 GHz interstellar scintillation (ISS) and 15 GHz intrinsic variability of compact, radio-selected active galactic nuclei (AGNs) drawn from the Microarcsecond Scintillation-Induced Variability (MASIV) Survey and the Owens Valley Radio Observatory blazar monitoring program. We discover that the strongest scintillators at 5 GHz (modulation index, m5 ≥ 0.02) all exhibit strong 15 GHz intrinsic variability (m15 ≥ 0.1). This relationship can be attributed mainly to the mutual dependence of intrinsic variability and ISS amplitudes on radio core compactness at ˜ 100 μas scales, and to a lesser extent, on their mutual dependences on source flux density, arcsec-scale core dominance and redshift. However, not all sources displaying strong intrinsic variations show high amplitude scintillation, since ISS is also strongly dependent on Galactic line-of-sight scattering properties. This observed relationship between intrinsic variability and ISS highlights the importance of optimizing the observing frequency, cadence, timespan and sky coverage of future radio variability surveys, such that these two effects can be better distinguished to study the underlying physics. For the full MASIV sample, we find that Fermi-detected gamma-ray loud sources exhibit significantly higher 5 GHz ISS amplitudes than gamma-ray quiet sources. This relationship is weaker than the known correlation between gamma-ray loudness and the 15 GHz variability amplitudes, most likely due to jet opacity effects.

Choice of Variables and Preconditioning for Time Dependent Problems

NASA Technical Reports Server (NTRS)

Turkel, Eli; Vatsa, Verr N.

2003-01-01

We consider the use of low speed preconditioning for time dependent problems. These are solved using a dual time step approach. We consider the effect of this dual time step on the parameter of the low speed preconditioning. In addition, we compare the use of two sets of variables, conservation and primitive variables, to solve the system. We show the effect of these choices on both the convergence to a steady state and the accuracy of the numerical solutions for low Mach number steady state and time dependent flows.

Density dependence in demography and dispersal generates fluctuating invasion speeds

PubMed Central

Li, Bingtuan; Miller, Tom E. X.

2017-01-01

Density dependence plays an important role in population regulation and is known to generate temporal fluctuations in population density. However, the ways in which density dependence affects spatial population processes, such as species invasions, are less understood. Although classical ecological theory suggests that invasions should advance at a constant speed, empirical work is illuminating the highly variable nature of biological invasions, which often exhibit nonconstant spreading speeds, even in simple, controlled settings. Here, we explore endogenous density dependence as a mechanism for inducing variability in biological invasions with a set of population models that incorporate density dependence in demographic and dispersal parameters. We show that density dependence in demography at low population densities—i.e., an Allee effect—combined with spatiotemporal variability in population density behind the invasion front can produce fluctuations in spreading speed. The density fluctuations behind the front can arise from either overcompensatory population growth or density-dependent dispersal, both of which are common in nature. Our results show that simple rules can generate complex spread dynamics and highlight a source of variability in biological invasions that may aid in ecological forecasting. PMID:28442569

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.…

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,…

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.

Emergence of context-dependent variability across a basal ganglia network.

PubMed

Woolley, Sarah C; Rajan, Raghav; Joshua, Mati; Doupe, Allison J

2014-04-02

Context dependence is a key feature of cortical-basal ganglia circuit activity, and in songbirds the cortical outflow of a basal ganglia circuit specialized for song, LMAN, shows striking increases in trial-by-trial variability and bursting when birds sing alone rather than to females. To reveal where this variability and its social regulation emerge, we recorded stepwise from corticostriatal (HVC) neurons and their target spiny and pallidal neurons in Area X. We find that corticostriatal and spiny neurons both show precise singing-related firing across both social settings. Pallidal neurons, in contrast, exhibit markedly increased trial-by-trial variation when birds sing alone, created by highly variable pauses in firing. This variability persists even when recurrent inputs from LMAN are ablated. These data indicate that variability and its context sensitivity emerge within the basal ganglia network, suggest a network mechanism for this emergence, and highlight variability generation and regulation as basal ganglia functions. Copyright © 2014 Elsevier Inc. All rights reserved.

Emergence of context-dependent variability across a basal ganglia network

PubMed Central

Woolley, Sarah C.; Rajan, Raghav; Joshua, Mati; Doupe, Allison J.

2014-01-01

Summary Context-dependence is a key feature of cortical-basal ganglia circuit activity, and in songbirds, the cortical outflow of a basal ganglia circuit specialized for song, LMAN, shows striking increases in trial-by-trial variability and bursting when birds sing alone rather than to females. To reveal where this variability and its social regulation emerge, we recorded stepwise from cortico-striatal (HVC) neurons and their target spiny and pallidal neurons in Area X. We find that cortico-striatal and spiny neurons both show precise singing-related firing across both social settings. Pallidal neurons, in contrast, exhibit markedly increased trial-by-trial variation when birds sing alone, created by highly variable pauses in firing. This variability persists even when recurrent inputs from LMAN are ablated. These data indicate that variability and its context-sensitivity emerge within the basal ganglia network, suggest a network mechanism for this emergence, and highlight variability generation and regulation as basal ganglia functions. PMID:24698276

Variables affecting the academic and social integration of nursing students.

PubMed

Zeitlin-Ophir, Iris; Melitz, Osnat; Miller, Rina; Podoshin, Pia; Mesh, Gustavo

2004-07-01

This study attempted to analyze the variables that influence the academic integration of nursing students. The theoretical model presented by Leigler was adapted to the existing conditions in a school of nursing in northern Israel. The independent variables included the student's background; amount of support received in the course of studies; extent of outside family and social commitments; satisfaction with the school's facilities and services; and level of social integration. The dependent variable was the student's level of academic integration. The findings substantiated four central hypotheses, with the study model explaining approximately 45% of the variance in the dependent variable. Academic integration is influenced by a number of variables, the most prominent of which is the social integration of the student with colleagues and educational staff. Among the background variables, country of origin was found to be significant to both social and academic integration for two main groups in the sample: Israeli-born students (both Jewish and Arab) and immigrant students.

Determination of riverbank erosion probability using Locally Weighted Logistic Regression

NASA Astrophysics Data System (ADS)

Ioannidou, Elena; Flori, Aikaterini; Varouchakis, Emmanouil A.; Giannakis, Georgios; Vozinaki, Anthi Eirini K.; Karatzas, George P.; Nikolaidis, Nikolaos

2015-04-01

Riverbank erosion is a natural geomorphologic process that affects the fluvial environment. The most important issue concerning riverbank erosion is the identification of the vulnerable locations. An alternative to the usual hydrodynamic models to predict vulnerable locations is to quantify the probability of erosion occurrence. This can be achieved by identifying the underlying relations between riverbank erosion and the geomorphological or hydrological variables that prevent or stimulate erosion. Thus, riverbank erosion can be determined by a regression model using independent variables that are considered to affect the erosion process. The impact of such variables may vary spatially, therefore, a non-stationary regression model is preferred instead of a stationary equivalent. Locally Weighted Regression (LWR) is proposed as a suitable choice. This method can be extended to predict the binary presence or absence of erosion based on a series of independent local variables by using the logistic regression model. It is referred to as Locally Weighted Logistic Regression (LWLR). Logistic regression is a type of regression analysis used for predicting the outcome of a categorical dependent variable (e.g. binary response) based on one or more predictor variables. The method can be combined with LWR to assign weights to local independent variables of the dependent one. LWR allows model parameters to vary over space in order to reflect spatial heterogeneity. The probabilities of the possible outcomes are modelled as a function of the independent variables using a logistic function. Logistic regression measures the relationship between a categorical dependent variable and, usually, one or several continuous independent variables by converting the dependent variable to probability scores. Then, a logistic regression is formed, which predicts success or failure of a given binary variable (e.g. erosion presence or absence) for any value of the independent variables. The erosion occurrence probability can be calculated in conjunction with the model deviance regarding the independent variables tested. The most straightforward measure for goodness of fit is the G statistic. It is a simple and effective way to study and evaluate the Logistic Regression model efficiency and the reliability of each independent variable. The developed statistical model is applied to the Koiliaris River Basin on the island of Crete, Greece. Two datasets of river bank slope, river cross-section width and indications of erosion were available for the analysis (12 and 8 locations). Two different types of spatial dependence functions, exponential and tricubic, were examined to determine the local spatial dependence of the independent variables at the measurement locations. The results show a significant improvement when the tricubic function is applied as the erosion probability is accurately predicted at all eight validation locations. Results for the model deviance show that cross-section width is more important than bank slope in the estimation of erosion probability along the Koiliaris riverbanks. The proposed statistical model is a useful tool that quantifies the erosion probability along the riverbanks and can be used to assist managing erosion and flooding events. Acknowledgements This work is part of an on-going THALES project (CYBERSENSORS - High Frequency Monitoring System for Integrated Water Resources Management of Rivers). The project has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: THALES. Investing in knowledge society through the European Social Fund.

Evidence for a Time-Invariant Phase Variable in Human Ankle Control

PubMed Central

Gregg, Robert D.; Rouse, Elliott J.; Hargrove, Levi J.; Sensinger, Jonathon W.

2014-01-01

Human locomotion is a rhythmic task in which patterns of muscle activity are modulated by state-dependent feedback to accommodate perturbations. Two popular theories have been proposed for the underlying embodiment of phase in the human pattern generator: a time-dependent internal representation or a time-invariant feedback representation (i.e., reflex mechanisms). In either case the neuromuscular system must update or represent the phase of locomotor patterns based on the system state, which can include measurements of hundreds of variables. However, a much simpler representation of phase has emerged in recent designs for legged robots, which control joint patterns as functions of a single monotonic mechanical variable, termed a phase variable. We propose that human joint patterns may similarly depend on a physical phase variable, specifically the heel-to-toe movement of the Center of Pressure under the foot. We found that when the ankle is unexpectedly rotated to a position it would have encountered later in the step, the Center of Pressure also shifts forward to the corresponding later position, and the remaining portion of the gait pattern ensues. This phase shift suggests that the progression of the stance ankle is controlled by a biomechanical phase variable, motivating future investigations of phase variables in human locomotor control. PMID:24558485

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.

Latent mnemonic strengths are latent: a comment on Mickes, Wixted, and Wais (2007).

PubMed

Rouder, Jeffrey N; Pratte, Michael S; Morey, Richard D

2010-06-01

Mickes, Wixted, and Wais (2007) proposed a simple test of latent strength variability in recognition memory. They asked participants to rate their confidence using either a 20-point or a 99-point strength scale and plotted distributions of the resulting ratings. They found 25% more variability in ratings for studied than for new items, which they interpreted as providing evidence that latent mnemonic strength distributions are 25% more variable for studied than for new items. We show here that this conclusion is critically dependent on assumptions--so much so that these assumptions determine the conclusions. In fact, opposite conclusions, such that study does not affect the variability of latent strength, may be reached by making different but equally plausible assumptions. Because all measurements of mnemonic strength variability are critically dependent on untestable assumptions, all are arbitrary. Hence, there is no principled method for assessing the relative variability of latent mnemonic strength distributions.

Size-dependent standard deviation for growth rates: Empirical results and theoretical modeling

NASA Astrophysics Data System (ADS)

Podobnik, Boris; Horvatic, Davor; Pammolli, Fabio; Wang, Fengzhong; Stanley, H. Eugene; Grosse, I.

2008-05-01

We study annual logarithmic growth rates R of various economic variables such as exports, imports, and foreign debt. For each of these variables we find that the distributions of R can be approximated by double exponential (Laplace) distributions in the central parts and power-law distributions in the tails. For each of these variables we further find a power-law dependence of the standard deviation σ(R) on the average size of the economic variable with a scaling exponent surprisingly close to that found for the gross domestic product (GDP) [Phys. Rev. Lett. 81, 3275 (1998)]. By analyzing annual logarithmic growth rates R of wages of 161 different occupations, we find a power-law dependence of the standard deviation σ(R) on the average value of the wages with a scaling exponent β≈0.14 close to those found for the growth of exports, imports, debt, and the growth of the GDP. In contrast to these findings, we observe for payroll data collected from 50 states of the USA that the standard deviation σ(R) of the annual logarithmic growth rate R increases monotonically with the average value of payroll. However, also in this case we observe a power-law dependence of σ(R) on the average payroll with a scaling exponent β≈-0.08 . Based on these observations we propose a stochastic process for multiple cross-correlated variables where for each variable (i) the distribution of logarithmic growth rates decays exponentially in the central part, (ii) the distribution of the logarithmic growth rate decays algebraically in the far tails, and (iii) the standard deviation of the logarithmic growth rate depends algebraically on the average size of the stochastic variable.

Size-dependent standard deviation for growth rates: empirical results and theoretical modeling.

PubMed

Podobnik, Boris; Horvatic, Davor; Pammolli, Fabio; Wang, Fengzhong; Stanley, H Eugene; Grosse, I

2008-05-01

We study annual logarithmic growth rates R of various economic variables such as exports, imports, and foreign debt. For each of these variables we find that the distributions of R can be approximated by double exponential (Laplace) distributions in the central parts and power-law distributions in the tails. For each of these variables we further find a power-law dependence of the standard deviation sigma(R) on the average size of the economic variable with a scaling exponent surprisingly close to that found for the gross domestic product (GDP) [Phys. Rev. Lett. 81, 3275 (1998)]. By analyzing annual logarithmic growth rates R of wages of 161 different occupations, we find a power-law dependence of the standard deviation sigma(R) on the average value of the wages with a scaling exponent beta approximately 0.14 close to those found for the growth of exports, imports, debt, and the growth of the GDP. In contrast to these findings, we observe for payroll data collected from 50 states of the USA that the standard deviation sigma(R) of the annual logarithmic growth rate R increases monotonically with the average value of payroll. However, also in this case we observe a power-law dependence of sigma(R) on the average payroll with a scaling exponent beta approximately -0.08 . Based on these observations we propose a stochastic process for multiple cross-correlated variables where for each variable (i) the distribution of logarithmic growth rates decays exponentially in the central part, (ii) the distribution of the logarithmic growth rate decays algebraically in the far tails, and (iii) the standard deviation of the logarithmic growth rate depends algebraically on the average size of the stochastic variable.

Copula Models for Sociology: Measures of Dependence and Probabilities for Joint Distributions

ERIC Educational Resources Information Center

Vuolo, Mike

2017-01-01

Often in sociology, researchers are confronted with nonnormal variables whose joint distribution they wish to explore. Yet, assumptions of common measures of dependence can fail or estimating such dependence is computationally intensive. This article presents the copula method for modeling the joint distribution of two random variables, including…

Problems with change in R2 as applied to theory of reasoned action research.

PubMed

Trafimow, David

2004-12-01

The paradigm of choice for theory of reasoned action research seems to depend largely on the notion of change in variance accounted for (DeltaR2) as new independent variables are added to a multiple regression equation. If adding a particular independent variable of interest increases the variance in the dependent variable that can be accounted for by the list of independent variables, then the research is deemed to be 'successful', and the researcher is considered to have made a convincing argument about the importance of the new variable. In contrast to this trend, I present arguments that suggest serious problems with the paradigm, and conclude that studies on attitude-behaviour relations would advance the field of psychology to a far greater extent if researchers abandoned it.

Simple and Double Alfven Waves: Hamiltonian Aspects

NASA Astrophysics Data System (ADS)

Webb, G. M.; Zank, G. P.; Hu, Q.; le Roux, J. A.; Dasgupta, B.

2011-12-01

We discuss the nature of simple and double Alfvén waves. Simple waves depend on a single phase variable \\varphi, but double waves depend on two independent phase variables \\varphi1 and \\varphi2. The phase variables depend on the space and time coordinates x and t. Simple and double Alfvén waves have the same integrals, namely, the entropy, density, magnetic pressure, and group velocity (the sum of the Alfvén and fluid velocities) are constant throughout the flow. We present examples of both simple and double Alfvén waves, and discuss Hamiltonian formulations of the waves.

Refining the tobacco dependence phenotype using the Wisconsin Inventory of Smoking Dependence Motives (WISDM)

PubMed Central

Piper, Megan E.; Bolt, Daniel M.; Kim, Su-Young; Japuntich, Sandra J.; Smith, Stevens S.; Niederdeppe, Jeff; Cannon, Dale S.; Baker, Timothy B.

2008-01-01

The construct of tobacco dependence is important from both scientific and public health perspectives, but it is poorly understood. The current research integrates person-centered analyses (e.g., latent profile analysis) and variable-centered analyses (e.g., exploratory factor analysis) to understand better the latent structure of dependence and to guide distillation of the phenotype. Using data from four samples of smokers (including treatment and non-treatment samples), latent profiles were derived using the Wisconsin Inventory of Smoking Dependence Motives (WISDM) subscale scores. Across all four samples, results revealed a unique latent profile that had relative elevations on four dependence motive subscales (Automaticity, Craving, Loss of Control, and Tolerance). Variable-centered analyses supported the uniqueness of these four subscales both as measures of a common factor distinct from that underlying the other nine subscales, and as the strongest predictors of relapse, withdrawal and other dependence criteria. Conversely, the remaining nine motives carried little unique predictive validity regarding dependence. Applications of a factor mixture model further support the presence of a unique class of smokers in relation to a common factor underlying the four subscales. The results illustrate how person-centered analyses may be useful as a supplement to variable-centered analyses for uncovering variables that are necessary and/or sufficient predictors of disorder criteria, as they may uncover small segments of a population in which the variables are uniquely distributed. The results also suggest that severe dependence is associated with a pattern of smoking that is heavy, pervasive, automatic and relatively unresponsive to instrumental contingencies. PMID:19025223

Dependence of vestibular reactions on frequency of action of sign-variable accelerations

NASA Technical Reports Server (NTRS)

Lapayev, E. V.; Vorobyev, O. A.; Ivanov, V. V.

1980-01-01

It was revealed that during the tests with continuous action of sign variable Coriolis acceleration the development of kinetosis was proportionate to the time of head inclinations in the range of 1 to 4 seconds while illusions of rocking in sagittal plane was more expressed in fast inclinations. The obtained data provided the evidence of sufficient dependence of vestibulovegetative and vestibulosensory reactions on the period of repetition of sign variable Coriolis acceleration.

Occupant perception of indoor air and comfort in four hospitality environments.

PubMed

Moschandreas, D J; Chu, P

2002-01-01

This article reports on a survey of customer and staff perceptions of indoor air quality at two restaurants, a billiard hall, and a casino. The survey was conducted at each environment for 8 days: 2 weekend days on 2 consecutive weekends and 4 weekdays. Before and during the survey, each hospitality environment satisfied ventilation requirements set in ASHRAE Standard 62-1999, Ventilation for Acceptable Indoor Air. An objective of this study was to test the hypothesis: If a hospitality environment satisfies ASHRAE ventilation requirements, then the indoor air is acceptable, that is, fewer than 20% of the exposed occupants perceive the environment as unacceptable. A second objective was to develop a multiple regression model that predicts the dependent variable, the environment is acceptable, as a function of a number of independent perception variables. Occupant perception of environmental, comfort, and physical variables was measured using a questionnaire. This instrument was designed to be efficient and unobtrusive; subjects could complete it within 3 min. Significant differences of occupant environment perception were identified among customers and staff. The dependent variable, the environment is acceptable, is affected by temperature, occupant density, and occupant smoking status, odor perception, health conditions, sensitivity to chemicals, and enjoyment of activities. Depending on the hospitality environment, variation of independent variables explains as much as 77% of the variation of the dependent variable.

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.

[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.

Avoiding and Correcting Bias in Score-Based Latent Variable Regression with Discrete Manifest Items

ERIC Educational Resources Information Center

Lu, Irene R. R.; Thomas, D. Roland

2008-01-01

This article considers models involving a single structural equation with latent explanatory and/or latent dependent variables where discrete items are used to measure the latent variables. Our primary focus is the use of scores as proxies for the latent variables and carrying out ordinary least squares (OLS) regression on such scores to estimate…

Mating tactics determine patterns of condition dependence in a dimorphic horned beetle.

PubMed

Knell, Robert J; Simmons, Leigh W

2010-08-07

The persistence of genetic variability in performance traits such as strength is surprising given the directional selection that such traits experience, which should cause the fixation of the best genetic variants. One possible explanation is 'genic capture' which is usually considered as a candidate mechanism for the maintenance of high genetic variability in sexual signalling traits. This states that if a trait is 'condition dependent', with expression being strongly influenced by the bearer's overall viability, then genetic variability can be maintained via mutation-selection balance. Using a species of dimorphic beetle with males that gain matings either by fighting or by 'sneaking', we tested the prediction of strong condition dependence for strength, walking speed and testes mass. Strength was strongly condition dependent only in those beetles that fight for access to females. Walking speed, with less of an obvious selective advantage, showed no condition dependence, and testes mass was more condition dependent in sneaks, which engage in higher levels of sperm competition. Within a species, therefore, condition dependent expression varies between morphs, and corresponds to the specific selection pressures experienced by that morph. These results support genic capture as a general explanation for the maintenance of genetic variability in traits under directional selection.

X-ray variability of Pleiades late-type stars as observed with the ROSAT-PSPC

NASA Astrophysics Data System (ADS)

Marino, A.; Micela, G.; Peres, G.; Sciortino, S.

2003-08-01

We present a comprehensive analysis of X-ray variability of the late-type (dF7-dM) Pleiades stars, detected in all ROSAT-PSPC observations; X-ray variations on short (hours) and medium (months) time scales have been explored. We have grouped the stars in two samples: 89 observations of 42 distinct dF7-dK2 stars and 108 observations of 61 dK3-dM stars. The Kolmogorov-Smirnov test applied on all X-ray photon time series show that the percentage of cases of significant variability is quite similar on both samples, suggesting that the presence of variability does not depend on mass for the time scales and mass range explored. The comparison between the Time X-ray Amplitude Distribution functions (XAD) of the set of dF7-dK2 and of the dK3-dM show that, on short time scales, dK3-dM stars show larger variations than dF7-dK2. A subsample of eleven dF7-dK2 and eleven dK3-dM Pleiades stars allows the study of variability on longer time scales: we found that variability on medium - long time scales is relatively more common among dF7-dK2 stars than among dK3-dM ones. For both dF7-dK2 Pleiades stars and dF7-dK2 field stars, the variability on short time scales depends on Lx while this dependence has not been observed among dK3-dM stars. It may be that the variability among dK3-dM stars is dominated by flares that have a similar luminosity distribution for stars of different Lx, while flaring distribution in dF7-dK2 stars may depend on X-ray luminosity. The lowest mass stars show significant rapid variability (flares?) and no evidence of rotation modulation or cycles. On the contrary, dF7-dK2 Pleiades stars show both rapid variability and variations on longer time scales, likely associated with rotational modulation or cycles.

On accommodating spatial interactions in a Generalized Heterogeneous Data Model (GHDM) of mixed types of dependent variables.

DOT National Transportation Integrated Search

2015-12-01

We develop an econometric framework for incorporating spatial dependence in integrated model systems of latent variables and multidimensional mixed data outcomes. The framework combines Bhats Generalized Heterogeneous Data Model (GHDM) with a spat...

Symbol-and-Arrow Diagrams in Teaching Pharmacokinetics.

ERIC Educational Resources Information Center

Hayton, William L.

1990-01-01

Symbol-and-arrow diagrams are helpful adjuncts to equations derived from pharmacokinetic models. Both show relationships among dependent and independent variables. Diagrams show only qualitative relationships, but clearly show which variables are dependent and which are independent, helping students understand complex but important functional…

Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model

NASA Astrophysics Data System (ADS)

Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami

2017-06-01

A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.

Influence of rice straw cooking conditions in the soda-ethanol-water pulping on the mechanical properties of produced paper sheets.

PubMed

Navaee-Ardeh, S; Mohammadi-Rovshandeh, J; Pourjoozi, M

2004-03-01

A normalized design was used to examine the influence of independent variables (alcohol concentration, cooking time and temperature) in the catalytic soda-ethanol pulping of rice straw on various mechanical properties (breaking length, burst, tear index and folding endurance) of paper sheets obtained from each pulping process. An equation of each dependent variable as a function of cooking variables (independent variables) was obtained by multiple non-linear regression using the least square method by MATLAB software for developing of empirical models. The ranges of alcohol concentration, cooking time and temperature were 40-65% (w/w), 150-180 min and 195-210 degrees C, respectively. Three-dimensional graphs of dependent variables were also plotted versus independent variables. The optimum values of breaking length, burst and tear index and folding endurance were 4683.7 (m), 30.99 (kN/g), 376.93 (mN m2/g) and 27.31, respectively. However, short cooking time (150 min), high ethanol concentration (65%) and high temperature (210 degrees C) could be used to produce papers with suitable burst and tear index. However, for papers with best breaking length and folding endurance low temperature (195 degrees C) was desirable. Differences between optimum values of dependent variables obtained by normalized design and experimental data were less than 20%.

Anxiety, affect, self-esteem, and stress: mediation and moderation effects on depression.

PubMed

Nima, Ali Al; Rosenberg, Patricia; Archer, Trevor; Garcia, Danilo

2013-01-01

Mediation analysis investigates whether a variable (i.e., mediator) changes in regard to an independent variable, in turn, affecting a dependent variable. Moderation analysis, on the other hand, investigates whether the statistical interaction between independent variables predict a dependent variable. Although this difference between these two types of analysis is explicit in current literature, there is still confusion with regard to the mediating and moderating effects of different variables on depression. The purpose of this study was to assess the mediating and moderating effects of anxiety, stress, positive affect, and negative affect on depression. Two hundred and two university students (males  = 93, females  = 113) completed questionnaires assessing anxiety, stress, self-esteem, positive and negative affect, and depression. Mediation and moderation analyses were conducted using techniques based on standard multiple regression and hierarchical regression analyses. The results indicated that (i) anxiety partially mediated the effects of both stress and self-esteem upon depression, (ii) that stress partially mediated the effects of anxiety and positive affect upon depression, (iii) that stress completely mediated the effects of self-esteem on depression, and (iv) that there was a significant interaction between stress and negative affect, and between positive affect and negative affect upon depression. The study highlights different research questions that can be investigated depending on whether researchers decide to use the same variables as mediators and/or moderators.

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

PubMed

Marill, Keith A

2004-01-01

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

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

A continuum state variable theory to model the size-dependent surface energy of nanostructures.

PubMed

Jamshidian, Mostafa; Thamburaja, Prakash; Rabczuk, Timon

2015-10-14

We propose a continuum-based state variable theory to quantify the excess surface free energy density throughout a nanostructure. The size-dependent effect exhibited by nanoplates and spherical nanoparticles i.e. the reduction of surface energy with reducing nanostructure size is well-captured by our continuum state variable theory. Our constitutive theory is also able to predict the reducing energetic difference between the surface and interior (bulk) portions of a nanostructure with decreasing nanostructure size.

State-dependent rotations of spins by weak measurements

NASA Astrophysics Data System (ADS)

Miller, D. J.

2011-03-01

It is shown that a weak measurement of a quantum system produces a new state of the quantum system which depends on the prior state, as well as the (uncontrollable) measured position of the pointer variable of the weak-measurement apparatus. The result imposes a constraint on hidden-variable theories which assign a different state to a quantum system than standard quantum mechanics. The constraint means that a crypto-nonlocal hidden-variable theory can be ruled out in a more direct way than previously done.

DENSITY-DEPENDENT FLOW IN ONE-DIMENSIONAL VARIABLY-SATURATED MEDIA

EPA Science Inventory

A one-dimensional finite element is developed to simulate density-dependent flow of saltwater in variably saturated media. The flow and solute equations were solved in a coupled mode (iterative), in a partially coupled mode (non-iterative), and in a completely decoupled mode. P...

Significant Pre-Accession Factors Predicting Success or Failure During a Marine Corps Officer’s Initial Service Obligation

DTIC Science & Technology

2015-12-01

WAIVERS ..............................................................................................49  APPENDIX C. DESCRIPTIVE STATISTICS ... Statistics of Dependent Variables. .............................................23  Table 6.  Summary Statistics of Academics Variables...24  Table 7.  Summary Statistics of Application Variables ............................................25  Table 8

MULTIVARIATE ANALYSIS OF DRINKING BEHAVIOUR IN A RURAL POPULATION

PubMed Central

Mathrubootham, N.; Bashyam, V.S.P.; Shahjahan

1997-01-01

This study was carried out to find out the drinking pattern in a rural population, using multivariate techniques. 386 current users identified in a community were assessed with regard to their drinking behaviours using a structured interview. For purposes of the study the questions were condensed into 46 meaningful variables. In bivariate analysis, 14 variables including dependent variables such as dependence, MAST & CAGE (measuring alcoholic status), Q.F. Index and troubled drinking were found to be significant. Taking these variables and other multivariate techniques too such as ANOVA, correlation, regression analysis and factor analysis were done using both SPSS PC + and HCL magnum mainframe computer with FOCUS package and UNIX systems. Results revealed that number of factors such as drinking style, duration of drinking, pattern of abuse, Q.F. Index and various problems influenced drinking and some of them set up a vicious circle. Factor analysis revealed mainly 3 factors, abuse, dependence and social drinking factors. Dependence could be divided into low/moderate dependence. The implications and practical applications of these tests are also discussed. PMID:21584077

Examination of two methods for statistical analysis of data with magnitude and direction emphasizing vestibular research applications

NASA Technical Reports Server (NTRS)

Calkins, D. S.

1998-01-01

When the dependent (or response) variable response variable in an experiment has direction and magnitude, one approach that has been used for statistical analysis involves splitting magnitude and direction and applying univariate statistical techniques to the components. However, such treatment of quantities with direction and magnitude is not justifiable mathematically and can lead to incorrect conclusions about relationships among variables and, as a result, to flawed interpretations. This note discusses a problem with that practice and recommends mathematically correct procedures to be used with dependent variables that have direction and magnitude for 1) computation of mean values, 2) statistical contrasts of and confidence intervals for means, and 3) correlation methods.

Gravity dependence of subjective visual vertical variability.

PubMed

Tarnutzer, A A; Bockisch, C; Straumann, D; Olasagasti, I

2009-09-01

The brain integrates sensory input from the otolith organs, the semicircular canals, and the somatosensory and visual systems to determine self-orientation relative to gravity. Only the otoliths directly sense the gravito-inertial force vector and therefore provide the major input for perceiving static head-roll relative to gravity, as measured by the subjective visual vertical (SVV). Intraindividual SVV variability increases with head roll, which suggests that the effectiveness of the otolith signal is roll-angle dependent. We asked whether SVV variability reflects the spatial distribution of the otolithic sensors and the otolith-derived acceleration estimate. Subjects were placed in different roll orientations (0-360 degrees, 15 degrees steps) and asked to align an arrow with perceived vertical. Variability was minimal in upright, increased with head-roll peaking around 120-135 degrees, and decreased to intermediate values at 180 degrees. Otolith-dependent variability was modeled by taking into consideration the nonuniform distribution of the otolith afferents and their nonlinear firing rate. The otolith-derived estimate was combined with an internal bias shifting the estimated gravity-vector toward the body-longitudinal. Assuming an efficient otolith estimator at all roll angles, peak variability of the model matched our data; however, modeled variability in upside-down and upright positions was very similar, which is at odds with our findings. By decreasing the effectiveness of the otolith estimator with increasing roll, simulated variability matched our experimental findings better. We suggest that modulations of SVV precision in the roll plane are related to the properties of the otolith sensors and to central computational mechanisms that are not optimally tuned for roll-angles distant from upright.

Individual aptitude in Mandarin lexical tone perception predicts effectiveness of high-variability training

PubMed Central

Sadakata, Makiko; McQueen, James M.

2014-01-01

Although the high-variability training method can enhance learning of non-native speech categories, this can depend on individuals’ aptitude. The current study asked how general the effects of perceptual aptitude are by testing whether they occur with training materials spoken by native speakers and whether they depend on the nature of the to-be-learned material. Forty-five native Dutch listeners took part in a 5-day training procedure in which they identified bisyllabic Mandarin pseudowords (e.g., asa) pronounced with different lexical tone combinations. The training materials were presented to different groups of listeners at three levels of variability: low (many repetitions of a limited set of words recorded by a single speaker), medium (fewer repetitions of a more variable set of words recorded by three speakers), and high (similar to medium but with five speakers). Overall, variability did not influence learning performance, but this was due to an interaction with individuals’ perceptual aptitude: increasing variability hindered improvements in performance for low-aptitude perceivers while it helped improvements in performance for high-aptitude perceivers. These results show that the previously observed interaction between individuals’ aptitude and effects of degree of variability extends to natural tokens of Mandarin speech. This interaction was not found, however, in a closely matched study in which native Dutch listeners were trained on the Japanese geminate/singleton consonant contrast. This may indicate that the effectiveness of high-variability training depends not only on individuals’ aptitude in speech perception but also on the nature of the categories being acquired. PMID:25505434

Modelling Spatial Dependence Structures Between Climate Variables by Combining Mixture Models with Copula Models

NASA Astrophysics Data System (ADS)

Khan, F.; Pilz, J.; Spöck, G.

2017-12-01

Spatio-temporal dependence structures play a pivotal role in understanding the meteorological characteristics of a basin or sub-basin. This further affects the hydrological conditions and consequently will provide misleading results if these structures are not taken into account properly. In this study we modeled the spatial dependence structure between climate variables including maximum, minimum temperature and precipitation in the Monsoon dominated region of Pakistan. For temperature, six, and for precipitation four meteorological stations have been considered. For modelling the dependence structure between temperature and precipitation at multiple sites, we utilized C-Vine, D-Vine and Student t-copula models. For temperature, multivariate mixture normal distributions and for precipitation gamma distributions have been used as marginals under the copula models. A comparison was made between C-Vine, D-Vine and Student t-copula by observational and simulated spatial dependence structure to choose an appropriate model for the climate data. The results show that all copula models performed well, however, there are subtle differences in their performances. The copula models captured the patterns of spatial dependence structures between climate variables at multiple meteorological sites, however, the t-copula showed poor performance in reproducing the dependence structure with respect to magnitude. It was observed that important statistics of observed data have been closely approximated except of maximum values for temperature and minimum values for minimum temperature. Probability density functions of simulated data closely follow the probability density functions of observational data for all variables. C and D-Vines are better tools when it comes to modelling the dependence between variables, however, Student t-copulas compete closely for precipitation. Keywords: Copula model, C-Vine, D-Vine, Spatial dependence structure, Monsoon dominated region of Pakistan, Mixture models, EM algorithm.

Problems Identifying Independent and Dependent Variables

ERIC Educational Resources Information Center

Leatham, Keith R.

2012-01-01

This paper discusses one step from the scientific method--that of identifying independent and dependent variables--from both scientific and mathematical perspectives. It begins by analyzing an episode from a middle school mathematics classroom that illustrates the need for students and teachers alike to develop a robust understanding of…

Some Methodological Considerations in Researching the Family Career.

ERIC Educational Resources Information Center

White, James

Methodological issues which confront researchers using the concept of the family career include the selection of appropriate dependent variables; the efficacy of historical versus immediate effects; and scaling the family career (a proposed replacement for the "family life cycle"). The issue of which dependent variables should be…

An Empirical Examination of Weiner's Critique of Attribution Research.

ERIC Educational Resources Information Center

Covington, Martin V.; Omelich, Carol L.

1984-01-01

Weiner's allegations of errors in testing his theory (presumed detrimental effects of investigating a restricted range of variables, use of expectancy changes as a mediating variable, and presumed inappropriateness of classroom performance as a dependent variable) are evaluated. Disconfirmation of Weiner's predictions occurs irrespective of…

The Variability of Gender-Based Communication in Japanese Magazine Advertising.

ERIC Educational Resources Information Center

Maynard, Michael L.

1995-01-01

Analyzes Japanese magazine advertising text from an intracultural perspective based on gender. Uses content analysis to examine advertising text of eight gender-specific magazines. Reveals significant difference in the variability of message perception depending on target gender. Suggests the importance of recognizing intracultural variability,…

Benford's law and continuous dependent random variables

NASA Astrophysics Data System (ADS)

Becker, Thealexa; Burt, David; Corcoran, Taylor C.; Greaves-Tunnell, Alec; Iafrate, Joseph R.; Jing, Joy; Miller, Steven J.; Porfilio, Jaclyn D.; Ronan, Ryan; Samranvedhya, Jirapat; Strauch, Frederick W.; Talbut, Blaine

2018-01-01

Many mathematical, man-made and natural systems exhibit a leading-digit bias, where a first digit (base 10) of 1 occurs not 11% of the time, as one would expect if all digits were equally likely, but rather 30%. This phenomenon is known as Benford's Law. Analyzing which datasets adhere to Benford's Law and how quickly Benford behavior sets in are the two most important problems in the field. Most previous work studied systems of independent random variables, and relied on the independence in their analyses. Inspired by natural processes such as particle decay, we study the dependent random variables that emerge from models of decomposition of conserved quantities. We prove that in many instances the distribution of lengths of the resulting pieces converges to Benford behavior as the number of divisions grow, and give several conjectures for other fragmentation processes. The main difficulty is that the resulting random variables are dependent. We handle this by using tools from Fourier analysis and irrationality exponents to obtain quantified convergence rates as well as introducing and developing techniques to measure and control the dependencies. The construction of these tools is one of the major motivations of this work, as our approach can be applied to many other dependent systems. As an example, we show that the n ! entries in the determinant expansions of n × n matrices with entries independently drawn from nice random variables converges to Benford's Law.

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.

Modelling space of spread Dengue Hemorrhagic Fever (DHF) in Central Java use spatial durbin model

NASA Astrophysics Data System (ADS)

Ispriyanti, Dwi; Prahutama, Alan; Taryono, Arkadina PN

2018-05-01

Dengue Hemorrhagic Fever is one of the major public health problems in Indonesia. From year to year, DHF causes Extraordinary Event in most parts of Indonesia, especially Central Java. Central Java consists of 35 districts or cities where each region is close to each other. Spatial regression is an analysis that suspects the influence of independent variables on the dependent variables with the influences of the region inside. In spatial regression modeling, there are spatial autoregressive model (SAR), spatial error model (SEM) and spatial autoregressive moving average (SARMA). Spatial Durbin model is the development of SAR where the dependent and independent variable have spatial influence. In this research dependent variable used is number of DHF sufferers. The independent variables observed are population density, number of hospitals, residents and health centers, and mean years of schooling. From the multiple regression model test, the variables that significantly affect the spread of DHF disease are the population and mean years of schooling. By using queen contiguity and rook contiguity, the best model produced is the SDM model with queen contiguity because it has the smallest AIC value of 494,12. Factors that generally affect the spread of DHF in Central Java Province are the number of population and the average length of school.

THE COLOR VARIABILITY OF QUASARS

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

Schmidt, Kasper B.; Rix, Hans-Walter; Knecht, Matthias

2012-01-10

We quantify quasar color variability using an unprecedented variability database-ugriz photometry of 9093 quasars from Sloan Digital Sky Survey (SDSS) Stripe 82, observed over 8 years at {approx}60 epochs each. We confirm previous reports that quasars become bluer when brightening. We find a redshift dependence of this blueing in a given set of bands (e.g., g and r), but show that it is the result of the flux contribution from less-variable or delayed emission lines in the different SDSS bands at different redshifts. After correcting for this effect, quasar color variability is remarkably uniform, and independent not only of redshift,more » but also of quasar luminosity and black hole mass. The color variations of individual quasars, as they vary in brightness on year timescales, are much more pronounced than the ranges in color seen in samples of quasars across many orders of magnitude in luminosity. This indicates distinct physical mechanisms behind quasar variability and the observed range of quasar luminosities at a given black hole mass-quasar variations cannot be explained by changes in the mean accretion rate. We do find some dependence of the color variability on the characteristics of the flux variations themselves, with fast, low-amplitude, brightness variations producing more color variability. The observed behavior could arise if quasar variability results from flares or ephemeral hot spots in an accretion disk.« less

Individual Differences in Well-Being in Older Breast Cancer Survivors

PubMed Central

Perkins, Elizabeth A.; Small, Brent J.; Balducci, Lodovico; Extermann, Martine; Robb, Claire; Haley, William E.

2007-01-01

Older women who survive breast cancer may differ significantly in their long-term well-being. Using a risk and protective factors model, we studied predictors of well-being in 127 women age 70 and above with a history of at least one year's survival of breast cancer. Mean post-cancer survivorship was 5.1 years. Using life satisfaction, depression and general health perceptions as outcome variables, we assessed whether demographic variables, cancer-related variables, health status and psychosocial resources predicted variability in well-being using correlational and hierarchical regression analyses. Higher age predicted increased depression but was not associated with life satisfaction or general health perceptions. Cancer-related variables, including duration of survival, and type of cancer treatment, were not significantly associated with survivors' well-being. Poorer health status was associated with poorer well-being in all three dependent variables. After controlling for demographics, cancer-related variables, and health status, higher levels of psychosocial resources including optimism, mastery, spirituality and social support predicted better outcome in all three dependent variables. While many older women survive breast cancer without severe sequelae, there is considerable variability in their well-being after survivorship. Successful intervention with older breast cancer survivors might include greater attention not only to cancer-specific concerns, but also attention to geriatric syndromes and functional impairment, and enhancement of protective psychosocial resources. PMID:17240157

Formulation and statistical optimization of self-microemulsifying drug delivery system of eprosartan mesylate for improvement of oral bioavailability.

PubMed

Dangre, Pankaj; Gilhotra, Ritu; Dhole, Shashikant

2016-10-01

The present investigation is aimed to design a statistically optimized self-microemulsifying drug delivery system (SMEDDS) of eprosartan mesylate (EM). Preliminary screening was carried out to find a suitable combination of various excipients for the formulation. A 3(2) full factorial design was employed to determine the effect of various independent variables on dependent (response) variables. The independent variables studied in the present work were concentration of oil (X 1) and the ratio of S mix (X 2), whereas the dependent variables were emulsification time (s), globule size (nm), polydispersity index (pdi), and zeta potential (mV), and the multiple linear regression analysis (MLRA) was employed to understand the influence of independent variables on dependent variables. Furthermore, a numerical optimization technique using the desirability function was used to develop a new optimized formulation with desired values of dependent variables. The optimized SMEDDS formulation of eprosartan mesylate (EMF-O) by the above method exhibited emulsification time, 118.45 ± 1.64 s; globule size, 196.81 ± 1.29 nm; zeta potential, -9.34 ± 1.2 mV, and polydispersity index, 0.354 ± 0.02. For the in vitro dissolution study, the optimized formulation (EMF-O) and pure drug were separately entrapped in the dialysis bag, and the study indicated higher release of the drug from EMF-O. In vivo pharmacokinetic studies in Wistar rats using PK solver software revealed 2.1-fold increment in oral bioavailability of EM from EMF-O, when compared with plain suspension of pure drug.

Motivation as an independent and a dependent variable in medical education: a review of the literature.

PubMed

Kusurkar, R A; Ten Cate, Th J; van Asperen, M; Croiset, G

2011-01-01

Motivation in learning behaviour and education is well-researched in general education, but less in medical education. To answer two research questions, 'How has the literature studied motivation as either an independent or dependent variable? How is motivation useful in predicting and understanding processes and outcomes in medical education?' in the light of the Self-determination Theory (SDT) of motivation. A literature search performed using the PubMed, PsycINFO and ERIC databases resulted in 460 articles. The inclusion criteria were empirical research, specific measurement of motivation and qualitative research studies which had well-designed methodology. Only studies related to medical students/school were included. Findings of 56 articles were included in the review. Motivation as an independent variable appears to affect learning and study behaviour, academic performance, choice of medicine and specialty within medicine and intention to continue medical study. Motivation as a dependent variable appears to be affected by age, gender, ethnicity, socioeconomic status, personality, year of medical curriculum and teacher and peer support, all of which cannot be manipulated by medical educators. Motivation is also affected by factors that can be influenced, among which are, autonomy, competence and relatedness, which have been described as the basic psychological needs important for intrinsic motivation according to SDT. Motivation is an independent variable in medical education influencing important outcomes and is also a dependent variable influenced by autonomy, competence and relatedness. This review finds some evidence in support of the validity of SDT in medical education.

Verification of Concurrent Programs. Part II. Temporal Proof Principles.

DTIC Science & Technology

1981-09-01

not modify any of the shared program variables. In order to ensure the correct synchronization between the processes we use three semaphore variables...direct, simple, and intuitive rides for the establishment of these properties. rhey usually replace long but repetitively similar chains of primitive ...modify the variables on which Q actually depends. A typical case is that of semaphores . We have the following property: The Semaphore Variable Rule

Learning a novel phonological contrast depends on interactions between individual differences and training paradigm design

PubMed Central

Perrachione, Tyler K.; Lee, Jiyeon; Ha, Louisa Y. Y.; Wong, Patrick C. M.

2011-01-01

Studies evaluating phonological contrast learning typically investigate either the predictiveness of specific pretraining aptitude measures or the efficacy of different instructional paradigms. However, little research considers how these factors interact—whether different students learn better from different types of instruction—and what the psychological basis for any interaction might be. The present study demonstrates that successfully learning a foreign-language phonological contrast for pitch depends on an interaction between individual differences in perceptual abilities and the design of the training paradigm. Training from stimuli with high acoustic-phonetic variability is generally thought to improve learning; however, we found high-variability training enhanced learning only for individuals with strong perceptual abilities. Learners with weaker perceptual abilities were actually impaired by high-variability training relative to a low-variability condition. A second experiment assessing variations on the high-variability training design determined that the property of this learning environment most detrimental to perceptually weak learners is the amount of trial-by-trial variability. Learners’ perceptual limitations can thus override the benefits of high-variability training where trial-by-trial variability in other irrelevant acoustic-phonetic features obfuscates access to the target feature. These results demonstrate the importance of considering individual differences in pretraining aptitudes when evaluating the efficacy of any speech training paradigm. PMID:21786912

Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

NASA Astrophysics Data System (ADS)

Cannon, Alex J.

2018-01-01

Most bias correction algorithms used in climatology, for example quantile mapping, are applied to univariate time series. They neglect the dependence between different variables. Those that are multivariate often correct only limited measures of joint dependence, such as Pearson or Spearman rank correlation. Here, an image processing technique designed to transfer colour information from one image to another—the N-dimensional probability density function transform—is adapted for use as a multivariate bias correction algorithm (MBCn) for climate model projections/predictions of multiple climate variables. MBCn is a multivariate generalization of quantile mapping that transfers all aspects of an observed continuous multivariate distribution to the corresponding multivariate distribution of variables from a climate model. When applied to climate model projections, changes in quantiles of each variable between the historical and projection period are also preserved. The MBCn algorithm is demonstrated on three case studies. First, the method is applied to an image processing example with characteristics that mimic a climate projection problem. Second, MBCn is used to correct a suite of 3-hourly surface meteorological variables from the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) across a North American domain. Components of the Canadian Forest Fire Weather Index (FWI) System, a complicated set of multivariate indices that characterizes the risk of wildfire, are then calculated and verified against observed values. Third, MBCn is used to correct biases in the spatial dependence structure of CanRCM4 precipitation fields. Results are compared against a univariate quantile mapping algorithm, which neglects the dependence between variables, and two multivariate bias correction algorithms, each of which corrects a different form of inter-variable correlation structure. MBCn outperforms these alternatives, often by a large margin, particularly for annual maxima of the FWI distribution and spatiotemporal autocorrelation of precipitation fields.

