Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies.

PubMed

Koerner, Tess K; Zhang, Yang

2017-02-27

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers.

FDR doesn't Tell the Whole Story: Joint Influence of Effect Size and Covariance Structure on the Distribution of the False Discovery Proportions

NASA Technical Reports Server (NTRS)

Feiveson, Alan H.; Ploutz-Snyder, Robert; Fiedler, James

2011-01-01

As part of a 2009 Annals of Statistics paper, Gavrilov, Benjamini, and Sarkar report results of simulations that estimated the false discovery rate (FDR) for equally correlated test statistics using a well-known multiple-test procedure. In our study we estimate the distribution of the false discovery proportion (FDP) for the same procedure under a variety of correlation structures among multiple dependent variables in a MANOVA context. Specifically, we study the mean (the FDR), skewness, kurtosis, and percentiles of the FDP distribution in the case of multiple comparisons that give rise to correlated non-central t-statistics when results at several time periods are being compared to baseline. Even if the FDR achieves its nominal value, other aspects of the distribution of the FDP depend on the interaction between signed effect sizes and correlations among variables, proportion of true nulls, and number of dependent variables. We show examples where the mean FDP (the FDR) is 10% as designed, yet there is a surprising probability of having 30% or more false discoveries. Thus, in a real experiment, the proportion of false discoveries could be quite different from the stipulated FDR.

Modulation of brain activity by multiple lexical and word form variables in visual word recognition: A parametric fMRI study.

PubMed

Hauk, Olaf; Davis, Matthew H; Pulvermüller, Friedemann

2008-09-01

Psycholinguistic research has documented a range of variables that influence visual word recognition performance. Many of these variables are highly intercorrelated. Most previous studies have used factorial designs, which do not exploit the full range of values available for continuous variables, and are prone to skewed stimulus selection as well as to effects of the baseline (e.g. when contrasting words with pseudowords). In our study, we used a parametric approach to study the effects of several psycholinguistic variables on brain activation. We focussed on the variable word frequency, which has been used in numerous previous behavioural, electrophysiological and neuroimaging studies, in order to investigate the neuronal network underlying visual word processing. Furthermore, we investigated the variable orthographic typicality as well as a combined variable for word length and orthographic neighbourhood size (N), for which neuroimaging results are still either scarce or inconsistent. Data were analysed using multiple linear regression analysis of event-related fMRI data acquired from 21 subjects in a silent reading paradigm. The frequency variable correlated negatively with activation in left fusiform gyrus, bilateral inferior frontal gyri and bilateral insulae, indicating that word frequency can affect multiple aspects of word processing. N correlated positively with brain activity in left and right middle temporal gyri as well as right inferior frontal gyrus. Thus, our analysis revealed multiple distinct brain areas involved in visual word processing within one data set.

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

NASA Astrophysics Data System (ADS)

Borovsky, Joseph E.

2017-12-01

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

Dynamic modal estimation using instrumental variables

NASA Technical Reports Server (NTRS)

Salzwedel, H.

1980-01-01

A method to determine the modes of dynamical systems is described. The inputs and outputs of a system are Fourier transformed and averaged to reduce the error level. An instrumental variable method that estimates modal parameters from multiple correlations between responses of single input, multiple output systems is applied to estimate aircraft, spacecraft, and off-shore platform modal parameters.

Health-related quality of life in multiple sclerosis: role of cognitive appraisals of self, illness and treatment.

PubMed

Wilski, Maciej; Tasiemski, Tomasz

2016-07-01

Health-related quality of life (HRQoL) is considered an important measure of treatment and rehabilitation outcomes in multiple sclerosis (MS) patients. In this study, we used multivariate regression analysis to examine the role of cognitive appraisals, adjusted for clinical, socioeconomic and demographic variables, as correlates of HRQoL in MS. The cross-sectional study included 257 MS patients, who completed Multiple Sclerosis Impact Scale, Generalized Self-Efficacy Scale, Rosenberg Self-Esteem Scale, Brief Illness Perception Questionnaire, Treatment Beliefs Scale, Actually Received Support Scale (a part of Berlin Social Support Scale) and Socioeconomic Resources Scale. Demographic and clinical characteristics of the participants were collected with a self-report survey. Correlation and regression analyses were conducted to determine associations between the variables. Five variables, illness identity (β = 0.29, p ≤ 0.001), self-esteem (β = -0.22, p ≤ 0.001), general self-efficacy (β = -0.21, p ≤ 0.001), disability subgroup "EDSS" (β = 0.14, p = 0.006) and age (β = 0.12, p = 0.012), were significant correlates of HRQoL in MS. These variables explained 46 % of variance in the dependent variable. Moreover, we identified correlates of physical and psychological dimensions of HRQoL. Cognitive appraisals, such as general self-efficacy, self-esteem and illness perception, are more salient correlates of HRQoL than social support, socioeconomic resources and clinical characteristics, such as type and duration of MS. Therefore, interventions aimed at cognitive appraisals may also improve HRQoL of MS patients.

Forward-backward multiplicity correlations in sNN=200 GeV Au+Au collisions

NASA Astrophysics Data System (ADS)

Back, B. B.; Baker, M. D.; Ballintijn, M.; Barton, D. S.; Betts, R. R.; Bickley, A. A.; Bindel, R.; Budzanowski, A.; Busza, W.; Carroll, A.; Chai, Z.; Decowski, M. P.; García, E.; Gburek, T.; George, N.; Gulbrandsen, K.; Gushue, S.; Halliwell, C.; Hamblen, J.; Hauer, M.; Heintzelman, G. A.; Henderson, C.; Hofman, D. J.; Hollis, R. S.; Hołyński, R.; Holzman, B.; Iordanova, A.; Johnson, E.; Kane, J. L.; Katzy, J.; Khan, N.; Kucewicz, W.; Kulinich, P.; Kuo, C. M.; Lin, W. T.; Manly, S.; McLeod, D.; Mignerey, A. C.; Noucier, R.; Olszewski, A.; Pak, R.; Park, I. C.; Pernegger, H.; Reed, C.; Remsberg, L. P.; Reuter, M.; Roland, C.; Roland, G.; Rosenberg, L.; Sagerer, J.; Sarin, P.; Sawicki, P.; Seals, H.; Sedykh, I.; Skulski, W.; Smith, C. E.; Stankiewicz, M. A.; Steinberg, P.; Stephans, G. S. F.; Sukhanov, A.; Tang, J.-L.; Tonjes, M. B.; Trzupek, A.; Vale, C.; Nieuwenhuizen, G. J. Van; Vaurynovich, S. S.; Verdier, R.; Veres, G. I.; Wenger, E.; Wolfs, F. L. H.; Wosiek, B.; Woźniak, K.; Wuosmaa, A. H.; Wysłouch, B.