Variables That Can Affect Student Ratings of Their Professors

ERIC Educational Resources Information Center

Gotlieb, Jerry

2013-01-01

Attribution theory was applied to help predict the results of an experiment that examined the effects of three independent variables on students' ratings of their professors. The dependent variables were students' perceptions of whether the professor caused the students' grades and student satisfaction with their professor. The results suggest…

Sources of Sex Discrimination in Educational Systems: A Conceptual Model

ERIC Educational Resources Information Center

Kutner, Nancy G.; Brogan, Donna

1976-01-01

A conceptual model is presented relating numerous variables contributing to sexism in American education. Discrimination is viewed as intervening between two sets of interrelated independent variables and the dependent variable of sex inequalities in educational attainment. Sex-role orientation changes are the key to significant change in the…

Environmental Literacy in Madeira Island (Portugal): The Influence of Demographic Variables

ERIC Educational Resources Information Center

Spinola, Hélder

2016-01-01

Demographic factors are among those that influence environmental literacy and, particularly, environmentally responsible behaviours, either directly or due to an aggregation effect dependent on other types of variables. Present study evaluates a set of demographic variables as predictors for environmental literacy among 9th grade students from…

A Composite Likelihood Inference in Latent Variable Models for Ordinal Longitudinal Responses

ERIC Educational Resources Information Center

Vasdekis, Vassilis G. S.; Cagnone, Silvia; Moustaki, Irini

2012-01-01

The paper proposes a composite likelihood estimation approach that uses bivariate instead of multivariate marginal probabilities for ordinal longitudinal responses using a latent variable model. The model considers time-dependent latent variables and item-specific random effects to be accountable for the interdependencies of the multivariate…

Assessing Mediational Models: Testing and Interval Estimation for Indirect Effects

ERIC Educational Resources Information Center

Biesanz, Jeremy C.; Falk, Carl F.; Savalei, Victoria

2010-01-01

Theoretical models specifying indirect or mediated effects are common in the social sciences. An indirect effect exists when an independent variable's influence on the dependent variable is mediated through an intervening variable. Classic approaches to assessing such mediational hypotheses (Baron & Kenny, 1986; Sobel, 1982) have in recent years…

Directional Dependence in Developmental Research

ERIC Educational Resources Information Center

von Eye, Alexander; DeShon, Richard P.

2012-01-01

In this article, we discuss and propose methods that may be of use to determine direction of dependence in non-normally distributed variables. First, it is shown that standard regression analysis is unable to distinguish between explanatory and response variables. Then, skewness and kurtosis are discussed as tools to assess deviation from…

Using ERA-Interim reanalysis for creating datasets of energy-relevant climate variables

NASA Astrophysics Data System (ADS)

Jones, Philip D.; Harpham, Colin; Troccoli, Alberto; Gschwind, Benoit; Ranchin, Thierry; Wald, Lucien; Goodess, Clare M.; Dorling, Stephen

2017-07-01

The construction of a bias-adjusted dataset of climate variables at the near surface using ERA-Interim reanalysis is presented. A number of different, variable-dependent, bias-adjustment approaches have been proposed. Here we modify the parameters of different distributions (depending on the variable), adjusting ERA-Interim based on gridded station or direct station observations. The variables are air temperature, dewpoint temperature, precipitation (daily only), solar radiation, wind speed, and relative humidity. These are available on either 3 or 6 h timescales over the period 1979-2016. The resulting bias-adjusted dataset is available through the Climate Data Store (CDS) of the Copernicus Climate Change Data Store (C3S) and can be accessed at present from ftp://ecem.climate.copernicus.eu. The benefit of performing bias adjustment is demonstrated by comparing initial and bias-adjusted ERA-Interim data against gridded observational fields.

Selection of latent variables for multiple mixed-outcome models

PubMed Central

ZHOU, LING; LIN, HUAZHEN; SONG, XINYUAN; LI, YI

2014-01-01

Latent variable models have been widely used for modeling the dependence structure of multiple outcomes data. However, the formulation of a latent variable model is often unknown a priori, the misspecification will distort the dependence structure and lead to unreliable model inference. Moreover, multiple outcomes with varying types present enormous analytical challenges. In this paper, we present a class of general latent variable models that can accommodate mixed types of outcomes. We propose a novel selection approach that simultaneously selects latent variables and estimates parameters. We show that the proposed estimator is consistent, asymptotically normal and has the oracle property. The practical utility of the methods is confirmed via simulations as well as an application to the analysis of the World Values Survey, a global research project that explores peoples’ values and beliefs and the social and personal characteristics that might influence them. PMID:27642219

Sensitivity study on durability variables of marine concrete structures

NASA Astrophysics Data System (ADS)

Zhou, Xin'gang; Li, Kefei

2013-06-01

In order to study the influence of parameters on durability of marine concrete structures, the parameter's sensitivity analysis was studied in this paper. With the Fick's 2nd law of diffusion and the deterministic sensitivity analysis method (DSA), the sensitivity factors of apparent surface chloride content, apparent chloride diffusion coefficient and its time dependent attenuation factor were analyzed. The results of the analysis show that the impact of design variables on concrete durability was different. The values of sensitivity factor of chloride diffusion coefficient and its time dependent attenuation factor were higher than others. Relative less error in chloride diffusion coefficient and its time dependent attenuation coefficient induces a bigger error in concrete durability design and life prediction. According to probability sensitivity analysis (PSA), the influence of mean value and variance of concrete durability design variables on the durability failure probability was studied. The results of the study provide quantitative measures of the importance of concrete durability design and life prediction variables. It was concluded that the chloride diffusion coefficient and its time dependent attenuation factor have more influence on the reliability of marine concrete structural durability. In durability design and life prediction of marine concrete structures, it was very important to reduce the measure and statistic error of durability design variables.

Integrated Logistics Support Analysis of the International Space Station Alpha, Background and Summary of Mathematical Modeling and Failure Density Distributions Pertaining to Maintenance Time Dependent Parameters

NASA Technical Reports Server (NTRS)

Sepehry-Fard, F.; Coulthard, Maurice H.

1995-01-01

The process of predicting the values of maintenance time dependent variable parameters such as mean time between failures (MTBF) over time must be one that will not in turn introduce uncontrolled deviation in the results of the ILS analysis such as life cycle costs, spares calculation, etc. A minor deviation in the values of the maintenance time dependent variable parameters such as MTBF over time will have a significant impact on the logistics resources demands, International Space Station availability and maintenance support costs. There are two types of parameters in the logistics and maintenance world: a. Fixed; b. Variable Fixed parameters, such as cost per man hour, are relatively easy to predict and forecast. These parameters normally follow a linear path and they do not change randomly. However, the variable parameters subject to the study in this report such as MTBF do not follow a linear path and they normally fall within the distribution curves which are discussed in this publication. The very challenging task then becomes the utilization of statistical techniques to accurately forecast the future non-linear time dependent variable arisings and events with a high confidence level. This, in turn, shall translate in tremendous cost savings and improved availability all around.

Anxiety, Affect, Self-Esteem, and Stress: Mediation and Moderation Effects on Depression

PubMed Central

Nima, Ali Al; Rosenberg, Patricia; Archer, Trevor; Garcia, Danilo

2013-01-01

Background Mediation analysis investigates whether a variable (i.e., mediator) changes in regard to an independent variable, in turn, affecting a dependent variable. Moderation analysis, on the other hand, investigates whether the statistical interaction between independent variables predict a dependent variable. Although this difference between these two types of analysis is explicit in current literature, there is still confusion with regard to the mediating and moderating effects of different variables on depression. The purpose of this study was to assess the mediating and moderating effects of anxiety, stress, positive affect, and negative affect on depression. Methods Two hundred and two university students (males  = 93, females  = 113) completed questionnaires assessing anxiety, stress, self-esteem, positive and negative affect, and depression. Mediation and moderation analyses were conducted using techniques based on standard multiple regression and hierarchical regression analyses. Main Findings The results indicated that (i) anxiety partially mediated the effects of both stress and self-esteem upon depression, (ii) that stress partially mediated the effects of anxiety and positive affect upon depression, (iii) that stress completely mediated the effects of self-esteem on depression, and (iv) that there was a significant interaction between stress and negative affect, and between positive affect and negative affect upon depression. Conclusion The study highlights different research questions that can be investigated depending on whether researchers decide to use the same variables as mediators and/or moderators. PMID:24039896

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.

[Optimization of Formulation and Process of Paclitaxel PEGylated Liposomes by Box-Behnken Response Surface Methodology].

PubMed

Shi, Ya-jun; Zhang, Xiao-feil; Guo, Qiu-ting

2015-12-01

To develop a procedure for preparing paclitaxel encapsulated PEGylated liposomes. The membrane hydration followed extraction method was used to prepare PEGylated liposomes. The process and formulation variables were optimized by "Box-Behnken Design (BBD)" of response surface methodology (RSM) with the amount of Soya phosphotidylcholine (SPC) and PEG2000-DSPE as well as the rate of SPC to drug as independent variables and entrapment efficiency as dependent variables for optimization of formulation variables while temperature, pressure and cycle times as independent variables and particle size and polydispersion index as dependent variables for process variables. The optimized liposomal formulation was characterized for particle size, Zeta potential, morphology and in vitro drug release. For entrapment efficiency, particle size, polydispersion index, Zeta potential, and in vitro drug release of PEGylated liposomes was found to be 80.3%, (97.15 ± 14.9) nm, 0.117 ± 0.019, (-30.3 ± 3.7) mV, and 37.4% in 24 h, respectively. The liposomes were found to be small, unilamellar and spherical with smooth surface as seen in transmission electron microscopy. The Box-Behnken response surface methodology facilitates the formulation and optimization of paclitaxel PEGylated liposomes.

An analysis of science versus pseudoscience

NASA Astrophysics Data System (ADS)

Hooten, James T.

2011-12-01

This quantitative study identified distinctive features in archival datasets commissioned by the National Science Foundation (NSF) for Science and Engineering Indicators reports. The dependent variables included education level, and scores for science fact knowledge, science process knowledge, and pseudoscience beliefs. The dependent variables were aggregated into nine NSF-defined geographic regions and examined for the years 2004 and 2006. The variables were also examined over all years available in the dataset. Descriptive statistics were determined and tests for normality and homogeneity of variances were performed using Statistical Package for the Social Sciences. Analysis of Variance was used to test for statistically significant differences between the nine geographic regions for each of the four dependent variables. Statistical significance of 0.05 was used. Tukey post-hoc analysis was used to compute practical significance of differences between regions. Post-hoc power analysis using G*Power was used to calculate the probability of Type II errors. Tests for correlations across all years of the dependent variables were also performed. Pearson's r was used to indicate the strength of the relationship between the dependent variables. Small to medium differences in science literacy and education level were observed between many of the nine U.S. geographic regions. The most significant differences occurred when the West South Central region was compared to the New England and the Pacific regions. Belief in pseudoscience appeared to be distributed evenly across all U.S. geographic regions. Education level was a strong indicator of science literacy regardless of a respondent's region of residence. Recommendations for further study include more in-depth investigation to uncover the nature of the relationship between education level and belief in pseudoscience.

Pressure model of a four-way spool valve for simulating electrohydraulic control systems

NASA Technical Reports Server (NTRS)

Gebben, V. D.

1976-01-01

An equation that relates the pressure flow characteristics of hydraulic spool valves was developed. The dependent variable is valve output pressure, and the independent variables are spool position and flow. This causal form of equation is preferred in applications that simulate the effects of hydraulic line dynamics. Results from this equation are compared with those from the conventional valve equation, whose dependent variable is flow. A computer program of the valve equations includes spool stops, leakage spool clearances, and dead-zone characteristics of overlap spools.

An improved multiple linear regression and data analysis computer program package

NASA Technical Reports Server (NTRS)

Sidik, S. M.

1972-01-01

NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.

Cross diffusion and exponential space dependent heat source impacts in radiated three-dimensional (3D) flow of Casson fluid by heated surface

NASA Astrophysics Data System (ADS)

Zaigham Zia, Q. M.; Ullah, Ikram; Waqas, M.; Alsaedi, A.; Hayat, T.

2018-03-01

This research intends to elaborate Soret-Dufour characteristics in mixed convective radiated Casson liquid flow by exponentially heated surface. Novel features of exponential space dependent heat source are introduced. Appropriate variables are implemented for conversion of partial differential frameworks into a sets of ordinary differential expressions. Homotopic scheme is employed for construction of analytic solutions. Behavior of various embedding variables on velocity, temperature and concentration distributions are plotted graphically and analyzed in detail. Besides, skin friction coefficients and heat and mass transfer rates are also computed and interpreted. The results signify the pronounced characteristics of temperature corresponding to convective and radiation variables. Concentration bears opposite response for Soret and Dufour variables.

Phase dependence of transport-aperture coordination variability reveals control strategy of reach-to-grasp movements.

PubMed

Rand, Miya K; Shimansky, Y P; Hossain, Abul B M I; Stelmach, George E

2010-11-01

Based on an assumption of movement control optimality in reach-to-grasp movements, we have recently developed a mathematical model of transport-aperture coordination (TAC), according to which the hand-target distance is a function of hand velocity and acceleration, aperture magnitude, and aperture velocity and acceleration (Rand et al. in Exp Brain Res 188:263-274, 2008). Reach-to-grasp movements were performed by young adults under four different reaching speeds and two different transport distances. The residual error magnitude of fitting the above model to data across different trials and subjects was minimal for the aperture-closure phase, but relatively much greater for the aperture-opening phase, indicating considerable difference in TAC variability between those phases. This study's goal is to identify the main reasons for that difference and obtain insights into the control strategy of reach-to-grasp movements. TAC variability within the aperture-opening phase of a single trial was found minimal, indicating that TAC variability between trials was not due to execution noise, but rather a result of inter-trial and inter-subject variability of motor plan. At the same time, the dependence of the extent of trial-to-trial variability of TAC in that phase on the speed of hand transport was sharply inconsistent with the concept of speed-accuracy trade-off: the lower the speed, the larger the variability. Conversely, the dependence of the extent of TAC variability in the aperture-closure phase on hand transport speed was consistent with that concept. Taking into account recent evidence that the cost of neural information processing is substantial for movement planning, the dependence of TAC variability in the aperture-opening phase on task performance conditions suggests that it is not the movement time that the CNS saves in that phase, but the cost of neuro-computational resources and metabolic energy required for TAC regulation in that phase. Thus, the CNS performs a trade-off between that cost and TAC regulation accuracy. It is further discussed that such trade-off is possible because, due to a special control law that governs optimal switching from aperture opening to aperture closure, the inter-trial variability of the end of aperture opening does not affect the high accuracy of TAC regulation in the subsequent aperture-closure phase.

Statistical Measurement and Analysis of Claimant and Demographic Variables Affecting Processing and Adjudication Duration in The United States Army Physical Disability Evaluation System.

DTIC Science & Technology

1997-02-06

Adjudication Duration 2 2. INTRODUCTION This retrospective study analyzes relationships of variables to adjudication and processing duration in the Army...Package for Social Scientists (SPSS), Standard Version 6.1, June 1994, to determine relationships among the dependent and independent variables... consanguinity between variables. Content and criterion validity is employed to determine the measure of scientific validity. Reliability is also

Statistics of Stokes variables for correlated Gaussian fields

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

Eliyahu, D.

1994-09-01

The joint and marginal probability distribution functions of the Stokes variables are derived for correlated Gaussian fields [an extension of D. Eliyahu, Phys. Rev. E 47, 2881 (1993)]. The statistics depend only on the first moment (averaged) Stokes variables and have a universal form for [ital S][sub 1], [ital S][sub 2], and [ital S][sub 3]. The statistics of the variables describing the Cartesian coordinates of the Poincare sphere are given also.

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.

Loyalty, Trust, Satisfaction and Participation in Universitas Terbuka Ambiance: Students' Perception

ERIC Educational Resources Information Center

Herman

2017-01-01

Factors affecting the loyalty of students in Universitas Terbuka are investigated in this paper. The aim was to elucidate how all the variables such as trust, satisfaction and participation interrelate with one another. Loyalty was the dependent variable; trust, satisfaction and participation were the independent variables. Data were accumulated…

Least Principal Components Analysis (LPCA): An Alternative to Regression Analysis.

ERIC Educational Resources Information Center

Olson, Jeffery E.

Often, all of the variables in a model are latent, random, or subject to measurement error, or there is not an obvious dependent variable. When any of these conditions exist, an appropriate method for estimating the linear relationships among the variables is Least Principal Components Analysis. Least Principal Components are robust, consistent,…

Culture, Organizational Learning and Selected Employee Background Variables in Small-Size Business Enterprises

ERIC Educational Resources Information Center

Graham, Carroll M.; Nafukho, Fredrick Muyia

2007-01-01

Purpose: The purpose of this study is to determine the relationship between four independent variables educational level, longevity, type of enterprise, and gender and the dependent variable culture, as a dimension that explains organizational learning readiness in seven small-size business enterprises. Design/methodology/approach: An exploratory…

Dynamic rupture modeling with laboratory-derived constitutive relations

USGS Publications Warehouse

Okubo, P.G.

1989-01-01

A laboratory-derived state variable friction constitutive relation is used in the numerical simulation of the dynamic growth of an in-plane or mode II shear crack. According to this formulation, originally presented by J.H. Dieterich, frictional resistance varies with the logarithm of the slip rate and with the logarithm of the frictional state variable as identified by A.L. Ruina. Under conditions of steady sliding, the state variable is proportional to (slip rate)-1. Following suddenly introduced increases in slip rate, the rate and state dependencies combine to produce behavior which resembles slip weakening. When rupture nucleation is artificially forced at fixed rupture velocity, rupture models calculated with the state variable friction in a uniformly distributed initial stress field closely resemble earlier rupture models calculated with a slip weakening fault constitutive relation. Model calculations suggest that dynamic rupture following a state variable friction relation is similar to that following a simpler fault slip weakening law. However, when modeling the full cycle of fault motions, rate-dependent frictional responses included in the state variable formulation are important at low slip rates associated with rupture nucleation. -from Author

Bayesian Techniques for Comparing Time-dependent GRMHD Simulations to Variable Event Horizon Telescope Observations

NASA Astrophysics Data System (ADS)

Kim, Junhan; Marrone, Daniel P.; Chan, Chi-Kwan; Medeiros, Lia; Özel, Feryal; Psaltis, Dimitrios

2016-12-01

The Event Horizon Telescope (EHT) is a millimeter-wavelength, very-long-baseline interferometry (VLBI) experiment that is capable of observing black holes with horizon-scale resolution. Early observations have revealed variable horizon-scale emission in the Galactic Center black hole, Sagittarius A* (Sgr A*). Comparing such observations to time-dependent general relativistic magnetohydrodynamic (GRMHD) simulations requires statistical tools that explicitly consider the variability in both the data and the models. We develop here a Bayesian method to compare time-resolved simulation images to variable VLBI data, in order to infer model parameters and perform model comparisons. We use mock EHT data based on GRMHD simulations to explore the robustness of this Bayesian method and contrast it to approaches that do not consider the effects of variability. We find that time-independent models lead to offset values of the inferred parameters with artificially reduced uncertainties. Moreover, neglecting the variability in the data and the models often leads to erroneous model selections. We finally apply our method to the early EHT data on Sgr A*.

BAYESIAN TECHNIQUES FOR COMPARING TIME-DEPENDENT GRMHD SIMULATIONS TO VARIABLE EVENT HORIZON TELESCOPE OBSERVATIONS

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

Kim, Junhan; Marrone, Daniel P.; Chan, Chi-Kwan

2016-12-01

The Event Horizon Telescope (EHT) is a millimeter-wavelength, very-long-baseline interferometry (VLBI) experiment that is capable of observing black holes with horizon-scale resolution. Early observations have revealed variable horizon-scale emission in the Galactic Center black hole, Sagittarius A* (Sgr A*). Comparing such observations to time-dependent general relativistic magnetohydrodynamic (GRMHD) simulations requires statistical tools that explicitly consider the variability in both the data and the models. We develop here a Bayesian method to compare time-resolved simulation images to variable VLBI data, in order to infer model parameters and perform model comparisons. We use mock EHT data based on GRMHD simulations to explore themore » robustness of this Bayesian method and contrast it to approaches that do not consider the effects of variability. We find that time-independent models lead to offset values of the inferred parameters with artificially reduced uncertainties. Moreover, neglecting the variability in the data and the models often leads to erroneous model selections. We finally apply our method to the early EHT data on Sgr A*.« less

Omnibus Tests for Interactions in Repeated Measures Designs with Dichotomous Dependent Variables.

ERIC Educational Resources Information Center

Serlin, Ronald C.; Marascuilo, Leonard A.

When examining a repeated measures design with independent groups for a significant group by trial interaction, classical analysis of variance or multivariate procedures can be used if the assumptions underlying the tests are met. Neither procedure may be justified for designs with small sample sizes and dichotomous dependent variables. An omnibus…

Modeling Time-Dependent Association in Longitudinal Data: A Lag as Moderator Approach

ERIC Educational Resources Information Center

Selig, James P.; Preacher, Kristopher J.; Little, Todd D.

2012-01-01

We describe a straightforward, yet novel, approach to examine time-dependent association between variables. The approach relies on a measurement-lag research design in conjunction with statistical interaction models. We base arguments in favor of this approach on the potential for better understanding the associations between variables by…

A Novel Information-Theoretic Approach for Variable Clustering and Predictive Modeling Using Dirichlet Process Mixtures

PubMed Central

Chen, Yun; Yang, Hui

2016-01-01

In the era of big data, there are increasing interests on clustering variables for the minimization of data redundancy and the maximization of variable relevancy. Existing clustering methods, however, depend on nontrivial assumptions about the data structure. Note that nonlinear interdependence among variables poses significant challenges on the traditional framework of predictive modeling. In the present work, we reformulate the problem of variable clustering from an information theoretic perspective that does not require the assumption of data structure for the identification of nonlinear interdependence among variables. Specifically, we propose the use of mutual information to characterize and measure nonlinear correlation structures among variables. Further, we develop Dirichlet process (DP) models to cluster variables based on the mutual-information measures among variables. Finally, orthonormalized variables in each cluster are integrated with group elastic-net model to improve the performance of predictive modeling. Both simulation and real-world case studies showed that the proposed methodology not only effectively reveals the nonlinear interdependence structures among variables but also outperforms traditional variable clustering algorithms such as hierarchical clustering. PMID:27966581

A Novel Information-Theoretic Approach for Variable Clustering and Predictive Modeling Using Dirichlet Process Mixtures.

PubMed

Chen, Yun; Yang, Hui

2016-12-14

In the era of big data, there are increasing interests on clustering variables for the minimization of data redundancy and the maximization of variable relevancy. Existing clustering methods, however, depend on nontrivial assumptions about the data structure. Note that nonlinear interdependence among variables poses significant challenges on the traditional framework of predictive modeling. In the present work, we reformulate the problem of variable clustering from an information theoretic perspective that does not require the assumption of data structure for the identification of nonlinear interdependence among variables. Specifically, we propose the use of mutual information to characterize and measure nonlinear correlation structures among variables. Further, we develop Dirichlet process (DP) models to cluster variables based on the mutual-information measures among variables. Finally, orthonormalized variables in each cluster are integrated with group elastic-net model to improve the performance of predictive modeling. Both simulation and real-world case studies showed that the proposed methodology not only effectively reveals the nonlinear interdependence structures among variables but also outperforms traditional variable clustering algorithms such as hierarchical clustering.

Compensation for Lithography Induced Process Variations during Physical Design

NASA Astrophysics Data System (ADS)

Chin, Eric Yiow-Bing

This dissertation addresses the challenge of designing robust integrated circuits in the deep sub micron regime in the presence of lithography process variability. By extending and combining existing process and circuit analysis techniques, flexible software frameworks are developed to provide detailed studies of circuit performance in the presence of lithography variations such as focus and exposure. Applications of these software frameworks to select circuits demonstrate the electrical impact of these variations and provide insight into variability aware compact models that capture the process dependent circuit behavior. These variability aware timing models abstract lithography variability from the process level to the circuit level and are used to estimate path level circuit performance with high accuracy with very little overhead in runtime. The Interconnect Variability Characterization (IVC) framework maps lithography induced geometrical variations at the interconnect level to electrical delay variations. This framework is applied to one dimensional repeater circuits patterned with both 90nm single patterning and 32nm double patterning technologies, under the presence of focus, exposure, and overlay variability. Studies indicate that single and double patterning layouts generally exhibit small variations in delay (between 1--3%) due to self compensating RC effects associated with dense layouts and overlay errors for layouts without self-compensating RC effects. The delay response of each double patterned interconnect structure is fit with a second order polynomial model with focus, exposure, and misalignment parameters with 12 coefficients and residuals of less than 0.1ps. The IVC framework is also applied to a repeater circuit with cascaded interconnect structures to emulate more complex layout scenarios, and it is observed that the variations on each segment average out to reduce the overall delay variation. The Standard Cell Variability Characterization (SCVC) framework advances existing layout-level lithography aware circuit analysis by extending it to cell-level applications utilizing a physically accurate approach that integrates process simulation, compact transistor models, and circuit simulation to characterize electrical cell behavior. This framework is applied to combinational and sequential cells in the Nangate 45nm Open Cell Library, and the timing response of these cells to lithography focus and exposure variations demonstrate Bossung like behavior. This behavior permits the process parameter dependent response to be captured in a nine term variability aware compact model based on Bossung fitting equations. For a two input NAND gate, the variability aware compact model captures the simulated response to an accuracy of 0.3%. The SCVC framework is also applied to investigate advanced process effects including misalignment and layout proximity. The abstraction of process variability from the layout level to the cell level opens up an entire new realm of circuit analysis and optimization and provides a foundation for path level variability analysis without the computationally expensive costs associated with joint process and circuit simulation. The SCVC framework is used with slight modification to illustrate the speedup and accuracy tradeoffs of using compact models. With variability aware compact models, the process dependent performance of a three stage logic circuit can be estimated to an accuracy of 0.7% with a speedup of over 50,000. Path level variability analysis also provides an accurate estimate (within 1%) of ring oscillator period in well under a second. Another significant advantage of variability aware compact models is that they can be easily incorporated into existing design methodologies for design optimization. This is demonstrated by applying cell swapping on a logic circuit to reduce the overall delay variability along a circuit path. By including these variability aware compact models in cell characterization libraries, design metrics such as circuit timing, power, area, and delay variability can be quickly assessed to optimize for the correct balance of all design metrics, including delay variability. Deterministic lithography variations can be easily captured using the variability aware compact models described in this dissertation. However, another prominent source of variability is random dopant fluctuations, which affect transistor threshold voltage and in turn circuit performance. The SCVC framework is utilized to investigate the interactions between deterministic lithography variations and random dopant fluctuations. Monte Carlo studies show that the output delay distribution in the presence of random dopant fluctuations is dependent on lithography focus and exposure conditions, with a 3.6 ps change in standard deviation across the focus exposure process window. This indicates that the electrical impact of random variations is dependent on systematic lithography variations, and this dependency should be included for precise analysis.

Moving Beyond Univariate Post-Hoc Testing in Exercise Science: A Primer on Descriptive Discriminate Analysis.

PubMed

Barton, Mitch; Yeatts, Paul E; Henson, Robin K; Martin, Scott B

2016-12-01

There has been a recent call to improve data reporting in kinesiology journals, including the appropriate use of univariate and multivariate analysis techniques. For example, a multivariate analysis of variance (MANOVA) with univariate post hocs and a Bonferroni correction is frequently used to investigate group differences on multiple dependent variables. However, this univariate approach decreases power, increases the risk for Type 1 error, and contradicts the rationale for conducting multivariate tests in the first place. The purpose of this study was to provide a user-friendly primer on conducting descriptive discriminant analysis (DDA), which is a post-hoc strategy to MANOVA that takes into account the complex relationships among multiple dependent variables. A real-world example using the Statistical Package for the Social Sciences syntax and data from 1,095 middle school students on their body composition and body image are provided to explain and interpret the results from DDA. While univariate post hocs increased the risk for Type 1 error to 76%, the DDA identified which dependent variables contributed to group differences and which groups were different from each other. For example, students in the very lean and Healthy Fitness Zone categories for body mass index experienced less pressure to lose weight, more satisfaction with their body, and higher physical self-concept than the Needs Improvement Zone groups. However, perceived pressure to gain weight did not contribute to group differences because it was a suppressor variable. Researchers are encouraged to use DDA when investigating group differences on multiple correlated dependent variables to determine which variables contributed to group differences.

[Bioacoustic of the advertisement call of Ceratophrys cranwelli (Anura: Ceratophryidae)].

PubMed

Valetti, Julián Alonso; Salas, Nancy Edith; Martino, Adolfo Ludovico

2013-03-01

The advertisement call plays an important role in the life history of anuran amphibians, mainly during the breeding season. Call features represent an important character to discriminate species, and sound emissions are very effective to assure or reinforce genetic incompatibility, especially in the case of sibling species. Since frogs are ectotherms, acoustic properties of their calls will vary with temperature. In this study, we described the advertisement call of C. cranwelli, quantifying the temperature effect on its components. The acoustic emissions were recorded during 2007 using a DAT record Sony TCD-100 with stereo microphone ECM-MS907 Sony and tape TDK DAT-RGX 60. As males emit their calls floating in temporary ponds, water temperatures were registered after recording the advertisement calls with a digital thermometer TES 1300+/-0.1 degreeC. Altogether, 54 calls from 18 males were analyzed. The temporal variables of each advertisement call were measured using oscillograms and sonograms and the analyses of dominant frequency were performed using a spectrogram. Multiple correlation analysis was used to identify the temperature-dependent acoustic variables and the temperature effect on these variables was quantified using linear regression models. The advertisement call of C. cranwelli consists of a single pulse group. Call duration, Pulse duration and Pulse interval decreased with the temperature, whereas the Pulse rate increased with temperature. The temperature-dependent variables were standardized at 25 degreeC according to the linear regression model obtained. The acoustic variables that were correlated with the temperature are the variables which emissions depend on laryngeal muscles and the temperature constraints the contractile properties of muscles. Our results indicated that temperature explains an important fraction of the variability in some acoustic variables (79% in the Pulse rate), and demonstrated the importance of considering the effect of temperature in acoustic components. The results suggest that acoustic variables show geographic variation to compare data with previous works.

Analysis of Lower Body Kinematic and Kinetic: Differences Between Age and Handicap in Golfers of Various Ages and Skill Levels

NASA Astrophysics Data System (ADS)

Smilensky, Alexander

The purpose of this thesis was to provide a preliminary analysis of lower body golf swing biomechanics. Fourteen golfers of various ages and handicaps performed 10 swings off a tee with their driver. This study focused on a number of dependent variables including lead knee joint flexion angles, internal/external rotations, valgus/varus angles, as well as ground reaction forces normalized to body weight (%BW), X-Factor angle and club head velocity. Dependent variables were analyzed at four specifically defined events (start, initiation of downswing, contact and swing termination). Simple linear regressions were performed using age and handicap as independent variables to see if patterns could be determined at any of the events. No significant trends or results were reported within our sample. An analysis of variance (ANOVA) was then used to examine the effect of event on specific dependent variables. A number of differences were reported within each of the variables across the four events. This study hoped to provide a more comprehensive understanding of the movement patterns occurring at the lower body with special focus on the lead knee.

Relationship of deer and moose populations to previous winters' snow

USGS Publications Warehouse

Mech, L.D.; McRoberts, R.E.; Peterson, R.O.; Page, R.E.

1987-01-01

(1) Linear regression was used to relate snow accumulation during single and consecutive winters with white-tailed deer (Odocoileus virginianus) fawn:doe ratios, mosse (Alces alces) twinning rates and calf:cow ratios, and annual changes in deer and moose populations. Significant relationships were found between snow accumulation during individual winters and these dependent variables during the following year. However, the strongest relationships were between the dependent variables and the sums of the snow accumulations over the previous three winters. The percentage of the variability explained was 36 to 51. (2) Significant relationships were also found between winter vulnerability of moose calves and the sum of the snow accumulations in the current, and up to seven previous, winters, with about 49% of the variability explained. (3) No relationship was found between wolf numbers and the above dependent variables. (4) These relationships imply that winter influences on maternal nutrition can accumulate for several years and that this cumulative effect strongly determines fecundity and/or calf and fawn survivability. Although wolf (Canis lupus L.) predation is the main direct mortality agent on fawns and calves, wolf density itself appears to be secondary to winter weather in influencing the deer and moose populations.

The Need for Speed in Rodent Locomotion Analyses

PubMed Central

Batka, Richard J.; Brown, Todd J.; Mcmillan, Kathryn P.; Meadows, Rena M.; Jones, Kathryn J.; Haulcomb, Melissa M.

2016-01-01

Locomotion analysis is now widely used across many animal species to understand the motor defects in disease, functional recovery following neural injury, and the effectiveness of various treatments. More recently, rodent locomotion analysis has become an increasingly popular method in a diverse range of research. Speed is an inseparable aspect of locomotion that is still not fully understood, and its effects are often not properly incorporated while analyzing data. In this hybrid manuscript, we accomplish three things: (1) review the interaction between speed and locomotion variables in rodent studies, (2) comprehensively analyze the relationship between speed and 162 locomotion variables in a group of 16 wild-type mice using the CatWalk gait analysis system, and (3) develop and test a statistical method in which locomotion variables are analyzed and reported in the context of speed. Notable results include the following: (1) over 90% of variables, reported by CatWalk, were dependent on speed with an average R2 value of 0.624, (2) most variables were related to speed in a nonlinear manner, (3) current methods of controlling for speed are insufficient, and (4) the linear mixed model is an appropriate and effective statistical method for locomotion analyses that is inclusive of speed-dependent relationships. Given the pervasive dependency of locomotion variables on speed, we maintain that valid conclusions from locomotion analyses cannot be made unless they are analyzed and reported within the context of speed. PMID:24890845

Normal forms of dispersive scalar Poisson brackets with two independent variables

NASA Astrophysics Data System (ADS)

Carlet, Guido; Casati, Matteo; Shadrin, Sergey

2018-03-01

We classify the dispersive Poisson brackets with one dependent variable and two independent variables, with leading order of hydrodynamic type, up to Miura transformations. We show that, in contrast to the case of a single independent variable for which a well-known triviality result exists, the Miura equivalence classes are parametrised by an infinite number of constants, which we call numerical invariants of the brackets. We obtain explicit formulas for the first few numerical invariants.

An Econometric Analysis of Volunteer Enlistments of Service and Cost Effectiveness Comparison of Service Incentive Programs

DTIC Science & Technology

1974-10-01

FIRST-TERM VOLUNTEER ENLISTMENTS WITH RESPECT TO UNEMPLOY - MENT RATES AND RECRUITING STRENGTH 3 Introduction 3 Findings of Previous Studies 4...variation in the dependent variable (volunteers per QMA) is not explained by the variation in the independent variables (relative wages, unemploy ...variable and one equation with an unemploy - ment variable. He found that the pay elasticity decreased from 1.77 to 1.01 with the addition of the

VeriML: A Dependently-Typed, User-Extensible and Language-Centric Approach to Proof Assistants

DTIC Science & Technology

2013-01-01

the locally nameless approach [McKinna and Pollack, 1993]. The former two techniques replace all variables by numbers, whereas the locally nameless ...needs to be reasoned about together with shifting. This complicates both the statements and proofs of related lemmas. The locally nameless approach...the locally nameless approach, we separate free variables from bound variables and use deBruijn indices for bound variables (denoted as bi in Table 3.1

Environmental and Water Quality Operational Studies: Proceedings of the DeGray Lake Symposium Held in Arkadelphia, Arkansas.

DTIC Science & Technology

1987-03-01

statistics for storm water quality variables and fractions of phosphorus, solids, and carbon are presented in Tables 7 and 8, respectively. The correlation...matrix and factor analysis (same method as used for baseflow) of storm water quality variables suggested three groups: Group I - TMG, TCA, TNA, TSI...models to predict storm water quality . The 11 static and 3 dynamic storm variables were used as potential dependent variables. All independent and

Learning a novel phonological contrast depends on interactions between individual differences and training paradigm design.

PubMed

Perrachione, Tyler K; Lee, Jiyeon; Ha, Louisa Y Y; Wong, Patrick C M

2011-07-01

Studies evaluating phonological contrast learning typically investigate either the predictiveness of specific pretraining aptitude measures or the efficacy of different instructional paradigms. However, little research considers how these factors interact--whether different students learn better from different types of instruction--and what the psychological basis for any interaction might be. The present study demonstrates that successfully learning a foreign-language phonological contrast for pitch depends on an interaction between individual differences in perceptual abilities and the design of the training paradigm. Training from stimuli with high acoustic-phonetic variability is generally thought to improve learning; however, we found high-variability training enhanced learning only for individuals with strong perceptual abilities. Learners with weaker perceptual abilities were actually impaired by high-variability training relative to a low-variability condition. A second experiment assessing variations on the high-variability training design determined that the property of this learning environment most detrimental to perceptually weak learners is the amount of trial-by-trial variability. Learners' perceptual limitations can thus override the benefits of high-variability training where trial-by-trial variability in other irrelevant acoustic-phonetic features obfuscates access to the target feature. These results demonstrate the importance of considering individual differences in pretraining aptitudes when evaluating the efficacy of any speech training paradigm. © 2011 Acoustical Society of America

Effects of lifetime tobacco, alcohol and drug use on psychological and behavioral problems among 10th grade students in Istanbul.

PubMed

Evren, Cuneyt; Evren, Bilge; Bozkurt, Muge; Ciftci-Demirci, Arzu

2015-11-01

The aim of this study was to determine the effects of life-time tobacco, alcohol, and substance use on psychological and behavioral variables among 10th grade students in Istanbul/Turkey. This study employed a cross-sectional online self-report survey conducted in 45 schools from the 15 districts in Istanbul. The questionnaire featured a section about use of substances, including tobacco, alcohol, and drugs. The depression, anxiety, anger, assertiveness, sensation seeking and impulsiveness subscales of the Psychological Screening Test for Adolescents (PSTA) were used. The analyses were conducted based on 4957 subjects. Logistic regression analyses were conducted with each school with the related and behavioral variables as the dependent variables. Gender, tobacco, alcohol, and drug use being the independent variables. All four independent variables predicted the dependent variables. Lifetime tobacco and drug use had significant effects on all the subscale score, whereas lifetime alcohol use had significant effects on all the subscale scores other than lack of assertiveness, and male gender was a significant covariant for all the subscale scores. Drug use showed the highest effect on dependent variables. Interaction was found between effects of tobacco and alcohol on anxiety, whereas interactions were found between effects of tobacco and drugs on lack of assertiveness and impulsiveness. The findings suggested that male students with lifetime tobacco, alcohol or drug use have particularly high risk of psychological and behavioral problems. The unique effects of substance clusters on these problems may be useful in developing secondary preventive practices for substance use and abuse problems in Istanbul.

Exploiting Data Missingness in Bayesian Network Modeling

NASA Astrophysics Data System (ADS)

Rodrigues de Morais, Sérgio; Aussem, Alex

This paper proposes a framework built on the use of Bayesian networks (BN) for representing statistical dependencies between the existing random variables and additional dummy boolean variables, which represent the presence/absence of the respective random variable value. We show how augmenting the BN with these additional variables helps pinpoint the mechanism through which missing data contributes to the classification task. The missing data mechanism is thus explicitly taken into account to predict the class variable using the data at hand. Extensive experiments on synthetic and real-world incomplete data sets reveals that the missingness information improves classification accuracy.

Including long-range dependence in integrate-and-fire models of the high interspike-interval variability of cortical neurons.

PubMed

Jackson, B Scott

2004-10-01

Many different types of integrate-and-fire models have been designed in order to explain how it is possible for a cortical neuron to integrate over many independent inputs while still producing highly variable spike trains. Within this context, the variability of spike trains has been almost exclusively measured using the coefficient of variation of interspike intervals. However, another important statistical property that has been found in cortical spike trains and is closely associated with their high firing variability is long-range dependence. We investigate the conditions, if any, under which such models produce output spike trains with both interspike-interval variability and long-range dependence similar to those that have previously been measured from actual cortical neurons. We first show analytically that a large class of high-variability integrate-and-fire models is incapable of producing such outputs based on the fact that their output spike trains are always mathematically equivalent to renewal processes. This class of models subsumes a majority of previously published models, including those that use excitation-inhibition balance, correlated inputs, partial reset, or nonlinear leakage to produce outputs with high variability. Next, we study integrate-and-fire models that have (nonPoissonian) renewal point process inputs instead of the Poisson point process inputs used in the preceding class of models. The confluence of our analytical and simulation results implies that the renewal-input model is capable of producing high variability and long-range dependence comparable to that seen in spike trains recorded from cortical neurons, but only if the interspike intervals of the inputs have infinite variance, a physiologically unrealistic condition. Finally, we suggest a new integrate-and-fire model that does not suffer any of the previously mentioned shortcomings. By analyzing simulation results for this model, we show that it is capable of producing output spike trains with interspike-interval variability and long-range dependence that match empirical data from cortical spike trains. This model is similar to the other models in this study, except that its inputs are fractional-gaussian-noise-driven Poisson processes rather than renewal point processes. In addition to this model's success in producing realistic output spike trains, its inputs have long-range dependence similar to that found in most subcortical neurons in sensory pathways, including the inputs to cortex. Analysis of output spike trains from simulations of this model also shows that a tight balance between the amounts of excitation and inhibition at the inputs to cortical neurons is not necessary for high interspike-interval variability at their outputs. Furthermore, in our analysis of this model, we show that the superposition of many fractional-gaussian-noise-driven Poisson processes does not approximate a Poisson process, which challenges the common assumption that the total effect of a large number of inputs on a neuron is well represented by a Poisson process.

Gender effects in gaming research: a case for regression residuals?

PubMed

Pfister, Roland

2011-10-01

Numerous recent studies have examined the impact of video gaming on various dependent variables, including the players' affective reactions, positive as well as detrimental cognitive effects, and real-world aggression. These target variables are typically analyzed as a function of game characteristics and player attributes-especially gender. However, findings on the uneven distribution of gaming experience between males and females, on the one hand, and the effect of gaming experience on several target variables, on the other hand, point at a possible confound when gaming experiments are analyzed with a standard analysis of variance. This study uses simulated data to exemplify analysis of regression residuals as a potentially beneficial data analysis strategy for such datasets. As the actual impact of gaming experience on each of the various dependent variables differs, the ultimate benefits of analysis of regression residuals entirely depend on the research question, but it offers a powerful statistical approach to video game research whenever gaming experience is a confounding factor.

Children's reasons for living, self-esteem, and violence.

PubMed

Merwin, Rhonda M; Ellis, Jon B

2004-01-01

Attitudes toward violence and reasons for living in young adolescents with high, moderate, and low self-esteem were examined. The authors devised an Attitudes Toward Violence questionnaire; the Rosenberg's Self-esteem Scale (RSE) and the Brief Reasons for Living in Adolescents (BRFL-A) was used to assess adaptive characteristics. The independent variables were gender and self-esteem. The dependent variables were total Reasons for Living score and Attitudes Toward Violence score. Participants included 138 boys and 95 girls, ages 11 to 15 years (M = 13.3) from a city middle school. The results showed that for the dependent variable attitudes toward violence, main effects were found for both gender and self-esteem. For the dependent variable reasons for living, a main effect was found for self-esteem but not for gender. An inverse relationship was found between violence and reasons for living. Being male and low self-esteem emerged as predictors of more accepting attitudes toward violence. Low self-esteem was significantly related to fewer reasons for living.

Eta Squared and Partial Eta Squared as Measures of Effect Size in Educational Research

ERIC Educational Resources Information Center

Richardson, John T. E.

2011-01-01

Eta squared measures the proportion of the total variance in a dependent variable that is associated with the membership of different groups defined by an independent variable. Partial eta squared is a similar measure in which the effects of other independent variables and interactions are partialled out. The development of these measures is…

Diagnoses as Moderators of the Relationship Between Biographical Variables and Psychiatric Decision in a Combat Zone

ERIC Educational Resources Information Center

Clum, George A.; Hoiberg, Anne

1971-01-01

The decision to return a man to combat duty was found to be related to biographical variables, and the nature of these relationships were found to have significant reliability. Also, evidence suggested that biographical variables were salient depending on whether the diagnostic group was character disorder or neurotic. (Author)

The Inevitable War?

DTIC Science & Technology

2011-05-20

69 67 Alan Bryman and Emma Bell , Business Research Methods, 2 ed. (Oxford: Oxford...University Press, USA, 2007), 727. Bryam and Bell define a dependant variable as “ a variable that is causally influenced by another variable.” As the...Pushing-for-Yuan-to-be-Global- Currency-But-Business-Leaders-Say-Not-Yet-114475409.html (accessed April 6, 2011). Bryman , Alan, and Emma Bell

Can Dynamic Visualizations with Variable Control Enhance the Acquisition of Intuitive Knowledge?

ERIC Educational Resources Information Center

Wichmann, Astrid; Timpe, Sebastian

2015-01-01

An important feature of inquiry learning is to take part in science practices including exploring variables and testing hypotheses. Computer-based dynamic visualizations have the potential to open up various exploration possibilities depending on the level of learner control. It is assumed that variable control, e.g., by changing parameters of a…

A Method for Evaluating Tuning Functions of Single Neurons based on Mutual Information Maximization

NASA Astrophysics Data System (ADS)

Brostek, Lukas; Eggert, Thomas; Ono, Seiji; Mustari, Michael J.; Büttner, Ulrich; Glasauer, Stefan

2011-03-01

We introduce a novel approach for evaluation of neuronal tuning functions, which can be expressed by the conditional probability of observing a spike given any combination of independent variables. This probability can be estimated out of experimentally available data. By maximizing the mutual information between the probability distribution of the spike occurrence and that of the variables, the dependence of the spike on the input variables is maximized as well. We used this method to analyze the dependence of neuronal activity in cortical area MSTd on signals related to movement of the eye and retinal image movement.

The Relationship of Field Dependent/Independent Cognitive Styles, Stimuli Variability and Time Factor on Student Achievement.

ERIC Educational Resources Information Center

Atang, Christopher I.

The effects of black and white and color illustrations on student achievement were studied to investigate the relationships between cognitive styles and instructional design. Field dependence (FD) and field independence (FI) were chosen as the cognitive style variables. Subjects were 85 freshman students in the Iowa State University Psychology…

Distribution of Personal Income in Agriculture-Dependent Counties of Midwestern States: A Policy Variables Approach.

ERIC Educational Resources Information Center

Goreham, Gary A.; And Others

Significant social, demographic, and economic changes have occurred in the North Central states since 1960. This document examines structural and policy variables related to distribution of income, during the years 1960-80 in the 397 counties defined as agriculture-dependent in 13 North Central states. Personal income distribution has been…

Social support at work and leisure time and its association with self-rated health and sickness absence.

PubMed

Falkenberg, A; Nyfjäll, M; Hellgren, C; Vingård, E

2012-01-01

The aim of this longitudinal study is to investigate how different aspects of social support at work and in leisure time are associated with self rated health and sickness absence. The 541 participants in the study were representative for a working population in the public sector in Sweden with a majority being woman. Most of the variables were created from data from a questionnaire in March-April 2005. There were four independent variables and two dependent variables. The dependent were based on data from November 2006. A logistic regression model was used for the analysis of associations. A separate model was adapted for each of the explanatory variables for each outcome, which gave five models per independent variable. The study has given a greater awareness of the importance of employees receiving social support, regardless of type of support or from whom the support is coming. Social support has a strong association with SRH in a longitudinal perspective and no association between social support and sickness absence.

Somatotype in high performance female netball players may influence player position and the incidence of lower limb and back injuries

PubMed Central

Hopper, Diana M

1997-01-01

Aims To investigate the relation between somatotype, performance characteristics, and the incidence of injury during the Australian Netball Championships. Method Two hundred and forty high performance netball players competed at the Australian Netball Championships in which 213 (89%) were measured using the Heath-Carter somatotype scale. During these championships, in conjunction with the injury assessments, data analysis included a three factor analysis of variance (level of competition, playing position, and injury) for the dependent somatoype variables (endomorphy, mesomorphy, and ectopmorphy), and the level of significance was set at 0.05. Results For the three dependent somatotype variables, there were no main effects between endomorphy, mesomorphy, and ectopmorphy and the incidence of injury. However, for the mesomorphy and ectomorphy variables, significant main effects for the playing position were found. No main effects existed between the somatotype variables and levels of competition. Conclusion The somatotype variables did not influence the incidence of injury, but mesomorphy and ectopmorphy did influence the different playing positions. PMID:9298552

On the Temporal Variability of Low-Mode Internal Tides in the Deep Ocean

NASA Technical Reports Server (NTRS)

Ray, Richard D.; Zaron, E. D.

2010-01-01

In situ measurements of internal tides are typically characterized by high temporal variability, with strong dependence on stratification, mesoscale eddies, and background currents commonly observed. Thus, it is surprising to find phase-locked internal tides detectable by satellite altimetry. An important question is how much tidal variability is missed by altimetry. We address this question in several ways. We subset the altimetry by season and find only very small changes -- an important exception being internal tides in the South China Sea where we observe strong seasonal dependence. A wavenumber-domain analysis confirms that throughout most of the global ocean there is little temporal variability in altimetric internal-tide signals, at least in the first baroclinic mode, which is the mode that dominates surface elevation. The analysis shows higher order modes to be significantly more variable. The results of this study have important practical implications for the anticipated SWOT wide-swath altimeter mission, for which removal of internal tide signals is critical for observing non-tidal submesoscale phenomena.

Operator- and software-related post-experimental variability and source of error in 2-DE analysis.

PubMed

Millioni, Renato; Puricelli, Lucia; Sbrignadello, Stefano; Iori, Elisabetta; Murphy, Ellen; Tessari, Paolo

2012-05-01

In the field of proteomics, several approaches have been developed for separating proteins and analyzing their differential relative abundance. One of the oldest, yet still widely used, is 2-DE. Despite the continuous advance of new methods, which are less demanding from a technical standpoint, 2-DE is still compelling and has a lot of potential for improvement. The overall variability which affects 2-DE includes biological, experimental, and post-experimental (software-related) variance. It is important to highlight how much of the total variability of this technique is due to post-experimental variability, which, so far, has been largely neglected. In this short review, we have focused on this topic and explained that post-experimental variability and source of error can be further divided into those which are software-dependent and those which are operator-dependent. We discuss these issues in detail, offering suggestions for reducing errors that may affect the quality of results, summarizing the advantages and drawbacks of each approach.

Constraining Dust Hazes at the L/T Transition via Variability

NASA Astrophysics Data System (ADS)

Radigan, Jacqueline; Apai, Daniel; Yang, Hao; Hiranaka, Kay; Cruz, Kelle; Buenzli, Esther; Marley, Mark

2014-12-01

The T2 dwarf SIMP 1629+03 is a variable L/T transition dwarf, with a normal near-infrared spectrum. However, it is remarkable in that the wavelength dependence of its variability differs markedly from that of other L/T transition brown dwarfs. In particular, the absence of a water absorption feature in its variability spectrum indicates that a patchy, high-altitude haze, rather than a deeper cloud layer is responsible for the observed variations. We propose to obtain Spitzer+HST observations of SIMP1629+02 over two consecutive rotations periods in order to simultaneously map it?s spectral variability across 1-5 um. The wide wavelength coverage will provide a suitable lever-arm for constraining the particle size distribution in the haze. A truly flat spectrum across this wavelength range would indicate large particle sizes in comparison to those inferred for red L-dwarf hazes, and would therefore provide direct evidence of grain growth with decreasing effective temperature and/or a grain-size dependence on surface gravity in brown dwarf atmospheres.

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.

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.

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

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

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

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.

Ensemble X-ray variability of active galactic nuclei. II. Excess variance and updated structure function

NASA Astrophysics Data System (ADS)

Vagnetti, F.; Middei, R.; Antonucci, M.; Paolillo, M.; Serafinelli, R.

2016-09-01

Context. Most investigations of the X-ray variability of active galactic nuclei (AGN) have been concentrated on the detailed analyses of individual, nearby sources. A relatively small number of studies have treated the ensemble behaviour of the more general AGN population in wider regions of the luminosity-redshift plane. Aims: We want to determine the ensemble variability properties of a rich AGN sample, called Multi-Epoch XMM Serendipitous AGN Sample (MEXSAS), extracted from the fifth release of the XMM-Newton Serendipitous Source Catalogue (XMMSSC-DR5), with redshift between ~0.1 and ~5, and X-ray luminosities in the 0.5-4.5 keV band between ~1042 erg/s and ~1047 erg/s. Methods: We urge caution on the use of the normalised excess variance (NXS), noting that it may lead to underestimate variability if used improperly. We use the structure function (SF), updating our previous analysis for a smaller sample. We propose a correction to the NXS variability estimator, taking account of the light curve duration in the rest frame on the basis of the knowledge of the variability behaviour gained by SF studies. Results: We find an ensemble increase of the X-ray variability with the rest-frame time lag τ, given by SF ∝ τ0.12. We confirm an inverse dependence on the X-ray luminosity, approximately as SF ∝ LX-0.19. We analyse the SF in different X-ray bands, finding a dependence of the variability on the frequency as SF ∝ ν-0.15, corresponding to a so-called softer when brighter trend. In turn, this dependence allows us to parametrically correct the variability estimated in observer-frame bands to that in the rest frame, resulting in a moderate (≲15%) shift upwards (V-correction). Conclusions: Ensemble X-ray variability of AGNs is best described by the structure function. An improper use of the normalised excess variance may lead to an underestimate of the intrinsic variability, so that appropriate corrections to the data or the models must be applied to prevent these effects. Full Table 1 is 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/593/A55

Religiosity and decreased risk of substance use disorders: is the effect mediated by social support or mental health status?

PubMed Central

Harris, Katherine M.; Koenig, Harold G.; Han, Xiaotong; Sullivan, Greer; Mattox, Rhonda; Tang, Lingqi

2009-01-01

Objective The negative association between religiosity (religious beliefs and church attendance) and the likelihood of substance use disorders is well established, but the mechanism(s) remain poorly understood. We investigated whether this association was mediated by social support or mental health status. Method We utilized cross-sectional data from the 2002 National Survey on Drug Use and Health (n = 36,370). We first used logistic regression to regress any alcohol use in the past year on sociodemographic and religiosity variables. Then, among individuals who drank in the past year, we regressed past year alcohol abuse/dependence on sociodemographic and religiosity variables. To investigate whether social support mediated the association between religiosity and alcohol use and alcohol abuse/dependence we repeated the above models, adding the social support variables. To the extent that these added predictors modified the magnitude of the effect of the religiosity variables, we interpreted social support as a possible mediator. We also formally tested for mediation using path analysis. We investigated the possible mediating role of mental health status analogously. Parallel sets of analyses were conducted for any drug use, and drug abuse/dependence among those using any drugs as the dependent variables. Results The addition of social support and mental health status variables to logistic regression models had little effect on the magnitude of the religiosity coefficients in any of the models. While some of the tests of mediation were significant in the path analyses, the results were not always in the expected direction, and the magnitude of the effects was small. Conclusions The association between religiosity and decreased likelihood of a substance use disorder does not appear to be substantively mediated by either social support or mental health status. PMID:19714282

Stress and Supports to Families with a Handicapped Child [and] Adjustment of Families with Handicapped Children.

ERIC Educational Resources Information Center

McDonald, Linda; And Others

The paper explores the impact of child variables, parent variables, and family resources (professional and informal supports) on the family's ability to cope with a child with special needs. Child variables include child gender, birth order, severity of handicap, degree of child dependency, extent of attachment, age of the child, and presence of…

Dynamic Quantum Allocation and Swap-Time Variability in Time-Sharing Operating Systems.

ERIC Educational Resources Information Center

Bhat, U. Narayan; Nance, Richard E.

The effects of dynamic quantum allocation and swap-time variability on central processing unit (CPU) behavior are investigated using a model that allows both quantum length and swap-time to be state-dependent random variables. Effective CPU utilization is defined to be the proportion of a CPU busy period that is devoted to program processing, i.e.…

An Analysis of Programmatic Variables Relating to the Pass Rates on the Licensure Examination by Practical Nurses in Tennessee Technology Centers

ERIC Educational Resources Information Center

Simpson, Janis Lee

2013-01-01

The purpose of this quantitative research study was to determine the degree to which Licensed Practical Nursing programmatic variables positively correlate with select Tennessee Technology Center institution pass rates on the licensure examination--NCLEX-PNRTM. This study investigated the relationship between the dependent variable of NCLEX-PNRTM…

Exploring the Influence of Select Demographic, Academic, and Athletic Variables on the Retention of Student-Athletes

ERIC Educational Resources Information Center

Johnson, James E.; Wessel, Roger D.; Pierce, David A.

2013-01-01

The population of 674 first-year student-athletes culled from 5 successive freshman classes (2004-2008) at a mid-size midwestern university was examined to determine what combination of demographic, academic, and athletic variables best predicted retention into the 2nd academic year. The dependent variable of retention was chosen because it is a…

The effect of workstation and task variables on forces applied during simulated meat cutting.

PubMed

McGorry, Raymond W; Dempsey, Patrick G; O'Brien, Niall V

2004-12-01

The purpose of the study was to investigate factors related to force and postural exposure during a simulated meat cutting task. The hypothesis was that workstation, tool and task variables would affect the dependent kinetic variables of gripping force, cutting moment and the dependent kinematic variables of elbow elevation and wrist angular displacement in the flexion/extension and radial/ulnar deviation planes. To evaluate this hypothesis a 3 x 3 x 2 x 2 x 2 (surface orientation by surface height by blade angle by cut complexity by work pace) within-subject factorial design was conducted with 12 participants. The results indicated that the variables can act and interact to modify the kinematics and kinetics of a cutting task. Participants used greater grip force and cutting moment when working at a pace based on productivity. The interactions of the work surface height and orientation indicated that the use of an adjustable workstation could minimize wrist deviation from neutral and improve shoulder posture during cutting operations. Angling the knife blade also interacted with workstation variables to improve wrist and upper extremity posture, but this benefit must be weighed against the potential for small increases in force exposure.

Aircrew coordination and decisionmaking: Peer ratings of video tapes made during a full mission simulation

NASA Technical Reports Server (NTRS)

Murphy, M. R.; Awe, C. A.

1986-01-01

Six professionally active, retired captains rated the coordination and decisionmaking performances of sixteen aircrews while viewing videotapes of a simulated commercial air transport operation. The scenario featured a required diversion and a probable minimum fuel situation. Seven point Likert-type scales were used in rating variables on the basis of a model of crew coordination and decisionmaking. The variables were based on concepts of, for example, decision difficulty, efficiency, and outcome quality; and leader-subordin ate concepts such as person and task-oriented leader behavior, and competency motivation of subordinate crewmembers. Five-front-end variables of the model were in turn dependent variables for a hierarchical regression procedure. The variance in safety performance was explained 46%, by decision efficiency, command reversal, and decision quality. The variance of decision quality, an alternative substantive dependent variable to safety performance, was explained 60% by decision efficiency and the captain's quality of within-crew communications. The variance of decision efficiency, crew coordination, and command reversal were in turn explained 78%, 80%, and 60% by small numbers of preceding independent variables. A principle component, varimax factor analysis supported the model structure suggested by regression analyses.

Bilinear Forms and Soliton Solutions for the Reduced Maxwell-Bloch Equations with Variable Coefficients in Nonlinear Optics

NASA Astrophysics Data System (ADS)

Chai, Jun; Tian, Bo; Chai, Han-Peng

2018-02-01

Investigation in this paper is given to the reduced Maxwell-Bloch equations with variable coefficients, describing the propagation of the intense ultra-short optical pulses through an inhomogeneous two-level dielectric medium. We apply the Hirota method and symbolic computation to study such equations. With the help of the dependent variable transformations, we present the variable-coefficient-dependent bilinear forms. Then, we construct the one-, two- and N-soliton solutions in analytic forms for them. Supported by the National Natural Science Foundation of China under Grant Nos. 11772017, 11272023, 11471050, the Fund of State Key Laboratory of Information Photonics and Optical Communications (Beijing University of Posts and Telecommunications), China (IPOC: 2017ZZ05), and the Fundamental Research Funds for the Central Universities of China under Grant No. 2011BUPTYB02

[Hydrologic variability and sensitivity based on Hurst coefficient and Bartels statistic].

PubMed

Lei, Xu; Xie, Ping; Wu, Zi Yi; Sang, Yan Fang; Zhao, Jiang Yan; Li, Bin Bin

2018-04-01

Due to the global climate change and frequent human activities in recent years, the pure stochastic components of hydrological sequence is mixed with one or several of the variation ingredients, including jump, trend, period and dependency. It is urgently needed to clarify which indices should be used to quantify the degree of their variability. In this study, we defined the hydrological variability based on Hurst coefficient and Bartels statistic, and used Monte Carlo statistical tests to test and analyze their sensitivity to different variants. When the hydrological sequence had jump or trend variation, both Hurst coefficient and Bartels statistic could reflect the variation, with the Hurst coefficient being more sensitive to weak jump or trend variation. When the sequence had period, only the Bartels statistic could detect the mutation of the sequence. When the sequence had a dependency, both the Hurst coefficient and the Bartels statistics could reflect the variation, with the latter could detect weaker dependent variations. For the four variations, both the Hurst variability and Bartels variability increased with the increases of variation range. Thus, they could be used to measure the variation intensity of the hydrological sequence. We analyzed the temperature series of different weather stations in the Lancang River basin. Results showed that the temperature of all stations showed the upward trend or jump, indicating that the entire basin had experienced warming in recent years and the temperature variability in the upper and lower reaches was much higher. This case study showed the practicability of the proposed method.

Analysis of Setting Efficacy in Young Male and Female Volleyball Players.

PubMed

González-Silva, Jara; Domínguez, Alberto Moreno; Fernández-Echeverría, Carmen; Rabaz, Fernando Claver; Arroyo, M Perla Moreno

2016-12-01

The main objective of this study was to analyse the variables that predicted setting efficacy in complex I (KI) in volleyball, in formative categories and depending on gender. The study sample was comprised of 5842 game actions carried out by the 16 male category and the 18 female category teams that participated in the Under-16 Spanish Championship. The dependent variable was setting efficacy. The independent variables were grouped into: serve variables (a serve zone, the type of serve, striking technique, an in-game role of the server and serve direction), reception variables (a reception zone, a receiver player and reception efficacy) and setting variables (a setter's position, a setting zone, the type of a set, setting technique, a set's area and tempo of a set). Multinomial logistic regression showed that the best predictive variables of setting efficacy, both in female and male categories, were reception efficacy, setting technique and tempo of a set. In the male category, the jump serve was the greatest predictor of setting efficacy, while in the female category, it was the set's area. Therefore, in the male category, it was not only the preceding action that affected setting efficacy, but also the serve. On the contrary, in the female category, only variables of the action itself and of the previous action, reception, affected setting efficacy. The results obtained in the present study should be taken into account in the training process of both male and female volleyball players in formative stages.

The spatial and temporal variability of groundwater recharge in a forested basin in northern Wisconsin

USGS Publications Warehouse

Dripps, W.R.; Bradbury, K.R.

2010-01-01

Recharge varies spatially and temporally as it depends on a wide variety of factors (e.g. vegetation, precipitation, climate, topography, geology, and soil type), making it one of the most difficult, complex, and uncertain hydrologic parameters to quantify. Despite its inherent variability, groundwater modellers, planners, and policy makers often ignore recharge variability and assume a single average recharge value for an entire watershed. Relatively few attempts have been made to quantify or incorporate spatial and temporal recharge variability into water resource planning or groundwater modelling efforts. In this study, a simple, daily soil-water balance model was developed and used to estimate the spatial and temporal distribution of groundwater recharge of the Trout Lake basin of northern Wisconsin for 1996-2000 as a means to quantify recharge variability. For the 5 years of study, annual recharge varied spatially by as much as 18 cm across the basin; vegetation was the predominant control on this variability. Recharge also varied temporally with a threefold annual difference over the 5-year period. Intra-annually, recharge was limited to a few isolated events each year and exhibited a distinct seasonal pattern. The results suggest that ignoring recharge variability may not only be inappropriate, but also, depending on the application, may invalidate model results and predictions for regional and local water budget calculations, water resource management, nutrient cycling, and contaminant transport studies. Recharge is spatially and temporally variable, and should be modelled as such. Copyright ?? 2009 John Wiley & Sons, Ltd.

An Analysis of a Contingency Program on Designated Drivers at a College Bar

ERIC Educational Resources Information Center

Kazbour, Richard R.; Bailey, Jon S.

2010-01-01

The present study evaluated the effects of prompts and incentives on designated drivers in a bar. We defined the dependent variable as the percentage of customers either functioning as or riding with a designated driver. We used an ABCA design to evaluate the effectiveness of prompts and incentives on the dependent variable. Results indicated that…

Inventory implications of using sampling variances in estimation of growth model coefficients

Treesearch

Albert R. Stage; William R. Wykoff

2000-01-01

Variables based on stand densities or stocking have sampling errors that depend on the relation of tree size to plot size and on the spatial structure of the population, ignoring the sampling errors of such variables, which include most measures of competition used in both distance-dependent and distance-independent growth models, can bias the predictions obtained from...

Evaluation of Confluence Model Variables on IQ and Achievement Test Scores in a Sample of 6- to 11-Year-Old Children.

ERIC Educational Resources Information Center

Svanum, Soren; Bringle, Robert G.

1980-01-01

The confluence model of cognitive development was tested on 7,060 children. Family size, sibling order within family sizes, and hypothesized age-dependent effects were tested. Findings indicated an inverse relationship between family size and the cognitive measures; age-dependent effects and other confluence variables were found to be…

Computational motor control: feedback and accuracy.

PubMed

Guigon, Emmanuel; Baraduc, Pierre; Desmurget, Michel

2008-02-01

Speed/accuracy trade-off is a ubiquitous phenomenon in motor behaviour, which has been ascribed to the presence of signal-dependent noise (SDN) in motor commands. Although this explanation can provide a quantitative account of many aspects of motor variability, including Fitts' law, the fact that this law is frequently violated, e.g. during the acquisition of new motor skills, remains unexplained. Here, we describe a principled approach to the influence of noise on motor behaviour, in which motor variability results from the interplay between sensory and motor execution noises in an optimal feedback-controlled system. In this framework, we first show that Fitts' law arises due to signal-dependent motor noise (SDN(m)) when sensory (proprioceptive) noise is low, e.g. under visual feedback. Then we show that the terminal variability of non-visually guided movement can be explained by the presence of signal-dependent proprioceptive noise. Finally, we show that movement accuracy can be controlled by opposite changes in signal-dependent sensory (SDN(s)) and SDN(m), a phenomenon that could be ascribed to muscular co-contraction. As the model also explains kinematics, kinetics, muscular and neural characteristics of reaching movements, it provides a unified framework to address motor variability.

Spatiotemporal Dependency of Age-Related Changes in Brain Signal Variability

PubMed Central

McIntosh, A. R.; Vakorin, V.; Kovacevic, N.; Wang, H.; Diaconescu, A.; Protzner, A. B.

2014-01-01

Recent theoretical and empirical work has focused on the variability of network dynamics in maturation. Such variability seems to reflect the spontaneous formation and dissolution of different functional networks. We sought to extend these observations into healthy aging. Two different data sets, one EEG (total n = 48, ages 18–72) and one magnetoencephalography (n = 31, ages 20–75) were analyzed for such spatiotemporal dependency using multiscale entropy (MSE) from regional brain sources. In both data sets, the changes in MSE were timescale dependent, with higher entropy at fine scales and lower at more coarse scales with greater age. The signals were parsed further into local entropy, related to information processed within a regional source, and distributed entropy (information shared between two sources, i.e., functional connectivity). Local entropy increased for most regions, whereas the dominant change in distributed entropy was age-related reductions across hemispheres. These data further the understanding of changes in brain signal variability across the lifespan, suggesting an inverted U-shaped curve, but with an important qualifier. Unlike earlier in maturation, where the changes are more widespread, changes in adulthood show strong spatiotemporal dependence. PMID:23395850

Flippin' Fluid Mechanics - Quasi-experimental Pre-test and Post-test Comparison Using Two Groups

NASA Astrophysics Data System (ADS)

Webster, D. R.; Majerich, D. M.; Luo, J.

2014-11-01

A flipped classroom approach has been implemented in an undergraduate fluid mechanics course. Students watch short on-line videos before class, participate in active in-class problem solving (in dyads), and complete individualized on-line quizzes weekly. In-class activities are designed to achieve a trifecta of: 1. developing problem solving skills, 2. learning subject content, and 3. developing inquiry skills. The instructor and assistants provide critical ``just-in-time tutoring'' during the in-class problem solving sessions. Comparisons are made with a simultaneous section offered in a traditional mode by a different instructor. Regression analysis was used to control for differences among students and to quantify the effect of the flipped fluid mechanics course. The dependent variable was the students' combined final examination and post-concept inventory scores and the independent variables were pre-concept inventory score, gender, major, course section, and (incoming) GPA. The R-square equaled 0.45 indicating that the included variables explain 45% of the variation in the dependent variable. The regression results indicated that if the student took the flipped fluid mechanics course, the dependent variable (i.e., combined final exam and post-concept inventory scores) was raised by 7.25 points. Interestingly, the comparison group reported significantly more often that their course emphasized memorization than did the flipped classroom group.

A Preliminary Investigation of the Predictors of Tanning Dependence

PubMed Central

Heckman, Carolyn J.; Egleston, Brian L.; Wilson, Diane B.; Ingersoll, Karen S.

2014-01-01

Objectives To investigate possible predictors of tanning dependence including demographic variables, exposure and protective behaviors, and other health-related behaviors. Methods This study consisted of an online survey of 400 students and other volunteers from a university community. Results Twenty-seven percent of the sample was classified as tanning dependent. Tanning dependence was predicted by ethnicity and skin type, indoor and outdoor tanning and burning, and lower skin protective behaviors, as well as smoking and body mass index. Conclusions Young adults are at risk for tanning dependence, which can be predicted by specific demographic and behavioral variables. PMID:18241130

Host-dependent variables: The missing link to personalized medicine.

PubMed

Demlova, Regina; Zdrazilova-Dubska, Lenka; Sterba, Jaroslav; Stanta, Giorgio; Valik, Dalibor

2018-04-26

Individualized medicine has the potential to tailor anticancer therapy with the best response and highest safety margin to provide better patient care. However, modern targeted therapies are still being tested through clinical trials comparing preselected patient cohorts and assessed upon behaviour of group averages. Clinically manifesting malignant disease requires identification of host- and tumour-dependent variables such as biological characteristics of the tumour and its microenvironment including immune response features, and overall capacity of the host to receive, tolerate and efficiently utilize treatment. Contemporary medical oncology including clinical trial design need to refocus from assessing group averages to individuality taking into consideration time dependent host-associated characteristics and reinventing outliers to be appreciated as naturally occurring variables collectively determining the ultimate outcome of malignant disease. Copyright © 2018. Published by Elsevier Ltd.

Effect of Native American ancestry on iron-related phenotypes of Alabama hemochromatosis probands with HFE C282Y homozygosity

PubMed Central

Barton, James C; Barton, Ellen H; Acton, Ronald T

2006-01-01

Background In age-matched cohorts of screening study participants recruited from primary care clinics, mean serum transferrin saturation values were significantly lower and mean serum ferritin concentrations were significantly higher in Native Americans than in whites. Twenty-eight percent of 80 Alabama white hemochromatosis probands with HFE C282Y homozygosity previously reported having Native American ancestry, but the possible effect of this ancestry on hemochromatosis phenotypes was unknown. Methods We compiled observations in these 80 probands and used univariate and multivariate methods to analyze associations of age, sex, Native American ancestry (as a dichotomous variable), report of ethanol consumption (as a dichotomous variable), percentage transferrin saturation and loge serum ferritin concentration at diagnosis, quantities of iron removed by phlebotomy to achieve iron depletion, and quantities of excess iron removed by phlebotomy. Results In a univariate analysis in which probands were grouped by sex, there were no significant differences in reports of ethanol consumption, transferrin saturation, loge serum ferritin concentration, quantities of iron removed to achieve iron depletion, and quantities of excess iron removed by phlebotomy in probands who reported Native American ancestry than in those who did not. In multivariate analyses, transferrin saturation (as a dependent variable) was not significantly associated with any of the available variables, including reports of Native American ancestry and ethanol consumption. The independent variable quantities of excess iron removed by phlebotomy was significantly associated with loge serum ferritin used as a dependent variable (p < 0.0001), but not with reports of Native American ancestry or reports of ethanol consumption. Loge serum ferritin was the only independent variable significantly associated with quantities of excess iron removed by phlebotomy used as a dependent variable (p < 0.0001) (p < 0.0001; ANOVA of regression). Conclusion We conclude that the iron-related phenotypes of hemochromatosis probands with HFE C282Y homozygosity are similar in those with and without Native American ancestry reports. PMID:16533407

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.

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.

Low adolescent self-esteem leads to multiple interpersonal problems: a test a social-adaptation theory.

PubMed

Kahle, L R; Kulka, R A; Klingel, D M

1980-09-01

This article reports the results of a study that annually monitored the self-esteem and interpersonal problems of over 100 boys during their sophomore, junior, and senior years of high school. Cross-lagged panel correlation differences show that low self-esteem leads to interpersonal problems in all three time lags when multiple interpersonal problems constitute the dependent variable but not when single interpersonal problem criteria constitute the dependent variable. These results are interpreted as supporting social-adaptation theory rather than self-perception theory. Implications for the conceptual status of personality variables as causal antecedents and for the assessment of individual differences are discussed.

Temporal, Spatial, and Spectral Variability at Ivanpah Playa Vicarious Calibration Site

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

Villa-Aleman, E.

2003-01-07

The Savannah River Technology Center (SRTC) conducted four reflectance vicarious calibrations at Ivanpah Playa, California since July 2000 in support of the MTI satellite. The multi-year study shows temporal, spatial and spectral variability at the playa. The temporal variability in the wavelength dependent reflectance and emissivity across the playa suggests a dependency with precipitation during the winter and early spring seasons. Satellite imagery acquired on September and November 2000, May 2001 and March 2002 in conjunction with ground truth during the September, May and March campaigns and water precipitation records were used to demonstrate the correlation observed at the playa

[Mix 10] HMACP mixture design : combined gradation.

DOT National Transportation Integrated Search

2011-01-01

Getting Started: Begin with the Combined Gradations or Summary sheet. Here you will select dependent variables such as specification year, mix type, asphalt content, combined aggregate, and others. These variable will affect the calculation of other ...

[Mix 4] HMACP mixture design : combined gradation.

DOT National Transportation Integrated Search

2011-01-01

Getting Started: Begin with the Combined Gradations or Summary sheet. Here you will select dependent variables such as specification year, mix type, asphalt content, combined aggregate, and others. These variable will affect the calculation of other ...

[Mix 5] HMACP mixture design : combined gradation.

DOT National Transportation Integrated Search

2011-01-01

Getting Started: Begin with the Combined Gradations or Summary sheet. Here you will select dependent variables such as specification year, mix type, asphalt content, combined aggregate, and others. These variable will affect the calculation of other ...

[Mix 13] HMACP mixture design : combined gradation.

DOT National Transportation Integrated Search

2007-01-01

Getting Started: Begin with the Combined Gradations or Summary sheet. Here you will select dependent variables such as specification year, mix type, asphalt content, combined aggregate, and others. These variable will affect the calculation of other ...

[Mix 3] HMACP mixture design : combined gradation.

DOT National Transportation Integrated Search

2010-01-01

Getting Started: Begin with the Combined Gradations or Summary sheet. Here you will select dependent variables such as specification year, mix type, asphalt content, combined aggregate, and others. These variable will affect the calculation of other ...

[Mix 14] HMACP mixture design : combined gradation.

DOT National Transportation Integrated Search

2007-01-01

Getting Started: Begin with the Combined Gradations or Summary sheet. Here you will select dependent variables such as specification year, mix type, asphalt content, combined aggregate, and others. These variable will affect the calculation of other ...

[Mix 7] HMACP mixture design : combined gradation.

DOT National Transportation Integrated Search

2004-01-01

Getting Started: Begin with the Combined Gradations or Summary sheet. Here you will select dependent variables such as specification year, mix type, asphalt content, combined aggregate, and others. These variable will affect the calculation of other ...

[Mix 16] HMACP mixture design : combined gradation.

DOT National Transportation Integrated Search

2004-01-01

Getting Started: Begin with the Combined Gradations or Summary sheet. Here you will select dependent variables such as specification year, mix type, asphalt content, combined aggregate, and others. These variable will affect the calculation of other ...

[Mix 6] HMACP mixture design : combined gradation.

DOT National Transportation Integrated Search

2007-01-01

Getting Started: Begin with the Combined Gradations or Summary sheet. Here you will select dependent variables such as specification year, mix type, asphalt content, combined aggregate, and others. These variable will affect the calculation of other ...

[Mix 12] HMACP mixture design : combined gradation.

DOT National Transportation Integrated Search

2004-01-01

Getting Started: Begin with the Combined Gradations or Summary sheet. Here you will select dependent variables such as specification year, mix type, asphalt content, combined aggregate, and others. These variable will affect the calculation of other ...

[Mix 1] HMACP mixture design : combined gradation.

DOT National Transportation Integrated Search

2010-01-01

Getting Started: Begin with the Combined Gradations or Summary sheet. Here you will select dependent variables such as specification year, mix type, asphalt content, combined aggregate, and others. These variable will affect the calculation of other ...

[Mix 2] HMACP mixture design : combined gradation.

DOT National Transportation Integrated Search

2010-01-01

Getting Started: Begin with the Combined Gradations or Summary sheet. Here you will select dependent variables such as specification year, mix type, asphalt content, combined aggregate, and others. These variable will affect the calculation of other ...

[Mix 8] HMACP mixture design : combined gradation.

DOT National Transportation Integrated Search

2007-01-01

Getting Started: Begin with the Combined Gradations or Summary sheet. Here you will select dependent variables such as specification year, mix type, asphalt content, combined aggregate, and others. These variable will affect the calculation of other ...

[Mix 11] HMACP mixture design : combined gradation.

DOT National Transportation Integrated Search

2007-01-01

Getting Started: Begin with the Combined Gradations or Summary sheet. Here you will select dependent variables such as specification year, mix type, asphalt content, combined aggregate, and others. These variable will affect the calculation of other ...

[Mix 15] HMACP mixture design : combined gradation.

DOT National Transportation Integrated Search

2004-01-01

Getting Started: Begin with the Combined Gradations or Summary sheet. Here you will select dependent variables such as specification year, mix type, asphalt content, combined aggregate, and others. These variable will affect the calculation of other ...

[Mix 9] HMACP mixture design : combined gradation.

DOT National Transportation Integrated Search

2007-01-01

Getting Started: Begin with the Combined Gradations or Summary sheet. Here you will select dependent variables such as specification year, mix type, asphalt content, combined aggregate, and others. These variable will affect the calculation of other ...

Measuring monotony in two-dimensional samples

NASA Astrophysics Data System (ADS)

Kachapova, Farida; Kachapov, Ilias

2010-04-01

This note introduces a monotony coefficient as a new measure of the monotone dependence in a two-dimensional sample. Some properties of this measure are derived. In particular, it is shown that the absolute value of the monotony coefficient for a two-dimensional sample is between |r| and 1, where r is the Pearson's correlation coefficient for the sample; that the monotony coefficient equals 1 for any monotone increasing sample and equals -1 for any monotone decreasing sample. This article contains a few examples demonstrating that the monotony coefficient is a more accurate measure of the degree of monotone dependence for a non-linear relationship than the Pearson's, Spearman's and Kendall's correlation coefficients. The monotony coefficient is a tool that can be applied to samples in order to find dependencies between random variables; it is especially useful in finding couples of dependent variables in a big dataset of many variables. Undergraduate students in mathematics and science would benefit from learning and applying this measure of monotone dependence.

Discrete-time BAM neural networks with variable delays

NASA Astrophysics Data System (ADS)

Liu, Xin-Ge; Tang, Mei-Lan; Martin, Ralph; Liu, Xin-Bi

2007-07-01

This Letter deals with the global exponential stability of discrete-time bidirectional associative memory (BAM) neural networks with variable delays. Using a Lyapunov functional, and linear matrix inequality techniques (LMI), we derive a new delay-dependent exponential stability criterion for BAM neural networks with variable delays. As this criterion has no extra constraints on the variable delay functions, it can be applied to quite general BAM neural networks with a broad range of time delay functions. It is also easy to use in practice. An example is provided to illustrate the theoretical development.

Rapidly variable relatvistic absorption

NASA Astrophysics Data System (ADS)

Parker, M.; Pinto, C.; Fabian, A.; Lohfink, A.; Buisson, D.; Alston, W.; Jiang, J.

2017-10-01

I will present results from the 1.5Ms XMM-Newton observing campaign on the most X-ray variable AGN, IRAS 13224-3809. We find a series of nine absorption lines with a velocity of 0.24c from an ultra-fast outflow. For the first time, we are able to see extremely rapid variability of the UFO features, and can link this to the X-ray variability from the inner accretion disk. We find a clear flux dependence of the outflow features, suggesting that the wind is ionized by increasing X-ray emission.

Maximum likelihood estimation for predicting the probability of obtaining variable shortleaf pine regeneration densities

Treesearch

Thomas B. Lynch; Jean Nkouka; Michael M. Huebschmann; James M. Guldin

2003-01-01

A logistic equation is the basis for a model that predicts the probability of obtaining regeneration at specified densities. The density of regeneration (trees/ha) for which an estimate of probability is desired can be specified by means of independent variables in the model. When estimating parameters, the dependent variable is set to 1 if the regeneration density (...

Data Mining in Institutional Economics Tasks

NASA Astrophysics Data System (ADS)

Kirilyuk, Igor; Kuznetsova, Anna; Senko, Oleg

2018-02-01

The paper discusses problems associated with the use of data mining tools to study discrepancies between countries with different types of institutional matrices by variety of potential explanatory variables: climate, economic or infrastructure indicators. An approach is presented which is based on the search of statistically valid regularities describing the dependence of the institutional type on a single variable or a pair of variables. Examples of regularities are given.

Smoke optical depths - Magnitude, variability, and wavelength dependence

NASA Technical Reports Server (NTRS)

Pueschel, R. F.; Russell, P. B.; Colburn, D. A.; Ackerman, T. P.; Allen, D. A.

1988-01-01

An airborne autotracking sun-photometer has been used to measure magnitudes, temporal/spatial variabilities, and the wavelength dependence of optical depths in the near-ultraviolet to near-infrared spectrum of smoke from two forest fires and one jet fuel fire and of background air. Jet fuel smoke optical depths were found to be generally less wavelength dependent than background aerosol optical depths. Forest fire smoke optical depths, however, showed a wide range of wavelength depedences, such as incidents of wavelength-independent extinction.

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.

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 review of precipitation and temperature control on seedling emergence and establishment for ponderosa and lodgepole pine forest regeneration

Treesearch

M. D. Petrie; A. M. Wildeman; J. B. Bradford; Robert Hubbard; W. K. Lauenroth

2016-01-01

The persistence of ponderosa pine and lodgepole pine forests in the 21st century depends to a large extent on how seedling emergence and establishment are influenced by driving climate and environmental variables, which largely govern forest regeneration. We surveyed the literature, and identified 96 publications that reported data on dependent variables of seedling...

How spatial and temporal rainfall variability affect runoff across basin scales: insights from field observations in the (semi-)urbanised Charlotte watershed

NASA Astrophysics Data System (ADS)

Ten Veldhuis, M. C.; Smith, J. A.; Zhou, Z.

2017-12-01

Impacts of rainfall variability on runoff response are highly scale-dependent. Sensitivity analyses based on hydrological model simulations have shown that impacts are likely to depend on combinations of storm type, basin versus storm scale, temporal versus spatial rainfall variability. So far, few of these conclusions have been confirmed on observational grounds, since high quality datasets of spatially variable rainfall and runoff over prolonged periods are rare. Here we investigate relationships between rainfall variability and runoff response based on 30 years of radar-rainfall datasets and flow measurements for 16 hydrological basins ranging from 7 to 111 km2. Basins vary not only in scale, but also in their degree of urbanisation. We investigated temporal and spatial variability characteristics of rainfall fields across a range of spatial and temporal scales to identify main drivers for variability in runoff response. We identified 3 ranges of basin size with different temporal versus spatial rainfall variability characteristics. Total rainfall volume proved to be the dominant agent determining runoff response at all basin scales, independent of their degree of urbanisation. Peak rainfall intensity and storm core volume are of secondary importance. This applies to all runoff parameters, including runoff volume, runoff peak, volume-to-peak and lag time. Position and movement of the storm with respect to the basin have a negligible influence on runoff response, with the exception of lag times in some of the larger basins. This highlights the importance of accuracy in rainfall estimation: getting the position right but the volume wrong will inevitably lead to large errors in runoff prediction. Our study helps to identify conditions where rainfall variability matters for correct estimation of the rainfall volume as well as the associated runoff response.

Automatic differentiation evaluated as a tool for rotorcraft design and optimization

NASA Technical Reports Server (NTRS)

Walsh, Joanne L.; Young, Katherine C.

1995-01-01

This paper investigates the use of automatic differentiation (AD) as a means for generating sensitivity analyses in rotorcraft design and optimization. This technique transforms an existing computer program into a new program that performs sensitivity analysis in addition to the original analysis. The original FORTRAN program calculates a set of dependent (output) variables from a set of independent (input) variables, the new FORTRAN program calculates the partial derivatives of the dependent variables with respect to the independent variables. The AD technique is a systematic implementation of the chain rule of differentiation, this method produces derivatives to machine accuracy at a cost that is comparable with that of finite-differencing methods. For this study, an analysis code that consists of the Langley-developed hover analysis HOVT, the comprehensive rotor analysis CAMRAD/JA, and associated preprocessors is processed through the AD preprocessor ADIFOR 2.0. The resulting derivatives are compared with derivatives obtained from finite-differencing techniques. The derivatives obtained with ADIFOR 2.0 are exact within machine accuracy and do not depend on the selection of step-size, as are the derivatives obtained with finite-differencing techniques.

The development and evaluation of accident predictive models

NASA Astrophysics Data System (ADS)

Maleck, T. L.

1980-12-01

A mathematical model that will predict the incremental change in the dependent variables (accident types) resulting from changes in the independent variables is developed. The end product is a tool for estimating the expected number and type of accidents for a given highway segment. The data segments (accidents) are separated in exclusive groups via a branching process and variance is further reduced using stepwise multiple regression. The standard error of the estimate is calculated for each model. The dependent variables are the frequency, density, and rate of 18 types of accidents among the independent variables are: district, county, highway geometry, land use, type of zone, speed limit, signal code, type of intersection, number of intersection legs, number of turn lanes, left-turn control, all-red interval, average daily traffic, and outlier code. Models for nonintersectional accidents did not fit nor validate as well as models for intersectional accidents.

Predicting Use of Nurse Care Coordination by Older Adults With Chronic Conditions.

PubMed

Vanderboom, Catherine E; Holland, Diane E; Mandrekar, Jay; Lohse, Christine M; Witwer, Stephanie G; Hunt, Vicki L

2017-07-01

To be effective, nurse care coordination must be targeted at individuals who will use the service. The purpose of this study was to identify variables that predicted use of care coordination by primary care patients. Data on the potential predictor variables were obtained from patient interviews, the electronic health record, and an administrative database of 178 adults eligible for care coordination. Use of care coordination was obtained from an administrative database. A multivariable logistic regression model was developed using a bootstrap sampling approach. Variables predicting use of care coordination were dependence in both activities of daily living (ADL) and instrumental activities of daily living (IADL; odds ratio [OR] = 5.30, p = .002), independent for ADL but dependent for IADL (OR = 2.68, p = .01), and number of prescription medications (OR = 1.12, p = .002). Consideration of these variables may improve identification of patients to target for care coordination.

Whole-Body Movements in Long-Term Weightlessness: Hierarchies of the Controlled Variables Are Gravity-Dependent.

PubMed

Casellato, Claudia; Pedrocchi, Alessandra; Ferrigno, Giancarlo

2017-01-01

Switching between contexts affects the mechanisms underlying motion planning, in particular it may entail reranking the variables to be controlled in defining the motor solutions. Three astronauts performed multiple sessions of whole-body pointing, in normogravity before launch, in prolonged weightlessness onboard the International Space Station, and after return. The effect of gravity context on kinematic and dynamic components was evaluated. Hand trajectory was gravity independent; center-of-mass excursion was highly variable within and between subjects. The body-environment effort exchange, expressed as inertial ankle momentum, was systematically lower in weightlessness than in normogravity. After return on Earth, the system underwent a rapid 1-week readaptation. The study indicates that minimizing the control effort is given greater weight when optimizing the motor plan in weightlessness compared to normogravity: the hierarchies of the controlled variables are gravity dependent.

Modelling infant mortality rate in Central Java, Indonesia use generalized poisson regression method

NASA Astrophysics Data System (ADS)

Prahutama, Alan; Sudarno

2018-05-01

The infant mortality rate is the number of deaths under one year of age occurring among the live births in a given geographical area during a given year, per 1,000 live births occurring among the population of the given geographical area during the same year. This problem needs to be addressed because it is an important element of a country’s economic development. High infant mortality rate will disrupt the stability of a country as it relates to the sustainability of the population in the country. One of regression model that can be used to analyze the relationship between dependent variable Y in the form of discrete data and independent variable X is Poisson regression model. Recently The regression modeling used for data with dependent variable is discrete, among others, poisson regression, negative binomial regression and generalized poisson regression. In this research, generalized poisson regression modeling gives better AIC value than poisson regression. The most significant variable is the Number of health facilities (X1), while the variable that gives the most influence to infant mortality rate is the average breastfeeding (X9).

Scheduling admissions and reducing variability in bed demand.

PubMed

Bekker, René; Koeleman, Paulien M

2011-09-01

Variability in admissions and lengths of stay inherently leads to variability in bed occupancy. The aim of this paper is to analyse the impact of these sources of variability on the required amount of capacity and to determine admission quota for scheduled admissions to regulate the occupancy pattern. For the impact of variability on the required number of beds, we use a heavy-traffic limit theorem for the G/G/∞ queue yielding an intuitively appealing approximation in case the arrival process is not Poisson. Also, given a structural weekly admission pattern, we apply a time-dependent analysis to determine the mean offered load per day. This time-dependent analysis is combined with a Quadratic Programming model to determine the optimal number of elective admissions per day, such that an average desired daily occupancy is achieved. From the mathematical results, practical scenarios and guidelines are derived that can be used by hospital managers and support the method of quota scheduling. In practice, the results can be implemented by providing admission quota prescribing the target number of admissions for each patient group.

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.

Women's perceptions of their male batterers' characteristics and level of violence.

PubMed

Torres, Sara; Han, Hae-Ra

2003-01-01

This article describes the characteristics of male perpetrators of domestic violence and their relationship to the level of violence. The data about the male partners obtained from 151 battered women were used for this analysis. Using multiple regression, demographic variables and three behavioral indicators, including use of alcohol before a violent episode, history of arrests, and the generality of violence, were examined together for their relationship with the violence scores. With the level of violence as measured by the Conflict Tactics Scale (CTS) as the dependent variable, demographic variables explained 19.1% of the variability, with the behavioral indicators accounting for an additional 4.6% of the variability. Several research and clinical implications are addressed.

On the use of internal state variables in thermoviscoplastic constitutive equations

NASA Technical Reports Server (NTRS)

Allen, D. H.; Beek, J. M.

1985-01-01

The general theory of internal state variables are reviewed to apply it to inelastic metals in use in high temperature environments. In this process, certain constraints and clarifications will be made regarding internal state variables. It is shown that the Helmholtz free energy can be utilized to construct constitutive equations which are appropriate for metallic superalloys. Internal state variables are shown to represent locally averaged measures of dislocation arrangement, dislocation density, and intergranular fracture. The internal state variable model is demonstrated to be a suitable framework for comparison of several currently proposed models for metals and can therefore be used to exhibit history dependence, nonlinearity, and rate as well as temperature sensitivity.

ABCB1 genetic variability and methadone dosage requirements in opioid-dependent individuals.

PubMed

Coller, Janet K; Barratt, Daniel T; Dahlen, Karianne; Loennechen, Morten H; Somogyi, Andrew A

2006-12-01

The most common treatment for opioid dependence is substitution therapy with another opioid such as methadone. The methadone dosage is individualized but highly variable, and program retention rates are low due in part to nonoptimal dosing resulting in withdrawal symptoms and further heroin craving and use. Methadone is a substrate for the P-glycoprotein transporter, encoded by the ABCB1 gene, which regulates central nervous system exposure. This retrospective study aimed to investigate the influence of ABCB1 genetic variability on methadone dose requirements. Genomic deoxyribonucleic acid was isolated from opioid-dependent subjects (n = 60) and non-opioid-dependent control subjects (n = 60), and polymerase chain reaction-restriction fragment length polymorphism and allele-specific polymerase chain reaction were used to determine the presence of single nucleotide polymorphisms at positions 61, 1199, 1236, 2677, and 3435. ABCB1 haplotypes were inferred with PHASE software (version 2.1). There were no significant differences in the allele or genotype frequencies of the individual single nucleotide polymorphisms or haplotypes between the 2 populations. ABCB1 genetic variability influenced daily methadone dose requirements, such that subjects carrying 2 copies of the wild-type haplotype required higher doses compared with those with 1 copy and those with no copies (98.3 +/- 10.4, 58.6 +/- 20.9, and 55.4 +/- 26.1 mg/d, respectively; P = .029). In addition, carriers of the AGCTT haplotype required significantly lower doses than noncarriers (38.0 +/- 16.8 and 61.3 +/- 24.6 mg/d, respectively; P = .04). Although ABCB1 genetic variability is not related to the development of opioid dependence, identification of variant haplotypes may, after larger prospective studies have been performed, provide clinicians with a tool for methadone dosage individualization.

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

DOE PAGES

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

2017-10-13

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

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

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

Biogeographical drivers of ragweed pollen concentrations in Europe

NASA Astrophysics Data System (ADS)

Matyasovszky, István; Makra, László; Tusnády, Gábor; Csépe, Zoltán; Nyúl, László G.; Chapman, Daniel S.; Sümeghy, Zoltán; Szűcs, Gábor; Páldy, Anna; Magyar, Donát; Mányoki, Gergely; Erostyák, János; Bodnár, Károly; Bergmann, Karl-Christian; Deák, Áron József; Thibaudon, Michel; Albertini, Roberto; Bonini, Maira; Šikoparija, Branko; Radišić, Predrag; Gehrig, Regula; Rybníček, Ondřej; Severova, Elena; Rodinkova, Victoria; Prikhodko, Alexander; Maleeva, Anna; Stjepanović, Barbara; Ianovici, Nicoleta; Berger, Uwe; Seliger, Andreja Kofol; Weryszko-Chmielewska, Elżbieta; Šaulienė, Ingrida; Shalaboda, Valentina; Yankova, Raina; Peternel, Renata; Ščevková, Jana; Bullock, James M.