2006-07-01

Forward-backward correlations of charged-particle multiplicities in symmetric bins in pseudorapidity are studied to gain insight into the underlying correlation structure of particle production in Au+Au collisions. The PHOBOS detector is used to measure integrated multiplicities in bins centered at η, defined within |η|<3, and covering intervals Δη. The variance σC2 of a suitably defined forward-backward asymmetry variable C is calculated as a function of η,Δη, and centrality. It is found to be sensitive to short-range correlations, and the concept of “clustering” is used to interpret comparisons to phenomenological models.

CADDIS Volume 4. Data Analysis: Exploratory Data Analysis

EPA Pesticide Factsheets

Intro to exploratory data analysis. Overview of variable distributions, scatter plots, correlation analysis, GIS datasets. Use of conditional probability to examine stressor levels and impairment. Exploring correlations among multiple stressors.

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

PubMed

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

2016-06-01

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

Longitudinal change in physical activity and its correlates in relapsing-remitting multiple sclerosis.

PubMed

Motl, Robert W; McAuley, Edward; Sandroff, Brian M

2013-08-01

Physical activity is beneficial for people with multiple sclerosis (MS), but this population is largely inactive. There is minimal information on change in physical activity and its correlates for informing the development of behavioral interventions. This study examined change in physical activity and its symptomatic, social-cognitive, and ambulatory or disability correlates over a 2.5-year period of time in people with relapsing-remitting multiple sclerosis. On 6 occasions, each separated by 6 months, people (N=269) with relapsing-remitting multiple sclerosis completed assessments of symptoms, self-efficacy, walking impairment, disability, and physical activity. The participants wore an accelerometer for 7 days. The change in study variables over 6 time points was examined with unconditional latent growth curve modeling. The association among changes in study variables over time was examined using conditional latent growth curve modeling, and the associations were expressed as standardized path coefficients (β). There were significant linear changes in self-reported and objectively measured physical activity, self-efficacy, walking impairment, and disability over the 2.5-year period; there were no changes in fatigue, depression, and pain. The changes in self-reported and objective physical activity were associated with change in self-efficacy (β=.49 and β=.61, respectively), after controlling for other variables and confounders. The primary limitations of the study were the generalizability of results among those with progressive multiple sclerosis and inclusion of a single variable from social-cognitive theory. Researchers should consider designing interventions that target self-efficacy for the promotion and maintenance of physical activity in this population.

MULTIVARIATE LINEAR MIXED MODELS FOR MULTIPLE OUTCOMES. (R824757)

EPA Science Inventory

We propose a multivariate linear mixed (MLMM) for the analysis of multiple outcomes, which generalizes the latent variable model of Sammel and Ryan. The proposed model assumes a flexible correlation structure among the multiple outcomes, and allows a global test of the impact of ...

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies

PubMed Central

Koerner, Tess K.; Zhang, Yang

2017-01-01

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers. PMID:28264422

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.

Communicative participation restrictions in multiple sclerosis: associated variables and correlation with social functioning.

PubMed

Yorkston, Kathryn M; Baylor, Carolyn; Amtmann, Dagmar

2014-01-01

Individuals with multiple sclerosis (MS) are at risk for communication problems that may restrict their ability to take participation in important life roles such as maintenance of relationships, work, or household management. The aim of this project is to examine selected demographic and symptom-related variables that may contribute to participation restrictions. This examination is intended to aid clinicians in predicting who might be at risk for such restrictions and what variables may be targeted in interventions. Community-dwelling adults with MS (n=216) completed a survey either online or using paper forms. The survey included the 46-item version of the Communicative Participation Item Bank, demographics (age, sex, living situation, employment status, education, and time since onset of diagnosis of MS), and self-reported symptom-related variables (physical activity, emotional problems, fatigue, pain, speech severity, and cognitive/communication skills). In order to identify predictors of restrictions in communicative participation, these variables were entered into a backwards stepwise multiple linear regression analysis. Five variables (cognitive/communication skills, speech severity, speech usage, physical activity, and education) were statistically significant predictors of communication participation. In order to examine the relationship of communicative participation and social role variables, bivariate Spearman correlations were conducted. Results suggest only a fair to moderate relationship between communicative participation and measures of social roles. Communicative participation is a complex construct associated with a number of self-reported variables. Clinicians should be alert to risk factors for reduced communicative participation including reduced cognitive and speech skills, lower levels of speech usage, limitations in physical activities and higher levels of education. The reader will be able to: (a) describe the factors that may restrict participation in individuals with multiple sclerosis; (b) list measures of social functioning that may be pertinent in adults with multiple sclerosis; (c) discuss factors that can be used to predict communicative participation in multiple sclerosis. Copyright © 2014 Elsevier Inc. All rights reserved.

Social Cognitive Correlates of Physical Activity in Black Individuals With Multiple Sclerosis.

PubMed

Kinnett-Hopkins, Dominique; Motl, Robert W

2016-04-01

To examine variables from social cognitive theory as correlates of physical activity in black and white individuals with multiple sclerosis (MS). Cross-sectional. National survey. Black (n=151) and white (n=185) individuals with MS were recruited through the North American Research Committee on Multiple Sclerosis Registry. Not applicable. The battery of questionnaires included information on demographic and clinical characteristics, physical activity, exercise self-efficacy, function, social support, exercise outcome expectations, and exercise goal setting and planning. Black individuals with MS reported significantly lower levels of physical activity compared with white individuals with MS. Physical activity levels were significantly correlated with self-efficacy, outcome expectations, functional limitations as impediments, and goal setting in black participants with MS. The pattern and magnitude of correlations were comparable with those observed in white participants based on Fisher z tests. Researchers should consider applying behavioral interventions that target social cognitive theory variables for increasing physical activity levels among black individuals with MS. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Relationships between Lifestyle, Living Environments, and Incidence of Hypertension in Japan (in Men): Based on Participant’s Data from the Nationwide Medical Check-Up