2017-06-01

The drivers of spatial variation in ragweed pollen concentrations, contributing to severe allergic rhinitis and asthma, are poorly quantified. We analysed the spatiotemporal variability in 16-year (1995-2010) annual total (66 stations) and annual total (2010) (162 stations) ragweed pollen counts and 8 independent variables (start, end and duration of the ragweed pollen season, maximum daily and calendar day of the maximum daily ragweed pollen counts, last frost day in spring, first frost day in fall and duration of the frost-free period) for Europe (16 years, 1995-2010) as a function of geographical coordinates. Then annual total pollen counts, annual daily peak pollen counts and date of this peak were regressed against frost-related variables, daily mean temperatures and daily precipitation amounts. To achieve this, we assembled the largest ragweed pollen data set to date for Europe. The dependence of the annual total ragweed pollen counts and the eight independent variables against geographical coordinates clearly distinguishes the three highly infected areas: the Pannonian Plain, Western Lombardy and the Rhône-Alpes region. All the eight variables are sensitive to longitude through its temperature dependence. They are also sensitive to altitude, due to the progressively colder climate with increasing altitude. Both annual total pollen counts and the maximum daily pollen counts depend on the start and the duration of the ragweed pollen season. However, no significant changes were detected in either the eight independent variables as a function of increasing latitude. This is probably due to a mixed climate induced by strong geomorphological inhomogeneities in Europe.

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis.

PubMed

Sakhanenko, Nikita A; Kunert-Graf, James; Galas, David J

2017-12-01

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. We present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discrete variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis-that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. We illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.

Prediction and experimental observation of damage dependent damping in laminated composite beams

NASA Technical Reports Server (NTRS)

Allen, D. H.; Harris, C. E.; Highsmith, A. L.

1987-01-01

The equations of motion are developed for laminated composite beams with load-induced matrix cracking. The damage is accounted for by utilizing internal state variables. The net result of these variables on the field equations is the introduction of both enhanced damping, and degraded stiffness. Both quantities are history dependent and spatially variable, thus resulting in nonlinear equations of motion. It is explained briefly how these equations may be quasi-linearized for laminated polymeric composites under certain types of structural loading. The coupled heat conduction equation is developed, and it is shown that an enhanced Zener damping effect is produced by the introduction of microstructural damage. The resulting equations are utilized to demonstrate how damage dependent material properties may be obtained from dynamic experiments. Finaly, experimental results are compared to model predictions for several composite layups.

Shoulder pain and time dependent structure in wheelchair propulsion variability

PubMed Central

Jayaraman, Chandrasekaran; Moon, Yaejin; Sosnoff, Jacob J.

2016-01-01

Manual wheelchair propulsion places considerable repetitive mechanical strain on the upper limbs leading to shoulder injury and pain. While recent research indicates that the amount of variability in wheelchair propulsion and shoulder pain may be related. There has been minimal inquiry into the fluctuation over time (i.e. time-dependent structure) in wheelchair propulsion variability. Consequently the purpose of this investigation was to examine if the time-dependent structure in the wheelchair propulsion parameters are related to shoulder pain. 27 experienced wheelchair users manually propelled their own wheelchair fitted with a SMARTWheel on a roller at 1.1 m/s for 3 minutes. Time-dependent structure of cycle-to-cycle fluctuations in contact angle and inter push time interval was quantified using sample entropy (SampEn) and compared between the groups with/without shoulder pain using non-parametric statistics. Overall findings were, (1) variability observed in contact angle fluctuations during manual wheelchair propulsion is structured (Z=3.15;p<0.05), (2) individuals with shoulder pain exhibited higher SampEn magnitude for contact angle during wheelchair propulsion than those without pain (χ2(1)=6.12;p<0.05); and (3) SampEn of contact angle correlated significantly with self-reported shoulder pain (rs (WUSPI) =0.41;rs (VAS)=0.56;p<0.05). It was concluded that the time-dependent structure in wheelchair propulsion may provide novel information for tracking and monitoring shoulder pain. PMID:27134151

A Reduced Form Model for Ozone Based on Two Decades of ...

EPA Pesticide Factsheets

A Reduced Form Model (RFM) is a mathematical relationship between the inputs and outputs of an air quality model, permitting estimation of additional modeling without costly new regional-scale simulations. A 21-year Community Multiscale Air Quality (CMAQ) simulation for the continental United States provided the basis for the RFM developed in this study. Predictors included the principal component scores (PCS) of emissions and meteorological variables, while the predictand was the monthly mean of daily maximum 8-hour CMAQ ozone for the ozone season at each model grid. The PCS form an orthogonal basis for RFM inputs. A few PCS incorporate most of the variability of emissions and meteorology, thereby reducing the dimensionality of the source-receptor problem. Stochastic kriging was used to estimate the model. The RFM was used to separate the effects of emissions and meteorology on ozone concentrations. by running the RFM with emissions constant (ozone dependent on meteorology), or constant meteorology (ozone dependent on emissions). Years with ozone-conducive meteorology were identified, and meteorological variables best explaining meteorology-dependent ozone were identified. Meteorology accounted for 19% to 55% of ozone variability in the eastern US, and 39% to 92% in the western US. Temporal trends estimated for original CMAQ ozone data and emission-dependent ozone were mostly negative, but the confidence intervals for emission-dependent ozone are much

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

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

Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd

Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test ofmore » the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.« less

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

NASA Astrophysics Data System (ADS)

Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd; Baharum, Adam

2015-10-01

Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test of the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.

Poor environmental tracking can make extinction risk insensitive to the colour of environmental noise

PubMed Central

van de Pol, Martijn; Vindenes, Yngvild; Sæther, Bernt-Erik; Engen, Steinar; Ens, Bruno J.; Oosterbeek, Kees; Tinbergen, Joost M.

2011-01-01

The relative importance of environmental colour for extinction risk compared with other aspects of environmental noise (mean and interannual variability) is poorly understood. Such knowledge is currently relevant, as climate change can cause the mean, variability and temporal autocorrelation of environmental variables to change. Here, we predict that the extinction risk of a shorebird population increases with the colour of a key environmental variable: winter temperature. However, the effect is weak compared with the impact of changes in the mean and interannual variability of temperature. Extinction risk was largely insensitive to noise colour, because demographic rates are poor in tracking the colour of the environment. We show that three mechanisms—which probably act in many species—can cause poor environmental tracking: (i) demographic rates that depend nonlinearly on environmental variables filter the noise colour, (ii) demographic rates typically depend on several environmental signals that do not change colour synchronously, and (iii) demographic stochasticity whitens the colour of demographic rates at low population size. We argue that the common practice of assuming perfect environmental tracking may result in overemphasizing the importance of noise colour for extinction risk. Consequently, ignoring environmental autocorrelation in population viability analysis could be less problematic than generally thought. PMID:21561978

Lower limb kinematics during treadmill walking after space flight: implications for gaze stabilization

NASA Technical Reports Server (NTRS)

McDonald, P. V.; Basdogan, C.; Bloomberg, J. J.; Layne, C. S.

1996-01-01

We examined the lower limb joint kinematics observed during pre- and postflight treadmill walking performed by seven subjects from three Space Shuttle flights flown between March 1992 and February 1994. Basic temporal characteristics of the gait patterns, such as stride time and duty cycle, showed no significant changes after flight. Evaluation of phaseplane variability across the gait cycle suggests that postflight treadmill walking is more variable than preflight, but the response throughout the course of a cycle is joint dependent and, furthermore, the changes are subject dependent. However, analysis of the phaseplane variability at the specific locomotor events of heel strike and toe off indicated statistically significant postflight increases in knee variability at the moment of heel strike and significantly higher postflight hip joint variability at the moment of toe off. Nevertheless, the observation of component-specific variability was not sufficient to cause a change in the overall lower limb joint system stability, since there was no significant change in an index used to evaluate this at both toe off and heel strike. The implications of the observed lower limb kinematics for head and gaze control during locomotion are discussed in light of a hypothesized change in the energy attenuation capacity of the musculoskeletal system in adapting to weightlessness.

Lower limb kinematics during treadmill walking after space flight: implications for gaze stabilization.

PubMed

McDonald, P V; Basdogan, C; Bloomberg, J J; Layne, C S

1996-11-01

We examined the lower limb joint kinematics observed during pre- and postflight treadmill walking performed by seven subjects from three Space Shuttle flights flown between March 1992 and February 1994. Basic temporal characteristics of the gait patterns, such as stride time and duty cycle, showed no significant changes after flight. Evaluation of phaseplane variability across the gait cycle suggests that postflight treadmill walking is more variable than preflight, but the response throughout the course of a cycle is joint dependent and, furthermore, the changes are subject dependent. However, analysis of the phaseplane variability at the specific locomotor events of heel strike and toe off indicated statistically significant postflight increases in knee variability at the moment of heel strike and significantly higher postflight hip joint variability at the moment of toe off. Nevertheless, the observation of component-specific variability was not sufficient to cause a change in the overall lower limb joint system stability, since there was no significant change in an index used to evaluate this at both toe off and heel strike. The implications of the observed lower limb kinematics for head and gaze control during locomotion are discussed in light of a hypothesized change in the energy attenuation capacity of the musculoskeletal system in adapting to weightlessness.

Species interactions may help explain the erratic periodicity of whooping cough dynamics.

PubMed

Bhattacharyya, Samit; Ferrari, Matthew J; Bjørnstad, Ottar N

2017-12-14

Incidence of whooping cough exhibits variable dynamics across time and space. The periodicity of this disease varies from annual to five years in different geographic regions in both developing and developed countries. Many hypotheses have been put forward to explain this variability such as nonlinearity and seasonality, stochasticity, variable recruitment of susceptible individuals via birth, immunization, and immune boosting. We propose an alternative hypothesis to describe the variability in periodicity - the intricate dynamical variability of whooping cough may arise from interactions between its dominant etiological agents of Bordetella pertussis and Bordetella parapertussis. We develop a two-species age-structured model, where two pathogens are allowed to interact by age-dependent convalescence of individuals with severe illness from infections. With moderate strength of interactions, the model exhibits multi-annual coexisting attractors that depend on the R 0 of the two pathogens. We also examine how perturbation from case importation and noise in transmission may push the system from one dynamical regime to another. The coexistence of multi-annual cycles and the behavior of switching between attractors suggest that variable dynamics of whopping cough could be an emergent property of its multi-agent etiology. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

[Gene method for inconsistent hydrological frequency calculation. I: Inheritance, variability and evolution principles of hydrological genes].

PubMed

Xie, Ping; Wu, Zi Yi; Zhao, Jiang Yan; Sang, Yan Fang; Chen, Jie

2018-04-01

A stochastic hydrological process is influenced by both stochastic and deterministic factors. A hydrological time series contains not only pure random components reflecting its inheri-tance characteristics, but also deterministic components reflecting variability characteristics, such as jump, trend, period, and stochastic dependence. As a result, the stochastic hydrological process presents complicated evolution phenomena and rules. To better understand these complicated phenomena and rules, this study described the inheritance and variability characteristics of an inconsistent hydrological series from two aspects: stochastic process simulation and time series analysis. In addition, several frequency analysis approaches for inconsistent time series were compared to reveal the main problems in inconsistency study. Then, we proposed a new concept of hydrological genes origined from biological genes to describe the inconsistent hydrolocal processes. The hydrologi-cal genes were constructed using moments methods, such as general moments, weight function moments, probability weight moments and L-moments. Meanwhile, the five components, including jump, trend, periodic, dependence and pure random components, of a stochastic hydrological process were defined as five hydrological bases. With this method, the inheritance and variability of inconsistent hydrological time series were synthetically considered and the inheritance, variability and evolution principles were fully described. Our study would contribute to reveal the inheritance, variability and evolution principles in probability distribution of hydrological elements.

Mean convergence theorems and weak laws of large numbers for weighted sums of random variables under a condition of weighted integrability

NASA Astrophysics Data System (ADS)

Ordóñez Cabrera, Manuel; Volodin, Andrei I.

2005-05-01

From the classical notion of uniform integrability of a sequence of random variables, a new concept of integrability (called h-integrability) is introduced for an array of random variables, concerning an array of constantsE We prove that this concept is weaker than other previous related notions of integrability, such as Cesàro uniform integrability [Chandra, Sankhya Ser. A 51 (1989) 309-317], uniform integrability concerning the weights [Ordóñez Cabrera, Collect. Math. 45 (1994) 121-132] and Cesàro [alpha]-integrability [Chandra and Goswami, J. Theoret. ProbabE 16 (2003) 655-669]. Under this condition of integrability and appropriate conditions on the array of weights, mean convergence theorems and weak laws of large numbers for weighted sums of an array of random variables are obtained when the random variables are subject to some special kinds of dependence: (a) rowwise pairwise negative dependence, (b) rowwise pairwise non-positive correlation, (c) when the sequence of random variables in every row is [phi]-mixing. Finally, we consider the general weak law of large numbers in the sense of Gut [Statist. Probab. Lett. 14 (1992) 49-52] under this new condition of integrability for a Banach space setting.

Natural variability of marine ecosystems inferred from a coupled climate to ecosystem simulation

NASA Astrophysics Data System (ADS)

Le Mézo, Priscilla; Lefort, Stelly; Séférian, Roland; Aumont, Olivier; Maury, Olivier; Murtugudde, Raghu; Bopp, Laurent

2016-01-01

This modeling study analyzes the simulated natural variability of pelagic ecosystems in the North Atlantic and North Pacific. Our model system includes a global Earth System Model (IPSL-CM5A-LR), the biogeochemical model PISCES and the ecosystem model APECOSM that simulates upper trophic level organisms using a size-based approach and three interactive pelagic communities (epipelagic, migratory and mesopelagic). Analyzing an idealized (e.g., no anthropogenic forcing) 300-yr long pre-industrial simulation, we find that low and high frequency variability is dominant for the large and small organisms, respectively. Our model shows that the size-range exhibiting the largest variability at a given frequency, defined as the resonant range, also depends on the community. At a given frequency, the resonant range of the epipelagic community includes larger organisms than that of the migratory community and similarly, the latter includes larger organisms than the resonant range of the mesopelagic community. This study shows that the simulated temporal variability of marine pelagic organisms' abundance is not only influenced by natural climate fluctuations but also by the structure of the pelagic community. As a consequence, the size- and community-dependent response of marine ecosystems to climate variability could impact the sustainability of fisheries in a warming world.

Modelling Inter-relationships among water, governance, human development variables in developing countries with Bayesian networks.

NASA Astrophysics Data System (ADS)

Dondeynaz, C.; Lopez-Puga, J.; Carmona-Moreno, C.

2012-04-01

Improving Water and Sanitation Services (WSS), being a complex and interdisciplinary issue, passes through collaboration and coordination of different sectors (environment, health, economic activities, governance, and international cooperation). This inter-dependency has been recognised with the adoption of the "Integrated Water Resources Management" principles that push for the integration of these various dimensions involved in WSS delivery to ensure an efficient and sustainable management. The understanding of these interrelations appears as crucial for decision makers in the water sector in particular in developing countries where WSS still represent an important leverage for livelihood improvement. In this framework, the Joint Research Centre of the European Commission has developed a coherent database (WatSan4Dev database) containing 29 indicators from environmental, socio-economic, governance and financial aid flows data focusing on developing countries (Celine et al, 2011 under publication). The aim of this work is to model the WatSan4Dev dataset using probabilistic models to identify the key variables influencing or being influenced by the water supply and sanitation access levels. Bayesian Network Models are suitable to map the conditional dependencies between variables and also allows ordering variables by level of influence on the dependent variable. Separated models have been built for water supply and for sanitation because of different behaviour. The models are validated if complying with statistical criteria but either with scientific knowledge and literature. A two steps approach has been adopted to build the structure of the model; Bayesian network is first built for each thematic cluster of variables (e.g governance, agricultural pressure, or human development) keeping a detailed level for interpretation later one. A global model is then built based on significant indicators of each cluster being previously modelled. The structure of the relationships between variable are set a priori according to literature and/or experience in the field (expert knowledge). The statistical validation is verified according to error rate of classification, and the significance of the variables. Sensibility analysis has also been performed to characterise the relative influence of every single variable in the model. Once validated, the models allow the estimation of impact of each variable on the behaviour of the water supply or sanitation providing an interesting mean to test scenarios and predict variables behaviours. The choices made, methods and description of the various models, for each cluster as well as the global model for water supply and sanitation will be presented. Key results and interpretation of the relationships depicted by the models will be detailed during the conference.

A Bayesian approach for convex combination of two Gumbel-Barnett copulas

NASA Astrophysics Data System (ADS)

Fernández, M.; González-López, V. A.

2013-10-01

In this paper it was applied a new Bayesian approach to model the dependence between two variables of interest in public policy: "Gonorrhea Rates per 100,000 Population" and "400% Federal Poverty Level and over" with a small number of paired observations (one pair for each U.S. state). We use a mixture of Gumbel-Barnett copulas suitable to represent situations with weak and negative dependence, which is the case treated here. The methodology allows even making a prediction of the dependence between the variables from one year to another, showing whether there was any alteration in the dependence.

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.

The analysis of morphometric data on rocky mountain wolves and artic wolves using statistical method

NASA Astrophysics Data System (ADS)

Ammar Shafi, Muhammad; Saifullah Rusiman, Mohd; Hamzah, Nor Shamsidah Amir; Nor, Maria Elena; Ahmad, Noor’ani; Azia Hazida Mohamad Azmi, Nur; Latip, Muhammad Faez Ab; Hilmi Azman, Ahmad

2018-04-01

Morphometrics is a quantitative analysis depending on the shape and size of several specimens. Morphometric quantitative analyses are commonly used to analyse fossil record, shape and size of specimens and others. The aim of the study is to find the differences between rocky mountain wolves and arctic wolves based on gender. The sample utilised secondary data which included seven variables as independent variables and two dependent variables. Statistical modelling was used in the analysis such was the analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA). The results showed there exist differentiating results between arctic wolves and rocky mountain wolves based on independent factors and gender.

Utilization of accident databases and fuzzy sets to estimate frequency of HazMat transport accidents.

PubMed

Qiao, Yuanhua; Keren, Nir; Mannan, M Sam

2009-08-15

Risk assessment and management of transportation of hazardous materials (HazMat) require the estimation of accident frequency. This paper presents a methodology to estimate hazardous materials transportation accident frequency by utilizing publicly available databases and expert knowledge. The estimation process addresses route-dependent and route-independent variables. Negative binomial regression is applied to an analysis of the Department of Public Safety (DPS) accident database to derive basic accident frequency as a function of route-dependent variables, while the effects of route-independent variables are modeled by fuzzy logic. The integrated methodology provides the basis for an overall transportation risk analysis, which can be used later to develop a decision support system.

Measuring determinants of career satisfaction of anesthesiologists: validation of a survey instrument.

PubMed

Afonso, Anoushka M; Diaz, James H; Scher, Corey S; Beyl, Robbie A; Nair, Singh R; Kaye, Alan David

2013-06-01

To measure the parameter of job satisfaction among anesthesiologists. Survey instrument. Academic anesthesiology departments in the United States. 320 anesthesiologists who attended the annual meeting of the ASA in 2009 (95% response rate). The anonymous 50-item survey collected information on 26 independent demographic variables and 24 dependent ranked variables of career satisfaction among practicing anesthesiologists. Mean survey scores were calculated for each demographic variable and tested for statistically significant differences by analysis of variance. Questions within each domain that were internally consistent with each other within domains were identified by Cronbach's alpha ≥ 0.7. P-values ≤ 0.05 were considered statistically significant. Cronbach's alpha analysis showed strong internal consistency for 10 dependent outcome questions in the practice factor-related domain (α = 0.72), 6 dependent outcome questions in the peer factor-related domain (α = 0.71), and 8 dependent outcome questions in the personal factor-related domain (α = 0.81). Although age was not a variable, full-time status, early satisfaction within the first 5 years of practice, working with respected peers, and personal choice factors were all significantly associated with anesthesiologist job satisfaction. Improvements in factors related to job satisfaction among anesthesiologists may lead to higher early and current career satisfaction. Copyright © 2013 Elsevier Inc. All rights reserved.

Natural variability of biochemical biomarkers in the macro-zoobenthos: Dependence on life stage and environmental factors.

PubMed

Scarduelli, Lucia; Giacchini, Roberto; Parenti, Paolo; Migliorati, Sonia; Di Brisco, Agnese Maria; Vighi, Marco

2017-11-01

Biomarkers are widely used in ecotoxicology as indicators of exposure to toxicants. However, their ability to provide ecologically relevant information remains controversial. One of the major problems is understanding whether the measured responses are determined by stress factors or lie within the natural variability range. In a previous work, the natural variability of enzymatic levels in invertebrates sampled in pristine rivers was proven to be relevant across both space and time. In the present study, the experimental design was improved by considering different life stages of the selected taxa and by measuring more environmental parameters. The experimental design considered sampling sites in 2 different rivers, 8 sampling dates covering the whole seasonal cycle, 4 species from 3 different taxonomic groups (Plecoptera, Perla grandis; Ephemeroptera, Baetis alpinus and Epeorus alpicula; Tricoptera, Hydropsyche pellucidula), different life stages for each species, and 4 enzymes (acetylcholinesterase, glutathione S-transferase, alkaline phosphatase, and catalase). Biomarker levels were related to environmental (physicochemical) parameters to verify any kind of dependence. Data were statistically elaborated using hierarchical multilevel Bayesian models. Natural variability was found to be relevant across both space and time. The results of the present study proved that care should be paid when interpreting biomarker results. Further research is needed to better understand the dependence of the natural variability on environmental parameters. Environ Toxicol Chem 2017;36:3158-3167. © 2017 SETAC. © 2017 SETAC.

Bounds on internal state variables in viscoplasticity

NASA Technical Reports Server (NTRS)

Freed, Alan D.

1993-01-01

A typical viscoplastic model will introduce up to three types of internal state variables in order to properly describe transient material behavior; they are as follows: the back stress, the yield stress, and the drag strength. Different models employ different combinations of these internal variables--their selection and description of evolution being largely dependent on application and material selection. Under steady-state conditions, the internal variables cease to evolve and therefore become related to the external variables (stress and temperature) through simple functional relationships. A physically motivated hypothesis is presented that links the kinetic equation of viscoplasticity with that of creep under steady-state conditions. From this hypothesis one determines how the internal variables relate to one another at steady state, but most importantly, one obtains bounds on the magnitudes of stress and back stress, and on the yield stress and drag strength.

Electrical Advantages of Dendritic Spines

PubMed Central

Gulledge, Allan T.; Carnevale, Nicholas T.; Stuart, Greg J.

2012-01-01

Many neurons receive excitatory glutamatergic input almost exclusively onto dendritic spines. In the absence of spines, the amplitudes and kinetics of excitatory postsynaptic potentials (EPSPs) at the site of synaptic input are highly variable and depend on dendritic location. We hypothesized that dendritic spines standardize the local geometry at the site of synaptic input, thereby reducing location-dependent variability of local EPSP properties. We tested this hypothesis using computational models of simplified and morphologically realistic spiny neurons that allow direct comparison of EPSPs generated on spine heads with EPSPs generated on dendritic shafts at the same dendritic locations. In all morphologies tested, spines greatly reduced location-dependent variability of local EPSP amplitude and kinetics, while having minimal impact on EPSPs measured at the soma. Spine-dependent standardization of local EPSP properties persisted across a range of physiologically relevant spine neck resistances, and in models with variable neck resistances. By reducing the variability of local EPSPs, spines standardized synaptic activation of NMDA receptors and voltage-gated calcium channels. Furthermore, spines enhanced activation of NMDA receptors and facilitated the generation of NMDA spikes and axonal action potentials in response to synaptic input. Finally, we show that dynamic regulation of spine neck geometry can preserve local EPSP properties following plasticity-driven changes in synaptic strength, but is inefficient in modifying the amplitude of EPSPs in other cellular compartments. These observations suggest that one function of dendritic spines is to standardize local EPSP properties throughout the dendritic tree, thereby allowing neurons to use similar voltage-sensitive postsynaptic mechanisms at all dendritic locations. PMID:22532875

Predictive Inference Using Latent Variables with Covariates*

PubMed Central

Schofield, Lynne Steuerle; Junker, Brian; Taylor, Lowell J.; Black, Dan A.

2014-01-01

Plausible Values (PVs) are a standard multiple imputation tool for analysis of large education survey data that measures latent proficiency variables. When latent proficiency is the dependent variable, we reconsider the standard institutionally-generated PV methodology and find it applies with greater generality than shown previously. When latent proficiency is an independent variable, we show that the standard institutional PV methodology produces biased inference because the institutional conditioning model places restrictions on the form of the secondary analysts’ model. We offer an alternative approach that avoids these biases based on the mixed effects structural equations (MESE) model of Schofield (2008). PMID:25231627

Constrained Stochastic Extended Redundancy Analysis.

PubMed

DeSarbo, Wayne S; Hwang, Heungsun; Stadler Blank, Ashley; Kappe, Eelco

2015-06-01

We devise a new statistical methodology called constrained stochastic extended redundancy analysis (CSERA) to examine the comparative impact of various conceptual factors, or drivers, as well as the specific predictor variables that contribute to each driver on designated dependent variable(s). The technical details of the proposed methodology, the maximum likelihood estimation algorithm, and model selection heuristics are discussed. A sports marketing consumer psychology application is provided in a Major League Baseball (MLB) context where the effects of six conceptual drivers of game attendance and their defining predictor variables are estimated. Results compare favorably to those obtained using traditional extended redundancy analysis (ERA).

Using collective variables to drive molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Fiorin, Giacomo; Klein, Michael L.; Hénin, Jérôme

2013-12-01

A software framework is introduced that facilitates the application of biasing algorithms to collective variables of the type commonly employed to drive massively parallel molecular dynamics (MD) simulations. The modular framework that is presented enables one to combine existing collective variables into new ones, and combine any chosen collective variable with available biasing methods. The latter include the classic time-dependent biases referred to as steered MD and targeted MD, the temperature-accelerated MD algorithm, as well as the adaptive free-energy biases called metadynamics and adaptive biasing force. The present modular software is extensible, and portable between commonly used MD simulation engines.

Scales of variability of black carbon plumes and their dependence on resolution of ECHAM6-HAM

NASA Astrophysics Data System (ADS)

Weigum, Natalie; Stier, Philip; Schutgens, Nick; Kipling, Zak

2015-04-01

Prediction of the aerosol effect on climate depends on the ability of three-dimensional numerical models to accurately estimate aerosol properties. However, a limitation of traditional grid-based models is their inability to resolve variability on scales smaller than a grid box. Past research has shown that significant aerosol variability exists on scales smaller than these grid-boxes, which can lead to discrepancies between observations and aerosol models. The aim of this study is to understand how a global climate model's (GCM) inability to resolve sub-grid scale variability affects simulations of important aerosol features. This problem is addressed by comparing observed black carbon (BC) plume scales from the HIPPO aircraft campaign to those simulated by ECHAM-HAM GCM, and testing how model resolution affects these scales. This study additionally investigates how model resolution affects BC variability in remote and near-source regions. These issues are examined using three different approaches: comparison of observed and simulated along-flight-track plume scales, two-dimensional autocorrelation analysis, and 3-dimensional plume analysis. We find that the degree to which GCMs resolve variability can have a significant impact on the scales of BC plumes, and it is important for models to capture the scales of aerosol plume structures, which account for a large degree of aerosol variability. In this presentation, we will provide further results from the three analysis techniques along with a summary of the implication of these results on future aerosol model development.

The Reliability of Pharyngeal High Resolution Manometry with Impedance for Derivation of Measures of Swallowing Function in Healthy Volunteers

PubMed Central

Omari, Taher I.; Savilampi, Johanna; Kokkinn, Karmen; Schar, Mistyka; Lamvik, Kristin; Doeltgen, Sebastian; Cock, Charles

2016-01-01

Purpose. We evaluated the intra- and interrater agreement and test-retest reliability of analyst derivation of swallow function variables based on repeated high resolution manometry with impedance measurements. Methods. Five subjects swallowed 10 × 10 mL saline on two occasions one week apart producing a database of 100 swallows. Swallows were repeat-analysed by six observers using software. Swallow variables were indicative of contractility, intrabolus pressure, and flow timing. Results. The average intraclass correlation coefficients (ICC) for intra- and interrater comparisons of all variable means showed substantial to excellent agreement (intrarater ICC 0.85–1.00; mean interrater ICC 0.77–1.00). Test-retest results were less reliable. ICC for test-retest comparisons ranged from slight to excellent depending on the class of variable. Contractility variables differed most in terms of test-retest reliability. Amongst contractility variables, UES basal pressure showed excellent test-retest agreement (mean ICC 0.94), measures of UES postrelaxation contractile pressure showed moderate to substantial test-retest agreement (mean Interrater ICC 0.47–0.67), and test-retest agreement of pharyngeal contractile pressure ranged from slight to substantial (mean Interrater ICC 0.15–0.61). Conclusions. Test-retest reliability of HRIM measures depends on the class of variable. Measures of bolus distension pressure and flow timing appear to be more test-retest reliable than measures of contractility. PMID:27190520

Dietary behaviors and portion sizes of Black women who enrolled in SisterTalk and variation by demographic characteristics

PubMed Central

Gans, Kim M.; Risica, Patricia Markham; Kirtania, Usree; Jennings, Alishia; Strolla, Leslie O.; Steiner-Asiedu, Matilda; Hardy, Norma; Lasater, Thomas M.

2009-01-01

Objective To describe the dietary behaviors of Black women who enrolled in the SisterTalk weight control study. Design Baseline data collected via telephone survey and in-person screening. Setting Boston, MA and surrounding areas. Participants A total of 461 Black women completed the baseline. Variables Measured Measured height and weight; self reported demographics, risk factors, and dietary variables including fat-related eating behaviors, food portion size, fruit, vegetable, and beverage intake. Analysis Descriptive analyses for demographic, risk factors and dietary variables; ANOVA models with Food Habits Questionnaire (FHQ) scores as the dependent variable and demographic categories as the independent variables; ANOVA models with individual FHQ item scores as the dependent variable, and ethnic identification as the independent variable. Results The data indicate a low prevalence of many fat lowering behaviors. More than 60% reported eating less than five servings of fruits and vegetables per day. Self-reported portion sizes were large for most foods. Older age, being born outside the US, living without children and being retired were significantly associated with a higher prevalence of fat-lowering behaviors. The frequency of specific fat-lowering behaviors and portion size also differed by ethnic identification. Conclusions and Implications The findings support the need for culturally appropriate interventions to improve the dietary intake of Black Americans. Further studies should examine the dietary habits, food preparation methods and portion sizes of diverse groups of Black women and how such habits may differ by demographics. PMID:19161918

A Mulitivariate Statistical Model Describing the Compound Nature of Soil Moisture Drought

NASA Astrophysics Data System (ADS)

Manning, Colin; Widmann, Martin; Bevacqua, Emanuele; Maraun, Douglas; Van Loon, Anne; Vrac, Mathieu

2017-04-01

Soil moisture in Europe acts to partition incoming energy into sensible and latent heat fluxes, thereby exerting a large influence on temperature variability. Soil moisture is predominantly controlled by precipitation and evapotranspiration. When these meteorological variables are accumulated over different timescales, their joint multivariate distribution and dependence structure can be used to provide information of soil moisture. We therefore consider soil moisture drought as a compound event of meteorological drought (deficits of precipitation) and heat waves, or more specifically, periods of high Potential Evapotraspiration (PET). We present here a statistical model of soil moisture based on Pair Copula Constructions (PCC) that can describe the dependence amongst soil moisture and its contributing meteorological variables. The model is designed in such a way that it can account for concurrences of meteorological drought and heat waves and describe the dependence between these conditions at a local level. The model is composed of four variables; daily soil moisture (h); a short term and a long term accumulated precipitation variable (Y1 and Y_2) that account for the propagation of meteorological drought to soil moisture drought; and accumulated PET (Y_3), calculated using the Penman Monteith equation, which can represent the effect of a heat wave on soil conditions. Copula are multivariate distribution functions that allow one to model the dependence structure of given variables separately from their marginal behaviour. PCCs then allow in theory for the formulation of a multivariate distribution of any dimension where the multivariate distribution is decomposed into a product of marginal probability density functions and two-dimensional copula, of which some are conditional. We apply PCC here in such a way that allows us to provide estimates of h and their uncertainty through conditioning on the Y in the form h=h|y_1,y_2,y_3 (1) Applying the model to various Fluxnet sites across Europe, we find the model has good skill and can particularly capture periods of low soil moisture well. We illustrate the relevance of the dependence structure of these Y variables to soil moisture and show how it may be generalised to offer information of soil moisture on a widespread scale where few observations of soil moisture exist. We then present results from a validation study of a selection of EURO CORDEX climate models where we demonstrate the skill of these models in representing these dependencies and so offer insight into the skill seen in the representation of soil moisture in these models.

Forecasting defoliation by the gypsy moth in oak stands

Treesearch

Robert W. Campbell; Joseph P. Standaert

1974-01-01

A multiple-regression model is presented that reflects statistically significant correlations between defoliation by the gypsy moth, the dependent variable, and a series of biotic and physical independent variables. Both possible uses and shortcomings of this model are discussed.

Representative Values of Icing-Related Variables Aloft in Freezing Rain and Freezing Drizzle

DOT National Transportation Integrated Search

1996-03-01

Radiosonde and surface observations in freezing rain (ZR) and freezing drizzle (ZL), and a limited number of aircraft measurements in ZR, have been examined for information on the magnitude and altitude dependence of meteorological variables associat...

Defining and quantifying state of good repair (SGR) for the pedestrian network.

DOT National Transportation Integrated Search

2015-02-01

State of Good Repair is difficult to quantify in a pedestrian context. Dozens and dozens of : variables can affect the utility of the pedestrian network, and these variables change depending : upon the environmental context (urban, suburban, rural). ...

An Exploratory Contingency Model for Schools.

ERIC Educational Resources Information Center

Whorton, David M.

In an application of contingency theory, data from 45 Arizona schools were analyzed to determine the relationships between three sets of independent variables (organizational structure, leadership style, and environmental characteristics) and the dependent variable (organizational effectiveness as perceived by principals and teachers). Contingency…

Temporal variability and climatology of hydrodynamic, water property and water quality parameters in the West Johor Strait of Singapore.

PubMed

Behera, Manasa Ranjan; Chun, Cui; Palani, Sundarambal; Tkalich, Pavel

2013-12-15

The study presents a baseline variability and climatology study of measured hydrodynamic, water properties and some water quality parameters of West Johor Strait, Singapore at hourly-to-seasonal scales to uncover their dependency and correlation to one or more drivers. The considered parameters include, but not limited by sea surface elevation, current magnitude and direction, solar radiation and air temperature, water temperature, salinity, chlorophyll-a and turbidity. FFT (Fast Fourier Transform) analysis is carried out for the parameters to delineate relative effect of tidal and weather drivers. The group and individual correlations between the parameters are obtained by principal component analysis (PCA) and cross-correlation (CC) technique, respectively. The CC technique also identifies the dependency and time lag between driving natural forces and dependent water property and water quality parameters. The temporal variability and climatology of the driving forces and the dependent parameters are established at the hourly, daily, fortnightly and seasonal scales. Copyright © 2013 Elsevier Ltd. All rights reserved.

On-chip optical phase locking of single growth monolithically integrated Slotted Fabry Perot lasers.

PubMed

Morrissey, P E; Cotter, W; Goulding, D; Kelleher, B; Osborne, S; Yang, H; O'Callaghan, J; Roycroft, B; Corbett, B; Peters, F H

2013-07-15

This work investigates the optical phase locking performance of Slotted Fabry Perot (SFP) lasers and develops an integrated variable phase locked system on chip for the first time to our knowledge using these lasers. Stable phase locking is demonstrated between two SFP lasers coupled on chip via a variable gain waveguide section. The two lasers are biased differently, one just above the threshold current of the device with the other at three times this value. The coupling between the lasers can be controlled using the variable gain section which can act as a variable optical attenuator or amplifier depending on bias. Using this, the width of the stable phase locking region on chip is shown to be variable.

The relationship between venture capital investment and macro economic variables via statistical computation method

NASA Astrophysics Data System (ADS)

Aygunes, Gunes

2017-07-01

The objective of this paper is to survey and determine the macroeconomic factors affecting the level of venture capital (VC) investments in a country. The literary depends on venture capitalists' quality and countries' venture capital investments. The aim of this paper is to give relationship between venture capital investment and macro economic variables via statistical computation method. We investigate the countries and macro economic variables. By using statistical computation method, we derive correlation between venture capital investments and macro economic variables. According to method of logistic regression model (logit regression or logit model), macro economic variables are correlated with each other in three group. Venture capitalists regard correlations as a indicator. Finally, we give correlation matrix of our results.

The use of auxiliary variables in capture-recapture and removal experiments

USGS Publications Warehouse

Pollock, K.H.; Hines, J.E.; Nichols, J.D.

1984-01-01

The dependence of animal capture probabilities on auxiliary variables is an important practical problem which has not been considered in the development of estimation procedures for capture-recapture and removal experiments. In this paper the linear logistic binary regression model is used to relate the probability of capture to continuous auxiliary variables. The auxiliary variables could be environmental quantities such as air or water temperature, or characteristics of individual animals, such as body length or weight. Maximum likelihood estimators of the population parameters are considered for a variety of models which all assume a closed population. Testing between models is also considered. The models can also be used when one auxiliary variable is a measure of the effort expended in obtaining the sample.

Algebraic Functions of H-Functions with Specific Dependency Structure.

DTIC Science & Technology

1984-05-01

a study of its characteristic function. Such analysis is reproduced in books by Springer (17), Anderson (23), Feller (34,35), Mood and Graybill (52...following linearity property for expectations of jointly distributed random variables is derived. r 1 Theorem 1.1: If X and Y are real random variables...appear in American Journal of Mathematical and Management Science. 13. Mathai, A.M., and R.K. Saxena, "On linear combinations of stochastic variables

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

Overcoming multicollinearity in multiple regression using correlation coefficient

NASA Astrophysics Data System (ADS)

Zainodin, H. J.; Yap, S. J.

2013-09-01

Multicollinearity happens when there are high correlations among independent variables. In this case, it would be difficult to distinguish between the contributions of these independent variables to that of the dependent variable as they may compete to explain much of the similar variance. Besides, the problem of multicollinearity also violates the assumption of multiple regression: that there is no collinearity among the possible independent variables. Thus, an alternative approach is introduced in overcoming the multicollinearity problem in achieving a well represented model eventually. This approach is accomplished by removing the multicollinearity source variables on the basis of the correlation coefficient values based on full correlation matrix. Using the full correlation matrix can facilitate the implementation of Excel function in removing the multicollinearity source variables. It is found that this procedure is easier and time-saving especially when dealing with greater number of independent variables in a model and a large number of all possible models. Hence, in this paper detailed insight of the procedure is shown, compared and implemented.

Facial first impressions from another angle: How social judgements are influenced by changeable and invariant facial properties.

PubMed

Sutherland, Clare A M; Young, Andrew W; Rhodes, Gillian

2017-05-01

First impressions made to photographs of faces can depend as much on momentary characteristics of the photographed image (within-person variability) as on consistent properties of the face of the person depicted (between-person variability). Here, we examine two important sources of within-person variability: emotional expression and viewpoint. We find more within-person variability than between-person variability for social impressions of key traits of trustworthiness, dominance, and attractiveness, which index the main dimensions in theoretical models of facial impressions. The most important source of this variability is the emotional expression of the face, but the viewpoint of the photograph also affects impressions and modulates the effects of expression. For example, faces look most trustworthy with a happy expression when they are facing the perceiver, compared to when they are facing elsewhere, whereas the opposite is true for anger and disgust. Our findings highlight the integration of these different sources of variability in social impression formation. © 2016 The British Psychological Society.

Relationship among several measurements of slipperiness obtained in a laboratory environment.

PubMed

Chang, Wen-Ruey; Chang, Chien-Chi

2018-04-01

Multiple sensing mechanisms could be used in forming responses to avoid slips, but previous studies, correlating only two parameters, revealed a limited picture of this complex system. In this study, the participants walked as fast as possible without a slip under 15 conditions of different degrees of slipperiness. The relationships among various response parameters, including perceived slipperiness rating, utilized coefficient of friction (UCOF), slipmeter measurement and kinematic parameters, were evaluated. The results showed that the UCOF, perceived rating and heel angle had higher adjusted R 2 values as dependent variables in the multiple linear regressions with the remaining variables in the final pool as independent variables. Although each variable in the final data pool could reflect some measurement of slipperiness, these three variables are more inclusive than others in representing the other variables and were bigger predictors of other variables, so they could be better candidates for measurements of slipperiness. Copyright © 2017 Elsevier Ltd. All rights reserved.

Experimental verification of a real-time tuning method of a model-based controller by perturbations to its poles

NASA Astrophysics Data System (ADS)

Kajiwara, Itsuro; Furuya, Keiichiro; Ishizuka, Shinichi

2018-07-01

Model-based controllers with adaptive design variables are often used to control an object with time-dependent characteristics. However, the controller's performance is influenced by many factors such as modeling accuracy and fluctuations in the object's characteristics. One method to overcome these negative factors is to tune model-based controllers. Herein we propose an online tuning method to maintain control performance for an object that exhibits time-dependent variations. The proposed method employs the poles of the controller as design variables because the poles significantly impact performance. Specifically, we use the simultaneous perturbation stochastic approximation (SPSA) to optimize a model-based controller with multiple design variables. Moreover, a vibration control experiment of an object with time-dependent characteristics as the temperature is varied demonstrates that the proposed method allows adaptive control and stably maintains the closed-loop characteristics.

Using a cross section to train veterinary students to visualize anatomical structures in three dimensions

NASA Astrophysics Data System (ADS)

Provo, Judy; Lamar, Carlton; Newby, Timothy

2002-01-01

A cross section was used to enhance three-dimensional knowledge of anatomy of the canine head. All veterinary students in two successive classes (n = 124) dissected the head; experimental groups also identified structures on a cross section of the head. A test assessing spatial knowledge of the head generated 10 dependent variables from two administrations. The test had content validity and statistically significant interrater and test-retest reliability. A live-dog examination generated one additional dependent variable. Analysis of covariance controlling for performance on course examinations and quizzes revealed no treatment effect. Including spatial skill as a third covariate revealed a statistically significant effect of spatial skill on three dependent variables. Men initially had greater spatial skill than women, but spatial skills were equal after 8 months. A qualitative analysis showed the positive impact of this experience on participants. Suggestions for improvement and future research are discussed.

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

AGE-DEPENDENT HETEROGENEITY OF GENE EXPRESSIONS IN FISHER 344 RAT RETINAL.

EPA Science Inventory

Recent evidence suggests the elderly may be a sensitive subpopulation with regard to environmental exposure to toxic compounds. One source of this sensitivity within the aged subpopulation could be an enhanced variability in response to exposures. This variability, if sufficien...

Analysis of Factors Influencing Energy Consumption at an Air Force Base.

DTIC Science & Technology

1995-12-01

include them in energy consumption projections. 28 Table 2-3 Selected Independent Variables ( Morill , 1985) Dependent Variable Energy Conservation...most appropriate method for forecasting energy consumption (Weck, 1981; Tinsley, 1981; and Morill , 1985). This section will present a brief

Problems in using p-curve analysis and text-mining to detect rate of p-hacking and evidential value.

PubMed

Bishop, Dorothy V M; Thompson, Paul A

2016-01-01

Background. The p-curve is a plot of the distribution of p-values reported in a set of scientific studies. Comparisons between ranges of p-values have been used to evaluate fields of research in terms of the extent to which studies have genuine evidential value, and the extent to which they suffer from bias in the selection of variables and analyses for publication, p-hacking. Methods. p-hacking can take various forms. Here we used R code to simulate the use of ghost variables, where an experimenter gathers data on several dependent variables but reports only those with statistically significant effects. We also examined a text-mined dataset used by Head et al. (2015) and assessed its suitability for investigating p-hacking. Results. We show that when there is ghost p-hacking, the shape of the p-curve depends on whether dependent variables are intercorrelated. For uncorrelated variables, simulated p-hacked data do not give the "p-hacking bump" just below .05 that is regarded as evidence of p-hacking, though there is a negative skew when simulated variables are inter-correlated. The way p-curves vary according to features of underlying data poses problems when automated text mining is used to detect p-values in heterogeneous sets of published papers. Conclusions. The absence of a bump in the p-curve is not indicative of lack of p-hacking. Furthermore, while studies with evidential value will usually generate a right-skewed p-curve, we cannot treat a right-skewed p-curve as an indicator of the extent of evidential value, unless we have a model specific to the type of p-values entered into the analysis. We conclude that it is not feasible to use the p-curve to estimate the extent of p-hacking and evidential value unless there is considerable control over the type of data entered into the analysis. In particular, p-hacking with ghost variables is likely to be missed.

Assessing landslide susceptibility by statistical data analysis and GIS: the case of Daunia (Apulian Apennines, Italy)

NASA Astrophysics Data System (ADS)

Ceppi, C.; Mancini, F.; Ritrovato, G.

2009-04-01

This study aim at the landslide susceptibility mapping within an area of the Daunia (Apulian Apennines, Italy) by a multivariate statistical method and data manipulation in a Geographical Information System (GIS) environment. Among the variety of existing statistical data analysis techniques, the logistic regression was chosen to produce a susceptibility map all over an area where small settlements are historically threatened by landslide phenomena. By logistic regression a best fitting between the presence or absence of landslide (dependent variable) and the set of independent variables is performed on the basis of a maximum likelihood criterion, bringing to the estimation of regression coefficients. The reliability of such analysis is therefore due to the ability to quantify the proneness to landslide occurrences by the probability level produced by the analysis. The inventory of dependent and independent variables were managed in a GIS, where geometric properties and attributes have been translated into raster cells in order to proceed with the logistic regression by means of SPSS (Statistical Package for the Social Sciences) package. A landslide inventory was used to produce the bivariate dependent variable whereas the independent set of variable concerned with slope, aspect, elevation, curvature, drained area, lithology and land use after their reductions to dummy variables. The effect of independent parameters on landslide occurrence was assessed by the corresponding coefficient in the logistic regression function, highlighting a major role played by the land use variable in determining occurrence and distribution of phenomena. Once the outcomes of the logistic regression are determined, data are re-introduced in the GIS to produce a map reporting the proneness to landslide as predicted level of probability. As validation of results and regression model a cell-by-cell comparison between the susceptibility map and the initial inventory of landslide events was performed and an agreement at 75% level achieved.

Case-Crossover Analysis of Air Pollution Health Effects: A Systematic Review of Methodology and Application

PubMed Central

Carracedo-Martínez, Eduardo; Taracido, Margarita; Tobias, Aurelio; Saez, Marc; Figueiras, Adolfo

2010-01-01

Background Case-crossover is one of the most used designs for analyzing the health-related effects of air pollution. Nevertheless, no one has reviewed its application and methodology in this context. Objective We conducted a systematic review of case-crossover (CCO) designs used to study the relationship between air pollution and morbidity and mortality, from the standpoint of methodology and application. Data sources and extraction A search was made of the MEDLINE and EMBASE databases. Reports were classified as methodologic or applied. From the latter, the following information was extracted: author, study location, year, type of population (general or patients), dependent variable(s), independent variable(s), type of CCO design, and whether effect modification was analyzed for variables at the individual level. Data synthesis The review covered 105 reports that fulfilled the inclusion criteria. Of these, 24 addressed methodological aspects, and the remainder involved the design’s application. In the methodological reports, the designs that yielded the best results in simulation were symmetric bidirectional CCO and time-stratified CCO. Furthermore, we observed an increase across time in the use of certain CCO designs, mainly symmetric bidirectional and time-stratified CCO. The dependent variables most frequently analyzed were those relating to hospital morbidity; the pollutants most often studied were those linked to particulate matter. Among the CCO-application reports, 13.6% studied effect modification for variables at the individual level. Conclusions The use of CCO designs has undergone considerable growth; the most widely used designs were those that yielded better results in simulation studies: symmetric bidirectional and time-stratified CCO. However, the advantages of CCO as a method of analysis of variables at the individual level are put to little use. PMID:20356818

The Importance of Distance to Resources in the Spatial Modelling of Bat Foraging Habitat

PubMed Central

Rainho, Ana; Palmeirim, Jorge M.