PubMed Central

Oka, Mayumi; Yamamoto, Mio; Mure, Kanae; Takeshita, Tatsuya; Arita, Mikio

2016-01-01

This study aims to investigate factors that contribute to the differences in incidence of hypertension between different regions in Japan, by accounting for not only individual lifestyles, but also their living environments. The target participants of this survey were individuals who received medical treatment for hypertension, as well as hypertension patients who have not received any treatment. The objective variable for analysis was the incidence of hypertension as data aggregated per prefecture. We used data (in men) including obesity, salt intake, vegetable intake, habitual alcohol consumption, habitual smoking, and number of steps walked per day. The variables within living environment included number of rail stations, standard/light vehicle usage, and slope of habitable land. In addition, we analyzed data for the variables related to medical environment including, participation rate in medical check-ups and number of hospitals. We performed multiple stepwise regression analyses to elucidate the correlation of these variables by using hypertension incidence as the objective variable. Hypertension incidence showed a significant negative correlation with walking and medical check-ups, and a significant positive correlation with light-vehicle usage and slope. Between the number of steps and variables related to the living environment, number of rail stations showed a significant positive correlation, while, standard- and light-vehicle usage showed significant negative correlation. Moreover, with stepwise multiple regression analysis, walking showed the strongest effect. The differences in daily walking based on living environment were associated with the disparities in the hypertension incidence in Japan. PMID:27788198

The comparison of multiple F-wave variable studies and magnetic resonance imaging examinations in the assessment of cervical radiculopathy.

PubMed

Lin, Chu-Hsu; Tsai, Yuan-Hsiung; Chang, Chia-Hao; Chen, Chien-Min; Hsu, Hung-Chih; Wu, Chun-Yen; Hong, Chang-Zern

2013-09-01

The aims of this study were to investigate the correlation of the findings of multiple median and ulnar F-wave variables and magnetic resonance imaging examinations in the prediction of cervical radiculopathy. The data of 68 patients who underwent both nerve conduction studies of the upper extremities and cervical spine magnetic resonance imaging within 3 mos of the nerve conduction studies were retrospectively reviewed and reinterpreted. The associations between multiple median and ulnar F-wave variables (including persistence, chronodispersion, and minimal, maximal, and mean latencies) and magnetic resonance imaging evidence of lower cervical spondylotic radiculopathy (i.e., C7, C8, and T1 radiculopathy) were investigated. Patients with lower cervical radiculopathy exhibited reduced right median F-wave persistence (P = 0.011), increased right ulnar F-wave chronodispersion (P = 0.041), and a trend toward increased left ulnar F-wave chronodispersion (P = 0.059); however, there were no other consistent significant differences in the F-wave variables between patients with and patients without magnetic resonance imaging evidence of lower cervical radiculopathy. In comparison with normal reference values established previously, the sensitivity and positive predictive value of F-wave variable abnormalities for predicting lower cervical radiculopathy were low. There was a low correlation between F-wave studies and magnetic resonance imaging examinations. The diagnostic utility of multiple F-wave variables in the prediction of cervical radiculopathy was not supported by this study.

Systems effects on family planning innovativeness.

PubMed

Lee, S B

1983-12-01

Data from Korea were used to explore the importance of community level variables in explaining family planning adoption at the individual level. An open system concept was applied, assuming that individual family planning behavior is influenced by both environmental and individual factors. The environmental factors were measured at the village level and designated as community characteristics. The dimension of communication network variables was introduced. Each individual was characterized in terms of the degree of her involvement in family planning communication with others in her village. It was assumed that the nature of the communication network linking individuals with each other effects family planning adoption at the individual level. Specific objectives were to determine 1) the relative importance of the specific independent variables in explaining family planning adoption and 2) the relative importance of the community level variables in comparison with the individual level variables in explaining family planning adoption at the individual level. The data were originally gathered in a 1973 research project on Korea's mothers' clubs. 1047 respondents were interviewed, comprising all married women in 25 sample villages having mothers' clubs. The dependent variable was family planning adoption behavior, defined as current use of any of the modern methods of family planning. The independent variables were defined at 3 levels: individual, community, and at a level intermediate between them involving communication links between individuals. More of the individual level independent variables were significantly correlated with the dependent variables than the community level variables. Among those variables with statistically significant correlations, the correlation coefficients were consistently higher for the individual level than for the community level variables. More of the variance in the dependent variable was explained by individual level than by community level variables. Community level variables accounted for only about 2.5% of the total variance in the dependent variable, in marked contrast to the result showing individual level variables accounting for as much as 19% of the total variance. When both individual and community level variables were entered into a multiple correlation analysis, a multiple correlation coefficient of .4714 was obtained together they explained about 20% of the total variance. The 2 communication network variables--connectedness and integrativeness--were correlated with the dependent variable at much higher levels than most of the individual or community level variables. Connectedness accounted for the greatest amount of the total variance. The communication network variables as a group explained as much of the total variance in the dependent variable as the individual level variables and greatly more that the community level variables.

Multivariate localization methods for ensemble Kalman filtering

NASA Astrophysics Data System (ADS)

Roh, S.; Jun, M.; Szunyogh, I.; Genton, M. G.

2015-05-01

In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (entry-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

Heart rate variability is differentially altered in multiple sclerosis: implications for acute, worsening and progressive disability.

PubMed

Studer, Valeria; Rocchi, Camilla; Motta, Caterina; Lauretti, Benedetta; Perugini, Jacopo; Brambilla, Laura; Pareja-Gutierrez, Lorena; Camera, Giorgia; Barbieri, Francesca Romana; Marfia, Girolama A; Centonze, Diego; Rossi, Silvia

2017-01-01

Sympathovagal imbalance has been associated with poor prognosis in chronic diseases, but there is conflicting evidence in multiple sclerosis. The objective of this study was to investigate the autonomic nervous system dysfunction correlation with inflammation and progression in multiple sclerosis. Heart rate variability was analysed in 120 multiple sclerosis patients and 60 healthy controls during supine rest and head-up tilt test; the normalised units of low frequency and high frequency power were considered to assess sympathetic and vagal components, respectively. Correlation analyses with clinical and radiological markers of disease activity and progression were performed. Sympathetic dysfunction was closely related to the progression of disability in multiple sclerosis: progressive patients showed altered heart rate variability with respect to healthy controls and relapsing-remitting patients, with higher rest low frequency power and lacking the expected low frequency power increase during the head-up tilt test. In relapsing-remitting patients, disease activity, even subclinical, was associated with lower rest low frequency power, whereas stable relapsing-remitting patients did not differ from healthy controls. Less sympathetic reactivity and higher low frequency power at rest were associated with incomplete recovery from relapse. Autonomic balance appears to be intimately linked with both the inflammatory activity of multiple sclerosis, which is featured by an overall hypoactivity of the sympathetic nervous system, and its compensatory plastic processes, which appear inefficient in case of worsening and progressive multiple sclerosis.