2011-01-01

Many bats are threatened by habitat loss, but opportunities to manage their habitats are now increasing. Success of management depends greatly on the capacity to determine where and how interventions should take place, so models predicting how animals use landscapes are important to plan them. Bats are quite distinctive in the way they use space for foraging because (i) most are colonial central-place foragers and (ii) exploit scattered and distant resources, although this increases flying costs. To evaluate how important distances to resources are in modelling foraging bat habitat suitability, we radio-tracked two cave-dwelling species of conservation concern (Rhinolophus mehelyi and Miniopterus schreibersii) in a Mediterranean landscape. Habitat and distance variables were evaluated using logistic regression modelling. Distance variables greatly increased the performance of models, and distance to roost and to drinking water could alone explain 86 and 73% of the use of space by M. schreibersii and R. mehelyi, respectively. Land-cover and soil productivity also provided a significant contribution to the final models. Habitat suitability maps generated by models with and without distance variables differed substantially, confirming the shortcomings of maps generated without distance variables. Indeed, areas shown as highly suitable in maps generated without distance variables proved poorly suitable when distance variables were also considered. We concluded that distances to resources are determinant in the way bats forage across the landscape, and that using distance variables substantially improves the accuracy of suitability maps generated with spatially explicit models. Consequently, modelling with these variables is important to guide habitat management in bats and similarly mobile animals, particularly if they are central-place foragers or depend on spatially scarce resources. PMID:21547076

Spectral Variability of Two Rapidly Rotating Brown Dwarfs: 2MASS J08354256-0819237 and 2MASS J18212815+1414010

NASA Astrophysics Data System (ADS)

Schlawin, E.; Burgasser, Adam J.; Karalidi, T.; Gizis, J. E.; Teske, J.

2017-11-01

L dwarfs exhibit low-level, rotationally modulated photometric variability generally associated with heterogeneous, cloud-covered atmospheres. The spectral character of these variations yields insight into the particle sizes and vertical structure of the clouds. Here, we present the results of a high-precision, ground-based, near-infrared, spectral monitoring study of two mid-type L dwarfs that have variability reported in the literature, 2MASS J08354256-0819237 and 2MASS J18212815+1414010, using the SpeX instrument on the Infrared Telescope Facility. By simultaneously observing a nearby reference star, we achieve < 0.15 % per-band sensitivity in relative brightness changes across the 0.9-2.4 μm bandwidth. We find that 2MASS J0835-0819 exhibits marginal (≲0.5% per band) variability with no clear spectral dependence, while 2MASS J1821+1414 varies by up to ±1.5% at 0.9 μm, with the variability amplitude declining toward longer wavelengths. The latter result extends the variability trend observed in prior HST/WFC3 spectral monitoring of 2MASS J1821+1414, and we show that the full 0.9-2.4 μm variability amplitude spectrum can be reproduced by Mie extinction from dust particles with a log-normal particle size distribution with a median radius of 0.24 μm. We do not detect statistically significant phase variations with wavelength. The different variability behavior of 2MASS J0835-0819 and 2MASS J1821+1414 suggests dependencies on viewing angle and/or overall cloud content, underlying factors that can be examined through a broader survey.

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

Yust, B.L.

The relationship between fuels used by households in a rural region of Leyte Province, the Philippines, and the variables that can affect the type and amount of fuel used were examined. Data were drawn from interviews conducted in a previous study with 150 female heads of households from 10 villages near Baybay, Leyte. Within a family-ecosystem framework, a multiple regression model was developed to identify predictors of fuel use in the households. Inputs to the system included the following independent variables representing aspects of household environments; (1) natural--geographic location of the village, (2) technical--cook stove and equipment ownership, (3) economic--distancemore » to fuel sources and number of hectares of land owned, and (4) cultural-cooking fuel preference. Two regression equations were developed. The first used as the dependent variable the number of units of each of four specific fuels used in the household in one week: wood, coconut fronds, and coconut shells, and coconut husks with shells. The second used as the dependent variable an aggregate measure, barrel oil equivalent (boe), of the quantity of all fuels used in the household in one week. The households in this study were primarily dependent on biomass fuels gathered by family members; a limited quantity of commercial fuels was used.« less

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.

An investigation of the influence of process and formulation variables on mechanical properties of high shear granules using design of experiment.

PubMed

Mangwandi, Chirangano; Adams, Michael J; Hounslow, Michael J; Salman, Agba D

2012-05-10

Being able to predict the properties of granules from the knowledge of the process and formulation variables is what most industries are striving for. This research uses experimental design to investigate the effect of process variables and formulation variables on mechanical properties of pharmaceutical granules manufactured from a classical blend of lactose and starch using hydroxypropyl cellulose (HPC) as the binder. The process parameters investigated were granulation time and impeller speed whilst the formulation variables were starch-to-lactose ratio and HPC concentration. The granule properties investigated include granule packing coefficient and granule strength. The effect of some components of the formulation on mechanical properties would also depend on the process variables used in granulation process. This implies that by subjecting the same formulation to different process conditions results in products with different properties. Copyright © 2012 Elsevier B.V. All rights reserved.

Generalized Likelihood Uncertainty Estimation (GLUE) methodology for optimization of extraction in natural products.

PubMed

Maulidiani; Rudiyanto; Abas, Faridah; Ismail, Intan Safinar; Lajis, Nordin H

2018-06-01

Optimization process is an important aspect in the natural product extractions. Herein, an alternative approach is proposed for the optimization in extraction, namely, the Generalized Likelihood Uncertainty Estimation (GLUE). The approach combines the Latin hypercube sampling, the feasible range of independent variables, the Monte Carlo simulation, and the threshold criteria of response variables. The GLUE method is tested in three different techniques including the ultrasound, the microwave, and the supercritical CO 2 assisted extractions utilizing the data from previously published reports. The study found that this method can: provide more information on the combined effects of the independent variables on the response variables in the dotty plots; deal with unlimited number of independent and response variables; consider combined multiple threshold criteria, which is subjective depending on the target of the investigation for response variables; and provide a range of values with their distribution for the optimization. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Study of Effects of MultiCollinearity in the Multivariable Analysis

PubMed Central

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; (Peter) He, Qinghua; Lillard, James W.

2015-01-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables. PMID:25664257

A Study of Effects of MultiCollinearity in the Multivariable Analysis.

PubMed

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; Peter He, Qinghua; Lillard, James W

2014-10-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables.

Pharmacokinetic variability of long-acting stimulants in the treatment of children and adults with attention-deficit hyperactivity disorder.

PubMed

Ermer, James C; Adeyi, Ben A; Pucci, Michael L

2010-12-01

Methylphenidate- and amfetamine-based stimulants are first-line pharmacotherapies for attention-deficit hyperactivity disorder, a common neurobehavioural disorder in children and adults. A number of long-acting stimulant formulations have been developed with the aim of providing once-daily dosing, employing various means to extend duration of action, including a transdermal delivery system, an osmotic-release oral system, capsules with a mixture of immediate- and delayed-release beads, and prodrug technology. Coefficients of variance of pharmacokinetic measures can estimate the levels of pharmacokinetic variability based on the measurable variance between different individuals receiving the same dose of stimulant (interindividual variability) and within the same individual over multiple administrations (intraindividual variability). Differences in formulation clearly impact pharmacokinetic profiles. Many medications exhibit wide interindividual variability in clinical response. Stimulants with low levels of inter- and intraindividual variability may be better suited to provide consistent levels of medication to patients. The pharmacokinetic profile of stimulants using pH-dependent bead technology can vary depending on food consumption or concomitant administration of medications that alter gastric pH. While delivery of methylphenidate with the transdermal delivery system would be unaffected by gastrointestinal factors, intersubject variability is nonetheless substantial. Unlike the beaded formulations and, to some extent (when considering total exposure) the osmotic-release formulation, systemic exposure to amfetamine with the prodrug stimulant lisdexamfetamine dimesylate appears largely unaffected by such factors, likely owing to its dependence on systemic enzymatic cleavage of the precursor molecule, which occurs primarily in the blood involving red blood cells. The high capacity but as yet unidentified enzymatic system for conversion of lisdexamfetamine dimesylate may contribute to its consistent pharmacokinetic profile. The reasons underlying observed differential responses to stimulants are likely to be multifactorial, including pharmacodynamic factors. While the use of stimulants with low inter- and intrapatient pharmacokinetic variability does not obviate the need to titrate stimulant doses, stimulants with low intraindividual variation in pharmacokinetic parameters may reduce the likelihood of patients falling into subtherapeutic drug concentrations or reaching drug concentrations at which the risk of adverse events increases. As such, clinicians are urged both to adjust stimulant doses based on therapeutic response and the risk for adverse events and to monitor patients for potential causes of pharmacokinetic variability.

Spatial variability assessment of soil nutrients in an intense agricultural area, a case study of Rugao County in Yangtze River Delta Region, China

NASA Astrophysics Data System (ADS)

Zhao, Yongcun; Xu, Xianghua; Darilek, Jeremy Landon; Huang, Biao; Sun, Weixia; Shi, Xuezheng

2009-05-01

Topsoil samples (0-20 cm) ( n = 237) were collected from Rugao County, China. Geostatistical variogram analysis, sequential Gaussian simulation (SGS), and principal component (PC) analysis were applied to assess spatial variability of soil nutrients, identify the possible areas of nutrient deficiency, and explore spatial scale of variability of soil nutrients in the county. High variability of soil nutrient such as soil organic matter (SOM), total nitrogen (TN), available P, K, Fe, Mn, Cu, Zn, and B concentrations were observed. Soil nutrient properties displayed significant differences in their spatial structures, with available Cu having strong spatial dependence, SOM and available P having weak spatial dependence, and other nutrient properties having moderate spatial dependence. The soil nutrient deficiency, defined here as measured nutrient concentrations which do not meet the advisory threshold values specific to the county for dominant crops, namely rice, wheat, and rape seeds, was observed in available K and Zn, and the deficient areas covered 38 and 11%, respectively. The first three PCs of the nine soil nutrient properties explained 62.40% of the total variance. TN and SOM with higher loadings on PC1 are closely related to soil texture derived from different parent materials. The PC2 combined intermediate response variables such as available Zn and P that are likely to be controlled by land use and soil pH. Available B has the highest loading on PC3 and its variability of concentrations may be primarily ascribed to localized anthropogenic influence. The amelioration of soil physical properties (i.e. soil texture) and soil pH may improve the availability of soil nutrients and the sustainability of the agricultural system of Rugao County.

Linear response theory for annealing of radiation damage in semiconductor devices

NASA Technical Reports Server (NTRS)

Litovchenko, Vitaly

1988-01-01

A theoretical study of the radiation/annealing response of MOS ICs is described. Although many experiments have been performed in this field, no comprehensive theory dealing with radiation/annealing response has been proposed. Many attempts have been made to apply linear response theory, but no theoretical foundation has been presented. The linear response theory outlined here is capable of describing a broad area of radiation/annealing response phenomena in MOS ICs, in particular, both simultaneous irradiation and annealing, as well as short- and long-term annealing, including the case when annealing is nearing completion. For the first time, a simple procedure is devised to determine the response function from experimental radiation/annealing data. In addition, this procedure enables us to study the effect of variable temperature and dose rate, effects which are of interest in spaceflight. In the past, the shift in threshold potential due to radiation/annealing has usually been assumed to depend on one variable: the time lapse between an impulse dose and the time of observation. While such a suggestion of uniformity in time is certainly true for a broad range of radiation annealing phenomena, it may not hold for some ranges of the variables of interest (temperature, dose rate, etc.). A response function is projected which is dependent on two variables: the time of observation and the time of the impulse dose. This dependence on two variables allows us to extend the theory to the treatment of a variable dose rate. Finally, the linear theory is generalized to the case in which the response is nonlinear with impulse dose, but is proportional to some impulse function of dose. A method to determine both the impulse and response functions is presented.

The contribution of individual and pairwise combinations of SNPs in the APOA1 and APOC3 genes to interindividual HDL-C variability.

PubMed

Brown, C M; Rea, T J; Hamon, S C; Hixson, J E; Boerwinkle, E; Clark, A G; Sing, C F

2006-07-01

Apolipoproteins (apo) A-I and C-III are components of high-density lipoprotein-cholesterol (HDL-C), a quantitative trait negatively correlated with risk of cardiovascular disease (CVD). We analyzed the contribution of individual and pairwise combinations of single nucleotide polymorphisms (SNPs) in the APOA1/APOC3 genes to HDL-C variability to evaluate (1) consistency of published single-SNP studies with our single-SNP analyses; (2) consistency of single-SNP and two-SNP phenotype-genotype relationships across race-, gender-, and geographical location-dependent contexts; and (3) the contribution of single SNPs and pairs of SNPs to variability beyond that explained by plasma apo A-I concentration. We analyzed 45 SNPs in 3,831 young African-American (N=1,858) and European-American (N=1,973) females and males ascertained by the Coronary Artery Risk Development in Young Adults (CARDIA) study. We found three SNPs that significantly impact HDL-C variability in both the literature and the CARDIA sample. Single-SNP analyses identified only one of five significant HDL-C SNP genotype relationships in the CARDIA study that was consistent across all race-, gender-, and geographical location-dependent contexts. The other four were consistent across geographical locations for a particular race-gender context. The portion of total phenotypic variance explained by single-SNP genotypes and genotypes defined by pairs of SNPs was less than 3%, an amount that is miniscule compared to the contribution explained by variability in plasma apo A-I concentration. Our findings illustrate the impact of context-dependence on SNP selection for prediction of CVD risk factor variability.

The Sloan Digital Sky Survey Reverberation Mapping Project: The C IV Blueshift, Its Variability, and Its Dependence Upon Quasar Properties

NASA Astrophysics Data System (ADS)

Sun, Mouyuan; Xue, Yongquan; Richards, Gordon T.; Trump, Jonathan R.; Shen, Yue; Brandt, W. N.; Schneider, D. P.

2018-02-01

We use the multi-epoch spectra of 362 quasars from the Sloan Digital Sky Survey Reverberation Mapping project to investigate the dependence of the blueshift of C IV relative to Mg II on quasar properties. We confirm that high-blueshift sources tend to have low C IV equivalent widths (EWs), and that the low-EW sources span a range of blueshift. Other high-ionization lines, such as He II, also show similar blueshift properties. The ratio of the line width (measured as both the full width at half maximum and the velocity dispersion) of C IV to that of Mg II increases with blueshift. Quasar variability enhances the connection between the C IV blueshift and quasar properties (e.g., EW). The variability of the Mg II line center (i.e., the wavelength that bisects the cumulative line flux) increases with blueshift. In contrast, the C IV line center shows weaker variability at the extreme blueshifts. Quasars with the high-blueshift C IV lines tend to have less variable continuum emission, when controlling for EW, luminosity, and redshift. Our results support the scenario that high-blueshift sources tend to have large Eddington ratios.

Analysis of the Influence of Quantile Regression Model on Mainland Tourists' Service Satisfaction Performance

PubMed Central

Wang, Wen-Cheng; Cho, Wen-Chien; Chen, Yin-Jen

2014-01-01

It is estimated that mainland Chinese tourists travelling to Taiwan can bring annual revenues of 400 billion NTD to the Taiwan economy. Thus, how the Taiwanese Government formulates relevant measures to satisfy both sides is the focus of most concern. Taiwan must improve the facilities and service quality of its tourism industry so as to attract more mainland tourists. This paper conducted a questionnaire survey of mainland tourists and used grey relational analysis in grey mathematics to analyze the satisfaction performance of all satisfaction question items. The first eight satisfaction items were used as independent variables, and the overall satisfaction performance was used as a dependent variable for quantile regression model analysis to discuss the relationship between the dependent variable under different quantiles and independent variables. Finally, this study further discussed the predictive accuracy of the least mean regression model and each quantile regression model, as a reference for research personnel. The analysis results showed that other variables could also affect the overall satisfaction performance of mainland tourists, in addition to occupation and age. The overall predictive accuracy of quantile regression model Q0.25 was higher than that of the other three models. PMID:24574916

Indicators of Dysphagia in Aged Care Facilities.

PubMed

Pu, Dai; Murry, Thomas; Wong, May C M; Yiu, Edwin M L; Chan, Karen M K

2017-09-18

The current cross-sectional study aimed to investigate risk factors for dysphagia in elderly individuals in aged care facilities. A total of 878 individuals from 42 aged care facilities were recruited for this study. The dependent outcome was speech therapist-determined swallowing function. Independent factors were Eating Assessment Tool score, oral motor assessment score, Mini-Mental State Examination, medical history, and various functional status ratings. Binomial logistic regression was used to identify independent variables associated with dysphagia in this cohort. Two statistical models were constructed. Model 1 used variables from case files without the need for hands-on assessment, and Model 2 used variables that could be obtained from hands-on assessment. Variables positively associated with dysphagia identified in Model 1 were male gender, total dependence for activities of daily living, need for feeding assistance, mobility, requiring assistance walking or using a wheelchair, and history of pneumonia. Variables positively associated with dysphagia identified in Model 2 were Mini-Mental State Examination score, edentulousness, and oral motor assessments score. Cognitive function, dentition, and oral motor function are significant indicators associated with the presence of swallowing in the elderly. When assessing the frail elderly, case file information can help clinicians identify frail elderly individuals who may be suffering from dysphagia.

Application of Probabilistic Methods for the Determination of an Economically Robust HSCT Configuration

NASA Technical Reports Server (NTRS)

Mavris, Dimitri N.; Bandte, Oliver; Schrage, Daniel P.

1996-01-01

This paper outlines an approach for the determination of economically viable robust design solutions using the High Speed Civil Transport (HSCT) as a case study. Furthermore, the paper states the advantages of a probability based aircraft design over the traditional point design approach. It also proposes a new methodology called Robust Design Simulation (RDS) which treats customer satisfaction as the ultimate design objective. RDS is based on a probabilistic approach to aerospace systems design, which views the chosen objective as a distribution function introduced by so called noise or uncertainty variables. Since the designer has no control over these variables, a variability distribution is defined for each one of them. The cumulative effect of all these distributions causes the overall variability of the objective function. For cases where the selected objective function depends heavily on these noise variables, it may be desirable to obtain a design solution that minimizes this dependence. The paper outlines a step by step approach on how to achieve such a solution for the HSCT case study and introduces an evaluation criterion which guarantees the highest customer satisfaction. This customer satisfaction is expressed by the probability of achieving objective function values less than a desired target value.

Analysis of the influence of quantile regression model on mainland tourists' service satisfaction performance.

PubMed

Wang, Wen-Cheng; Cho, Wen-Chien; Chen, Yin-Jen

2014-01-01

It is estimated that mainland Chinese tourists travelling to Taiwan can bring annual revenues of 400 billion NTD to the Taiwan economy. Thus, how the Taiwanese Government formulates relevant measures to satisfy both sides is the focus of most concern. Taiwan must improve the facilities and service quality of its tourism industry so as to attract more mainland tourists. This paper conducted a questionnaire survey of mainland tourists and used grey relational analysis in grey mathematics to analyze the satisfaction performance of all satisfaction question items. The first eight satisfaction items were used as independent variables, and the overall satisfaction performance was used as a dependent variable for quantile regression model analysis to discuss the relationship between the dependent variable under different quantiles and independent variables. Finally, this study further discussed the predictive accuracy of the least mean regression model and each quantile regression model, as a reference for research personnel. The analysis results showed that other variables could also affect the overall satisfaction performance of mainland tourists, in addition to occupation and age. The overall predictive accuracy of quantile regression model Q0.25 was higher than that of the other three models.

Size, Loading Efficiency, and Cytotoxicity of Albumin-Loaded Chitosan Nanoparticles: An Artificial Neural Networks Study.

PubMed

Baharifar, Hadi; Amani, Amir

2017-01-01

When designing nanoparticles for drug delivery, many variables such as size, loading efficiency, and cytotoxicity should be considered. Usually, smaller particles are preferred in drug delivery because of longer blood circulation time and their ability to escape from immune system, whereas smaller nanoparticles often show increased toxicity. Determination of parameters which affect size of particles and factors such as loading efficiency and cytotoxicity could be very helpful in designing drug delivery systems. In this work, albumin (as a protein drug model)-loaded chitosan nanoparticles were prepared by polyelectrolyte complexation method. Simultaneously, effects of 4 independent variables including chitosan and albumin concentrations, pH, and reaction time were determined on 3 dependent variables (i.e., size, loading efficiency, and cytotoxicity) by artificial neural networks. Results showed that concentrations of initial materials are the most important factors which may affect the dependent variables. A drop in the concentrations decreases the size directly, but they simultaneously decrease loading efficiency and increase cytotoxicity. Therefore, an optimization of the independent variables is required to obtain the most useful preparation. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

An open-source software package for multivariate modeling and clustering: applications to air quality management.

PubMed

Wang, Xiuquan; Huang, Guohe; Zhao, Shan; Guo, Junhong

2015-09-01

This paper presents an open-source software package, rSCA, which is developed based upon a stepwise cluster analysis method and serves as a statistical tool for modeling the relationships between multiple dependent and independent variables. The rSCA package is efficient in dealing with both continuous and discrete variables, as well as nonlinear relationships between the variables. It divides the sample sets of dependent variables into different subsets (or subclusters) through a series of cutting and merging operations based upon the theory of multivariate analysis of variance (MANOVA). The modeling results are given by a cluster tree, which includes both intermediate and leaf subclusters as well as the flow paths from the root of the tree to each leaf subcluster specified by a series of cutting and merging actions. The rSCA package is a handy and easy-to-use tool and is freely available at http://cran.r-project.org/package=rSCA . By applying the developed package to air quality management in an urban environment, we demonstrate its effectiveness in dealing with the complicated relationships among multiple variables in real-world problems.

Combinations of response-reinforcer relations in periodic and aperiodic schedules.

PubMed

Kuroda, Toshikazu; Cançado, Carlos R X; Lattal, Kennon A; Elcoro, Mirari; Dickson, Chata A; Cook, James E

2013-03-01

Key pecking of 4 pigeons was studied under a two-component multiple schedule in which food deliveries were arranged according to a fixed and a variable interfood interval. The percentage of response-dependent food in each component was varied, first in ascending (0, 10, 30, 70 and 100%) and then in descending orders, in successive conditions. The change in response rates was positively related to the percentage of response-dependent food in each schedule component. Across conditions, positively accelerated and linear patterns of responding occurred consistently in the fixed and variable components, respectively. These results suggest that the response-food dependency determines response rates in periodic and aperiodic schedules, and that the temporal distribution of food determines response patterns independently of the response-food dependency. Running rates, but not postfood pauses, also were positively related to the percentage of dependent food in each condition, in both fixed and variable components. Thus, the relation between overall response rate and the percentage of dependent food was mediated by responding that occurred after postfood pausing. The findings together extend previous studies wherein the dependency was either always present or absent, and increase the generality of the effects of variations in the response-food dependency from aperiodic to periodic schedules. © Society for the Experimental Analysis of Behavior.

A robust variable sampling time BLDC motor control design based upon μ-synthesis.

PubMed

Hung, Chung-Wen; Yen, Jia-Yush

2013-01-01

The variable sampling rate system is encountered in many applications. When the speed information is derived from the position marks along the trajectory, one would have a speed dependent sampling rate system. The conventional fixed or multisampling rate system theory may not work in these cases because the system dynamics include the uncertainties which resulted from the variable sampling rate. This paper derived a convenient expression for the speed dependent sampling rate system. The varying sampling rate effect is then translated into multiplicative uncertainties to the system. The design then uses the popular μ-synthesis process to achieve a robust performance controller design. The implementation on a BLDC motor demonstrates the effectiveness of the design approach.

A Robust Variable Sampling Time BLDC Motor Control Design Based upon μ-Synthesis

PubMed Central

Yen, Jia-Yush

2013-01-01

The variable sampling rate system is encountered in many applications. When the speed information is derived from the position marks along the trajectory, one would have a speed dependent sampling rate system. The conventional fixed or multisampling rate system theory may not work in these cases because the system dynamics include the uncertainties which resulted from the variable sampling rate. This paper derived a convenient expression for the speed dependent sampling rate system. The varying sampling rate effect is then translated into multiplicative uncertainties to the system. The design then uses the popular μ-synthesis process to achieve a robust performance controller design. The implementation on a BLDC motor demonstrates the effectiveness of the design approach. PMID:24327804

Silicon monoxide in the 4 micron infrared spectrum of long-period variables

NASA Technical Reports Server (NTRS)

Hinkle, K. H.; Barnes, T. G.; Lambert, D. L.; Beer, R.

1976-01-01

The first-overtone sequence of vibration-rotation transitions of the free radical silicon monoxide are shown to have extreme phase-dependent variations in the spectra of two M-type long-period variables, Omicron Ceti and R Leonis, and the mild S-type long-period variable, Chi Cygni. At maximum light, the SiO band heads are not detectable. Near minimum light, the band heads of (Si-25)O are detected in the 4-micron spectra of all three stars. The band heads of the terrestrially less abundant isotopic species, (Si-29)O and (Si-30)O, are detected in Chi Cygni. Possible explanations of the phase-dependent behavior are discussed, and the role of the stellar chromosphere is considered.

Increasing Self-Regulation and Classroom Participation of a Child Who Is Deafblind.

PubMed

Nelson, Catherine; Hyte, Holly A; Greenfield, Robin

2016-01-01

Self-regulation has been identified as essential to school success. However, for a variety of reasons, its development may be compromised in children and youth who are deafblind. A single-case multiple-baseline study of a child who was deafblind examined the effects of three groups of evidence-based interventions on variables thought to be associated with self-regulation. The dependent variables were (a) frequency and duration of behaviors thought to indicate dysregulation, (b) active participation in school activities, and (c) time from onset of behaviors indicating dysregulation until achievement of a calm, regulated state. The interventions, which included provision of meaningful, enjoyable, and interactive activities, anticipatory strategies, and calming strategies, significantly influenced the dependent variables and are described in detail.

Antisaccade performance of 1,273 men: effects of schizotypy, anxiety, and depression.

PubMed

Smyrnis, Nikolaos; Evdokimidis, Ioannis; Stefanis, Nicholas C; Avramopoulos, Dimitrios; Constantinidis, Theodoros S; Stavropoulos, Alexios; Stefanis, Costas N

2003-08-01

A total of 1,273 conscripts of the Greek Air Force performed antisaccades and completed self-reporting questionnaires measuring schizotypy and current state-dependent psychopathology. Only 1.0% of variability in antisaccade performance indices was related to psychometric scores in the population and could be attributed more to current state-dependent symptoms such as anxiety rather than to schizotypy. In contrast, a specific increase of error rate and response latency variability and a high correlation of these 2 variables was observed in a group with very high schizotypy scores. This effect was independent of anxiety and depression, suggesting that a specific group of psychosis-prone individuals has a characteristic deviance in antisaccade performance that is not present in the general population.

Shoulder pain and time dependent structure in wheelchair propulsion variability.

PubMed

Jayaraman, Chandrasekaran; Moon, Yaejin; Sosnoff, Jacob J

2016-07-01

Manual wheelchair propulsion places considerable repetitive mechanical strain on the upper limbs leading to shoulder injury and pain. While recent research indicates that the amount of variability in wheelchair propulsion and shoulder pain may be related. There has been minimal inquiry into the fluctuation over time (i.e. time-dependent structure) in wheelchair propulsion variability. Consequently the purpose of this investigation was to examine if the time-dependent structure in the wheelchair propulsion parameters are related to shoulder pain. 27 experienced wheelchair users manually propelled their own wheelchair fitted with a SMARTWheel on a roller at 1.1m/s for 3min. Time-dependent structure of cycle-to-cycle fluctuations in contact angle and inter push time interval was quantified using sample entropy (SampEn) and compared between the groups with/without shoulder pain using non-parametric statistics. Overall findings were, (1) variability observed in contact angle fluctuations during manual wheelchair propulsion is structured (Z=3.15;p<0.05), (2) individuals with shoulder pain exhibited higher SampEn magnitude for contact angle during wheelchair propulsion than those without pain (χ(2)(1)=6.12;p<0.05); and (3) SampEn of contact angle correlated significantly with self-reported shoulder pain (rs (WUSPI) =0.41;rs (VAS)=0.56;p<0.05). It was concluded that the time-dependent structure in wheelchair propulsion may provide novel information for tracking and monitoring shoulder pain. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Assessment of variability in the hydrological cycle of the Loess Plateau, China: examining dependence structures of hydrological processes

NASA Astrophysics Data System (ADS)

Guo, A.; Wang, Y.

2017-12-01

Investigating variability in dependence structures of hydrological processes is of critical importance for developing an understanding of mechanisms of hydrological cycles in changing environments. In focusing on this topic, present work involves the following: (1) identifying and eliminating serial correlation and conditional heteroscedasticity in monthly streamflow (Q), precipitation (P) and potential evapotranspiration (PE) series using the ARMA-GARCH model (ARMA: autoregressive moving average; GARCH: generalized autoregressive conditional heteroscedasticity); (2) describing dependence structures of hydrological processes using partial copula coupled with the ARMA-GARCH model and identifying their variability via copula-based likelihood-ratio test method; and (3) determining conditional probability of annual Q under different climate scenarios on account of above results. This framework enables us to depict hydrological variables in the presence of conditional heteroscedasticity and to examine dependence structures of hydrological processes while excluding the influence of covariates by using partial copula-based ARMA-GARCH model. Eight major catchments across the Loess Plateau (LP) are used as study regions. Results indicate that (1) The occurrence of change points in dependence structures of Q and P (PE) varies across the LP. Change points of P-PE dependence structures in all regions almost fully correspond to the initiation of global warming, i.e., the early 1980s. (3) Conditional probabilities of annual Q under various P and PE scenarios are estimated from the 3-dimensional joint distribution of (Q, P and PE) based on the above change points. These findings shed light on mechanisms of the hydrological cycle and can guide water supply planning and management, particularly in changing environments.

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

Miller, D. J.

It is shown that a weak measurement of a quantum system produces a new state of the quantum system which depends on the prior state, as well as the (uncontrollable) measured position of the pointer variable of the weak-measurement apparatus. The result imposes a constraint on hidden-variable theories which assign a different state to a quantum system than standard quantum mechanics. The constraint means that a crypto-nonlocal hidden-variable theory can be ruled out in a more direct way than previously done.

The finite element method scheme for a solution of an evolution variational inequality with a nonlocal space operator

NASA Astrophysics Data System (ADS)

Glazyrina, O. V.; Pavlova, M. F.

2016-11-01

We consider the parabolic inequality with monotone with respect to a gradient space operator, which is depended on integral with respect to space variables solution characteristic. We construct a two-layer differential scheme for this problem with use of penalty method, semidiscretization with respect to time variable method and the finite element method (FEM) with respect to space variables. We proved a convergence of constructed mothod.

Association of Fatigue With Sarcopenia and its Elements: A Secondary Analysis of SABE-Bogotá

PubMed Central

Patino-Hernandez, Daniela; David-Pardo, David Gabriel; Borda, Miguel Germán; Pérez-Zepeda, Mario Ulises; Cano-Gutiérrez, Carlos

2017-01-01

Objective: Sarcopenia, fatigue, and depression are associated with higher mortality rates and adverse outcomes in the aging population. Understanding the association among clinical variables, mainly symptoms, is important for screening and appropriately managing these conditions. The aim of this article is to evaluate the association among sarcopenia and its elements with depression and fatigue. Method: We used cross-sectional data from 2012 SABE (Salud, Bienestar y Envejecimiento)-Bogotá study, which included 2,000 participants of ages ≥60 years. Sarcopenia and its elements were taken as the dependent variable, while fatigue and depression were the main independent variables. We tested the association among these through multiple logistic regression models, which were fitted for each dependent variable and adjusted for confounding variables. Results: Our findings showed that gait speed was associated with fatigue (adjusted odds ratio [OR] = 1.41, 95% confidence interval [CI] = [1.05, 1.90], p = .02) as well as abnormal handgrip strength (adjusted OR = 1.40, 95% CI = [1.02, 1.93], p = .04). No other associations were significant. Conclusion: While sarcopenia and fatigue are not associated, two of the sarcopenia-defining variables are associated with fatigue; this suggests that lack of sarcopenia does not exclude undesirable outcomes related to fatigue in aging adults. Also, the lack of association between sarcopenia-defining elements and depression demonstrates that depression and fatigue are different concepts. PMID:28474000

Applying causal mediation analysis to personality disorder research.

PubMed

Walters, Glenn D

2018-01-01

This article is designed to address fundamental issues in the application of causal mediation analysis to research on personality disorders. Causal mediation analysis is used to identify mechanisms of effect by testing variables as putative links between the independent and dependent variables. As such, it would appear to have relevance to personality disorder research. It is argued that proper implementation of causal mediation analysis requires that investigators take several factors into account. These factors are discussed under 5 headings: variable selection, model specification, significance evaluation, effect size estimation, and sensitivity testing. First, care must be taken when selecting the independent, dependent, mediator, and control variables for a mediation analysis. Some variables make better mediators than others and all variables should be based on reasonably reliable indicators. Second, the mediation model needs to be properly specified. This requires that the data for the analysis be prospectively or historically ordered and possess proper causal direction. Third, it is imperative that the significance of the identified pathways be established, preferably with a nonparametric bootstrap resampling approach. Fourth, effect size estimates should be computed or competing pathways compared. Finally, investigators employing the mediation method are advised to perform a sensitivity analysis. Additional topics covered in this article include parallel and serial multiple mediation designs, moderation, and the relationship between mediation and moderation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Canonical correlation analysis of infant's size at birth and maternal factors: a study in rural northwest Bangladesh.

PubMed

Kabir, Alamgir; Merrill, Rebecca D; Shamim, Abu Ahmed; Klemn, Rolf D W; Labrique, Alain B; Christian, Parul; West, Keith P; Nasser, Mohammed

2014-01-01

This analysis was conducted to explore the association between 5 birth size measurements (weight, length and head, chest and mid-upper arm [MUAC] circumferences) as dependent variables and 10 maternal factors as independent variables using canonical correlation analysis (CCA). CCA considers simultaneously sets of dependent and independent variables and, thus, generates a substantially reduced type 1 error. Data were from women delivering a singleton live birth (n = 14,506) while participating in a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural Bangladesh. The first canonical correlation was 0.42 (P<0.001), demonstrating a moderate positive correlation mainly between the 5 birth size measurements and 5 maternal factors (preterm delivery, early pregnancy MUAC, infant sex, age and parity). A significant interaction between infant sex and preterm delivery on birth size was also revealed from the score plot. Thirteen percent of birth size variability was explained by the composite score of the maternal factors (Redundancy, RY/X = 0.131). Given an ability to accommodate numerous relationships and reduce complexities of multiple comparisons, CCA identified the 5 maternal variables able to predict birth size in this rural Bangladesh setting. CCA may offer an efficient, practical and inclusive approach to assessing the association between two sets of variables, addressing the innate complexity of interactions.

Climate-driven vital rates do not always mean climate-driven population.

PubMed

Tavecchia, Giacomo; Tenan, Simone; Pradel, Roger; Igual, José-Manuel; Genovart, Meritxell; Oro, Daniel

2016-12-01

Current climatic changes have increased the need to forecast population responses to climate variability. A common approach to address this question is through models that project current population state using the functional relationship between demographic rates and climatic variables. We argue that this approach can lead to erroneous conclusions when interpopulation dispersal is not considered. We found that immigration can release the population from climate-driven trajectories even when local vital rates are climate dependent. We illustrated this using individual-based data on a trans-equatorial migratory seabird, the Scopoli's shearwater Calonectris diomedea, in which the variation of vital rates has been associated with large-scale climatic indices. We compared the population annual growth rate λ i , estimated using local climate-driven parameters with ρ i , a population growth rate directly estimated from individual information and that accounts for immigration. While λ i varied as a function of climatic variables, reflecting the climate-dependent parameters, ρ i did not, indicating that dispersal decouples the relationship between population growth and climate variables from that between climatic variables and vital rates. Our results suggest caution when assessing demographic effects of climatic variability especially in open populations for very mobile organisms such as fish, marine mammals, bats, or birds. When a population model cannot be validated or it is not detailed enough, ignoring immigration might lead to misleading climate-driven projections. © 2016 John Wiley & Sons Ltd.

Variation, Repetition, and Choice

ERIC Educational Resources Information Center

Abreu-Rodrigues, Josele; Lattal, Kennon A.; dos Santos, Cristiano V.; Matos, Ricardo A.

2005-01-01

Experiment 1 investigated the controlling properties of variability contingencies on choice between repeated and variable responding. Pigeons were exposed to concurrent-chains schedules with two alternatives. In the REPEAT alternative, reinforcers in the terminal link depended on a single sequence of four responses. In the VARY alternative, a…

Development of variable LRFD \\0x03C6 factors for deep foundation design due to site variability [summary].

DOT National Transportation Integrated Search

2012-01-01

Both the Florida Department of Transportation : (FDOT) and the Federal Highway Administration : (FHWA) specify use of fixed resistance factors () : for Load and Resistance Factored Design (LRFD) of : deep foundations, depending on design approach :...

Age Dependent Variability in Gene Expression in Fischer 344 Rat Retina.

EPA Science Inventory

Recent evidence suggests older adults may be a sensitive population with regard to environmental exposure to toxic compounds. One source of this sensitivity could be an enhanced variability in response. Studies on phenotypic differences have suggested that variation in response d...

Quantitative variability of renewable energy resources in Norway

NASA Astrophysics Data System (ADS)

Christakos, Konstantinos; Varlas, George; Cheliotis, Ioannis; Aalstad, Kristoffer; Papadopoulos, Anastasios; Katsafados, Petros; Steeneveld, Gert-Jan

2017-04-01

Based on European Union (EU) targets for 2030, the share of renewable energy (RE) consumption should be increased at 27%. RE resources such as hydropower, wind, wave power and solar power are strongly depending on the chaotic behavior of the weather conditions and climate. Due to this dependency, the prediction of the spatiotemporal variability of the RE resources is more crucial factor than in other energy resources (i.e. carbon based energy). The fluctuation of the RE resources can affect the development of the RE technologies, the energy grid, supply and prices. This study investigates the variability of the potential RE resources in Norway. More specifically, hydropower, wind, wave, and solar power are quantitatively analyzed and correlated with respect to various spatial and temporal scales. In order to analyze the diversities and their interrelationships, reanalysis and observational data of wind, precipitation, wave, and solar radiation are used for a quantitative assessment. The results indicate a high variability of marine RE resources in the North Sea and the Norwegian Sea.

Serial position effects are sensitive predictors of conversion from MCI to Alzheimer's disease dementia.

PubMed

Egli, Simone C; Beck, Irene R; Berres, Manfred; Foldi, Nancy S; Monsch, Andreas U; Sollberger, Marc

2014-10-01

It is unclear whether the predictive strength of established cognitive variables for progression to Alzheimer's disease (AD) dementia from mild cognitive impairment (MCI) varies depending on time to conversion. We investigated which cognitive variables were best predictors, and which of these variables remained predictive for patients with longer times to conversion. Seventy-five participants with MCI were assessed on measures of learning, memory, language, and executive function. Relative predictive strengths of these measures were analyzed using Cox regression models. Measures of word-list position-namely, serial position scores-together with Short Delay Free Recall of word-list learning best predicted conversion to AD dementia. However, only serial position scores predicted those participants with longer time to conversion. Results emphasize that the predictive strength of cognitive variables varies depending on time to conversion to dementia. Moreover, finer measures of learning captured by serial position scores were the most sensitive predictors of AD dementia. Copyright © 2014 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Attentional modulation of neuronal variability in circuit models of cortex

PubMed Central

Kanashiro, Tatjana; Ocker, Gabriel Koch; Cohen, Marlene R; Doiron, Brent

2017-01-01

The circuit mechanisms behind shared neural variability (noise correlation) and its dependence on neural state are poorly understood. Visual attention is well-suited to constrain cortical models of response variability because attention both increases firing rates and their stimulus sensitivity, as well as decreases noise correlations. We provide a novel analysis of population recordings in rhesus primate visual area V4 showing that a single biophysical mechanism may underlie these diverse neural correlates of attention. We explore model cortical networks where top-down mediated increases in excitability, distributed across excitatory and inhibitory targets, capture the key neuronal correlates of attention. Our models predict that top-down signals primarily affect inhibitory neurons, whereas excitatory neurons are more sensitive to stimulus specific bottom-up inputs. Accounting for trial variability in models of state dependent modulation of neuronal activity is a critical step in building a mechanistic theory of neuronal cognition. DOI: http://dx.doi.org/10.7554/eLife.23978.001 PMID:28590902

Modeling of laser transmission contour welding process using FEA and DoE

NASA Astrophysics Data System (ADS)

Acherjee, Bappa; Kuar, Arunanshu S.; Mitra, Souren; Misra, Dipten

2012-07-01

In this research, a systematic investigation on laser transmission contour welding process is carried out using finite element analysis (FEA) and design of experiments (DoE) techniques. First of all, a three-dimensional thermal model is developed to simulate the laser transmission contour welding process with a moving heat source. The commercial finite element code ANSYS® multi-physics is used to obtain the numerical results by implementing a volumetric Gaussian heat source, and combined convection-radiation boundary conditions. Design of experiments together with regression analysis is then employed to plan the experiments and to develop mathematical models based on simulation results. Four key process parameters, namely power, welding speed, beam diameter, and carbon black content in absorbing polymer, are considered as independent variables, while maximum temperature at weld interface, weld width, and weld depths in transparent and absorbing polymers are considered as dependent variables. Sensitivity analysis is performed to determine how different values of an independent variable affect a particular dependent variable.

Influence of age on the correlations of hematological and biochemical variables with the stability of erythrocyte membrane in relation to sodium dodecyl sulfate.

PubMed

de Freitas, Mariana V; Marquez-Bernardes, Liandra F; de Arvelos, Letícia R; Paraíso, Lara F; Gonçalves E Oliveira, Ana Flávia M; Mascarenhas Netto, Rita de C; Neto, Morun Bernardino; Garrote-Filho, Mario S; de Souza, Paulo César A; Penha-Silva, Nilson

2014-10-01

To evaluate the influence of age on the relationships between biochemical and hematological variables and stability of erythrocyte membrane in relation to the sodium dodecyl sulfate (SDS) in population of 105 female volunteers between 20 and 90 years. The stability of RBC membrane was determined by non-linear regression of the dependency of the absorbance of hemoglobin released as a function of SDS concentration, represented by the half-transition point of the curve (D50) and the variation in the concentration of the detergent to promote lysis (dD). There was an age-dependent increase in the membrane stability in relation to SDS. Analyses by multiple linear regression showed that this stability increase is significantly related to the hematological variable red cell distribution width (RDW) and the biochemical variables blood albumin and cholesterol. The positive association between erythrocyte stability and RDW may reflect one possible mechanism involved in the clinical meaning of this hematological index.

Methods for measuring, enhancing, and accounting for medication adherence in clinical trials.

PubMed

Vrijens, B; Urquhart, J

2014-06-01

Adherence to rationally prescribed medications is essential for effective pharmacotherapy. However, widely variable adherence to protocol-specified dosing regimens is prevalent among participants in ambulatory drug trials, mostly manifested in the form of underdosing. Drug actions are inherently dose and time dependent, and as a result, variable underdosing diminishes the actions of trial medications by various degrees. The ensuing combination of increased variability and decreased magnitude of trial drug actions reduces statistical power to discern between-group differences in drug actions. Variable underdosing has many adverse consequences, some of which can be mitigated by the combination of reliable measurements of ambulatory patients' adherence to trial and nontrial medications, measurement-guided management of adherence, statistically and pharmacometrically sound analyses, and modifications in trial design. Although nonadherence is prevalent across all therapeutic areas in which the patients are responsible for treatment administration, the significance of the adverse consequences depends on the characteristics of both the disease and the medications.

Relationship of negative self-schemas and attachment styles with appearance schemas.

PubMed

Ledoux, Tracey; Winterowd, Carrie; Richardson, Tamara; Clark, Julie Dorton

2010-06-01

The purpose was to test, among women, the relationship between negative self-schemas and styles of attachment with men and women and two types of appearance investment (Self-evaluative and Motivational Salience). Predominantly Caucasian undergraduate women (N=194) completed a modified version of the Relationship Questionnaire, the Young Schema Questionnaire-Short Form, and the Appearance Schemas Inventory-Revised. Linear multiple regression analyses were conducted with Motivational Salience and Self-evaluative Salience of appearance serving as dependent variables and relevant demographic variables, negative self-schemas, and styles of attachment to men serving as independent variables. Styles of attachment to women were not entered into these regression models because Pearson correlations indicated they were not related to either dependent variable. Self-evaluative Salience of appearance was related to impaired autonomy and performance negative self-schema and the preoccupation style of attachment with men, while Motivational Salience of appearance was related only to the preoccupation style of attachment with men. 2010 Elsevier Ltd. All rights reserved.

Computation of Standard Errors

PubMed Central

Dowd, Bryan E; Greene, William H; Norton, Edward C

2014-01-01

Objectives We discuss the problem of computing the standard errors of functions involving estimated parameters and provide the relevant computer code for three different computational approaches using two popular computer packages. Study Design We show how to compute the standard errors of several functions of interest: the predicted value of the dependent variable for a particular subject, and the effect of a change in an explanatory variable on the predicted value of the dependent variable for an individual subject and average effect for a sample of subjects. Empirical Application Using a publicly available dataset, we explain three different methods of computing standard errors: the delta method, Krinsky–Robb, and bootstrapping. We provide computer code for Stata 12 and LIMDEP 10/NLOGIT 5. Conclusions In most applications, choice of the computational method for standard errors of functions of estimated parameters is a matter of convenience. However, when computing standard errors of the sample average of functions that involve both estimated parameters and nonstochastic explanatory variables, it is important to consider the sources of variation in the function's values. PMID:24800304

Finite parametrization of solutions of equations in a free monoid. II

NASA Astrophysics Data System (ADS)

Makanin, G. S.

2004-04-01

In the preceding paper of the author parametrizing functions Fi, Th, Ro were introduced depending on word variables, positive-integer variables, and variables whose values are finite sequences of positive-integer variables. With the help of the parametrizing functions Fi, Th, Ro finite formulae are written out for the family of solutions of every equation of the form \\varphi(x_1,x_2,x_3) x_4=\\psi(x_1,x_2,x_3) x_5, where \\varphi(x_1,x_2,x_3) and \\psi(x_1,x_2,x_3) are arbitrary words in the alphabet x_1, x_2, x_3 in a free monoid.

Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care.

PubMed

Kowalski, Amanda

2016-01-02

Efforts to control medical care costs depend critically on how individuals respond to prices. I estimate the price elasticity of expenditure on medical care using a censored quantile instrumental variable (CQIV) estimator. CQIV allows estimates to vary across the conditional expenditure distribution, relaxes traditional censored model assumptions, and addresses endogeneity with an instrumental variable. My instrumental variable strategy uses a family member's injury to induce variation in an individual's own price. Across the conditional deciles of the expenditure distribution, I find elasticities that vary from -0.76 to -1.49, which are an order of magnitude larger than previous estimates.

Relative roles of weather variables and change in human population in malaria: comparison over different states of India.