Illness perception, treatment beliefs, self-esteem, and self-efficacy as correlates of self-management in multiple sclerosis.

PubMed

Wilski, M; Tasiemski, T

2016-05-01

Self-management of a disease is considered one of the most important factors affecting the treatment outcome. The research on the correlates of self-management in multiple sclerosis (MS) is limited. The aim of this study was to determine if personal factors, such as illness perception, treatment beliefs, self-esteem and self-efficacy, are correlates of self-management in MS. This cross-sectional study included 210 patients with MS who completed Multiple Sclerosis Self-Management Scale - Revised, Brief Illness Perception Questionnaire, Treatment Beliefs Scale, Rosenberg Self-Esteem Scale, and Generalized Self-Efficacy Scale. The patients were recruited from a MS rehabilitation clinic. Demographic data and illness-related problems of the study participants were collected with a self-report survey. Correlation and regression analyses were performed to determine associations between variables. Four factors: age at the time of the study (β = 0.14, P = 0.032), timeline (β = 0.16, P = 0.018), treatment control (β = 0.17, P = 0.022), and general self-efficacy (β = 0.19, P = 0.014) turned out to be the significant correlates of self-management in MS. The model including these variables explained 25% of variance in self-management in MS. Personal factors, such as general self-efficacy, perception of treatment control and realistic MS timeline perspective, are more salient correlates of self-management in MS than the objective clinical variables, such as the severity, type, and duration of MS. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Theory and simulations of covariance mapping in multiple dimensions for data analysis in high-event-rate experiments

NASA Astrophysics Data System (ADS)

Zhaunerchyk, V.; Frasinski, L. J.; Eland, J. H. D.; Feifel, R.

2014-05-01

Multidimensional covariance analysis and its validity for correlation of processes leading to multiple products are investigated from a theoretical point of view. The need to correct for false correlations induced by experimental parameters which fluctuate from shot to shot, such as the intensity of self-amplified spontaneous emission x-ray free-electron laser pulses, is emphasized. Threefold covariance analysis based on simple extension of the two-variable formulation is shown to be valid for variables exhibiting Poisson statistics. In this case, false correlations arising from fluctuations in an unstable experimental parameter that scale linearly with signals can be eliminated by threefold partial covariance analysis, as defined here. Fourfold covariance based on the same simple extension is found to be invalid in general. Where fluctuations in an unstable parameter induce nonlinear signal variations, a technique of contingent covariance analysis is proposed here to suppress false correlations. In this paper we also show a method to eliminate false correlations associated with fluctuations of several unstable experimental parameters.

Introductory Guide for Conducting ASVAB Validation/Standards Studies in the U.S. Navy

DTIC Science & Technology

2014-10-16

and leadership with an average multiple correlation of .37 but to predict maintaining personal discipline and physical fitness and military bearing...but to predict maintaining personal discipline and physical fitness and military bearing with mean multiple correlations of only .17 and .16...have been mixed, with results varying by the specific personality traits , intervening variables, and dimensions studied (for a review, see Johnson

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.

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.

Relationship between body composition and postural control in prepubertal overweight/obese children: A cross-sectional study.

PubMed

Villarrasa-Sapiña, Israel; Álvarez-Pitti, Julio; Cabeza-Ruiz, Ruth; Redón, Pau; Lurbe, Empar; García-Massó, Xavier

2018-02-01

Excess body weight during childhood causes reduced motor functionality and problems in postural control, a negative influence which has been reported in the literature. Nevertheless, no information regarding the effect of body composition on the postural control of overweight and obese children is available. The objective of this study was therefore to establish these relationships. A cross-sectional design was used to establish relationships between body composition and postural control variables obtained in bipedal eyes-open and eyes-closed conditions in twenty-two children. Centre of pressure signals were analysed in the temporal and frequency domains. Pearson correlations were applied to establish relationships between variables. Principal component analysis was applied to the body composition variables to avoid potential multicollinearity in the regression models. These principal components were used to perform a multiple linear regression analysis, from which regression models were obtained to predict postural control. Height and leg mass were the body composition variables that showed the highest correlation with postural control. Multiple regression models were also obtained and several of these models showed a higher correlation coefficient in predicting postural control than simple correlations. These models revealed that leg and trunk mass were good predictors of postural control. More equations were found in the eyes-open than eyes-closed condition. Body weight and height are negatively correlated with postural control. However, leg and trunk mass are better postural control predictors than arm or body mass. Finally, body composition variables are more useful in predicting postural control when the eyes are open. Copyright © 2017 Elsevier Ltd. All rights reserved.

Motivation and Burnout in Professional Rugby Players

ERIC Educational Resources Information Center

Cresswell, Scott L.; Eklund, Robert C.

2005-01-01

The authors examined relationships among burnout and motivational types differing in self-determination, using simple correlational analyses as well as more sophisticated canonical correlation analyses allowing for the simultaneous examination of multiple independent and dependent variables. The authors hypothesized that: (a) motivation low in…

The association between histological, macroscopic and magnetic resonance imaging assessed synovitis in end-stage knee osteoarthritis: a cross-sectional study.

PubMed

Riis, R G C; Gudbergsen, H; Simonsen, O; Henriksen, M; Al-Mashkur, N; Eld, M; Petersen, K K; Kubassova, O; Bay Jensen, A C; Damm, J; Bliddal, H; Arendt-Nielsen, L; Boesen, M