PubMed

Goswami, Prashant; Murty, Upadhayula Suryanarayana; Mutheneni, Srinivasa Rao; Krishnan, Swathi Trithala

2014-01-01

Pro-active and effective control as well as quantitative assessment of impact of climate change on malaria requires identification of the major drivers of the epidemic. Malaria depends on vector abundance which, in turn, depends on a combination of weather variables. However, there remain several gaps in our understanding and assessment of malaria in a changing climate. Most of the studies have considered weekly or even monthly mean values of weather variables, while the malaria vector is sensitive to daily variations. Secondly, rarely all the relevant meteorological variables have been considered together. An important question is the relative roles of weather variables (vector abundance) and change in host (human) population, in the change in disease load. We consider the 28 states of India, characterized by diverse climatic zones and changing population as well as complex variability in malaria, as a natural test bed. An annual vector load for each of the 28 states is defined based on the number of vector genesis days computed using daily values of temperature, rainfall and humidity from NCEP daily Reanalysis; a prediction of potential malaria load is defined by taking into consideration changes in the human population and compared with the reported number of malaria cases. For most states, the number of malaria cases is very well correlated with the vector load calculated with the combined conditions of daily values of temperature, rainfall and humidity; no single weather variable has any significant association with the observed disease prevalence. The association between vector-load and daily values of weather variables is robust and holds for different climatic regions (states of India). Thus use of all the three weather variables provides a reliable means of pro-active and efficient vector sanitation and control as well as assessment of impact of climate change on malaria.

Relative Roles of Weather Variables and Change in Human Population in Malaria: Comparison over Different States of India

PubMed Central

Goswami, Prashant; Murty, Upadhayula Suryanarayana; Mutheneni, Srinivasa Rao; Krishnan, Swathi Trithala

2014-01-01

Background Pro-active and effective control as well as quantitative assessment of impact of climate change on malaria requires identification of the major drivers of the epidemic. Malaria depends on vector abundance which, in turn, depends on a combination of weather variables. However, there remain several gaps in our understanding and assessment of malaria in a changing climate. Most of the studies have considered weekly or even monthly mean values of weather variables, while the malaria vector is sensitive to daily variations. Secondly, rarely all the relevant meteorological variables have been considered together. An important question is the relative roles of weather variables (vector abundance) and change in host (human) population, in the change in disease load. Method We consider the 28 states of India, characterized by diverse climatic zones and changing population as well as complex variability in malaria, as a natural test bed. An annual vector load for each of the 28 states is defined based on the number of vector genesis days computed using daily values of temperature, rainfall and humidity from NCEP daily Reanalysis; a prediction of potential malaria load is defined by taking into consideration changes in the human population and compared with the reported number of malaria cases. Results For most states, the number of malaria cases is very well correlated with the vector load calculated with the combined conditions of daily values of temperature, rainfall and humidity; no single weather variable has any significant association with the observed disease prevalence. Conclusion The association between vector-load and daily values of weather variables is robust and holds for different climatic regions (states of India). Thus use of all the three weather variables provides a reliable means of pro-active and efficient vector sanitation and control as well as assessment of impact of climate change on malaria. PMID:24971510

Validation of spatial variability in downscaling results from the VALUE perfect predictor experiment

NASA Astrophysics Data System (ADS)

Widmann, Martin; Bedia, Joaquin; Gutiérrez, Jose Manuel; Maraun, Douglas; Huth, Radan; Fischer, Andreas; Keller, Denise; Hertig, Elke; Vrac, Mathieu; Wibig, Joanna; Pagé, Christian; Cardoso, Rita M.; Soares, Pedro MM; Bosshard, Thomas; Casado, Maria Jesus; Ramos, Petra

2016-04-01

VALUE is an open European network to validate and compare downscaling methods for climate change research. Within VALUE a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods has been developed. In the first validation experiment the downscaling methods are validated in a setup with perfect predictors taken from the ERA-interim reanalysis for the period 1997 - 2008. This allows to investigate the isolated skill of downscaling methods without further error contributions from the large-scale predictors. One aspect of the validation is the representation of spatial variability. As part of the VALUE validation we have compared various properties of the spatial variability of downscaled daily temperature and precipitation with the corresponding properties in observations. We have used two test validation datasets, one European-wide set of 86 stations, and one higher-density network of 50 stations in Germany. Here we present results based on three approaches, namely the analysis of i.) correlation matrices, ii.) pairwise joint threshold exceedances, and iii.) regions of similar variability. We summarise the information contained in correlation matrices by calculating the dependence of the correlations on distance and deriving decorrelation lengths, as well as by determining the independent degrees of freedom. Probabilities for joint threshold exceedances and (where appropriate) non-exceedances are calculated for various user-relevant thresholds related for instance to extreme precipitation or frost and heat days. The dependence of these probabilities on distance is again characterised by calculating typical length scales that separate dependent from independent exceedances. Regionalisation is based on rotated Principal Component Analysis. The results indicate which downscaling methods are preferable if the dependency of variability at different locations is relevant for the user.

A viscoelastic higher-order beam finite element

NASA Technical Reports Server (NTRS)

Johnson, Arthur R.; Tressler, Alexander

1996-01-01

A viscoelastic internal variable constitutive theory is applied to a higher-order elastic beam theory and finite element formulation. The behavior of the viscous material in the beam is approximately modeled as a Maxwell solid. The finite element formulation requires additional sets of nodal variables for each relaxation time constant needed by the Maxwell solid. Recent developments in modeling viscoelastic material behavior with strain variables that are conjugate to the elastic strain measures are combined with advances in modeling through-the-thickness stresses and strains in thick beams. The result is a viscous thick-beam finite element that possesses superior characteristics for transient analysis since its nodal viscous forces are not linearly dependent an the nodal velocities, which is the case when damping matrices are used. Instead, the nodal viscous forces are directly dependent on the material's relaxation spectrum and the history of the nodal variables through a differential form of the constitutive law for a Maxwell solid. The thick beam quasistatic analysis is explored herein as a first step towards developing more complex viscoelastic models for thick plates and shells, and for dynamic analyses. The internal variable constitutive theory is derived directly from the Boltzmann superposition theorem. The mechanical strains and the conjugate internal strains are shown to be related through a system of first-order, ordinary differential equations. The total time-dependent stress is the superposition of its elastic and viscous components. Equations of motion for the solid are derived from the virtual work principle using the total time-dependent stress. Numerical examples for the problems of relaxation, creep, and cyclic creep are carried out for a beam made from an orthotropic Maxwell solid.

Smoker Characteristics and Smoking-Cessation Milestones

PubMed Central

Japuntich, Sandra J.; Leventhal, Adam M.; Piper, Megan E.; Bolt, Daniel M.; Roberts, Linda J.; Fiore, Michael C.; Baker, Timothy B.

2011-01-01

Background Contextual variables often predict long-term abstinence, but little is known about how these variables exert their effects. These variables could influence abstinence by affecting the ability to quit at all, or by altering risk of lapsing, or progressing from a lapse to relapse. Purpose To examine the effect of common predictors of smoking-cessation failure on smoking-cessation processes. Methods The current study (N = 1504, 58% female, 84% Caucasian; recruited from January 2005 to June 2007; data analyzed in 2009) uses the approach advocated by Shiffman et al., (2006), which measures cessation outcomes on three different cessation milestones (achieving initial abstinence, lapse risk, and the lapse-relapse transition) to examine relationships of smoker characteristics (dependence, contextual and demographic factors) with smoking-cessation process. Results High nicotine dependence strongly predicted all milestones: not achieving initial abstinence, and a higher risk of both lapse and transitioning from lapse to complete relapse. Numerous contextual and demographic variables were associated with higher initial cessation rates and/or decreased lapse risk at 6 months post-quit (e.g., ethnicity, gender, marital status, education, smoking in the workplace, number of smokers in the social network, and number of supportive others). However, aside from nicotine dependence, only gender significantly predicted the risk of transition from lapse to relapse. Conclusions These findings demonstrate that: (1) higher nicotine dependence predicted worse outcomes across every cessation milestone; (2) demographic and contextual variables are generally associated with initial abstinence rates and lapse risk and not the lapse-relapse transition. These results identify groups who are at risk for failure at specific stages of the smoking-cessation process, and this may have implications for treatment. PMID:21335259

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

PubMed

Marill, Keith A

2004-01-01

Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

Comment on Hall et al. (2017), "How to Choose Between Measures of Tinnitus Loudness for Clinical Research? A Report on the Reliability and Validity of an Investigator-Administered Test and a Patient-Reported Measure Using Baseline Data Collected in a Phase IIa Drug Trial".

PubMed

Sabour, Siamak

2018-03-08

The purpose of this letter, in response to Hall, Mehta, and Fackrell (2017), is to provide important knowledge about methodology and statistical issues in assessing the reliability and validity of an audiologist-administered tinnitus loudness matching test and a patient-reported tinnitus loudness rating. The author uses reference textbooks and published articles regarding scientific assessment of the validity and reliability of a clinical test to discuss the statistical test and the methodological approach in assessing validity and reliability in clinical research. Depending on the type of the variable (qualitative or quantitative), well-known statistical tests can be applied to assess reliability and validity. The qualitative variables of sensitivity, specificity, positive predictive value, negative predictive value, false positive and false negative rates, likelihood ratio positive and likelihood ratio negative, as well as odds ratio (i.e., ratio of true to false results), are the most appropriate estimates to evaluate validity of a test compared to a gold standard. In the case of quantitative variables, depending on distribution of the variable, Pearson r or Spearman rho can be applied. Diagnostic accuracy (validity) and diagnostic precision (reliability or agreement) are two completely different methodological issues. Depending on the type of the variable (qualitative or quantitative), well-known statistical tests can be applied to assess validity.

THE EFFECTS OF RESPONSE EFFORT ON SAFE PERFORMANCE BY THERAPISTS AT AN AUTISM TREATMENT FACILITY

PubMed Central

Casella, Sarah E; Wilder, David A; Neidert, Pamela; Rey, Catalina; Compton, Megan; Chong, Ivy

2010-01-01

The effects of response effort on safe behaviors (i.e., glove wearing, hand sanitizing, and electrical outlet replacement) exhibited by therapists at an autism treatment center were examined. Participants were exposed to 2 or 3 levels of effort (i.e., high, medium, low) for each dependent variable. Results showed increased safe performance during the low-effort conditions relative to other conditions across all dependent variables for all participants. PMID:21541157

The effects of spatial autoregressive dependencies on inference in ordinary least squares: a geometric approach

NASA Astrophysics Data System (ADS)

Smith, Tony E.; Lee, Ka Lok

2012-01-01

There is a common belief that the presence of residual spatial autocorrelation in ordinary least squares (OLS) regression leads to inflated significance levels in beta coefficients and, in particular, inflated levels relative to the more efficient spatial error model (SEM). However, our simulations show that this is not always the case. Hence, the purpose of this paper is to examine this question from a geometric viewpoint. The key idea is to characterize the OLS test statistic in terms of angle cosines and examine the geometric implications of this characterization. Our first result is to show that if the explanatory variables in the regression exhibit no spatial autocorrelation, then the distribution of test statistics for individual beta coefficients in OLS is independent of any spatial autocorrelation in the error term. Hence, inferences about betas exhibit all the optimality properties of the classic uncorrelated error case. However, a second more important series of results show that if spatial autocorrelation is present in both the dependent and explanatory variables, then the conventional wisdom is correct. In particular, even when an explanatory variable is statistically independent of the dependent variable, such joint spatial dependencies tend to produce "spurious correlation" that results in over-rejection of the null hypothesis. The underlying geometric nature of this problem is clarified by illustrative examples. The paper concludes with a brief discussion of some possible remedies for this problem.

Single-diffractive production of dijets within the kt-factorization approach

NASA Astrophysics Data System (ADS)

Łuszczak, Marta; Maciuła, Rafał; Szczurek, Antoni; Babiarz, Izabela

2017-09-01

We discuss single-diffractive production of dijets. The cross section is calculated within the resolved Pomeron picture, for the first time in the kt-factorization approach, neglecting transverse momentum of the Pomeron. We use Kimber-Martin-Ryskin unintegrated parton (gluon, quark, antiquark) distributions in both the proton as well as in the Pomeron or subleading Reggeon. The unintegrated parton distributions are calculated based on conventional mmht2014nlo parton distribution functions in the proton and H1 Collaboration diffractive parton distribution functions used previously in the analysis of diffractive structure function and dijets at HERA. For comparison, we present results of calculations performed within the collinear-factorization approach. Our results remain those obtained in the next-to-leading-order approach. The calculation is (must be) supplemented by the so-called gap survival factor, which may, in general, depend on kinematical variables. We try to describe the existing data from Tevatron and make detailed predictions for possible LHC measurements. Several differential distributions are calculated. The E¯T, η ¯ and xp ¯ distributions are compared with the Tevatron data. A reasonable agreement is obtained for the first two distributions. The last one requires introducing a gap survival factor which depends on kinematical variables. We discuss how the phenomenological dependence on one kinematical variable may influence dependence on other variables such as E¯T and η ¯. Several distributions for the LHC are shown.

Review of Factors, Methods, and Outcome Definition in Designing Opioid Abuse Predictive Models.

PubMed

Alzeer, Abdullah H; Jones, Josette; Bair, Matthew J

2018-05-01

Several opioid risk assessment tools are available to prescribers to evaluate opioid analgesic abuse among chronic patients. The objectives of this study are to 1) identify variables available in the literature to predict opioid abuse; 2) explore and compare methods (population, database, and analysis) used to develop statistical models that predict opioid abuse; and 3) understand how outcomes were defined in each statistical model predicting opioid abuse. The OVID database was searched for this study. The search was limited to articles written in English and published from January 1990 to April 2016. This search generated 1,409 articles. Only seven studies and nine models met our inclusion-exclusion criteria. We found nine models and identified 75 distinct variables. Three studies used administrative claims data, and four studies used electronic health record data. The majority, four out of seven articles (six out of nine models), were primarily dependent on the presence or absence of opioid abuse or dependence (ICD-9 diagnosis code) to define opioid abuse. However, two articles used a predefined list of opioid-related aberrant behaviors. We identified variables used to predict opioid abuse from electronic health records and administrative data. Medication variables are the recurrent variables in the articles reviewed (33 variables). Age and gender are the most consistent demographic variables in predicting opioid abuse. Overall, there is similarity in the sampling method and inclusion/exclusion criteria (age, number of prescriptions, follow-up period, and data analysis methods). Intuitive research to utilize unstructured data may increase opioid abuse models' accuracy.

Hydration level is an internal variable for computing motivation to obtain water rewards in monkeys.

PubMed

Minamimoto, Takafumi; Yamada, Hiroshi; Hori, Yukiko; Suhara, Tetsuya

2012-05-01

In the process of motivation to engage in a behavior, valuation of the expected outcome is comprised of not only external variables (i.e., incentives) but also internal variables (i.e., drive). However, the exact neural mechanism that integrates these variables for the computation of motivational value remains unclear. Besides, the signal of physiological needs, which serves as the primary internal variable for this computation, remains to be identified. Concerning fluid rewards, the osmolality level, one of the physiological indices for the level of thirst, may be an internal variable for valuation, since an increase in the osmolality level induces drinking behavior. Here, to examine the relationship between osmolality and the motivational value of a water reward, we repeatedly measured the blood osmolality level, while 2 monkeys continuously performed an instrumental task until they spontaneously stopped. We found that, as the total amount of water earned increased, the osmolality level progressively decreased (i.e., the hydration level increased) in an individual-dependent manner. There was a significant negative correlation between the error rate of the task (the proportion of trials with low motivation) and the osmolality level. We also found that the increase in the error rate with reward accumulation can be well explained by a formula describing the changes in the osmolality level. These results provide a biologically supported computational formula for the motivational value of a water reward that depends on the hydration level, enabling us to identify the neural mechanism that integrates internal and external variables.

Non-neural BOLD variability in block and event-related paradigms.

PubMed

Kannurpatti, Sridhar S; Motes, Michael A; Rypma, Bart; Biswal, Bharat B

2011-01-01

Block and event-related stimulus designs are typically used in fMRI studies depending on the importance of detection power or estimation efficiency. The extent of vascular contribution to variability in block and event-related fMRI-BOLD response is not known. With scaling, the extent of vascular variability in the fMRI-BOLD response during block and event-related design tasks was investigated. Blood oxygen level-dependent (BOLD) contrast data from healthy volunteers performing a block design motor task and an event-related memory task requiring performance of a motor response were analyzed from the regions of interest (ROIs) surrounding the primary and supplementary motor cortices. Average BOLD signal change was significantly larger during the block design compared to the event-related design. In each subject, BOLD signal change across voxels in the ROIs had higher variation during the block design task compared to the event-related design task. Scaling using the resting state fluctuation of amplitude (RSFA) and breath-hold (BH), which minimizes BOLD variation due to vascular origins, reduced the within-subject BOLD variability in every subject during both tasks but significantly reduced BOLD variability across subjects only during the block design task. The strong non-neural source of intra- and intersubject variability of BOLD response during the block design compared to event-related task indicates that study designs optimizing for statistical power through enhancement of the BOLD contrast (for, e.g., block design) can be affected by enhancement of non-neural sources of BOLD variability. Copyright © 2011. Published by Elsevier Inc.

Systems Engineering-Based Tool for Identifying Critical Research Systems

ERIC Educational Resources Information Center

Abbott, Rodman P.; Stracener, Jerrell

2016-01-01

This study investigates the relationship between the designated research project system independent variables of Labor, Travel, Equipment, and Contract total annual costs and the dependent variables of both the associated matching research project total annual academic publication output and thesis/dissertation number output. The Mahalanobis…

Physics in Oceanography.

ERIC Educational Resources Information Center

Charnock, H.

1980-01-01

Described is physical oceanography as analyzed by seven dependent variables, (three components of velocity, the pressure, density, temperature and salinity) as a function of three space variables and time. Topics discussed include the heat balance of the earth, current patterns in the ocean, heat transport, the air-sea interaction, and prospects…

Internal Validity: A Must in Research Designs

ERIC Educational Resources Information Center

Cahit, Kaya

2015-01-01

In experimental research, internal validity refers to what extent researchers can conclude that changes in dependent variable (i.e. outcome) are caused by manipulations in independent variable. The causal inference permits researchers to meaningfully interpret research results. This article discusses (a) internal validity threats in social and…

Making Student Online Teams Work

ERIC Educational Resources Information Center

Olsen, Joel; Kalinski, Ray

2017-01-01

Online professors typically assign teams based on time zones, performance, or alphabet, but are these the best ways to position student virtual teams for success? Personality and task complexity could provide additional direction. Personality and task complexity were used as independent variables related to the depended variable of team…

Perception toward Organizational Learning Culture in Small-Size Business Enterprises

ERIC Educational Resources Information Center

Graham, Carroll M.; Nafukho, Fredrick M.

2007-01-01

This study sought to determine the relationship between four independent variables educational level, longevity, gender, type of enterprise, and the dependent variable respondents' perception of culture toward organizational learning readiness. An exploratory correlational research design was employed to survey 498 employees in seven small…

Regional and social differences concerning overweight, participation in health check-ups and vaccination. Analysis of data from a whole birth cohort of 6-year old children in a prosperous German city

PubMed Central

Koller, Daniela; Mielck, Andreas

2009-01-01

Background Studies on health inequalities still focus mostly on adults. Research about social disparities and health in children is slowly increasing, also in Germany, but these studies are mostly restricted to individual social variables derived from the parents to determine social class. This paper analyses the data of the medical check-up prior to school enrolment to determine differences concerning overweight, participation in health check-ups and immunization; it includes individual social variables but also regional variables describing the social environment of the children. Methods The dataset includes 9,353 children who started school in 2004 in Munich, Germany. Three dependent variables are included (i.e. overweight, health check-ups, vaccinations). The individual level social variables are: children's sex, mother tongue of the parents, Kindergarten visit. On the small scale school district level, two regional social variables could be included as well, i.e. percentage of single-parent households, percentage of households with low educational level. Associations are assessed by cross tables and regression analyses. The regional level variables are included by multilevel analyses. Results The analyses indicate that there is a large variation between the school districts concerning the three dependent variables, and that there is no district with very 'problematic values' for all three of them (i.e. high percentage of overweight, low levels of health check-ups and vaccinations). Throughout the bivariate and multivariate analyses, the mother tongue of the children's parents shows the most pronounced association with these dependent variables; i.e. children growing up in non-German-speaking families tend to be more overweight and don't visit preventive check-ups as often as children of German-speaking parents. An opposite association can be seen concerning vaccinations. Regional level influences are present as well, but they are rather small when the individual level social variables are controlled for. Conclusion The dataset of the medical check-up prior to school enrolment offers a great opportunity for public health research, as it comprises a whole age cohort. The number and scope of variables is quite limited, though. On one hand, it includes only few variables on health or health related risks. On the other, it would be important to have more information from the region where the children live, e.g. the availability of community and health care services for parents and children, social networks of families with children, areas where children can play outside, traffic noise and air pollution. Despite these shortcomings, the need for specific interventions can already be derived from the data analyzed here, e.g. programs to reduce overweight in children should focus on parents with a mother tongue other than German. PMID:19183444

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.

Total ozone trend significance from space time variability of daily Dobson data

NASA Technical Reports Server (NTRS)

Wilcox, R. W.

1981-01-01

Estimates of standard errors of total ozone time and area means, as derived from ozone's natural temporal and spatial variability and autocorrelation in middle latitudes determined from daily Dobson data are presented. Assessing the significance of apparent total ozone trends is equivalent to assessing the standard error of the means. Standard errors of time averages depend on the temporal variability and correlation of the averaged parameter. Trend detectability is discussed, both for the present network and for satellite measurements.

The SYSGEN user package

NASA Technical Reports Server (NTRS)

Carlson, C. R.

1981-01-01

The user documentation of the SYSGEN model and its links with other simulations is described. The SYSGEN is a production costing and reliability model of electric utility systems. Hydroelectric, storage, and time dependent generating units are modeled in addition to conventional generating plants. Input variables, modeling options, output variables, and reports formats are explained. SYSGEN also can be run interactively by using a program called FEPS (Front End Program for SYSGEN). A format for SYSGEN input variables which is designed for use with FEPS is presented.

Direct and indirect effects of environmental variability on growth and survivorship of pre-reproductive Joshua trees, Yucca brevifolia Engelm (Agavaceae)

USGS Publications Warehouse

Esque, Todd C.; Medica, Phil A.; Shryock, Daniel F.; Defalco, Lesley A.; Webb, Robert H.; Hunter, Richard B.

2015-01-01

• Conclusions: A rare establishment event for Y. brevifolia during 1983–1984, triggered by above-average summer rainfall, provided a unique opportunity to track early survival and growth. Infrequent but acute episodes of herbivory during drought influenced demography for decades. Variability in survival among young Y. brevifolia indicates that size-dependent demographic variables will improve forecasts for this long-lived desert species under predicted regional climate change.

Population activity statistics dissect subthreshold and spiking variability in V1.

PubMed

Bányai, Mihály; Koman, Zsombor; Orbán, Gergő

2017-07-01

Response variability, as measured by fluctuating responses upon repeated performance of trials, is a major component of neural responses, and its characterization is key to interpret high dimensional population recordings. Response variability and covariability display predictable changes upon changes in stimulus and cognitive or behavioral state, providing an opportunity to test the predictive power of models of neural variability. Still, there is little agreement on which model to use as a building block for population-level analyses, and models of variability are often treated as a subject of choice. We investigate two competing models, the doubly stochastic Poisson (DSP) model assuming stochasticity at spike generation, and the rectified Gaussian (RG) model tracing variability back to membrane potential variance, to analyze stimulus-dependent modulation of both single-neuron and pairwise response statistics. Using a pair of model neurons, we demonstrate that the two models predict similar single-cell statistics. However, DSP and RG models have contradicting predictions on the joint statistics of spiking responses. To test the models against data, we build a population model to simulate stimulus change-related modulations in pairwise response statistics. We use single-unit data from the primary visual cortex (V1) of monkeys to show that while model predictions for variance are qualitatively similar to experimental data, only the RG model's predictions are compatible with joint statistics. These results suggest that models using Poisson-like variability might fail to capture important properties of response statistics. We argue that membrane potential-level modeling of stochasticity provides an efficient strategy to model correlations. NEW & NOTEWORTHY Neural variability and covariability are puzzling aspects of cortical computations. For efficient decoding and prediction, models of information encoding in neural populations hinge on an appropriate model of variability. Our work shows that stimulus-dependent changes in pairwise but not in single-cell statistics can differentiate between two widely used models of neuronal variability. Contrasting model predictions with neuronal data provides hints on the noise sources in spiking and provides constraints on statistical models of population activity. Copyright © 2017 the American Physiological Society.

Motivational and psychological correlates of bodybuilding dependence

PubMed Central

EMINI, NEIM N.; BOND, MALCOLM J.

2014-01-01

Abstract Background and aims: Exercise may become physically and psychologically maladaptive if taken to extremes. One example is the dependence reported by some individuals who engage in weight training. The current study explored potential psychological, motivational, emotional and behavioural concomitants of bodybuilding dependence, with a particular focus on motives for weight training. Using a path analysis paradigm, putative causal models sought to explain associations among key study variables. Methods: A convenience sample of 101 men aged between 18 and 67 years was assembled from gymnasia in Adelaide, South Australia. Active weight trainers voluntarily completed a questionnaire that included measures of bodybuilding dependence (social dependency, training dependency, and mastery), anger, hostility and aggression, stress and motivations for weight training. Results: Three motives for weight training were identified: mood control, physique anxiety and personal challenge. Of these, personal challenge and mood control were the most directly salient to dependence. Social dependency was particularly relevant to personal challenge, whereas training dependency was associated with both personal challenge and mood control. Mastery demonstrated a direct link with physique anxiety, thus reflecting a unique component of exercise dependence. Conclusions: While it was not possible to determine causality with the available data, the joint roles of variables that influence, or are influenced by, bodybuilding dependence are identified. Results highlight unique motivations for bodybuilding and suggest that dependence could be a result of, and way of coping with, stress manifesting as aggression. A potential framework for future research is provided through the demonstration of plausible causal linkages among these variables. PMID:25317342

Motivational and psychological correlates of bodybuilding dependence.

PubMed

Emini, Neim N; Bond, Malcolm J

2014-09-01

Exercise may become physically and psychologically maladaptive if taken to extremes. One example is the dependence reported by some individuals who engage in weight training. The current study explored potential psychological, motivational, emotional and behavioural concomitants of bodybuilding dependence, with a particular focus on motives for weight training. Using a path analysis paradigm, putative causal models sought to explain associations among key study variables. A convenience sample of 101 men aged between 18 and 67 years was assembled from gymnasia in Adelaide, South Australia. Active weight trainers voluntarily completed a questionnaire that included measures of bodybuilding dependence (social dependency, training dependency, and mastery), anger, hostility and aggression, stress and motivations for weight training. Three motives for weight training were identified: mood control, physique anxiety and personal challenge. Of these, personal challenge and mood control were the most directly salient to dependence. Social dependency was particularly relevant to personal challenge, whereas training dependency was associated with both personal challenge and mood control. Mastery demonstrated a direct link with physique anxiety, thus reflecting a unique component of exercise dependence. While it was not possible to determine causality with the available data, the joint roles of variables that influence, or are influenced by, bodybuilding dependence are identified. RESULTS highlight unique motivations for bodybuilding and suggest that dependence could be a result of, and way of coping with, stress manifesting as aggression. A potential framework for future research is provided through the demonstration of plausible causal linkages among these variables.

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.

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

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.

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.

Spatial analysis of participation in the Waterloo Residential Energy Efficiency Project

NASA Astrophysics Data System (ADS)

Song, Ge Bella

Researchers are in broad agreement that energy-conserving actions produce economic as well as energy savings. Household energy rating systems (HERS) have been established in many countries to inform households of their house's current energy performance and to help reduce their energy consumption and greenhouse gas emissions. In Canada, the national EnerGuide for Houses (EGH) program is delivered by many local delivery agents, including non-profit green community organizations. Waterloo Region Green Solutions is the local non-profit that offers the EGH residential energy evaluation service to local households. The purpose of this thesis is to explore the determinants of household's participation in the residential energy efficiency program (REEP) in Waterloo Region, to explain the relationship between the explanatory variables and REEP participation, and to propose ways to improve this kind of program. A spatial (trend) analysis was conducted within a geographic information system (GIS) to determine the spatial patterns of the REEP participation in Waterloo Region from 1999 to 2006. The impact of sources of information on participation and relationships between participation rates and explanatory variables were identified. GIS proved successful in presenting a visual interpretation of spatial patterns of the REEP participation. In general, the participating households tend to be clustered in urban areas and scattered in rural areas. Different sources of information played significant roles in reaching participants in different years. Moreover, there was a relationship between each explanatory variable and the REEP participation rates. Statistical analysis was applied to obtain a quantitative assessment of relationships between hypothesized explanatory variables and participation in the REEP. The Poisson regression model was used to determine the relationship between hypothesized explanatory variables and REEP participation at the CDA level. The results show that all of the independent variables have a statistically significant positive relationship with REEP participation. These variables include level of education, average household income, employment rate, home ownership, population aged 65 and over, age of home, and number of eligible dwellings. The logistic regression model was used to assess the ability of the hypothesized explanatory variables to predict whether or not households would participate in a second follow-up evaluation after completing upgrades to their home. The results show all the explanatory variables have significant relationships with the dependent variable. The increased rating score, average household income, aged population, and age of home are positively related to the dependent variable. While the dwelling size and education has negative relationships with the dependent variable. In general, the contribution of this work provides a practical understanding of how the energy efficiency program operates, and insight into the type of variables that may be successful in bringing about changes in performance in the energy efficiency project in Waterloo Region. Secondly, with the completion of this research, future residential energy efficiency programs can use the information from this research and emulate or expand upon the efforts and lessons learned from the Residential Energy Efficiency Project in Waterloo Region case study. Thirdly, this research also contributes to practical experience on how to integrate different datasets using GIS.

Correlation of arterial fetal base deficit and lactate changes with severity of variable heart rate decelerations in the near-term ovine fetus.

PubMed

Ross, Michael G; Jessie, Marquis; Amaya, Kevin; Matushewski, Brad; Durosier, L Daniel; Frasch, Martin G; Richardson, Bryan S

2013-04-01

Recent guidelines classify variable decelerations without detail as to degree of depth. We hypothesized that variable deceleration severity is highly correlated with fetal base deficit accumulation. Seven near-term fetal sheep underwent a series of graded umbilical cord occlusions resulting in mild (30 bpm decrease), moderate (60 bpm decrease), or severe (decrease of 90 bpm to baseline <70 bpm) variable decelerations at 2.5 minute intervals. Mild, moderate, and severe variable decelerations increased fetal base deficit (0.21 ± 0.03, 0.27 ± 0.03, and 0.54 ± 0.09 mEq/L per minute) in direct proportion to severity. During recovery, fetal base deficit cleared at 0.12 mEq/L per minute. In this model, ovine fetuses can tolerate repetitive mild and moderate variable decelerations with minimal change in base deficit and lactate. In contrast, repetitive severe variable decelerations may result in significant base deficit increases, dependent on frequency. Modified guideline differentiation of mild/moderate vs severe variable decelerations may aid in the interpretation of fetal heart rate tracings and optimization of clinical management paradigms. Copyright © 2013 Mosby, Inc. All rights reserved.

Context effects on second-language learning of tonal contrasts.

PubMed

Chang, Charles B; Bowles, Anita R

2015-12-01

Studies of lexical tone  learning generally focus on monosyllabic contexts, while reports of phonetic learning benefits associated with input variability are based largely on experienced learners. This study trained inexperienced learners on Mandarin tonal contrasts to test two hypotheses regarding the influence of context and variability on tone  learning. The first hypothesis was that increased phonetic variability of tones in disyllabic contexts makes initial tone  learning more challenging in disyllabic than monosyllabic words. The second hypothesis was that the learnability of a given tone varies across contexts due to differences in tonal variability. Results of a word learning experiment supported both hypotheses: tones were acquired less successfully in disyllables than in monosyllables, and the relative difficulty of disyllables was closely related to contextual tonal variability. These results indicate limited relevance of monosyllable-based data on Mandarin learning for the disyllabic majority of the Mandarin lexicon. Furthermore, in the short term, variability can diminish learning; its effects are not necessarily beneficial but dependent on acquisition stage and other learner characteristics. These findings thus highlight the importance of considering contextual variability and the interaction between variability and type of learner in the design, interpretation, and application of research on phonetic learning.

Learning dependence from samples.

PubMed

Seth, Sohan; Príncipe, José C

2014-01-01

Mutual information, conditional mutual information and interaction information have been widely used in scientific literature as measures of dependence, conditional dependence and mutual dependence. However, these concepts suffer from several computational issues; they are difficult to estimate in continuous domain, the existing regularised estimators are almost always defined only for real or vector-valued random variables, and these measures address what dependence, conditional dependence and mutual dependence imply in terms of the random variables but not finite realisations. In this paper, we address the issue that given a set of realisations in an arbitrary metric space, what characteristic makes them dependent, conditionally dependent or mutually dependent. With this novel understanding, we develop new estimators of association, conditional association and interaction association. Some attractive properties of these estimators are that they do not require choosing free parameter(s), they are computationally simpler, and they can be applied to arbitrary metric spaces.

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

A Two-Step Approach to Analyze Satisfaction Data

ERIC Educational Resources Information Center

Ferrari, Pier Alda; Pagani, Laura; Fiorio, Carlo V.

2011-01-01

In this paper a two-step procedure based on Nonlinear Principal Component Analysis (NLPCA) and Multilevel models (MLM) for the analysis of satisfaction data is proposed. The basic hypothesis is that observed ordinal variables describe different aspects of a latent continuous variable, which depends on covariates connected with individual and…

Effects of Acoustic Variability on Second Language Vocabulary Learning

ERIC Educational Resources Information Center

Barcroft, Joe; Sommers, Mitchell S.

2005-01-01

This study examined the effects of acoustic variability on second language vocabulary learning. English native speakers learned new words in Spanish. Exposure frequency to the words was constant. Dependent measures were accuracy and latency of picture-to-Spanish and Spanish-to-English recall. Experiment 1 compared presentation formats of neutral…

Preschool Children's Outdoor Play Area Preferences

ERIC Educational Resources Information Center

Holmes, Robyn M.; Procaccino, Jill K.

2009-01-01

This study explores preschool children's outdoor play preferences. The sample was 40 (20 male, 20 female) primarily European-American three and four year olds. Data were collected via naturalistic observation and analyzed using repeated measures ANOVAs and MANOVAs. The independent variable was sex of child; dependent variable was play space…

Children's Attitudes toward Physical Activity and Self-Esteem.

ERIC Educational Resources Information Center

Ewy, Stan R.

This study was conducted to investigate attitudes toward physical activity and self-esteem of students (N=82) in grades three through five. The independent variables were gender, grade placement, and physical fitness. The dependent variables were scores from the Grade 3 Children's Attitudes Toward Physical Activity, the Revised Children's…

Spatio-temporal response of maize yield to edaphic and meteorological conditions in a saline farmland

USDA-ARS?s Scientific Manuscript database

Spatio-temporal variability of crop production strongly depends on soil heterogeneity, meteorological conditions, and their interaction. Canopy reflectance can be used to describe crop status and yield spatial variability. The objectives of this work were to understand the spatio-temporal variabilit...

Principal Selection Decisions Made by Teachers: The Influence of Principal Candidate Experience

ERIC Educational Resources Information Center

Winter, Paul A.; Jaeger, Mary Grace

2004-01-01

Public school teachers (N = 189) role-played as members of school councils making principal selection decisions by rating simulated candidates for principal vacancies. The independent variables were principal candidate job experience, candidate person characteristics, and teacher school level. The dependent variable was teacher rating of the job…

Characteristics of Successful Community College Students

ERIC Educational Resources Information Center

Forman, Scheherazade West

2009-01-01

The purpose of this quantitative study was to find predictors of student success. Using a predictive correlational design, the intent of the study was to find the relationships between the dichotomous dependent variable with the categories, degree recipients and non-degree recipients, and the independent variables, student characteristics and risk…

The Effect of Classroom Walkthroughs on Middle School Teacher Motivation

ERIC Educational Resources Information Center

Dickenson, Karen Nadean

2016-01-01

The purpose of this pretest-posttest control group experimental study was to see the effect of classroom walkthroughs on middle school teacher motivation. The independent variable was; classroom walkthroughs and the four dependent variables were teachers' self-concept of the ability to affect student achievement, teachers' attitude toward the…

The Conservative Corner of the Liberal Academy? Fraternity/Sorority Membership, Politics, and Activism

ERIC Educational Resources Information Center

Hevel, Michael S.; Weeden, Dustin D.; Pasquesi, Kira; Pascarella, Ernest T.

2015-01-01

We use a longitudinal dataset to explore the effect of fraternity/sorority membership on political orientation and social/political activism. After controlling for a variety of potentially confounding variables, including pretests on the dependent variables, fraternity and sorority members were significantly less liberal that their unaffiliated…

Differential V-Q Ability: Twenty Years Later

ERIC Educational Resources Information Center

McCarthy, S. Viterbo

1975-01-01

The initial portion of this paper addresses itself to some of the methodological concerns associated with Verbal-Quantitative (V-Q) research. The second section focuses on studies using differential V-Q ability as an independent variable. The final section focuses on reasearch using V-Q ability measures as dependent variables. (Author/BJG)

Gender-Linked Perceptions and Causal Attributions of Female/Male Competencies.

ERIC Educational Resources Information Center

Major, Harriet; Plake, Barbara S.

Undergraduate students (N=518) rated graduate application materials for males or females applying to traditionally perceived masculine or feminine fields. Independent variables were rater's pro/anti feminism, sex of subject, sex of referent, sex of field, and sex of attributes. Dependent variables were academic competence, personal dynamics,…

Investigating Antecedents of Task Commitment and Task Attraction in Service Learning Team Projects

ERIC Educational Resources Information Center

Schaffer, Bryan S.; Manegold, Jennifer G.

2018-01-01

The authors investigated the antecedents of team task cohesiveness in service learning classroom environments. Focusing on task commitment and task attraction as key dependent variables representing cohesiveness, and task interdependence as the primary independent variable, the authors position three important task action phase processes as…

Finding the Optimal Scaffoldings for Learners' Epistemological Beliefs during Ill-Structured Problem Solving

ERIC Educational Resources Information Center

Shin, Suhkyung; Song, Hae-Deok

2016-01-01

This study investigates how scaffolding type and learners' epistemological beliefs influence ill-structured problem solving. The independent variables in this study include the type of scaffolding (task-supported, self-monitoring) and the student's epistemological belief level (more advanced, less advanced). The dependent variables include three…

Using a Likert Scale to Measure "Environmental Responsibility"

ERIC Educational Resources Information Center

Horvat, Robert E.; Voelker, Alan M.

1976-01-01

An instrument (Some Ideas) was developed to assess the environmental responsibility of fifth and eighth grade students, and their perceptions of environmental problems and the people who work with them. Student scores served as the dependent variable in ANOVAS with the independent variables including grade, community, SES, IQ, and sex. (BT)

The Dimensions of Educational Leadership Amid the Unfamiliar.

ERIC Educational Resources Information Center

Dunifon, William S.

Today's paucity of effective leadership depends in part on the mistaken idea that leadership is a set of activities and behaviors isolated from everything else. Effective leadership, rather, is a product of the interdependence between leader behavior and a number of circumstantial variables. These variables include (1) the social, economic and…

Respondent Techniques for Reduction of Emotions Limiting School Adjustment: A Quantitative Review and Methodological Critique.

ERIC Educational Resources Information Center

Misra, Anjali; Schloss, Patrick J.

1989-01-01

The critical analysis of 23 studies using respondent techniques for the reduction of excessive emotional reactions in school children focuses on research design, dependent variables, independent variables, component analysis, and demonstrations of generalization and maintenance. Results indicate widespread methodological flaws that limit the…

Correlates of Teenage Drinking Behavior in Two Communities.

ERIC Educational Resources Information Center

Tjepkes, Phyllis Kathleen; Hayden, Davis C.

A survey of research literature on teenage alcohol use will reveal many variables related to teenage drinking. This study compared these variables in two separate communities to ascertain their global validity. To investigate factors leading to teenage alcohol use, 218 high school seniors from Washington and Iowa were surveyed. Dependent variables…

Measuring the Utility of a Cyber Incident Mission Impact Assessment (CIMIA) Process for Mission Assurance

DTIC Science & Technology

2011-03-01

1.179 1 22 .289 POP-UP .000 1 22 .991 Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a. Design ...POP-UP 2.104 1 22 .161 Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a. Design : Intercept... design also limited the number of intended treatments. The experimental design originally was suppose to test all three adverse events that threaten

Rate-compatible protograph LDPC code families with linear minimum distance

NASA Technical Reports Server (NTRS)

Divsalar, Dariush (Inventor); Dolinar, Jr., Samuel J. (Inventor); Jones, Christopher R. (Inventor)

2012-01-01

Digital communication coding methods are shown, which generate certain types of low-density parity-check (LDPC) codes built from protographs. A first method creates protographs having the linear minimum distance property and comprising at least one variable node with degree less than 3. A second method creates families of protographs of different rates, all structurally identical for all rates except for a rate-dependent designation of certain variable nodes as transmitted or non-transmitted. A third method creates families of protographs of different rates, all structurally identical for all rates except for a rate-dependent designation of the status of certain variable nodes as non-transmitted or set to zero. LDPC codes built from the protographs created by these methods can simultaneously have low error floors and low iterative decoding thresholds.

The value of using seasonality and meteorological variables to model intra-urban PM2.5 variation

NASA Astrophysics Data System (ADS)

Olvera Alvarez, Hector A.; Myers, Orrin B.; Weigel, Margaret; Armijos, Rodrigo X.

2018-06-01

A yearlong air monitoring campaign was conducted to assess the impact of local temperature, relative humidity, and wind speed on the temporal and spatial variability of PM2.5 in El Paso, Texas. Monitoring was conducted at four sites purposely selected to capture the local traffic variability. Effects of meteorological events on seasonal PM2.5 variability were identified. For instance, in winter low-wind and low-temperature conditions were associated with high PM2.5 events that contributed to elevated seasonal PM2.5 levels. Similarly, in spring, high PM2.5 events were associated with high-wind and low-relative humidity conditions. Correlation coefficients between meteorological variables and PM2.5 fluctuated drastically across seasons. Specifically, it was observed that for most sites correlations between PM2.5 and meteorological variables either changed from positive to negative or dissolved depending on the season. Overall, the results suggest that mixed effects analysis with season and site as fixed factors and meteorological variables as covariates could increase the explanatory value of LUR models for PM2.5.

The Effect of Latent Binary Variables on the Uncertainty of the Prediction of a Dichotomous Outcome Using Logistic Regression Based Propensity Score Matching.

PubMed

Szekér, Szabolcs; Vathy-Fogarassy, Ágnes

2018-01-01

Logistic regression based propensity score matching is a widely used method in case-control studies to select the individuals of the control group. This method creates a suitable control group if all factors affecting the output variable are known. However, if relevant latent variables exist as well, which are not taken into account during the calculations, the quality of the control group is uncertain. In this paper, we present a statistics-based research in which we try to determine the relationship between the accuracy of the logistic regression model and the uncertainty of the dependent variable of the control group defined by propensity score matching. Our analyses show that there is a linear correlation between the fit of the logistic regression model and the uncertainty of the output variable. In certain cases, a latent binary explanatory variable can result in a relative error of up to 70% in the prediction of the outcome variable. The observed phenomenon calls the attention of analysts to an important point, which must be taken into account when deducting conclusions.

NGA-West2 equations for predicting vertical-component PGA, PGV, and 5%-damped PSA from shallow crustal earthquakes

USGS Publications Warehouse

Stewart, Jonathan P.; Boore, David M.; Seyhan, Emel; Atkinson, Gail M.

2016-01-01

We present ground motion prediction equations (GMPEs) for computing natural log means and standard deviations of vertical-component intensity measures (IMs) for shallow crustal earthquakes in active tectonic regions. The equations were derived from a global database with M 3.0–7.9 events. The functions are similar to those for our horizontal GMPEs. We derive equations for the primary M- and distance-dependence of peak acceleration, peak velocity, and 5%-damped pseudo-spectral accelerations at oscillator periods between 0.01–10 s. We observe pronounced M-dependent geometric spreading and region-dependent anelastic attenuation for high-frequency IMs. We do not observe significant region-dependence in site amplification. Aleatory uncertainty is found to decrease with increasing magnitude; within-event variability is independent of distance. Compared to our horizontal-component GMPEs, attenuation rates are broadly comparable (somewhat slower geometric spreading, faster apparent anelastic attenuation), VS30-scaling is reduced, nonlinear site response is much weaker, within-event variability is comparable, and between-event variability is greater.

Nonlinear bivariate dependency of price-volume relationships in agricultural commodity futures markets: A perspective from Multifractal Detrended Cross-Correlation Analysis

NASA Astrophysics Data System (ADS)

He, Ling-Yun; Chen, Shu-Peng

2011-01-01

Nonlinear dependency between characteristic financial and commodity market quantities (variables) is crucially important, especially between trading volume and market price. Studies on nonlinear dependency between price and volume can provide practical insights into market trading characteristics, as well as the theoretical understanding of market dynamics. Actually, nonlinear dependency and its underlying dynamical mechanisms between price and volume can help researchers and technical analysts in understanding the market dynamics by integrating the market variables, instead of investigating them in the current literature. Therefore, for investigating nonlinear dependency of price-volume relationships in agricultural commodity futures markets in China and the US, we perform a new statistical test to detect cross-correlations and apply a new methodology called Multifractal Detrended Cross-Correlation Analysis (MF-DCCA), which is an efficient algorithm to analyze two spatially or temporally correlated time series. We discuss theoretically the relationship between the bivariate cross-correlation exponent and the generalized Hurst exponents for time series of respective variables. We also perform an empirical study and find that there exists a power-law cross-correlation between them, and that multifractal features are significant in all the analyzed agricultural commodity futures markets.

Nonlinear Gravitational and Radiation Aspects in Nanoliquid with Exponential Space Dependent Heat Source and Variable Viscosity

NASA Astrophysics Data System (ADS)

Gireesha, B. J.; Kumar, P. B. Sampath; Mahanthesh, B.; Shehzad, S. A.; Abbasi, F. M.

2018-05-01

The nonlinear convective flow of kerosene-Alumina nanoliquid subjected to an exponential space dependent heat source and temperature dependent viscosity is investigated here. This study is focuses on augmentation of heat transport rate in liquid propellant rocket engine. The kerosene-Alumina nanoliquid is considered as the regenerative coolant. Aspects of radiation and viscous dissipation are also covered. Relevant nonlinear system is solved numerically via RK based shooting scheme. Diverse flow fields are computed and examined for distinct governing variables. We figured out that the nanoliquid's temperature increased due to space dependent heat source and radiation aspects. The heat transfer rate is higher in case of changeable viscosity than constant viscosity.

Students' performance in accounting: differential effect of field dependence-independence as a learning style.

PubMed

Bernardi, Richard A

2003-08-01

This study examined the differential moderating effects associated with field dependence-independence and perceptions of stress on students' performance after controlling for SAT Mathematics and Verbal scores as well as students' actual effort on homework. The average performance of 178 third-year accounting majors over three examinations was used to evaluate their understanding of financial accounting. The students also took the Group Embedded Figures Test. While the data indicate that the most significant variables were students' effort, SAT Verbal scores, and their perceptions of stress, these variables were differentially associated with students' performance depending upon whether the student was classified as a field-independent or field-dependent learner.

Nonlinear Gravitational and Radiation Aspects in Nanoliquid with Exponential Space Dependent Heat Source and Variable Viscosity

NASA Astrophysics Data System (ADS)

Gireesha, B. J.; Kumar, P. B. Sampath; Mahanthesh, B.; Shehzad, S. A.; Abbasi, F. M.

2018-02-01

The nonlinear convective flow of kerosene-Alumina nanoliquid subjected to an exponential space dependent heat source and temperature dependent viscosity is investigated here. This study is focuses on augmentation of heat transport rate in liquid propellant rocket engine. The kerosene-Alumina nanoliquid is considered as the regenerative coolant. Aspects of radiation and viscous dissipation are also covered. Relevant nonlinear system is solved numerically via RK based shooting scheme. Diverse flow fields are computed and examined for distinct governing variables. We figured out that the nanoliquid's temperature increased due to space dependent heat source and radiation aspects. The heat transfer rate is higher in case of changeable viscosity than constant viscosity.

Explicit expressions of self-diffusion coefficient, shear viscosity, and the Stokes-Einstein relation for binary mixtures of Lennard-Jones liquids

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

Ohtori, Norikazu, E-mail: ohtori@chem.sc.niigata-u.ac.jp; Ishii, Yoshiki

Explicit expressions of the self-diffusion coefficient, D{sub i}, and shear viscosity, η{sub sv}, are presented for Lennard-Jones (LJ) binary mixtures in the liquid states along the saturated vapor line. The variables necessary for the expressions were derived from dimensional analysis of the properties: atomic mass, number density, packing fraction, temperature, and the size and energy parameters used in the LJ potential. The unknown dependence of the properties on each variable was determined by molecular dynamics (MD) calculations for an equimolar mixture of Ar and Kr at the temperature of 140 K and density of 1676 kg m{sup −3}. The scalingmore » equations obtained by multiplying all the single-variable dependences can well express D{sub i} and η{sub sv} evaluated by the MD simulation for a whole range of compositions and temperatures without any significant coupling between the variables. The equation for D{sub i} can also explain the dual atomic-mass dependence, i.e., the average-mass and the individual-mass dependence; the latter accounts for the “isotope effect” on D{sub i}. The Stokes-Einstein (SE) relation obtained from these equations is fully consistent with the SE relation for pure LJ liquids and that for infinitely dilute solutions. The main differences from the original SE relation are the presence of dependence on the individual mass and on the individual energy parameter. In addition, the packing-fraction dependence turned out to bridge another gap between the present and original SE relations as well as unifying the SE relation between pure liquids and infinitely dilute solutions.« less

Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care

PubMed Central

Kowalski, Amanda

2015-01-01

Efforts to control medical care costs depend critically on how individuals respond to prices. I estimate the price elasticity of expenditure on medical care using a censored quantile instrumental variable (CQIV) estimator. CQIV allows estimates to vary across the conditional expenditure distribution, relaxes traditional censored model assumptions, and addresses endogeneity with an instrumental variable. My instrumental variable strategy uses a family member’s injury to induce variation in an individual’s own price. Across the conditional deciles of the expenditure distribution, I find elasticities that vary from −0.76 to −1.49, which are an order of magnitude larger than previous estimates. PMID:26977117

Poor Health and Experiences of Being Bullied in Adolescents: Self-Perceived Overweight and Frustration with Appearance Matter.

PubMed

Lin, Yi-Ching; Latner, Janet D; Fung, Xavier C C; Lin, Chung-Ying

2018-02-01

To examine the associations between body image (actual and self-perceived weight status; feelings about appearance) and health outcomes (overall health, life satisfaction, and mental health) and between body image and experiences of being bullied. Participants included 8,303 children from 7th to 10th grade in the Health Behavior of School-Aged Children (HBSC) 2009-2010 data set, a large-scale sample in the United States. Several multiple linear regressions (with health outcomes as dependent variables) and multivariate logistic regressions (with being bullied or not as dependent variable) were conducted to investigate the associations between each dependent variable and the following independent variables: relationship with parents, frustration with appearance, and actual and self-perceived weight status. Self-perceived underweight, self-perceived overweight (OW), and frustration with appearance were positively associated with being bullied. Frustration with appearance was a risk factor, while good relationship with parents was a protective factor, especially for psychological health outcomes. Self-perceived OW had a stronger association with the experience of being bullied than actual OW. The relationship between actual OW and being bullied might be attenuated when self-perceived OW is simultaneously considered. Body image may be an important factor in the association between weight status and the experience of being bullied. © 2017 The Obesity Society.

Combinatorial techniques to efficiently investigate and optimize organic thin film processing and properties.

PubMed

Wieberger, Florian; Kolb, Tristan; Neuber, Christian; Ober, Christopher K; Schmidt, Hans-Werner

2013-04-08

In this article we present several developed and improved combinatorial techniques to optimize processing conditions and material properties of organic thin films. The combinatorial approach allows investigations of multi-variable dependencies and is the perfect tool to investigate organic thin films regarding their high performance purposes. In this context we develop and establish the reliable preparation of gradients of material composition, temperature, exposure, and immersion time. Furthermore we demonstrate the smart application of combinations of composition and processing gradients to create combinatorial libraries. First a binary combinatorial library is created by applying two gradients perpendicular to each other. A third gradient is carried out in very small areas and arranged matrix-like over the entire binary combinatorial library resulting in a ternary combinatorial library. Ternary combinatorial libraries allow identifying precise trends for the optimization of multi-variable dependent processes which is demonstrated on the lithographic patterning process. Here we verify conclusively the strong interaction and thus the interdependency of variables in the preparation and properties of complex organic thin film systems. The established gradient preparation techniques are not limited to lithographic patterning. It is possible to utilize and transfer the reported combinatorial techniques to other multi-variable dependent processes and to investigate and optimize thin film layers and devices for optical, electro-optical, and electronic applications.

Error in the Sampling Area of an Optical Disdrometer: Consequences in Computing Rain Variables

PubMed Central

Fraile, R.; Castro, A.; Fernández-Raga, M.; Palencia, C.; Calvo, A. I.

2013-01-01

The aim of this study is to improve the estimation of the characteristic uncertainties of optic disdrometers in an attempt to calculate the efficient sampling area according to the size of the drop and to study how this influences the computation of other parameters, taking into account that the real sampling area is always smaller than the nominal area. For large raindrops (a little over 6 mm), the effective sampling area may be half the area indicated by the manufacturer. The error committed in the sampling area is propagated to all the variables depending on this surface, such as the rain intensity and the reflectivity factor. Both variables tend to underestimate the real value if the sampling area is not corrected. For example, the rainfall intensity errors may be up to 50% for large drops, those slightly larger than 6 mm. The same occurs with reflectivity values, which may be up to twice the reflectivity calculated using the uncorrected constant sampling area. The Z-R relationships appear to have little dependence on the sampling area, because both variables depend on it the same way. These results were obtained by studying one particular rain event that occurred on April 16, 2006. PMID:23844393

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.

Weighted partial least squares based on the error and variance of the recovery rate in calibration set.

PubMed

Yu, Shaohui; Xiao, Xue; Ding, Hong; Xu, Ge; Li, Haixia; Liu, Jing

2017-08-05

The quantitative analysis is very difficult for the emission-excitation fluorescence spectroscopy of multi-component mixtures whose fluorescence peaks are serious overlapping. As an effective method for the quantitative analysis, partial least squares can extract the latent variables from both the independent variables and the dependent variables, so it can model for multiple correlations between variables. However, there are some factors that usually affect the prediction results of partial least squares, such as the noise, the distribution and amount of the samples in calibration set etc. This work focuses on the problems in the calibration set that are mentioned above. Firstly, the outliers in the calibration set are removed by leave-one-out cross-validation. Then, according to two different prediction requirements, the EWPLS method and the VWPLS method are proposed. The independent variables and dependent variables are weighted in the EWPLS method by the maximum error of the recovery rate and weighted in the VWPLS method by the maximum variance of the recovery rate. Three organic matters with serious overlapping excitation-emission fluorescence spectroscopy are selected for the experiments. The step adjustment parameter, the iteration number and the sample amount in the calibration set are discussed. The results show the EWPLS method and the VWPLS method are superior to the PLS method especially for the case of small samples in the calibration set. Copyright © 2017 Elsevier B.V. All rights reserved.

Annual variability of PAH concentrations in the Potomac River watershed

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

Maher, I.L.; Foster, G.D.

1995-12-31

Dynamics of organic contaminant transport in a large river system is influenced by annual variability in organic contaminant concentrations. Surface runoff and groundwater input control the flow of river waters. They are also the two major inputs of contaminants to river waters. The annual variability of contaminant concentrations in rivers may or may not represent similar trends to the flow changes of river waters. The purpose of the research is to define the annual variability in concentrations of polycyclic aromatic hydrocarbons (PAH) in riverine environment. To accomplish this, from March 1992 to March 1995 samples of Potomac River water weremore » collected monthly or bimonthly downstream of the Chesapeake Bay fall line (Chain Bridge) during base flow and main storm flow hydrologic conditions. Concentrations of selected PAHs were measured in the dissolved phase and the particulate phase via GC/MS. The study of the annual variability of PAH concentrations will be performed through comparisons of PAH concentrations seasonally, annually, and through study of PAH concentration river discharge dependency and rainfall dependency. For selected PAHs monthly and annual loadings will be estimated based on their measured concentrations and average daily river discharge. The monthly loadings of selected PAHs will be compared by seasons and annually.« less

Employee age and tenure within organizations: relationship to workplace satisfaction and workplace climate perceptions.

PubMed

Teclaw, Robert; Osatuke, Katerine; Fishman, Jonathan; Moore, Scott C; Dyrenforth, Sue

2014-01-01

This study estimated the relative influence of age/generation and tenure on job satisfaction and workplace climate perceptions. Data from the 2004, 2008, and 2012 Veterans Health Administration All Employee Survey (sample sizes >100 000) were examined in general linear models, with demographic characteristics simultaneously included as independent variables. Ten dependent variables represented a broad range of employee attitudes. Age/generation and tenure effects were compared through partial η(2) (95% confidence interval), P value of F statistic, and overall model R(2). Demographic variables taken together were only weakly related to employee attitudes, accounting for less than 10% of the variance. Consistently across survey years, for all dependent variables, age and age-squared had very weak to no effects, whereas tenure and tenure-squared had meaningfully greater partial η(2) values. Except for 1 independent variable in 1 year, none of the partial η(2) confidence intervals for age and age-squared overlapped those of tenure and tenure-squared. Much has been made in the popular and professional press of the importance of generational differences in workplace attitudes. Empirical studies have been contradictory and therefore inconclusive. The findings reported here suggest that age/generational differences might not influence employee perceptions to the extent that human resource and management practitioners have been led to believe.

Factors affecting collective action for forest fire management: a comparative study of community forest user groups in central Siwalik, Nepal.

PubMed

Sapkota, Lok Mani; Shrestha, Rajendra Prasad; Jourdain, Damien; Shivakoti, Ganesh P

2015-01-01

The attributes of social ecological systems affect the management of commons. Strengthening and enhancing social capital and the enforcement of rules and sanctions aid in the collective action of communities in forest fire management. Using a set of variables drawn from previous studies on the management of commons, we conducted a study across 20 community forest user groups in Central Siwalik, Nepal, by dividing the groups into two categories based on the type and level of their forest fire management response. Our study shows that the collective action in forest fire management is consistent with the collective actions in other community development activities. However, the effectiveness of collective action is primarily dependent on the complex interaction of various variables. We found that strong social capital, strong enforcement of rules and sanctions, and users' participation in crafting the rules were the major variables that strengthen collective action in forest fire management. Conversely, users' dependency on a daily wage and a lack of transparency were the variables that weaken collective action. In fire-prone forests such as the Siwalik, our results indicate that strengthening social capital and forming and enforcing forest fire management rules are important variables that encourage people to engage in collective action in fire management.

Robustness of norm-driven cooperation in the commons

PubMed Central

2016-01-01

Sustainable use of common-pool resources such as fish, water or forests depends on the cooperation of resource users that restrain their individual extraction to socially optimal levels. Empirical evidence has shown that under certain social and biophysical conditions, self-organized cooperation in the commons can evolve. Global change, however, may drastically alter these conditions. We assess the robustness of cooperation to environmental variability in a stylized model of a community that harvests a shared resource. Community members follow a norm of socially optimal resource extraction, which is enforced through social sanctioning. Our results indicate that both resource abundance and a small increase in resource variability can lead to collapse of cooperation observed in the no-variability case, while either scarcity or large variability have the potential to stabilize it. The combined effects of changes in amount and variability can reinforce or counteract each other depending on their size and the initial level of cooperation in the community. If two socially separate groups are ecologically connected through resource leakage, cooperation in one can destabilize the other. These findings provide insights into possible effects of global change and spatial connectivity, indicating that there is no simple answer as to their effects on cooperation and sustainable resource use. PMID:26740611

Muscular activity and torque of the foot dorsiflexor muscles during decremental isometric test: A cross-sectional study.

PubMed

Ruiz-Muñoz, Maria; González-Sánchez, Manuel; Martín-Martín, Jaime; Cuesta-Vargas, Antonio I

2017-06-01

To analyse the torque variation level that could be explained by the muscle activation (EMG) amplitude of the three major foot dorsiflexor muscles (tibialis anterior (TA), extensor digitorum longus (EDL), extensor hallucis longus (EHL)) during isometric foot dorsiflexion at different intensities. In a cross-sectional study, forty-one subjects performed foot dorsiflexion at 100%, 75%, 50% and 25% of maximal voluntary contractions (MVC) with the hip and knee flexed 90° and the ankle in neutral position (90° between leg and foot). Three foot dorsiflexions were performed for each intensity. Outcome variables were: maximum (100% MVC) and relative torque (75%, 50%, 25% MVC), maximum and relative EMG amplitude. A linear regression analysis was calculated for each intensity of the isometric foot dorsiflexion. The degree of torque variation (dependent variable) from the independent variables explain (EMG amplitude of the three major foot dorsiflexor muscles) the increases when the foot dorsiflexion intensity is increased, with values of R 2 that range from 0.194 (during 25% MVC) to 0.753 (during 100% MVC). The reliability of the outcome variables was excellent. The EMG amplitude of the three main foot dorsiflexors exhibited more variance in the dependent variable (torque) when foot dorsiflexion intensity increases. Copyright © 2016 Elsevier Ltd. All rights reserved.

State-variable theories for nonelastic deformation

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

Li, C.Y.

The various concepts of mechanical equation of state for nonelastic deformation in crystalline solids, originally proposed for plastic deformation, have been recently extended to describe additional phenomena such as anelastic and microplastic deformation including the Bauschinger effect. It has been demonstrated that it is possible to predict, based on current state variables in a unified way, the mechanical response of a material under an arbitrary loading. Thus, if the evolution laws of the state variables are known, one can describe the behavior of a material for a thermal-mechanical path of interest, for example, during constant load (or stress) creep withoutmore » relying on specialized theories. Some of the existing theories of mechanical equation of state for nonelastic deformation are reviewed. The establishment of useful forms of mechanical equation of state has to depend on extensive experimentation in the same way as that involved in the development, for example, the ideal gas law. Recent experimental efforts are also reviewed. It has been possible to develop state-variable deformation models based on experimental findings and apply them to creep, cyclic deformation, and other time-dependent deformation. Attempts are being made to correlate the material parameters of the state-variable models with the microstructure of a material. 24 figures.« less

The application of vacuum redistillation of patchouli oil to improve patchouli alcohol compound

NASA Astrophysics Data System (ADS)

Asnawi, T. M.; Alam, P. N.; Husin, H.; Zaki, M.

2018-04-01

Patchouli oil produced by traditional distillation of patchouli leaves and stems by farmers in Aceh still has low patchouli alcohol compound. In order to increase patchouli alcohol concentration, vacuum redistillation process using packed column was introduced. This research was conducted to fractionate terpene (alpha-copinene) from oxygenated hydrocarbon (patchouli alcohol) compound. The operation condition was conducted at two variables that was dependent variable and independent variable. The dependent variable was the 30 cm height distillation packed column, by using raschig ring with 8 mm x 8 mm dimension. And the independent variable was operating temperature 130 °C and 140 °C., vacuum pressure 143,61 mbar, 121,60 mbar and 88,59 mbar and operation time 2 hours, 3 hours and 5 hours. Total of treatments applied in this works were 3 x 3 x 3 or equal to 27 treatments. Patchouli oil used in this research was obtained from Desa Teladan-Lembah Seulawah, Aceh Province. The initial patchouli alcohol compound which analyzed with GC-MS contained 16,02% before treatment applied. After vacuum redistillation process treatment applied patchouli oil concentration increase up to 34,67%. Physico-chemical test of patchouli oil after vacuum redistillation is in accordance with SNI 06-23852006 standard.

Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations.

PubMed

Hayes, Andrew F; Matthes, Jörg

2009-08-01

Researchers often hypothesize moderated effects, in which the effect of an independent variable on an outcome variable depends on the value of a moderator variable. Such an effect reveals itself statistically as an interaction between the independent and moderator variables in a model of the outcome variable. When an interaction is found, it is important to probe the interaction, for theories and hypotheses often predict not just interaction but a specific pattern of effects of the focal independent variable as a function of the moderator. This article describes the familiar pick-a-point approach and the much less familiar Johnson-Neyman technique for probing interactions in linear models and introduces macros for SPSS and SAS to simplify the computations and facilitate the probing of interactions in ordinary least squares and logistic regression. A script version of the SPSS macro is also available for users who prefer a point-and-click user interface rather than command syntax.

Estimating degradation in real time and accelerated stability tests with random lot-to-lot variation: a simulation study.

PubMed

Magari, Robert T

2002-03-01

The effect of different lot-to-lot variability levels on the prediction of stability are studied based on two statistical models for estimating degradation in real time and accelerated stability tests. Lot-to-lot variability is considered as random in both models, and is attributed to two sources-variability at time zero, and variability of degradation rate. Real-time stability tests are modeled as a function of time while accelerated stability tests as a function of time and temperatures. Several data sets were simulated, and a maximum likelihood approach was used for estimation. The 95% confidence intervals for the degradation rate depend on the amount of lot-to-lot variability. When lot-to-lot degradation rate variability is relatively large (CV > or = 8%) the estimated confidence intervals do not represent the trend for individual lots. In such cases it is recommended to analyze each lot individually. Copyright 2002 Wiley-Liss, Inc. and the American Pharmaceutical Association J Pharm Sci 91: 893-899, 2002

On solving wave equations on fixed bounded intervals involving Robin boundary conditions with time-dependent coefficients

NASA Astrophysics Data System (ADS)

van Horssen, Wim T.; Wang, Yandong; Cao, Guohua

2018-06-01

In this paper, it is shown how characteristic coordinates, or equivalently how the well-known formula of d'Alembert, can be used to solve initial-boundary value problems for wave equations on fixed, bounded intervals involving Robin type of boundary conditions with time-dependent coefficients. A Robin boundary condition is a condition that specifies a linear combination of the dependent variable and its first order space-derivative on a boundary of the interval. Analytical methods, such as the method of separation of variables (SOV) or the Laplace transform method, are not applicable to those types of problems. The obtained analytical results by applying the proposed method, are in complete agreement with those obtained by using the numerical, finite difference method. For problems with time-independent coefficients in the Robin boundary condition(s), the results of the proposed method also completely agree with those as for instance obtained by the method of separation of variables, or by the finite difference method.

A review of precipitation and temperature control on seedling emergence and establishment for ponderosa and lodgepole pine forest regeneration

USGS Publications Warehouse

Petrie, Matthew; Wildeman, A.M.; Bradford, John B.; Hubbard, R.M.; Lauenroth, W.K.

2016-01-01

The persistence of ponderosa pine and lodgepole pine forests in the 21st century depends to a large extent on how seedling emergence and establishment are influenced by driving climate and environmental variables, which largely govern forest regeneration. We surveyed the literature, and identified 96 publications that reported data on dependent variables of seedling emergence and/or establishment and one or more independent variables of air temperature, soil temperature, precipitation and moisture availability. Our review suggests that seedling emergence and establishment for both species is highest at intermediate temperatures (20 to 25 °C), and higher precipitation and higher moisture availability support a higher percentage of seedling emergence and establishment at daily, monthly and annual timescales. We found that ponderosa pine seedlings may be more sensitive to temperature fluctuations whereas lodgepole pine seedlings may be more sensitive to moisture fluctuations. In a changing climate, increasing temperatures and declining moisture availability may hinder forest persistence by limiting seedling processes. Yet, only 23 studies in our review investigated the effects of driving climate and environmental variables directly. Furthermore, 74 studies occurred in a laboratory or greenhouse, which do not often replicate the conditions experienced by tree seedlings in a field setting. It is therefore difficult to provide strong conclusions on how sensitive emergence and establishment in ponderosa and lodgepole pine are to these specific driving variables, or to investigate their potential aggregate effects. Thus, the effects of many driving variables on seedling processes remain largely inconclusive. Our review stresses the need for additional field and laboratory studies to better elucidate the effects of driving climate and environmental variables on seedling emergence and establishment for ponderosa and lodgepole pine.

Angular position of the cleat according to torsional parameters of the cyclist's lower limb.

PubMed

Ramos-Ortega, Javier; Domínguez, Gabriel; Castillo, José Manuel; Fernández-Seguín, Lourdes; Munuera, Pedro V

2014-05-01

The aim of this work was to study the relationship of torsional and rotational parameters of the lower limb with a specific angular position of the cleat to establish whether these variables affect the adjustment of the cleat. Correlational study. Motion analysis laboratory. Thirty-seven male cyclists of high performance. The variables studied of the cyclist's lower limb were hip rotation (internal and external), tibial torsion angle, Q angle, and forefoot adductus angle. The cleat angle was measured through a photograph of the sole and with an Rx of this using the software AutoCAD 2008. The variables were photograph angle (photograph), the variable denominated cleat-tarsus minor angle, and a variable denominated cleat-second metatarsal angle (Rx). Analysis included the intraclass correlation coefficient for the reliability of the measurements, Student's t test performed on the dependent variables to compare side, and the multiple linear regression models were calculated using the software SPSS 15.0 for Windows. The Student's t test performed on the dependent variables to compare side showed no significant differences (P = 0.209 for the photograph angle, P = 0.735 for the cleat-tarsus minor angle, and P = 0.801 for the cleat-second metatarsal angle). Values of R and R2 for the photograph angle model were 0.303 and 0.092 (P = 0.08), the cleat/tarsus minor angle model were 0.683 and 0.466 (P < 0.001), and the cleat/second metatarsal angle model were 0.618 and 0.382, respectively (P < 0.001). The equation given by the model was cleat-tarsus minor angle = 75.094 - (0.521 × forefoot adductus angle) + (0.116 × outward rotation of the hips) + (0.220 × Q angle).

The intermediate endpoint effect in logistic and probit regression

PubMed Central

MacKinnon, DP; Lockwood, CM; Brown, CH; Wang, W; Hoffman, JM

2010-01-01

Background An intermediate endpoint is hypothesized to be in the middle of the causal sequence relating an independent variable to a dependent variable. The intermediate variable is also called a surrogate or mediating variable and the corresponding effect is called the mediated, surrogate endpoint, or intermediate endpoint effect. Clinical studies are often designed to change an intermediate or surrogate endpoint and through this intermediate change influence the ultimate endpoint. In many intermediate endpoint clinical studies the dependent variable is binary, and logistic or probit regression is used. Purpose The purpose of this study is to describe a limitation of a widely used approach to assessing intermediate endpoint effects and to propose an alternative method, based on products of coefficients, that yields more accurate results. Methods The intermediate endpoint model for a binary outcome is described for a true binary outcome and for a dichotomization of a latent continuous outcome. Plots of true values and a simulation study are used to evaluate the different methods. Results Distorted estimates of the intermediate endpoint effect and incorrect conclusions can result from the application of widely used methods to assess the intermediate endpoint effect. The same problem occurs for the proportion of an effect explained by an intermediate endpoint, which has been suggested as a useful measure for identifying intermediate endpoints. A solution to this problem is given based on the relationship between latent variable modeling and logistic or probit regression. Limitations More complicated intermediate variable models are not addressed in the study, although the methods described in the article can be extended to these more complicated models. Conclusions Researchers are encouraged to use an intermediate endpoint method based on the product of regression coefficients. A common method based on difference in coefficient methods can lead to distorted conclusions regarding the intermediate effect. PMID:17942466

Interpreting the concordance statistic of a logistic regression model: relation to the variance and odds ratio of a continuous explanatory variable.

PubMed

Austin, Peter C; Steyerberg, Ewout W

2012-06-20

When outcomes are binary, the c-statistic (equivalent to the area under the Receiver Operating Characteristic curve) is a standard measure of the predictive accuracy of a logistic regression model. An analytical expression was derived under the assumption that a continuous explanatory variable follows a normal distribution in those with and without the condition. We then conducted an extensive set of Monte Carlo simulations to examine whether the expressions derived under the assumption of binormality allowed for accurate prediction of the empirical c-statistic when the explanatory variable followed a normal distribution in the combined sample of those with and without the condition. We also examine the accuracy of the predicted c-statistic when the explanatory variable followed a gamma, log-normal or uniform distribution in combined sample of those with and without the condition. Under the assumption of binormality with equality of variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the product of the standard deviation of the normal components (reflecting more heterogeneity) and the log-odds ratio (reflecting larger effects). Under the assumption of binormality with unequal variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the standardized difference of the explanatory variable in those with and without the condition. In our Monte Carlo simulations, we found that these expressions allowed for reasonably accurate prediction of the empirical c-statistic when the distribution of the explanatory variable was normal, gamma, log-normal, and uniform in the entire sample of those with and without the condition. The discriminative ability of a continuous explanatory variable cannot be judged by its odds ratio alone, but always needs to be considered in relation to the heterogeneity of the population.

Temporal variation on environmental variables and pollution indicators in marine sediments under sea Salmon farming cages in protected and exposed zones in the Chilean inland Southern Sea.

PubMed

Urbina, Mauricio A

2016-12-15

The impacts of any activity on marine ecosystems will depend on the characteristics of the receptor medium and its resilience to external pressures. Salmon farming industry develops along a constant gradient of hydrodynamic conditions in the south of Chile. However, the influence of the hydrodynamic characteristics (weak or strong) on the impacts of intensive salmon farming is still poorly understood. This one year study evaluates the impacts of salmon farming on the marine sediments of both protected and exposed marine zones differing in their hydrodynamic characteristics. Six physico-chemical, five biological variables and seven indexes of marine sediments status were evaluated under the salmon farming cages and control sites. Our results identified a few key variables and indexes necessary to accurately evaluate the salmon farming impacts on both protected and exposed zones. Interestingly, the ranking of importance of the variables and the temporality of the observed changes, varied depending on the hydrodynamic characteristics. Biological variables (nematodes abundance) and environmental indexes (Simpson's dominance, Shannon's diversity and Pielou evenness) are the first to reflect detrimental impacts under the salmon farming cages. Then the physico-chemical variables such as redox, sulphurs and phosphorus in both zones also show detrimental impacts. Based on the present results we propose that the hydrodynamic regime is an important driver of the magnitude and temporality of the effects of salmon farming on marine sediments. The variables and indexes that best reflect the effects of salmon farming, in both protected and exposed zones, are also described. Copyright © 2016. Published by Elsevier B.V.

Mechanics of deformations in terms of scalar variables

NASA Astrophysics Data System (ADS)

Ryabov, Valeriy A.

2017-05-01

Theory of particle and continuous mechanics is developed which allows a treatment of pure deformation in terms of the set of variables "coordinate-momentum-force" instead of the standard treatment in terms of tensor-valued variables "strain-stress." This approach is quite natural for a microscopic description of atomic system, according to which only pointwise forces caused by the stress act to atoms making a body deform. The new concept starts from affine transformation of spatial to material coordinates in terms of the stretch tensor or its analogs. Thus, three principal stretches and three angles related to their orientation form a set of six scalar variables to describe deformation. Instead of volume-dependent potential used in the standard theory, which requires conditions of equilibrium for surface and body forces acting to a volume element, a potential dependent on scalar variables is introduced. A consistent introduction of generalized force associated with this potential becomes possible if a deformed body is considered to be confined on the surface of torus having six genuine dimensions. Strain, constitutive equations and other fundamental laws of the continuum and particle mechanics may be neatly rewritten in terms of scalar variables. Giving a new presentation for finite deformation new approach provides a full treatment of hyperelasticity including anisotropic case. Derived equations of motion generate a new kind of thermodynamical ensemble in terms of constant tension forces. In this ensemble, six internal deformation forces proportional to the components of Irving-Kirkwood stress are controlled by applied external forces. In thermodynamical limit, instead of the pressure and volume as state variables, this ensemble employs deformation force measured in kelvin unit and stretch ratio.

Sources of signal-dependent noise during isometric force production.

PubMed

Jones, Kelvin E; Hamilton, Antonia F; Wolpert, Daniel M

2002-09-01

It has been proposed that the invariant kinematics observed during goal-directed movements result from reducing the consequences of signal-dependent noise (SDN) on motor output. The purpose of this study was to investigate the presence of SDN during isometric force production and determine how central and peripheral components contribute to this feature of motor control. Peripheral and central components were distinguished experimentally by comparing voluntary contractions to those elicited by electrical stimulation of the extensor pollicis longus muscle. To determine other factors of motor-unit physiology that may contribute to SDN, a model was constructed and its output compared with the empirical data. SDN was evident in voluntary isometric contractions as a linear scaling of force variability (SD) with respect to the mean force level. However, during electrically stimulated contractions to the same force levels, the variability remained constant over the same range of mean forces. When the subjects were asked to combine voluntary with stimulation-induced contractions, the linear scaling relationship between the SD and mean force returned. The modeling results highlight that much of the basic physiological organization of the motor-unit pool, such as range of twitch amplitudes and range of recruitment thresholds, biases force output to exhibit linearly scaled SDN. This is in contrast to the square root scaling of variability with mean force present in any individual motor-unit of the pool. Orderly recruitment by twitch amplitude was a necessary condition for producing linearly scaled SDN. Surprisingly, the scaling of SDN was independent of the variability of motoneuron firing and therefore by inference, independent of presynaptic noise in the motor command. We conclude that the linear scaling of SDN during voluntary isometric contractions is a natural by-product of the organization of the motor-unit pool that does not depend on signal-dependent noise in the motor command. Synaptic noise in the motor command and common drive, which give rise to the variability and synchronization of motoneuron spiking, determine the magnitude of the force variability at a given level of mean force output.

Differing Roles of Functional Movement Variability as Experience Increases in Gymnastics

PubMed Central

Busquets, Albert; Marina, Michel; Davids, Keith; Angulo-Barroso, Rosa

2016-01-01

Current theories, like Ecological Dynamics, propose that inter-trial movement variability is functional when acquiring or refining movement coordination. Here, we examined how age-based experience levels of gymnasts constrained differences in emergent movement pattern variability during task performance. Specifically, we investigated different roles of movement pattern variability when gymnasts in different age groups performed longswings on a high bar, capturing the range of experience from beginner to advanced status. We also investigated the functionality of the relationships between levels of inter-trial variability and longswing amplitude during performance. One-hundred and thirteen male gymnasts in five age groups were observed performing longswings (with three different experience levels: beginners, intermediates and advanced performers). Performance was evaluated by analysis of key events in coordination of longswing focused on the arm-trunk and trunk-thigh segmental relations. Results revealed that 10 of 18 inter-trial variability measures changed significantly as a function of increasing task experience. Four of ten variability measures conformed to a U-shaped function with age implying exploratory strategies amongst beginners and functional adaptive variability amongst advanced performers. Inter-trial variability of arm-trunk coordination variables (6 of 10) conformed to a \\-shaped curve, as values were reduced to complete the longswings. Changes in coordination variability from beginner to intermediate status were largely restrictive, with only one variability measure related to exploration. Data revealed how inter-trial movement variability in gymnastics, relative to performance outcomes, needs careful interpretation, implying different roles as task experience changes. Key points Inter-trial variability while performing longswings on a high bar was assessed in a large sample (113 participants) divided into five age groups (form beginners to advanced gymnasts). Longswing assessment allowed us to evaluate inter-trial variability in representative performance context. Coordination variability presented two different configurations across experience levels depending on the variable of interest: either a U-shaped or a L- or \\-shaped graph. Increased inter-trial variability of the functional phase events offered flexibility to adapt the longswing performance in the advanced gymnasts, while decreasing variability in arm-trunk coordination modes was critical to improve longswing and to achieve the most advanced level. In addition, the relationship between variability measures and the global performance outcome (i.e. the swing amplitude) revealed different functional roles of movement variability (exploratory or restrictive) as a function of changes in experience levels. PMID:27274664

Novel models on fluid's variable thermo-physical properties for extensive study on convection heat and mass transfer

NASA Astrophysics Data System (ADS)

Shang, De-Yi; Zhong, Liang-Cai

2017-01-01

Our novel models for fluid's variable physical properties are improved and reported systematically in this work for enhancement of theoretical and practical value on study of convection heat and mass transfer. It consists of three models, namely (1) temperature parameter model, (2) polynomial model, and (3) weighted-sum model, respectively for treatment of temperature-dependent physical properties of gases, temperature-dependent physical properties of liquids, and concentration- and temperature-dependent physical properties of vapour-gas mixture. Two related components are proposed, and involved in each model for fluid's variable physical properties. They are basic physic property equations and theoretical similarity equations on physical property factors. The former, as the foundation of the latter, is based on the typical experimental data and physical analysis. The latter is built up by similarity analysis and mathematical derivation based on the former basic physical properties equations. These models are available for smooth simulation and treatment of fluid's variable physical properties for assurance of theoretical and practical value of study on convection of heat and mass transfer. Especially, so far, there has been lack of available study on heat and mass transfer of film condensation convection of vapour-gas mixture, and the wrong heat transfer results existed in widespread studies on the related research topics, due to ignorance of proper consideration of the concentration- and temperature-dependent physical properties of vapour-gas mixture. For resolving such difficult issues, the present novel physical property models have their special advantages.

Problems in using p-curve analysis and text-mining to detect rate of p-hacking and evidential value

PubMed Central

Thompson, Paul A.

2016-01-01

Background. The p-curve is a plot of the distribution of p-values reported in a set of scientific studies. Comparisons between ranges of p-values have been used to evaluate fields of research in terms of the extent to which studies have genuine evidential value, and the extent to which they suffer from bias in the selection of variables and analyses for publication, p-hacking. Methods. p-hacking can take various forms. Here we used R code to simulate the use of ghost variables, where an experimenter gathers data on several dependent variables but reports only those with statistically significant effects. We also examined a text-mined dataset used by Head et al. (2015) and assessed its suitability for investigating p-hacking. Results. We show that when there is ghost p-hacking, the shape of the p-curve depends on whether dependent variables are intercorrelated. For uncorrelated variables, simulated p-hacked data do not give the “p-hacking bump” just below .05 that is regarded as evidence of p-hacking, though there is a negative skew when simulated variables are inter-correlated. The way p-curves vary according to features of underlying data poses problems when automated text mining is used to detect p-values in heterogeneous sets of published papers. Conclusions. The absence of a bump in the p-curve is not indicative of lack of p-hacking. Furthermore, while studies with evidential value will usually generate a right-skewed p-curve, we cannot treat a right-skewed p-curve as an indicator of the extent of evidential value, unless we have a model specific to the type of p-values entered into the analysis. We conclude that it is not feasible to use the p-curve to estimate the extent of p-hacking and evidential value unless there is considerable control over the type of data entered into the analysis. In particular, p-hacking with ghost variables is likely to be missed. PMID:26925335

Seasonal Variability in European Radon Measurements

NASA Astrophysics Data System (ADS)

Groves-Kirkby, C. J.; Denman, A. R.; Phillips, P. S.; Crockett, R. G. M.; Sinclair, J. M.

2009-04-01

In temperate climates, domestic radon concentration levels are generally seasonally dependent, the level in the home reflecting the convolution of two time-dependent functions. These are the source soil-gas radon concentration itself, and the principal force driving radon into the building from the soil, namely the pressure-difference between interior and exterior environment. While the meteorological influence can be regarded as relatively uniform on a European scale, its variability being defined largely by the influence of North-Atlantic weather systems, soil-gas radon is generally more variable as it is essentially geologically dependent. Seasonal variability of domestic radon concentration can therefore be expected to exhibit geographical variability, as is indeed the case. To compensate for the variability of domestic radon levels when assessing the long term radon health risks, the results of individual short-term measurements are generally converted to equivalent mean annual levels by application of a Seasonal Correction Factor (SCF). This is a multiplying factor, typically derived from measurements of a large number of homes, applied to the measured short-term radon concentration to provide a meaningful annual mean concentration for dose-estimation purposes. Following concern as to the universal applicability of a single SCF set, detailed studies in both the UK and France have reported location-specific SCF sets for different regions of each country. Further results indicate that SCFs applicable to the UK differ significantly from those applicable elsewhere in Europe and North America in both amplitude and phase, supporting the thesis that seasonal variability in indoor radon concentration cannot realistically be compensated for by a single national or international SCF scheme. Published data characterising the seasonal variability of European national domestic radon concentrations, has been collated and analysed, with the objective of identifying correlations between published datasets and local geographic/geological conditions. Available data included regional SCF figures from the United Kingdom and from France, together with nationally-consolidated results from a number of other European countries. Analysis of this data shows significant variability between different countries and from region to region within those countries where regional data is available. Overall, radon-rich sedimentary geologies, particularly high porosity limestones etc., exhibit high seasonal variation, while radon-rich igneous geologies demonstrate relatively constant, albeit somewhat higher, radon concentration levels. Examples of the former can be found in the Pennines and South Downs in England, Languedoc and Brittany in France. Greatest variability is found in Switzerland, still subject to the ongoing Alpine orogeny, where the inhabited part of the country is largely overlain with recently-deposited light, porous sediments. Low-variability high-radon regions include the granite-rich Cornwall/Devon peninsular in England, and Auvergne and the Ardennes in France, all components of the Devonian-Carboniferous Hercynian belt, which extends from the Iberian peninsular through South-West Ireland and South-West England to France and Germany.

Groundwater level responses to precipitation variability in Mediterranean insular aquifers

NASA Astrophysics Data System (ADS)

Lorenzo-Lacruz, Jorge; Garcia, Celso; Morán-Tejeda, Enrique

2017-09-01

Groundwater is one of the largest and most important sources of fresh water on many regions under Mediterranean climate conditions, which are exposed to large precipitation variability that includes frequent meteorological drought episodes, and present high evapotranspiration rates and water demand during the dry season. The dependence on groundwater increases in those areas with predominant permeable lithologies, contributing to aquifer recharge and the abundance of ephemeral streams. The increasing pressure of tourism on water resources in many Mediterranean coastal areas, and uncertainty related to future precipitation and water availability, make it urgent to understand the spatio-temporal response of groundwater bodies to precipitation variability, if sustainable use of the resource is to be achieved. We present an assessment of the response of aquifers to precipitation variability based on correlations between the Standardized Precipitation Index (SPI) at various time scales and the Standardized Groundwater Index (SGI) across a Mediterranean island. We detected three main responses of aquifers to accumulated precipitation anomalies: (i) at short time scales of the SPI (<6 months); (ii) at medium time scales (6-24 months); and at long time scales (>24 months). The differing responses were mainly explained by differences in lithology and the percentage of highly permeable rock strata in the aquifer recharge areas. We also identified differences in the months and seasons when aquifer storages are more dependent on precipitation; these were related to climate seasonality and the degree of aquifer exploitation or underground water extraction. The recharge of some aquifers, especially in mountainous areas, is related to precipitation variability within a limited spatial extent, whereas for aquifers located in the plains, precipitation variability influence much larger areas; the topography and geological structure of the island explain these differences. Results indicate large spatial variability in the response of aquifers to precipitation in a very small area, highlighting the importance of having high spatial resolution hydro-climatic databases available to enable full understanding of the effects of climate variability on scarce water resources.

Variability in the prescription of non-biologic disease-modifying antirheumatic drugs for the treatment of spondyloarthritis in Spain.

PubMed

Silva-Fernández, Lucía; Pérez-Vicente, Sabina; Martín-Martínez, María Auxiliadora; López-González, Ruth

2015-06-01

To describe the variability in the prescription of non-biologic disease-modifying antirheumatic drugs (nbDMARDs) for the treatment of spondyloarthritis (SpA) in Spain and to explore which factors relating to the disease, patient, physician, and/or center contribute to these variations. A retrospective medical record review was performed using a probabilistic sample of 1168 patients with SpA from 45 centers distributed in 15/19 regions in Spain. The sociodemographic and clinical features and the use of drugs were recorded following a standardized protocol. Logistic regression, with nbDMARDs prescriptions as the dependent variable, was used for bivariable analysis. A multilevel logistic regression model was used to study variability. The probability of receiving an nbDMARD was higher in female patients [OR = 1.548; 95% confidence interval (CI): 1.208-1.984], in those with elevated C-reactive protein (OR = 1.039; 95% CI: 1.012-1.066) and erythrocyte sedimentation rate (OR = 1.012; 95% CI: 1.003-1.021), in those with a higher number of affected peripheral joints (OR = 12.921; 95% CI: 2.911-57.347), and in patients with extra-articular manifestations like dactylitis (OR = 2.997; 95% CI: 1.868-4.809), psoriasis (OR = 2.601; 95% CI: 1.870-3.617), and enthesitis (OR = 1.717; 95% CI: 1.224-2.410). There was a marked variability in the prescription of nbDMARDs for SpA patients, depending on the center (14.3%; variance 0.549; standard error 0.161; median odds ratio 2.366; p < 0.001). After adjusting for patient and center variables, this variability fell to 3.8%. A number of factors affecting variability in clinical practice, and which are independent of disease characteristics, are associated with the probability of SpA patients receiving nbDMARDs in Spain. Copyright © 2015 Elsevier Inc. All rights reserved.

Why Do We Stay? Career Rural Teachers' Burnout Compared to Personal Motivational Sources and Demographics

ERIC Educational Resources Information Center

Bell, David J.

2010-01-01

This study investigated the effects of individual motivational sources, demographics, and levels of burnout within career rural school teachers in Nebraska. The dependent variable was the psychological syndrome burnout as measured by the Maslach Burnout Inventory. Two independent variables were individual motivational sources (a personality trait…

Native temperature regime influences soil response to simulated warming

Treesearch

Timothy G. Whitby; Michael D. Madritch

2013-01-01

Anthropogenic climate change is expected to increase global temperatures and potentially increase soil carbon (C) mineralization, which could lead to a positive feedback between global warming and soil respiration. However the magnitude and spatial variability of belowground responses to warming are not yet fully understood. Some of the variability may depend...

An IRT Model with a Parameter-Driven Process for Change

ERIC Educational Resources Information Center

Rijmen, Frank; De Boeck, Paul; van der Maas, Han L. J.

2005-01-01

An IRT model with a parameter-driven process for change is proposed. Quantitative differences between persons are taken into account by a continuous latent variable, as in common IRT models. In addition, qualitative inter-individual differences and auto-dependencies are accounted for by assuming within-subject variability with respect to the…

Cineradiographic Examination of Articulatory Movement of Pseudo-Tongue, Hyoid, and Mandible in Congenital Aglossia

ERIC Educational Resources Information Center

McMicken, Betty; Vento-Wilson, Margaret; Von Berg, Shelley; Rogers, Kelly

2014-01-01

This research examined cineradiographic films (CRF) of articulatory movements in a person with congenital aglossia (PWCA) during speech production of four phrases. Pearson correlations and a multiple regression model investigated co-variation of independent variables, positions of mandible and hyoid; and pseudo-tongue-dependent variables,…

Planning, Supervision and Quality of Instructional Leadership of Girls' Day Secondary Schools in Kaduna State, Nigeria

ERIC Educational Resources Information Center

Duruh, Benjamin C.

2018-01-01

This study investigated the Planning, Supervision and Quality of Instructional Leadership of Girls' Day Secondary Schools in Kaduna State. The research design adopted was a survey design. The independent variables were the respondents which include principals, teachers, students, parents and government officials while dependent variable includes…

Explanations for Contempt Expressed Towards Old People.

ERIC Educational Resources Information Center

Maxwell, Eleanor Krassen; Maxwell, Robert J.

The issue of contempt expressed towards the aged was examined from a cross-cultural perspective. Eight reasons for expressions of contempt emerged from a study of 95 societies drawn from the Standard Cross-Cultural Sample, and were treated as independent variables, with the overall level of contempt as the dependent variable, in a application of…

Self-Esteem of Junior High and High School Students.

ERIC Educational Resources Information Center

Lee, Kimberly E.

The purpose of this thesis was to investigate the self-esteem of junior high and high school students. The independent variables investigated were quality of family life, birth order, family size, maternal employment, grade level and family structure. The dependent variables were the self-esteem scores from the following sub-scales of the Texas…

Changing Women's Ascriptions through a Leadership Training Program.

ERIC Educational Resources Information Center

Connell, Jim; Kimmel, Ellen B.

The purpose of this study was to determine if an intervention package designed to develop the administrative and managerial skills of women vocational educators would change their ascriptions to resemble those of male high achievers. The independent variable was a 2-week residential institute held in June 1982. The dependent variable was…

Career Choices in Engineering: The Influence of Peers and Parents Implication for Counselling

ERIC Educational Resources Information Center

Alika, Henrietta Ijeoma

2012-01-01

This study was designed to investigate the relationship between parental and peer group influence on career choice in engineering profession among adolescents. The research design adopted was correlational because it sought to establish the relationship between the independent variable and the dependent variable. One research question and one…

Learning-Method Choices and Personal Characteristics in Solving a Physical Education Problem

ERIC Educational Resources Information Center

Vincent-Morin, Madeleine; Lafont, Lucile

2005-01-01

The goal of this study was to identify the relationships between the learning choices made by pupils and their personal characteristics, including cognitive style (field dependence--independence), a motivational variable (feeling of self-efficacy), and a cognitive variable (task representation). The participants were 64 twelve-year-old sixth…

Determinants of Mobile Wireless Technology for Promoting Interactivity in Lecture Sessions: An Empirical Analysis

ERIC Educational Resources Information Center

Gan, Chin Lay; Balakrishnan, Vimala

2014-01-01

The aim of this paper is to identify adoption factors of mobile wireless technology to increase interactivity between lecturers and students during lectures. A theoretical framework to ascertain lecturers' intentions to use mobile wireless technology during lectures (dependent variable) is proposed with seven independent variables. The…

High School Students' Motivation to Learn Mathematics: The Role of Multiple Goals

ERIC Educational Resources Information Center

Ng, Chi-hung Clarence

2018-01-01

Using a sample of 310 Year 10 Chinese students from Hong Kong, this survey study examined the effects of multiple goals in learning mathematics. Independent variables were mastery, performance-approach, performance-avoidance, and pro-social goals. Dependent variables included perceived classroom goal structures, teacher's support, learning motives…

The Relationship Between Higher Order Need Strength and Sensitivity to Environmental Variations.

ERIC Educational Resources Information Center

Beehr, Terry A.; And Others

Higher order need strength (HONS) has been shown to moderate the relationship between work role characteristics and some traditional dependent variables in organizations. It was hypothesized that employees with strong HONS might be more sensitive to variability in their work environments than people with weaker HONS. This would happen because…

Disciplinary Action as an Intervention That Supports Students: Lessons from a Large Comprehensive High School

ERIC Educational Resources Information Center

Pharrams, Lorenza

2013-01-01

The purpose of this quantitative research study was to identify if there was a relationship between student or administrator characteristics (Independent variables) and the application of various disciplinary actions (Dependent variables). This study examined student's gender, race, grade point average, number of credits, and disciplinary…

Athletics, Applications, & Yields: The Relationship between Successful College Football and Institutional Attractiveness

ERIC Educational Resources Information Center

Jones, Willis A.