2017-02-01

To investigate the association between magnetic resonance imaging (MRI), macroscopic and histological assessments of synovitis in end-stage knee osteoarthritis (KOA). Synovitis of end-stage osteoarthritic knees was assessed using non-contrast-enhanced (CE), contrast-enhanced magnetic resonance imaging (CE-MRI) and dynamic contrast-enhanced (DCE)-MRI prior to (TKR) and correlated with microscopic and macroscopic assessments of synovitis obtained intraoperatively. Multiple bivariate correlations were used with a pre-specified threshold of 0.70 for significance. Also, multiple regression analyses with different subsets of MRI-variables as explanatory variables and the histology score as outcome variable were performed with the intention to find MRI-variables that best explain the variance in histological synovitis (i.e., highest R 2 ). A stepped approach was taken starting with basic characteristics and non-CE MRI-variables (model 1), after which CE-MRI-variables were added (model 2) with the final model also including DCE-MRI-variables (model 3). 39 patients (56.4% women, mean age 68 years, Kellgren-Lawrence (KL) grade 4) had complete MRI and histological data. Only the DCE-MRI variable MExNvoxel (surrogate of the volume and degree of synovitis) and the macroscopic score showed correlations above the pre-specified threshold for acceptance with histological inflammation. The maximum R 2 -value obtained in Model 1 was R 2  = 0.39. In Model 2, where the CE-MRI-variables were added, the highest R 2  = 0.52. In Model 3, a four-variable model consisting of the gender, one CE-MRI and two DCE-MRI-variables yielded a R 2  = 0.71. DCE-MRI is correlated with histological synovitis in end-stage KOA and the combination of CE and DCE-MRI may be a useful, non-invasive tool in characterising synovitis in KOA. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Human Resource Management and Nonjudicial Punishment Rates on Navy Ships

DTIC Science & Technology

1975-08-01

criterion but rather by multiple components. Likert and Bowers (1969) postulated that criteria or enc-result variables "are the dependent variables that...personnel involved in NJPs but rather the total number of NJPs. Thus, if an individual receives multiple NJPs during the reporting period, each NJP will be... Integracion of Mea and Mission -. 37* -. 30 SaData are not presently available for these indices. (* < .05 < .01 14 TABLE 5 Rank Ordering of Correlations

Multivariate localization methods for ensemble Kalman filtering

NASA Astrophysics Data System (ADS)

Roh, S.; Jun, M.; Szunyogh, I.; Genton, M. G.

2015-12-01

In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables that exist at the same locations has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

Statistical experiments using the multiple regression research for prediction of proper hardness in areas of phosphorus cast-iron brake shoes manufacturing

NASA Astrophysics Data System (ADS)

Kiss, I.; Cioată, V. G.; Ratiu, S. A.; Rackov, M.; Penčić, M.

2018-01-01

Multivariate research is important in areas of cast-iron brake shoes manufacturing, because many variables interact with each other simultaneously. This article focuses on expressing the multiple linear regression model related to the hardness assurance by the chemical composition of the phosphorous cast irons destined to the brake shoes, having in view that the regression coefficients will illustrate the unrelated contributions of each independent variable towards predicting the dependent variable. In order to settle the multiple correlations between the hardness of the cast-iron brake shoes, and their chemical compositions several regression equations has been proposed. Is searched a mathematical solution which can determine the optimum chemical composition for the hardness desirable values. Starting from the above-mentioned affirmations two new statistical experiments are effectuated related to the values of Phosphorus [P], Manganese [Mn] and Silicon [Si]. Therefore, the regression equations, which describe the mathematical dependency between the above-mentioned elements and the hardness, are determined. As result, several correlation charts will be revealed.

Effects of cross correlation on the relaxation time of a bistable system driven by cross-correlated noise

NASA Astrophysics Data System (ADS)

Mei, Dongcheng; Xie, Chongwei; Zhang, Li

2003-11-01

We study the effects of correlations between additive and multiplicative noise on relaxation time in a bistable system driven by cross-correlated noise. Using the projection-operator method, we derived an analytic expression for the relaxation time Tc of the system, which is the function of additive (α) and multiplicative (D) noise intensities, correlation intensity λ of noise, and correlation time τ of noise. After introducing a noise intensity ratio and a dimensionless parameter R=D/α, and then performing numerical computations, we find the following: (i) For the case of R<1, the relaxation time Tc increases as R increases. (ii) For the cases of R⩾1, there is a one-peak structure on the Tc-R plot and the effects of cross-correlated noise on the relaxation time are very notable. (iii) For the case of R<1, Tc almost does not change with both λ and τ, and for the cases of R⩾1, Tc decreases as λ increases, however Tc increases as τ increases. λ and τ play opposite roles in Tc, i.e., λ enhances the fluctuation decay of dynamical variable and τ slows down the fluctuation decay of dynamical variable.

General Nature of Multicollinearity in Multiple Regression Analysis.

ERIC Educational Resources Information Center

Liu, Richard

1981-01-01

Discusses multiple regression, a very popular statistical technique in the field of education. One of the basic assumptions in regression analysis requires that independent variables in the equation should not be highly correlated. The problem of multicollinearity and some of the solutions to it are discussed. (Author)

High-level language ability in healthy individuals and its relationship with verbal working memory.

PubMed

Antonsson, Malin; Longoni, Francesca; Einald, Christina; Hallberg, Lina; Kurt, Gabriella; Larsson, Kajsa; Nilsson, Tina; Hartelius, Lena

2016-01-01

The aims of the study were to investigate healthy subjects' performance on a clinical test of high-level language (HLL) and how it is related to demographic characteristics and verbal working memory (VWM). One hundred healthy subjects (20-79 years old) were assessed with the Swedish BeSS test (Laakso, Brunnegård, Hartelius, & Ahlsén, 2000) and two digit span tasks. Relationships between the demographic variables, VWM and BeSS were investigated both with bivariate correlations and multiple regression analysis. The results present the norms for BeSS. The correlations and multiple regression analysis show that demographic variables had limited influence on test performance. Measures of VWM were moderately related to total BeSS score and weakly to moderately correlated with five of the seven subtests. To conclude, education has an influence on the test as a whole but measures of VWM stood out as the most robust predictor of HLL.

Experimental characterization of quantum correlated triple beams generated by cascaded four-wave mixing processes

NASA Astrophysics Data System (ADS)

Qin, Zhongzhong; Cao, Leiming; Jing, Jietai

2015-05-01

Quantum correlations and entanglement shared among multiple modes are fundamental ingredients of most continuous-variable quantum technologies. Recently, a method used to generate multiple quantum correlated beams using cascaded four-wave mixing (FWM) processes was theoretically proposed and experimentally realized by our group [Z. Qin et al., Phys. Rev. Lett. 113, 023602 (2014)]. Our study of triple-beam quantum correlation paves the way to showing the tripartite entanglement in our system. Our system also promises to find applications in quantum information and precision measurement such as the controlled quantum communications, the generation of multiple quantum correlated images, and the realization of a multiport nonlinear interferometer. For its applications, the degree of quantum correlation is a crucial figure of merit. In this letter, we experimentally study how various parameters, such as the cell temperatures, one-photon, and two-photon detunings, influence the degree of quantum correlation between the triple beams generated from the cascaded two-FWM configuration.

Experimental characterization of quantum correlated triple beams generated by cascaded four-wave mixing processes

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

Qin, Zhongzhong; Cao, Leiming; Jing, Jietai, E-mail: jtjing@phy.ecnu.edu.cn

2015-05-25

Quantum correlations and entanglement shared among multiple modes are fundamental ingredients of most continuous-variable quantum technologies. Recently, a method used to generate multiple quantum correlated beams using cascaded four-wave mixing (FWM) processes was theoretically proposed and experimentally realized by our group [Z. Qin et al., Phys. Rev. Lett. 113, 023602 (2014)]. Our study of triple-beam quantum correlation paves the way to showing the tripartite entanglement in our system. Our system also promises to find applications in quantum information and precision measurement such as the controlled quantum communications, the generation of multiple quantum correlated images, and the realization of a multiportmore » nonlinear interferometer. For its applications, the degree of quantum correlation is a crucial figure of merit. In this letter, we experimentally study how various parameters, such as the cell temperatures, one-photon, and two-photon detunings, influence the degree of quantum correlation between the triple beams generated from the cascaded two-FWM configuration.« less

Meteorological Contribution to Variability in Particulate Matter Concentrations

NASA Astrophysics Data System (ADS)

Woods, H. L.; Spak, S. N.; Holloway, T.

2006-12-01

Local concentrations of fine particulate matter (PM) are driven by a number of processes, including emissions of aerosols and gaseous precursors, atmospheric chemistry, and meteorology at local, regional, and global scales. We apply statistical downscaling methods, typically used for regional climate analysis, to estimate the contribution of regional scale meteorology to PM mass concentration variability at a range of sites in the Upper Midwestern U.S. Multiple years of daily PM10 and PM2.5 data, reported by the U.S. Environmental Protection Agency (EPA), are correlated with large-scale meteorology over the region from the National Centers for Environmental Prediction (NCEP) reanalysis data. We use two statistical downscaling methods (multiple linear regression, MLR, and analog) to identify which processes have the greatest impact on aerosol concentration variability. Empirical Orthogonal Functions of the NCEP meteorological data are correlated with PM timeseries at measurement sites. We examine which meteorological variables exert the greatest influence on PM variability, and which sites exhibit the greatest response to regional meteorology. To evaluate model performance, measurement data are withheld for limited periods, and compared with model results. Preliminary results suggest that regional meteorological processes account over 50% of aerosol concentration variability at study sites.

Correlates of Successful Aging: Are They Universal?

ERIC Educational Resources Information Center

Litwin, Howard

2005-01-01

The analysis compared differing correlates of life satisfaction among three diverse population groups in Israel, examining background and health status variables, social environment factors, and activity indicators. Multiple regression analysis revealed that veteran Jewish-Israelis (n = 2,043) had the largest set of predictors, the strongest of…

Testing Multiple Outcomes in Repeated Measures Designs

ERIC Educational Resources Information Center

Lix, Lisa M.; Sajobi, Tolulope

2010-01-01

This study investigates procedures for controlling the familywise error rate (FWR) when testing hypotheses about multiple, correlated outcome variables in repeated measures (RM) designs. A content analysis of RM research articles published in 4 psychology journals revealed that 3 quarters of studies tested hypotheses about 2 or more outcome…

Systematic correlation of environmental exposure and physiological and self-reported behaviour factors with leukocyte telomere length.

PubMed

Patel, Chirag J; Manrai, Arjun K; Corona, Erik; Kohane, Isaac S

2017-02-01

It is hypothesized that environmental exposures and behaviour influence telomere length, an indicator of cellular ageing. We systematically associated 461 indicators of environmental exposures, physiology and self-reported behaviour with telomere length in data from the US National Health and Nutrition Examination Survey (NHANES) in 1999-2002. Further, we tested whether factors identified in the NHANES participants are also correlated with gene expression of telomere length modifying genes. We correlated 461 environmental exposures, behaviours and clinical variables with telomere length, using survey-weighted linear regression, adjusting for sex, age, age squared, race/ethnicity, poverty level, education and born outside the USA, and estimated the false discovery rate to adjust for multiple hypotheses. We conducted a secondary analysis to investigate the correlation between identified environmental variables and gene expression levels of telomere-associated genes in publicly available gene expression samples. After correlating 461 variables with telomere length, we found 22 variables significantly associated with telomere length after adjustment for multiple hypotheses. Of these varaibales, 14 were associated with longer telomeres, including biomarkers of polychlorinated biphenyls([PCBs; 0.1 to 0.2 standard deviation (SD) increase for 1 SD increase in PCB level, P  < 0.002] and a form of vitamin A, retinyl stearate. Eight variables associated with shorter telomeres, including biomarkers of cadmium, C-reactive protein and lack of physical activity. We could not conclude that PCBs are correlated with gene expression of telomere-associated genes. Both environmental exposures and chronic disease-related risk factors may play a role in telomere length. Our secondary analysis found no evidence of association between PCBs/smoking and gene expression of telomere-associated genes. All correlations between exposures, behaviours and clinical factors and changes in telomere length will require further investigation regarding biological influence of exposure. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association

Neuropsychological and Early Maturational Correlates of Intelligence.

ERIC Educational Resources Information Center

Denno, Deborah J.

A study designed to examine biological, sociological, and early maturational correlates of intelligence collected data prospectively, from birth to 15 years of age, on a sample of 987 black children. Multiple indicators of eight independent and three dependent variables were tested in a structural equation model. Altogether, clear sex differences…

Quantitative assessment of cervical vertebral maturation using cone beam computed tomography in Korean girls.

PubMed

Byun, Bo-Ram; Kim, Yong-Il; Yamaguchi, Tetsutaro; Maki, Koutaro; Son, Woo-Sung

2015-01-01

This study was aimed to examine the correlation between skeletal maturation status and parameters from the odontoid process/body of the second vertebra and the bodies of third and fourth cervical vertebrae and simultaneously build multiple regression models to be able to estimate skeletal maturation status in Korean girls. Hand-wrist radiographs and cone beam computed tomography (CBCT) images were obtained from 74 Korean girls (6-18 years of age). CBCT-generated cervical vertebral maturation (CVM) was used to demarcate the odontoid process and the body of the second cervical vertebra, based on the dentocentral synchondrosis. Correlation coefficient analysis and multiple linear regression analysis were used for each parameter of the cervical vertebrae (P < 0.05). Forty-seven of 64 parameters from CBCT-generated CVM (independent variables) exhibited statistically significant correlations (P < 0.05). The multiple regression model with the greatest R (2) had six parameters (PH2/W2, UW2/W2, (OH+AH2)/LW2, UW3/LW3, D3, and H4/W4) as independent variables with a variance inflation factor (VIF) of <2. CBCT-generated CVM was able to include parameters from the second cervical vertebral body and odontoid process, respectively, for the multiple regression models. This suggests that quantitative analysis might be used to estimate skeletal maturation status.