2009-01-01

This study examines the impact of fielding a successful college football team on institutional popularity using a dependent variable (admissions yield) and an independent variable (bowl game television rating) which have been unexamined in previous research on this topic. The findings suggest that college football success is correlated with a…

Capturing subregional variability in regional-scale climate change vulnerability assessments of natural resources

Treesearch

Polly C. Buotte; David L. Peterson; Kevin S. McKelvey; Jeffrey A. Hicke

2016-01-01

Natural resource vulnerability to climate change can depend on the climatology and ecological conditions at a particular site. Here we present a conceptual framework for incorporating spatial variability in natural resource vulnerability to climate change in a regional-scale assessment. The framework was implemented in the first regional-scale vulnerability...

A Better Lemon Squeezer? Maximum-Likelihood Regression with Beta-Distributed Dependent Variables

ERIC Educational Resources Information Center

Smithson, Michael; Verkuilen, Jay

2006-01-01

Uncorrectable skew and heteroscedasticity are among the "lemons" of psychological data, yet many important variables naturally exhibit these properties. For scales with a lower and upper bound, a suitable candidate for models is the beta distribution, which is very flexible and models skew quite well. The authors present…

The Impact of Community Disadvantage on the Relationship between the Family and Juvenile Crime

ERIC Educational Resources Information Center

Hay, Carter; Fortson, Edward N.; Hollist, Dusten R.; Altheimer, Irshad; Schaible, Lonnie M.

2006-01-01

Prior research on the family has identified many variables significantly associated with criminal involvement, including such things as parental supervision and discipline and the quality of the parent-child relationship. However, little attention has been devoted to the possibility that the effects of these variables on crime depend on…

Effectiveness of Blog Response Strategies to Minimize Crisis Effects

ERIC Educational Resources Information Center

Tomsic, Louis P.

2010-01-01

This study examined the effects of four post-crisis responses on five different variables using a blog tool. The four post-crisis responses are information only, compensation, apology, and sympathy. The five dependent variables are reputation, anger (negative emotion), negative word-of-mouth, account acceptance and state of the publics based on…

Causal Structure Learning over Time: Observations and Interventions

ERIC Educational Resources Information Center

Rottman, Benjamin M.; Keil, Frank C.

2012-01-01

Seven studies examined how people learn causal relationships in scenarios when the variables are temporally dependent--the states of variables are stable over time. When people intervene on X, and Y subsequently changes state compared to before the intervention, people infer that X influences Y. This strategy allows people to learn causal…

Ten-Year Trends in Physical Dating Violence Victimization?among?US?Adolescent?Females

ERIC Educational Resources Information Center

Howard, Donna E.; Debnam, Katrina J.; Wang, Min Q.

2013-01-01

Background: The study provides 10-year trend data on the psychosocial correlates of physical dating violence (PDV) victimization among females who participated in the national Youth Risk Behavior Surveys of US high school students between 1999 and 2009. Methods: The dependent variable was PDV. Independent variables included 4 dimensions: violence,…

The Adiabatic Invariance of the Action Variable in Classical Dynamics

ERIC Educational Resources Information Center

Wells, Clive G.; Siklos, Stephen T. C.

2007-01-01

We consider one-dimensional classical time-dependent Hamiltonian systems with quasi-periodic orbits. It is well known that such systems possess an adiabatic invariant which coincides with the action variable of the Hamiltonian formalism. We present a new proof of the adiabatic invariance of this quantity and illustrate our arguments by means of…

Understanding Chemical Change in Primary Education: The Effect of Two Cognitive Variables

ERIC Educational Resources Information Center

Stamovlasis, Dimitrios; Papageorgiou, George

2012-01-01

In this study, pupils' understanding of chemical change was investigated in relation to two cognitive variables: logical thinking and field-dependence/field-independence. The participants (N = 99) were sixth-grade elementary school pupils (aged 11/12), which were involved in two different tasks related to combustion. The pupils were tested for…

Do Teacher Salaries Make a Difference? Tennessee Teachers' Salaries and Student Achievement in the Year 2000.

ERIC Educational Resources Information Center

Miller-Whitehead, Marie

The 2000 Tennessee School Systems Report Card data for 138 Tennessee public school systems were examined to identify variables that predict student performance in reading, language arts, mathematics, science, social studies, writing, high school competency examinations, attendance, and graduation. The dependent variable was school system grade…

Bayesian Model Comparison for the Order Restricted RC Association Model

ERIC Educational Resources Information Center

Iliopoulos, G.; Kateri, M.; Ntzoufras, I.

2009-01-01

Association models constitute an attractive alternative to the usual log-linear models for modeling the dependence between classification variables. They impose special structure on the underlying association by assigning scores on the levels of each classification variable, which can be fixed or parametric. Under the general row-column (RC)…

Estimation of Latent Group Effects: Psychometric Technical Report No. 2.

ERIC Educational Resources Information Center

Mislevy, Robert J.

Conventional methods of multivariate normal analysis do not apply when the variables of interest are not observed directly, but must be inferred from fallible or incomplete data. For example, responses to mental test items may depend upon latent aptitude variables, which modeled in turn as functions of demographic effects in the population. A…

Career-Technical Students in Baccalaureate Programs: Predictors of the Intent to Persist and Satisfaction with Educational Pathways

ERIC Educational Resources Information Center

Uranis, Julie

2015-01-01

This research explores the intersections of descriptive attributes, expectations, and influences (independent variables) and the degree to which they predict the intent to persist and satisfaction (dependent variables) of students enrolled in career-technical programs at four-year institutions. Little research exists for this population, and…

Inside Track to the Future: Strategies, Structures, and Leadership for Change.

ERIC Educational Resources Information Center

Alfred, Richard; Carter, Patricia

1996-01-01

Describes the importance for community colleges of looking toward the future to compete effectively. Suggests that change is a variable process that progresses slowly or quickly depending on the interaction of three variables: competitors, customers, and organizational cultures. Includes a checklist for college leaders to determine their level of…

High School Teachers Perceptions of School Change and Its Implications for Student Achievement

ERIC Educational Resources Information Center

Mitchell, Anthony J.; Shoho, Alan R.

2017-01-01

This study sought to determine if there was a relationship between teacher perceptions of educational change and student achievement. Teacher perceptions of change represented the independent variable and the dependent variable consisted of eleventh grade math Texas Assessment of Knowledge and Skills scores, cohort completion rates, and math…

Manifest Variable Granger Causality Models for Developmental Research: A Taxonomy

ERIC Educational Resources Information Center

von Eye, Alexander; Wiedermann, Wolfgang

2015-01-01

Granger models are popular when it comes to testing hypotheses that relate series of measures causally to each other. In this article, we propose a taxonomy of Granger causality models. The taxonomy results from crossing the four variables Order of Lag, Type of (Contemporaneous) Effect, Direction of Effect, and Segment of Dependent Series…

Socio-Demographic Variables, General Psychological Well-Being and the Mental Health Continuum in an African Context

ERIC Educational Resources Information Center

Khumalo, I. P.; Temane, Q. M.; Wissing, M. P.

2012-01-01

Age, gender, marital status, education attainment, employment status, and environmental setting explain different amounts of variance in psychological well-being and mental health. Inconsistent findings are reported for the socio-demographic variables in psychological well-being depending amongst others on the definition and measurement of…

Virtual Teaming and Collaboration Technology: A Study of Influences on Virtual Project Outcomes

ERIC Educational Resources Information Center

Broils, Gary C.

2014-01-01

The purpose of this quantitative correlational study was to explore the relationships between the independent variables, contextual factors for virtual teams and collaboration technology, and the dependent variable, virtual project outcomes. The problem leading to the need for the study is a lower success rate for virtual projects compared to…

The Prevalence of Low Self-Esteem in an Intellectually Disabled Forensic Population

ERIC Educational Resources Information Center

Johnson, P.

2012-01-01

Background: This was a quantitative study to measure the prevalence low self-esteem in an intellectually disabled forensic population. The dependent variables used were the adapted six-item Rosenberg Self-Esteem Scale and the adapted Evaluative Beliefs Scale. It had a repeated measures design with independent variables including consideration of…

Education and Success: A Case Study of the Thai Public Service.

ERIC Educational Resources Information Center

Fry, Gerald W.

1980-01-01

Studied is the bureaucracy in Thailand, and access to an promotion within the system--or the "degree of openness" in the Thai public service. The key dependent variable is occupational attainment. Some key intervening variables include educational attainment, total job experience, sex, and regional remoteness of early schooling. (KC)

The Effects of Three Abstinence Sex Education Programs on Student Attitudes toward Sexual Activity.

ERIC Educational Resources Information Center

Olsen, Joseph A.; And Others

1991-01-01

Examined effects of three abstinence sex education programs on student attitudes toward sexual activity. Administered programs to seventh and tenth graders in three school districts. Independent variables were program, grade level, gender, and pre/posttest. Dependent variable was combined and averaged response to 12 questions. Found four-way…

Predicting 1-Year Change in Body Mass Index among College Students

ERIC Educational Resources Information Center

Adams, Troy; Rini, Angela

2007-01-01

Objective: Despite beliefs about weight gain in college, few researchers have evaluated this phenomenon. Participants: Participants were 18- to 31-year-old students at a midwestern university. The dependent variable was body mass index (BMI) change. Methods: The authors extracted predictor variables from a Health Risk Appraisal. These included…

Influence of Emotional Intelligence and Need for Achievement on Interpersonal Relations and Academic Achievement of Undergraduates

ERIC Educational Resources Information Center

Afolabi, Olukayode Ayooluwa; Ogunmwonyi, Edosa; Okediji, Abayomi

2009-01-01

This study examined influence of emotional intelligence and need for achievement on interpersonal relations and academic achievement of undergraduates. Questionnaires were administered to one hundred and ten (110) subjects. The independent variables are emotional intelligence and need for achievement, while the dependent variables are…

Consistent Visual Analyses of Intrasubject Data

ERIC Educational Resources Information Center

Kahng, SungWoo; Chung, Kyong-Mee; Gutshall, Katharine; Pitts, Steven C.; Kao, Joyce; Girolami, Kelli

2010-01-01

Visual inspection of single-case data is the primary method of interpretation of the effects of an independent variable on a dependent variable in applied behavior analysis. The purpose of the current study was to replicate and extend the results of DeProspero and Cohen (1979) by reexamining the consistency of visual analysis across raters. We…

Using the entire history in the analysis of nested case cohort samples.

PubMed

Rivera, C L; Lumley, T

2016-08-15

Countermatching designs can provide more efficient estimates than simple matching or case-cohort designs in certain situations such as when good surrogate variables for an exposure of interest are available. We extend pseudolikelihood estimation for the Cox model under countermatching designs to models where time-varying covariates are considered. We also implement pseudolikelihood with calibrated weights to improve efficiency in nested case-control designs in the presence of time-varying variables. A simulation study is carried out, which considers four different scenarios including a binary time-dependent variable, a continuous time-dependent variable, and the case including interactions in each. Simulation results show that pseudolikelihood with calibrated weights under countermatching offers large gains in efficiency if compared to case-cohort. Pseudolikelihood with calibrated weights yielded more efficient estimators than pseudolikelihood estimators. Additionally, estimators were more efficient under countermatching than under case-cohort for the situations considered. The methods are illustrated using the Colorado Plateau uranium miners cohort. Furthermore, we present a general method to generate survival times with time-varying covariates. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Multi-Objective Optimization of a Turbofan for an Advanced, Single-Aisle Transport

NASA Technical Reports Server (NTRS)

Berton, Jeffrey J.; Guynn, Mark D.

2012-01-01

Considerable interest surrounds the design of the next generation of single-aisle commercial transports in the Boeing 737 and Airbus A320 class. Aircraft designers will depend on advanced, next-generation turbofan engines to power these airplanes. The focus of this study is to apply single- and multi-objective optimization algorithms to the conceptual design of ultrahigh bypass turbofan engines for this class of aircraft, using NASA s Subsonic Fixed Wing Project metrics as multidisciplinary objectives for optimization. The independent design variables investigated include three continuous variables: sea level static thrust, wing reference area, and aerodynamic design point fan pressure ratio, and four discrete variables: overall pressure ratio, fan drive system architecture (i.e., direct- or gear-driven), bypass nozzle architecture (i.e., fixed- or variable geometry), and the high- and low-pressure compressor work split. Ramp weight, fuel burn, noise, and emissions are the parameters treated as dependent objective functions. These optimized solutions provide insight to the ultrahigh bypass engine design process and provide information to NASA program management to help guide its technology development efforts.

Value of Construction Company and its Dependence on Significant Variables

NASA Astrophysics Data System (ADS)

Vítková, E.; Hromádka, V.; Ondrušková, E.

2017-10-01

The paper deals with the value of the construction company assessment respecting usable approaches and determinable variables. The reasons of the value of the construction company assessment are different, but the most important reasons are the sale or the purchase of the company, the liquidation of the company, the fusion of the company with another subject or the others. According the reason of the value assessment it is possible to determine theoretically different approaches for valuation, mainly it concerns about the yield method of valuation and the proprietary method of valuation. Both approaches are dependant of detailed input variables, which quality will influence the final assessment of the company´s value. The main objective of the paper is to suggest, according to the analysis, possible ways of input variables, mainly in the form of expected cash-flows or the profit, determination. The paper is focused mainly on methods of time series analysis, regression analysis and mathematical simulation utilization. As the output, the results of the analysis on the case study will be demonstrated.

Radio-loud AGN Variability from Propagating Relativistic Jets

NASA Astrophysics Data System (ADS)

Li, Yutong; Schuh, Terance; Wiita, Paul J.

2018-06-01

The great majority of variable emission in radio-loud AGNs is understood to arise from the relativistic flows of plasma along two oppositely directed jets. We study this process using the Athena hydrodynamics code to simulate propagating three-dimensional relativistic jets for a wide range of input jet velocities and jet-to-ambient matter density ratios. We then focus on those simulations that remain essentially stable for extended distances (60-120 times the jet radius). Adopting results for the densities, pressures and velocities from these propagating simulations we estimate emissivities from each cell. The observed emissivity from each cell is strongly dependent upon its variable Doppler boosting factor, which depends upon the changing bulk velocities in those zones with respect to our viewing angle to the jet. We then sum the approximations to the fluxes from a large number of zones upstream of the primary reconfinement shock. The light curves so produced are similar to those of blazars, although turbulence on sub-grid scales is likely to be important for the variability on the shortest timescales.

Patient safety during assistant propelled wheelchair transfers: the effect of the seat cushion on risk of falling.

PubMed

Okunribido, Olanrewaju O

2013-01-01

This article is a report of a study of the effect of the seat cushion on risk of falling from a wheelchair. Two laboratory studies and simulated assistant propelled wheelchair transfers were conducted with four healthy female participants. For the laboratory studies there were three independent variables: trunk posture (upright/flexed forward), seat cushion (flat polyurethane/propad low profile), and feet condition (dangling/supported), and two dependent variables: occupied wheelchair (wheelchair) center of gravity (CG), and stability. For the simulated transfers there was one independent variable: seat cushion (flat polyurethane/propad low profile), and one dependent variable: perception of safety (risk of falling). Results showed that the wheelchair CG was closer to the front wheels, and stability lower for the propad low profile cushion compared to the polyurethane cushion, when the participants sat with their feet dangling. During the simulated transfers, sitting on the propad low profile cushion caused participants to feel more apprehensive (anxious or uneasy) compared to sitting on the polyurethane cushion. The findings can contribute to the assessment of risk and care planning of non-ambulatory wheelchair users.

Multinomial logistic regression in workers' health

NASA Astrophysics Data System (ADS)

Grilo, Luís M.; Grilo, Helena L.; Gonçalves, Sónia P.; Junça, Ana

2017-11-01

In European countries, namely in Portugal, it is common to hear some people mentioning that they are exposed to excessive and continuous psychosocial stressors at work. This is increasing in diverse activity sectors, such as, the Services sector. A representative sample was collected from a Portuguese Services' organization, by applying a survey (internationally validated), which variables were measured in five ordered categories in Likert-type scale. A multinomial logistic regression model is used to estimate the probability of each category of the dependent variable general health perception where, among other independent variables, burnout appear as statistically significant.

Quantification of Bone Growth Rate Variability in Rats Exposed to Micro- (near zero G) and Macrogravity (2G)

NASA Technical Reports Server (NTRS)

Bromage, Timothy G.; Doty, Stephen B.; Smolyar, Igor; Holton, Emily

1996-01-01

Our stated primary objective is to quantify the growth rate variability of rat lamellar bone exposed to micro and macrogravity (2G). The primary significance of the proposed work is that an elegant method will be established that unequivocally characterizes the morphological consequences of gravitational factors on developing bone. The integrity of this objective depends upon our successful preparation of thin sections suitable for imaging individual bone lamellae, and our imaging and quantitation of growth rate variability in populations of lamellae from individual bone samples.

Variables influencing allocation of capital expenditure in Indonesia

NASA Astrophysics Data System (ADS)

Muda, Iskandar; Naibaho, Revmianson

2018-03-01

The purpose of this study is to examine the factors affecting capital expenditure in Indonesia. The independent variables used are The Effects of Financing Surplus, Total Population and Regional Sizes and the dependent variable used is The Effects of Financing Surplus. This type of research is a causal associative research. The type of data used is secondary data in severals provinces in Indonesia with multiple regression analysis. The results show significantly the determinants of capital expenditure allocation in Indonesia are affected by Financing Surplus, Total Population and Regional Sizes.

Assessment of the effects of release variables on the consequences of LNG spillage onto water using FERC models.

PubMed

Qiao, Yuanhua; West, Harry H; Mannan, M Sam; Johnson, David W; Cornwell, John B

2006-03-17

Liquefied natural gas (LNG) release, spread, evaporation, and dispersion processes are illustrated using the Federal Energy Regulatory Commission models in this paper. The spillage consequences are dependent upon the tank conditions, release scenarios, and the environmental conditions. The effects of the contributing variables, including the tank configuration, breach hole size, ullage pressure, wind speed and stability class, and surface roughness, on the consequence of LNG spillage onto water are evaluated using the models. The sensitivities of the consequences to those variables are discussed.

Period variability of coupled noisy oscillators

NASA Astrophysics Data System (ADS)

Mori, Fumito; Kori, Hiroshi

2013-03-01

Period variability, quantified by the standard deviation (SD) of the cycle-to-cycle period, is investigated for noisy phase oscillators. We define the checkpoint phase as the beginning or end point of one oscillation cycle and derive an expression for the SD as a function of this phase. We find that the SD is dependent on the checkpoint phase only when oscillators are coupled. The applicability of our theory is verified using a realistic model. Our work clarifies the relationship between period variability and synchronization from which valuable information regarding coupling can be inferred.

Mathematical model for production of an industry focusing on worker status

NASA Astrophysics Data System (ADS)

Visalakshi, V.; kiran kumari, Sheshma

2018-04-01

Productivity improvement is posing a great challenge for industry everyday because of the difficulties in keeping track and priorising the variables that have significant impact on the productivity. The variation in production depends on the linguistic variables such as worker commitment, worker motivation and worker skills. Since the variables are linguistic we try to propose a model which gives an appropriate production of an industry. Fuzzy models aids the relationship between the factors and status. The model will support the industry to focus on the mentality of worker to increase the production.

Non-manipulation quantitative designs.

PubMed

Rumrill, Phillip D

2004-01-01

The article describes non-manipulation quantitative designs of two types, correlational and causal comparative studies. Both of these designs are characterized by the absence of random assignment of research participants to conditions or groups and non-manipulation of the independent variable. Without random selection or manipulation of the independent variable, no attempt is made to draw causal inferences regarding relationships between independent and dependent variables. Nonetheless, non-manipulation studies play an important role in rehabilitation research, as described in this article. Examples from the contemporary rehabilitation literature are included. Copyright 2004 IOS Press

Flow of sand and a variable mass Atwood machine

NASA Astrophysics Data System (ADS)

Flores, José; Solovey, Guillermo; Gil, Salvador

2003-07-01

We discuss a simple and inexpensive apparatus that lets us measure the instantaneous flow rate of granular media, such as sand, in real time. The measurements allow us to elucidate the phenomenological laws that govern the flow of granular media through an aperture. We use this apparatus to construct a variable mass system and study the motion of an Atwood machine with one weight changing in time in a controlled manner. The study illustrates Newton's second law for variable mass systems and lets us investigate the dependence of the flow rate on acceleration.

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/).

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.

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.

Predictors of patient dependence in mild-to-moderate Alzheimer's disease.

PubMed

Benke, Thomas; Sanin, Günter; Lechner, Anita; Dal-Bianco, Peter; Ransmayr, Gerhard; Uranüs, Margarete; Marksteiner, Josef; Gaudig, Maren; Schmidt, Reinhold

2015-01-01

Patient dependence has rarely been studied in mild-to-moderate Alzheimer's disease (AD). To identify factors which predict patient dependence in mild-to-moderate AD. We studied 398 non-institutionalized AD patients (234 females) of the ongoing Prospective Registry on Dementia (PRODEM) in Austria. The Dependence Scale (DS) was used to assess patient dependence. Patient assessment comprised functional abilities, neuropsychiatric symptoms and cognitive functions. A multiple linear regression analysis was performed to identify predictors of patient dependence. AD patients were mildly-to-moderately impaired (mean scores and SDs were: CDR 0.84 ± 0.43; DAD 74.4 ± 23.3, MMSE = 22.5 ± 3.6). Psychopathology and caregiver burden were in the low range (mean NPI score 13.2, range 0 to 98; mean ZBI score 18, range 0-64). Seventy five percent of patients were classified as having a mild level of patient dependence (DS sum score 0 to 6). Patient dependence correlated significantly and positively with age, functional measures, psychopathology and depression, disease duration, and caregiver burden. Significant negative, but low correlations were found between patient dependence, cognitive variables, and global cognition. Activities of daily living, patient age, and disease severity accounted for 63% of variance in patient dependence, whereas cognitive variables accounted for only 11%. Dependence in this cohort was mainly related to age and functional impairment, and less so to cognitive and neuropsychiatric variables. This differs from studies investigating patients in more advanced disease stages which found abnormal behavior and impairments of cognition as main predictors of patient dependence.

Resistance controllability and variability improvement in a TaO{sub x}-based resistive memory for multilevel storage application

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

Prakash, A., E-mail: amitknp@postech.ac.kr, E-mail: amit.knp02@gmail.com, E-mail: hwanghs@postech.ac.kr; Song, J.; Hwang, H., E-mail: amitknp@postech.ac.kr, E-mail: amit.knp02@gmail.com, E-mail: hwanghs@postech.ac.kr

In order to obtain reliable multilevel cell (MLC) characteristics, resistance controllability between the different resistance levels is required especially in resistive random access memory (RRAM), which is prone to resistance variability mainly due to its intrinsic random nature of defect generation and filament formation. In this study, we have thoroughly investigated the multilevel resistance variability in a TaO{sub x}-based nanoscale (<30 nm) RRAM operated in MLC mode. It is found that the resistance variability not only depends on the conductive filament size but also is a strong function of oxygen vacancy concentration in it. Based on the gained insights through experimentalmore » observations and simulation, it is suggested that forming thinner but denser conductive filament may greatly improve the temporal resistance variability even at low operation current despite the inherent stochastic nature of resistance switching process.« less

Mars dust storms - Interannual variability and chaos

NASA Technical Reports Server (NTRS)

Ingersoll, Andrew P.; Lyons, James R.

1993-01-01

The hypothesis is that the global climate system, consisting of atmospheric dust interacting with the circulation, produces its own interannual variability when forced at the annual frequency. The model has two time-dependent variables representing the amount of atmospheric dust in the northern and southern hemispheres, respectively. Absorption of sunlight by the dust drives a cross-equatorial Hadley cell that brings more dust into the heated hemisphere. The circulation decays when the dust storm covers the globe. Interannual variability manifests itself either as a periodic solution in which the period is a multiple of the Martian year, or as an aperiodic (chaotic) solution that never repeats. Both kinds of solution are found in the model, lending support to the idea that interannual variability is an intrinsic property of the global climate system. The next step is to develop a hierarchy of dust-circulation models capable of being integrated for many years.

Tuned Normalization Explains the Size of Attention Modulations

PubMed Central

Ni, Amy M.; Ray, Supratim; Maunsell, John H. R.

2012-01-01

SUMMARY The effect of attention on firing rates varies considerably within a single cortical area. The firing rate of some neurons is greatly modulated by attention while others are hardly affected. The reason for this variability across neurons is unknown. We found that the variability in attention modulation across neurons in area MT of macaques can be well explained by variability in the strength of tuned normalization across neurons. The presence of tuned normalization also explains a striking asymmetry in attention effects within neurons: when two stimuli are in a neuron’s receptive field, directing attention to the preferred stimulus modulates firing rates more than directing attention to the non-preferred stimulus. These findings show that much of the neuron-to-neuron variability in modulation of responses by attention depends on variability in the way the neurons process multiple stimuli, rather than differences in the influence of top-down signals related to attention. PMID:22365552

Using directed information for influence discovery in interconnected dynamical systems

NASA Astrophysics Data System (ADS)

Rao, Arvind; Hero, Alfred O.; States, David J.; Engel, James Douglas

2008-08-01

Structure discovery in non-linear dynamical systems is an important and challenging problem that arises in various applications such as computational neuroscience, econometrics, and biological network discovery. Each of these systems have multiple interacting variables and the key problem is the inference of the underlying structure of the systems (which variables are connected to which others) based on the output observations (such as multiple time trajectories of the variables). Since such applications demand the inference of directed relationships among variables in these non-linear systems, current methods that have a linear assumption on structure or yield undirected variable dependencies are insufficient. Hence, in this work, we present a methodology for structure discovery using an information-theoretic metric called directed time information (DTI). Using both synthetic dynamical systems as well as true biological datasets (kidney development and T-cell data), we demonstrate the utility of DTI in such problems.

Partitioning neuronal variability

PubMed Central

Goris, Robbe L.T.; Movshon, J. Anthony; Simoncelli, Eero P.

2014-01-01

Responses of sensory neurons differ across repeated measurements. This variability is usually treated as stochasticity arising within neurons or neural circuits. However, some portion of the variability arises from fluctuations in excitability due to factors that are not purely sensory, such as arousal, attention, and adaptation. To isolate these fluctuations, we developed a model in which spikes are generated by a Poisson process whose rate is the product of a drive that is sensory in origin, and a gain summarizing stimulus-independent modulatory influences on excitability. This model provides an accurate account of response distributions of visual neurons in macaque LGN, V1, V2, and MT, revealing that variability originates in large part from excitability fluctuations which are correlated over time and between neurons, and which increase in strength along the visual pathway. The model provides a parsimonious explanation for observed systematic dependencies of response variability and covariability on firing rate. PMID:24777419

A new approach in space-time analysis of multivariate hydrological data: Application to Brazil's Nordeste region rainfall

NASA Astrophysics Data System (ADS)

Sicard, Emeline; Sabatier, Robert; Niel, HéLèNe; Cadier, Eric

2002-12-01

The objective of this paper is to implement an original method for spatial and multivariate data, combining a method of three-way array analysis (STATIS) with geostatistical tools. The variables of interest are the monthly amounts of rainfall in the Nordeste region of Brazil, recorded from 1937 to 1975. The principle of the technique is the calculation of a linear combination of the initial variables, containing a large part of the initial variability and taking into account the spatial dependencies. It is a promising method that is able to analyze triple variability: spatial, seasonal, and interannual. In our case, the first component obtained discriminates a group of rain gauges, corresponding approximately to the Agreste, from all the others. The monthly variables of July and August strongly influence this separation. Furthermore, an annual study brings out the stability of the spatial structure of components calculated for each year.

Characteristics of acute care hospitals with diversity plans and translation services.

PubMed

Moseley, Charles B; Shen, Jay J; Ginn, Gregory O

2011-01-01

Hospitals provide diversity activities for a number of reasons. The authors examined community demand, resource availability, managed care, institutional pressure, and external orientation related variables that were associated with acute care hospital diversity plans and translation services. The authors used multiple logistic regression to analyze the data for 478 hospitals in the 2006 National Inpatient Sample (NIS) dataset that had available data on the racial and ethnic status of their discharges. We also used 2004 and 2006 American Hospital Association (AHA) data to measure the two dependent diversity variables and the other independent variables. We found that resource, managed care, and external orientation variables were associated with having a diversity plan and that resource, managed care, institutional, and external orientation variables were associated with providing translation services. The authors concluded that more evidence for diversity's impact, additional resources, and more institutional pressure may be needed to motivate more hospitals to provide diversity planning and translation services.

Polynomial chaos expansion with random and fuzzy variables

NASA Astrophysics Data System (ADS)

Jacquelin, E.; Friswell, M. I.; Adhikari, S.; Dessombz, O.; Sinou, J.-J.

2016-06-01

A dynamical uncertain system is studied in this paper. Two kinds of uncertainties are addressed, where the uncertain parameters are described through random variables and/or fuzzy variables. A general framework is proposed to deal with both kinds of uncertainty using a polynomial chaos expansion (PCE). It is shown that fuzzy variables may be expanded in terms of polynomial chaos when Legendre polynomials are used. The components of the PCE are a solution of an equation that does not depend on the nature of uncertainty. Once this equation is solved, the post-processing of the data gives the moments of the random response when the uncertainties are random or gives the response interval when the variables are fuzzy. With the PCE approach, it is also possible to deal with mixed uncertainty, when some parameters are random and others are fuzzy. The results provide a fuzzy description of the response statistical moments.

Tuned normalization explains the size of attention modulations.

PubMed

Ni, Amy M; Ray, Supratim; Maunsell, John H R

2012-02-23

The effect of attention on firing rates varies considerably within a single cortical area. The firing rate of some neurons is greatly modulated by attention while others are hardly affected. The reason for this variability across neurons is unknown. We found that the variability in attention modulation across neurons in area MT of macaques can be well explained by variability in the strength of tuned normalization across neurons. The presence of tuned normalization also explains a striking asymmetry in attention effects within neurons: when two stimuli are in a neuron's receptive field, directing attention to the preferred stimulus modulates firing rates more than directing attention to the nonpreferred stimulus. These findings show that much of the neuron-to-neuron variability in modulation of responses by attention depends on variability in the way the neurons process multiple stimuli, rather than differences in the influence of top-down signals related to attention. Copyright © 2012 Elsevier Inc. All rights reserved.

On X-Ray Variability in Seyfert Galaxies

NASA Technical Reports Server (NTRS)

Turner, T. J.; George, I. M.; Nandra, K.; Turcan, D.

1999-01-01

This paper presents a quantification of the X-ray variability amplitude for 79 ASCA observations of 36 Seyfert 1 galaxies. We find that consideration of sources with the narrowest permitted lines in the optical band introduces scatter into the established correlation between X-ray variability and nuclear luminosity. Consideration of the X-ray spectral index and variability properties together shows distinct groupings in parameter space for broad and narrow-line Seyfert 1 galaxies, confirming previous studies. A strong correlation is found between hard X-ray variability and FWHM Hbeta. A range of nuclear mass and accretion rate across the Seyfert population can explain the differences observed in X-ray and optical properties. An attractive alternative model, which does not depend on any systematic difference in central mass, is that the circumnuclear gas of NLSy1s is different to BLSy1s in temperature, optical depth, density or geometry.

Variables related to romanticism and self-esteem in pregnant teenagers.

PubMed

Medora, N P; Goldstein, A; von der Hellen, C

1993-01-01

In this study, the Dean Romanticism Scale and the Bachman Self-esteem Scale were administered to 121 teenagers between the ages of 12 and 19 in Southern California to investigate their degree of romanticism and self-esteem. The study also explored whether there was any relationship between the dependent variables of romanticism and self-esteem and ten independent variables--age, race, place of residence during pregnancy, age when first sexual intercourse occurred, age when pregnancy occurred, incidence of sexual abuse, incidence of abortion, adoption considerations, whether the subject was currently sexually active, and whether the teenager planned to have a child with the father of the baby. The results indicated that two variables were significantly related to feelings of romanticism--adoption considerations and whether the adolescent planned to have a child with the baby's father. In addition, two variables were significantly related to self-esteem--the incidence of sexual abuse and the incidence of abortion.

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.

[Optimal extraction of effective constituents from Aralia elata by central composite design and response surface methodology].

PubMed

Lv, Shao-Wa; Liu, Dong; Hu, Pan-Pan; Ye, Xu-Yan; Xiao, Hong-Bin; Kuang, Hai-Xue

2010-03-01

To optimize the process of extracting effective constituents from Aralia elata by response surface methodology. The independent variables were ethanol concentration, reflux time and solvent fold, the dependent variable was extraction rate of total saponins in Aralia elata. Linear or no-linear mathematic models were used to estimate the relationship between independent and dependent variables. Response surface methodology was used to optimize the process of extraction. The prediction was carried out through comparing the observed and predicted values. Regression coefficient of binomial fitting complex model was as high as 0.9617, the optimum conditions of extraction process were 70% ethanol, 2.5 hours for reflux, 20-fold solvent and 3 times for extraction. The bias between observed and predicted values was -2.41%. It shows the optimum model is highly predictive.

Predictors of physical performance and functional ability in people 50+ with and without fibromyalgia.

PubMed

Jones, C Jessie; Rutledge, Dana N; Aquino, Jordan

2010-07-01

The purposes of this study were to determine whether people with and without fibromyalgia (FM) age 50 yr and above showed differences in physical performance and perceived functional ability and to determine whether age, gender, depression, and physical activity level altered the impact of FM status on these factors. Dependent variables included perceived function and 6 performance measures (multidimensional balance, aerobic endurance, overall functional mobility, lower body strength, and gait velocity-normal or fast). Independent (predictor) variables were FM status, age, gender, depression, and physical activity level. Results indicated significant differences between adults with and without FM on all physical-performance measures and perceived function. Linear-regression models showed that the contribution of significant predictors was in expected directions. All regression models were significant, accounting for 16-65% of variance in the dependent variables.

A computing method for sound propagation through a nonuniform jet stream

NASA Technical Reports Server (NTRS)

Padula, S. L.; Liu, C. H.

1974-01-01

The classical formulation of sound propagation through a jet flow was found to be inadequate for computer solutions. Previous investigations selected the phase and amplitude of the acoustic pressure as dependent variables requiring the solution of a system of nonlinear algebraic equations. The nonlinearities complicated both the analysis and the computation. A reformulation of the convective wave equation in terms of a new set of dependent variables is developed with a special emphasis on its suitability for numerical solutions on fast computers. The technique is very attractive because the resulting equations are linear in nonwaving variables. The computer solution to such a linear system of algebraic equations may be obtained by well-defined and direct means which are conservative of computer time and storage space. Typical examples are illustrated and computational results are compared with available numerical and experimental data.

Effect of land use on the spatial variability of organic matter and nutrient status in an Oxisol

NASA Astrophysics Data System (ADS)

Paz-Ferreiro, Jorge; Alves, Marlene Cristina; Vidal Vázquez, Eva

2013-04-01

Heterogeneity is now considered as an inherent soil property. Spatial variability of soil attributes in natural landscapes results mainly from soil formation factors. In cultivated soils much heterogeneity can additionally occur as a result of land use, agricultural systems and management practices. Organic matter content (OMC) and nutrients associated to soil exchange complex are key attribute in the maintenance of a high quality soil. Neglecting spatial heterogeneity in soil OMC and nutrient status at the field scale might result in reduced yield and in environmental damage. We analyzed the impact of land use on the pattern of spatial variability of OMC and soil macronutrients at the stand scale. The study was conducted in São Paulo state, Brazil. Land uses were pasture, mango orchard and corn field. Soil samples were taken at 0-10 cm and 10-20 cm depth in 84 points, within 100 m x 100 m plots. Texture, pH, OMC, cation exchange capacity (CEC), exchangeable cations (Ca, Mg, K, H, Al) and resin extractable phosphorus were analyzed.. Statistical variability was found to be higher in parameters defining the soil nutrient status (resin extractable P, K, Ca and Mg) than in general soil properties (OMC, CEC, base saturation and pH). Geostatistical analysis showed contrasting patterns of spatial dependence for the different soil uses, sampling depths and studied properties. Most of the studied data sets collected at two different depths exhibited spatial dependence at the sampled scale and their semivariograms were modeled by a nugget effect plus a structure. The pattern of soil spatial variability was found to be different between the three study soil uses and at the two sampling depths, as far as model type, nugget effect or ranges of spatial dependence were concerned. Both statistical and geostatistical results pointed out the importance of OMC as a driver responsible for the spatial variability of soil nutrient status.

Effects of spatial structure of population size on the population dynamics of barnacles across their elevational range.

PubMed

Fukaya, Keiichi; Okuda, Takehiro; Nakaoka, Masahiro; Noda, Takashi

2014-11-01

Explanations for why population dynamics vary across the range of a species reflect two contrasting hypotheses: (i) temporal variability of populations is larger in the centre of the range compared to the margins because overcompensatory density dependence destabilizes population dynamics and (ii) population variability is larger near the margins, where populations are more susceptible to environmental fluctuations. In both of these hypotheses, positions within the range are assumed to affect population variability. In contrast, the fact that population variability is often related to mean population size implies that the spatial structure of the population size within the range of a species may also be a useful predictor of the spatial variation in temporal variability of population size over the range of the species. To explore how population temporal variability varies spatially and the underlying processes responsible for the spatial variation, we focused on the intertidal barnacle Chthamalus dalli and examined differences in its population dynamics along the tidal levels it inhabits. Changes in coverage of barnacle populations were monitored for 10.5 years at 25 plots spanning the elevational range of this species. Data were analysed by fitting a population dynamics model to estimate the effects of density-dependent and density-independent processes on population growth. We also examined the temporal mean-variance relationship of population size with parameters estimated from the population dynamics model. We found that the relative variability of populations tended to increase from the centre of the elevational range towards the margins because of an increase in the magnitude of stochastic fluctuations of growth rates. Thus, our results supported hypothesis (2). We also found that spatial variations in temporal population variability were well characterized by Taylor's power law, the relative population variability being inversely related to the mean population size. Results suggest that understanding the population dynamics of a species over its range may be facilitated by taking the spatial structure of population size into account as well as by considering changes in population processes as a function of position within the range of the species. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

Collocation mismatch uncertainties in satellite aerosol retrieval validation

NASA Astrophysics Data System (ADS)

Virtanen, Timo H.; Kolmonen, Pekka; Sogacheva, Larisa; Rodríguez, Edith; Saponaro, Giulia; de Leeuw, Gerrit

2018-02-01

Satellite-based aerosol products are routinely validated against ground-based reference data, usually obtained from sun photometer networks such as AERONET (AEROsol RObotic NETwork). In a typical validation exercise a spatial sample of the instantaneous satellite data is compared against a temporal sample of the point-like ground-based data. The observations do not correspond to exactly the same column of the atmosphere at the same time, and the representativeness of the reference data depends on the spatiotemporal variability of the aerosol properties in the samples. The associated uncertainty is known as the collocation mismatch uncertainty (CMU). The validation results depend on the sampling parameters. While small samples involve less variability, they are more sensitive to the inevitable noise in the measurement data. In this paper we study systematically the effect of the sampling parameters in the validation of AATSR (Advanced Along-Track Scanning Radiometer) aerosol optical depth (AOD) product against AERONET data and the associated collocation mismatch uncertainty. To this end, we study the spatial AOD variability in the satellite data, compare it against the corresponding values obtained from densely located AERONET sites, and assess the possible reasons for observed differences. We find that the spatial AOD variability in the satellite data is approximately 2 times larger than in the ground-based data, and the spatial variability correlates only weakly with that of AERONET for short distances. We interpreted that only half of the variability in the satellite data is due to the natural variability in the AOD, and the rest is noise due to retrieval errors. However, for larger distances (˜ 0.5°) the correlation is improved as the noise is averaged out, and the day-to-day changes in regional AOD variability are well captured. Furthermore, we assess the usefulness of the spatial variability of the satellite AOD data as an estimate of CMU by comparing the retrieval errors to the total uncertainty estimates including the CMU in the validation. We find that accounting for CMU increases the fraction of consistent observations.

Nonparametric methods in actigraphy: An update

PubMed Central

Gonçalves, Bruno S.B.; Cavalcanti, Paula R.A.; Tavares, Gracilene R.; Campos, Tania F.; Araujo, John F.

2014-01-01

Circadian rhythmicity in humans has been well studied using actigraphy, a method of measuring gross motor movement. As actigraphic technology continues to evolve, it is important for data analysis to keep pace with new variables and features. Our objective is to study the behavior of two variables, interdaily stability and intradaily variability, to describe rest activity rhythm. Simulated data and actigraphy data of humans, rats, and marmosets were used in this study. We modified the method of calculation for IV and IS by modifying the time intervals of analysis. For each variable, we calculated the average value (IVm and ISm) results for each time interval. Simulated data showed that (1) synchronization analysis depends on sample size, and (2) fragmentation is independent of the amplitude of the generated noise. We were able to obtain a significant difference in the fragmentation patterns of stroke patients using an IVm variable, while the variable IV60 was not identified. Rhythmic synchronization of activity and rest was significantly higher in young than adults with Parkinson׳s when using the ISM variable; however, this difference was not seen using IS60. We propose an updated format to calculate rhythmic fragmentation, including two additional optional variables. These alternative methods of nonparametric analysis aim to more precisely detect sleep–wake cycle fragmentation and synchronization. PMID:26483921

Simultaneous Optimization of Multiple Response Variables for the Gelatin-chitosan Microcapsules Containing Angelica Essential Oil.

PubMed

Li, Qiang; Sun, Li-Jian; Gong, Xian-Feng; Wang, Yang; Zhao, Xue-Ling

2017-01-01

Angelica essential oil (AO), a major pharmacologically active component of Angelica sinensis (Oliv.) Diels, possesses hemogenesis, analgesic activities, and sedative effect. The application of AO in pharmaceutical systems had been limited because of its low oxidative stability. The AO-loaded gelatin-chitosan microcapsules with prevention from oxidation were developed and optimized using response surface methodology. The effects of formulation variables (pH at complex coacervation, gelatin concentration, and core/wall ratio) on multiple response variables (yield, encapsulation efficiency, antioxidation rate, percent of drug released in 1 h, and time to 85% drug release) were systemically investigated. A desirability function that combined these five response variables was constructed. All response variables investigated were found to be highly dependent on the formulation variables, with strong interactions observed between the formulation variables. It was found that optimum overall desirability of AO microcapsules could be obtained at pH 6.20, gelatin concentration 25.00%, and core/wall ratio 40.40%. The experimental values of the response variables highly agreed with the predicted values. The antioxidation rate of optimum formulation was approximately 8 times higher than that of AO. The in-vitro drug release from microcapsules was followed Higuchi model with super case-II transport mechanism.

What weather variables are important in predicting heat-related mortality? A new application of statistical learning methods

PubMed Central

Zhang, Kai; Li, Yun; Schwartz, Joel D.; O'Neill, Marie S.

2014-01-01

Hot weather increases risk of mortality. Previous studies used different sets of weather variables to characterize heat stress, resulting in variation in heat-mortality- associations depending on the metric used. We employed a statistical learning method – random forests – to examine which of various weather variables had the greatest impact on heat-related mortality. We compiled a summertime daily weather and mortality counts dataset from four U.S. cities (Chicago, IL; Detroit, MI; Philadelphia, PA; and Phoenix, AZ) from 1998 to 2006. A variety of weather variables were ranked in predicting deviation from typical daily all-cause and cause-specific death counts. Ranks of weather variables varied with city and health outcome. Apparent temperature appeared to be the most important predictor of heat-related mortality for all-cause mortality. Absolute humidity was, on average, most frequently selected one of the top variables for all-cause mortality and seven cause-specific mortality categories. Our analysis affirms that apparent temperature is a reasonable variable for activating heat alerts and warnings, which are commonly based on predictions of total mortality in next few days. Additionally, absolute humidity should be included in future heat-health studies. Finally, random forests can be used to guide choice of weather variables in heat epidemiology studies. PMID:24834832

BIOPHYSICAL CHARACTERISATION OF THE UNDER-APPRECIATED AND IMPORTANT RELATIONSHIP BETWEEN HEART RATE VARIABILITY AND HEART RATE

PubMed Central

Monfredi, Oliver; Lyashkov, Alexey E; Johnsen, Anne-Berit; Inada, Shin; Schneider, Heiko; Wang, Ruoxi; Nirmalan, Mahesh; Wisloff, Ulrik; Maltsev, Victor A; Lakatta, Edward G; Zhang, Henggui; Boyett, Mark R

2014-01-01

Heart rate variability (beat-to-beat changes in the RR interval) has attracted considerable attention over the last 30+ years (PubMed currently lists >17,000 publications). Clinically, a decrease in heart rate variability is correlated to higher morbidity and mortality in diverse conditions, from heart disease to foetal distress. It is usually attributed to fluctuation in cardiac autonomic nerve activity. We calculated heart rate variability parameters from a variety of cardiac preparations (including humans, living animals, Langendorff-perfused heart and single sinoatrial nodal cell) in diverse species, combining this with data from previously published papers. We show that regardless of conditions, there is a universal exponential decay-like relationship between heart rate variability and heart rate. Using two biophysical models, we develop a theory for this, and confirm that heart rate variability is primarily dependent on heart rate and cannot be used in any simple way to assess autonomic nerve activity to the heart. We suggest that the correlation between a change in heart rate variability and altered morbidity and mortality is substantially attributable to the concurrent change in heart rate. This calls for re-evaluation of the findings from many papers that have not adjusted properly or at all for heart rate differences when comparing heart rate variability in multiple circumstances. PMID:25225208

Variables selection methods in near-infrared spectroscopy.

PubMed

Xiaobo, Zou; Jiewen, Zhao; Povey, Malcolm J W; Holmes, Mel; Hanpin, Mao

2010-05-14

Near-infrared (NIR) spectroscopy has increasingly been adopted as an analytical tool in various fields, such as the petrochemical, pharmaceutical, environmental, clinical, agricultural, food and biomedical sectors during the past 15 years. A NIR spectrum of a sample is typically measured by modern scanning instruments at hundreds of equally spaced wavelengths. The large number of spectral variables in most data sets encountered in NIR spectral chemometrics often renders the prediction of a dependent variable unreliable. Recently, considerable effort has been directed towards developing and evaluating different procedures that objectively identify variables which contribute useful information and/or eliminate variables containing mostly noise. This review focuses on the variable selection methods in NIR spectroscopy. Selection methods include some classical approaches, such as manual approach (knowledge based selection), "Univariate" and "Sequential" selection methods; sophisticated methods such as successive projections algorithm (SPA) and uninformative variable elimination (UVE), elaborate search-based strategies such as simulated annealing (SA), artificial neural networks (ANN) and genetic algorithms (GAs) and interval base algorithms such as interval partial least squares (iPLS), windows PLS and iterative PLS. Wavelength selection with B-spline, Kalman filtering, Fisher's weights and Bayesian are also mentioned. Finally, the websites of some variable selection software and toolboxes for non-commercial use are given. Copyright 2010 Elsevier B.V. All rights reserved.

A non-marine source of variability in Adélie Penguin demography

USGS Publications Warehouse

Fraser, William R.; Patterson-Fraser, Donna L.; Ribic, Christine; Schofield, Oscar; Ducklow, Hugh

2013-01-01

A primary research objective of the Palmer Long Term Ecological Research (LTER) program has been to identify and understand the factors that regulate the demography of Adélie penguins (Pygoscelis adeliae). In this context, our work has been focused on variability in the marine environment on which this species depends for virtually all aspects of its life history (Ainley, 2002). As we show here, however, there are patterns evident in the population dynamics of Adélie penguins that are better explained by variability in breeding habitat quality rather than by variability in the marine system. Interactions between the geomorphology of the terrestrial environment that, in turn, affect patterns of snow deposition, drive breeding habitat quality.

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.