Multiple regression for physiological data analysis: the problem of multicollinearity.

PubMed

Slinker, B K; Glantz, S A

1985-07-01

Multiple linear regression, in which several predictor variables are related to a response variable, is a powerful statistical tool for gaining quantitative insight into complex in vivo physiological systems. For these insights to be correct, all predictor variables must be uncorrelated. However, in many physiological experiments the predictor variables cannot be precisely controlled and thus change in parallel (i.e., they are highly correlated). There is a redundancy of information about the response, a situation called multicollinearity, that leads to numerical problems in estimating the parameters in regression equations; the parameters are often of incorrect magnitude or sign or have large standard errors. Although multicollinearity can be avoided with good experimental design, not all interesting physiological questions can be studied without encountering multicollinearity. In these cases various ad hoc procedures have been proposed to mitigate multicollinearity. Although many of these procedures are controversial, they can be helpful in applying multiple linear regression to some physiological problems.

Climate change but not unemployment explains the changing suicidality in Thessaloniki Greece (2000-2012).

PubMed

Fountoulakis, Konstantinos N; Savopoulos, Christos; Zannis, Prodromos; Apostolopoulou, Martha; Fountoukidis, Ilias; Kakaletsis, Nikolaos; Kanellos, Ilias; Dimellis, Dimos; Hyphantis, Thomas; Tsikerdekis, Athanasios; Pompili, Maurizio; Hatzitolios, Apostolos I

2016-03-15

Recently there was a debate concerning the etiology behind attempts and completed suicides. The aim of the current study was to search for possible correlations between the rates of attempted and completed suicide and climate variables and regional unemployment per year in the county of Thessaloniki, Macedonia, northern Greece, for the years 2000-12. The regional rates of suicide and attempted suicide as well as regional unemployment were available from previous publications of the authors. The climate variables were calculated from the daily E-OBS gridded dataset which is based on observational data Only the male suicide rates correlate significantly with high mean annual temperature but not with unemployment. The multiple linear regression analysis results suggest that temperature is the only variable that determines male suicides and explains 51% of their variance. Unemployment fails to contribute significantly to the model. There seems to be a seasonal distribution for attempts with mean rates being higher for the period from May to October and the rates clearly correlate with temperature. The highest mean rates were observed during May and August and the lowest during December and February. Multiple linear regression analysis suggests that temperature also determines the female attempts rate although the explained variable is significant but very low (3-5%) Climate variables and specifically high temperature correlate both with suicide and attempted suicide rates but with a different way between males and females. The climate effect was stronger than the effect of unemployment. Copyright © 2016 Elsevier B.V. All rights reserved.

Accelerometry in persons with multiple sclerosis: measurement of physical activity or walking mobility?

PubMed

Weikert, Madeline; Motl, Robert W; Suh, Yoojin; McAuley, Edward; Wynn, Daniel

2010-03-15

Motion sensors such as accelerometers have been recognized as an ideal measure of physical activity in persons with MS. This study examined the hypothesis that accelerometer movement counts represent a measure of both physical activity and walking mobility in individuals with MS. The sample included 269 individuals with a definite diagnosis of relapsing-remitting MS who completed the Godin Leisure-Time Exercise Questionnaire (GLTEQ), International Physical Activity Questionnaire (IPAQ), Multiple Sclerosis Walking Scale-12 (MSWS-12), Patient Determined Disease Steps (PDDS), and then wore an ActiGraph accelerometer for 7days. The data were analyzed using bivariate correlation and confirmatory factor analysis. The results indicated that (a) the GLTEQ and IPAQ scores were strongly correlated and loaded significantly on a physical activity latent variable, (b) the MSWS-12 and PDDS scores strongly correlated and loaded significantly on a walking mobility latent variable, and (c) the accelerometer movement counts correlated similarly with the scores from the four self-report questionnaires and cross-loaded on both physical activity and walking mobility latent variables. Our data suggest that accelerometers are measuring both physical activity and walking mobility in persons with MS, whereas self-report instruments are measuring either physical activity or walking mobility in this population.

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.

Estimating weak ratiometric signals in imaging data. II. Meta-analysis with multiple, dual-channel datasets.

PubMed

Sornborger, Andrew; Broder, Josef; Majumder, Anirban; Srinivasamoorthy, Ganesh; Porter, Erika; Reagin, Sean S; Keith, Charles; Lauderdale, James D

2008-09-01

Ratiometric fluorescent indicators are used for making quantitative measurements of a variety of physiological variables. Their utility is often limited by noise. This is the second in a series of papers describing statistical methods for denoising ratiometric data with the aim of obtaining improved quantitative estimates of variables of interest. Here, we outline a statistical optimization method that is designed for the analysis of ratiometric imaging data in which multiple measurements have been taken of systems responding to the same stimulation protocol. This method takes advantage of correlated information across multiple datasets for objectively detecting and estimating ratiometric signals. We demonstrate our method by showing results of its application on multiple, ratiometric calcium imaging experiments.

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,…

A variance-decomposition approach to investigating multiscale habitat associations

USGS Publications Warehouse

Lawler, J.J.; Edwards, T.C.

2006-01-01

The recognition of the importance of spatial scale in ecology has led many researchers to take multiscale approaches to studying habitat associations. However, few of the studies that investigate habitat associations at multiple spatial scales have considered the potential effects of cross-scale correlations in measured habitat variables. When cross-scale correlations in such studies are strong, conclusions drawn about the relative strength of habitat associations at different spatial scales may be inaccurate. Here we adapt and demonstrate an analytical technique based on variance decomposition for quantifying the influence of cross-scale correlations on multiscale habitat associations. We used the technique to quantify the variation in nest-site locations of Red-naped Sapsuckers (Sphyrapicus nuchalis) and Northern Flickers (Colaptes auratus) associated with habitat descriptors at three spatial scales. We demonstrate how the method can be used to identify components of variation that are associated only with factors at a single spatial scale as well as shared components of variation that represent cross-scale correlations. Despite the fact that no explanatory variables in our models were highly correlated (r < 0.60), we found that shared components of variation reflecting cross-scale correlations accounted for roughly half of the deviance explained by the models. These results highlight the importance of both conducting habitat analyses at multiple spatial scales and of quantifying the effects of cross-scale correlations in such analyses. Given the limits of conventional analytical techniques, we recommend alternative methods, such as the variance-decomposition technique demonstrated here, for analyzing habitat associations at multiple spatial scales. ?? The Cooper Ornithological Society 2006.

Confidence Intervals for Squared Semipartial Correlation Coefficients: The Effect of Nonnormality

ERIC Educational Resources Information Center

Algina, James; Keselman, H. J.; Penfield, Randall D.

2010-01-01

The increase in the squared multiple correlation coefficient ([delta]R[superscript 2]) associated with a variable in a regression equation is a commonly used measure of importance in regression analysis. Algina, Keselman, and Penfield found that intervals based on asymptotic principles were typically very inaccurate, even though the sample size…

Pressures, Stresses, Anxieties, and On-Job Safety of the School Superintendent.

ERIC Educational Resources Information Center

Chand, Krishan

Identification of the causes of job stress for public school superintendents, with a focus on personal-experiential and task variables, is the purpose of this study. Methodology involved a mail survey of 1,531 randomly selected superintendents. Canonical correlation analysis (CCA) and multiple regression correlation (MCR) analysis were used to…

Exact Interval Estimation, Power Calculation, and Sample Size Determination in Normal Correlation Analysis

ERIC Educational Resources Information Center

Shieh, Gwowen

2006-01-01

This paper considers the problem of analysis of correlation coefficients from a multivariate normal population. A unified theorem is derived for the regression model with normally distributed explanatory variables and the general results are employed to provide useful expressions for the distributions of simple, multiple, and partial-multiple…

Performance evaluation of receive-diversity free-space optical communications over correlated Gamma-Gamma fading channels.

PubMed

Yang, Guowei; Khalighi, Mohammad-Ali; Ghassemlooy, Zabih; Bourennane, Salah

2013-08-20

The efficacy of spatial diversity in practical free-space optical communication systems is impaired by the fading correlation among the underlying subchannels. We consider in this paper the generation of correlated Gamma-Gamma random variables in view of evaluating the system outage probability and bit-error-rate under the condition of correlated fading. Considering the case of receive-diversity systems with intensity modulation and direct detection, we propose a set of criteria for setting the correlation coefficients on the small- and large-scale fading components based on scintillation theory. We verify these criteria using wave-optics simulations and further show through Monte Carlo simulations that we can effectively neglect the correlation corresponding to the small-scale turbulence in most practical systems, irrespective of the specific turbulence conditions. This has not been clarified before, to the best of our knowledge. We then present some numerical results to illustrate the effect of fading correlation on the system performance. Our conclusions can be generalized to the cases of multiple-beam and multiple-beam multiple-aperture systems.

Characterizing the Joint Effect of Diverse Test-Statistic Correlation Structures and Effect Size on False Discovery Rates in a Multiple-Comparison Study of Many Outcome Measures

NASA Technical Reports Server (NTRS)

Feiveson, Alan H.; Ploutz-Snyder, Robert; Fiedler, James

2011-01-01

In their 2009 Annals of Statistics paper, Gavrilov, Benjamini, and Sarkar report the results of a simulation assessing the robustness of their adaptive step-down procedure (GBS) for controlling the false discovery rate (FDR) when normally distributed test statistics are serially correlated. In this study we extend the investigation to the case of multiple comparisons involving correlated non-central t-statistics, in particular when several treatments or time periods are being compared to a control in a repeated-measures design with many dependent outcome measures. In addition, we consider several dependence structures other than serial correlation and illustrate how the FDR depends on the interaction between effect size and the type of correlation structure as indexed by Foerstner s distance metric from an identity. The relationship between the correlation matrix R of the original dependent variables and R, the correlation matrix of associated t-statistics is also studied. In general R depends not only on R, but also on sample size and the signed effect sizes for the multiple comparisons.

Progranulin genetic polymorphisms influence progression of disability and relapse recovery in multiple sclerosis.

PubMed

Vercellino, Marco; Fenoglio, Chiara; Galimberti, Daniela; Mattioda, Alessandra; Chiavazza, Carlotta; Binello, Eleonora; Pinessi, Lorenzo; Giobbe, Dario; Scarpini, Elio; Cavalla, Paola

2016-07-01

Progranulin (GRN) is a multifunctional protein involved in inflammation and repair, and also a neurotrophic factor critical for neuronal survival. Progranulin is strongly expressed in multiple sclerosis (MS) brains by macrophages and microglia. In this study we evaluated GRN genetic variability in 400 MS patients, in correlation with clinical variables such as disease severity and relapse recovery. We also evaluated serum progranulin levels in the different groups of GRN variants carriers. We found that incomplete recovery after a relapse is correlated with an increased frequency of the rs9897526 A allele (odds ratio (OR) 4.367, p = 0.005). A more severe disease course (Multiple Sclerosis Severity Score > 5) is correlated with an increased frequency of the rs9897526 A allele (OR 1.886, p = 0.002) and of the rs5848 T allele (OR 1.580, p = 0.019). Carriers of the variants associated with a more severe disease course (rs9897526 A, rs5848 T) have significantly lower levels of circulating progranulin (80.5 ± 9.1 ng/mL vs. 165.7 ng/mL, p = 0.01). GRN genetic polymorphisms likely influence disease course and relapse recovery in MS. © The Author(s), 2015.

Accounting for multiple climate components when estimating climate change exposure and velocity

USGS Publications Warehouse

Nadeau, Christopher P.; Fuller, Angela K.

2015-01-01

The effect of anthropogenic climate change on organisms will likely be related to climate change exposure and velocity at local and regional scales. However, common methods to estimate climate change exposure and velocity ignore important components of climate that are known to affect the ecology and evolution of organisms.We develop a novel index of climate change (climate overlap) that simultaneously estimates changes in the means, variation and correlation between multiple weather variables. Specifically, we estimate the overlap between multivariate normal probability distributions representing historical and current or projected future climates. We provide methods for estimating the statistical significance of climate overlap values and methods to estimate velocity using climate overlap.We show that climates have changed significantly across 80% of the continental United States in the last 32 years and that much of this change is due to changes in the variation and correlation between weather variables (two statistics that are rarely incorporated into climate change studies). We also show that projected future temperatures are predicted to be locally novel (<1·5% overlap) across most of the global land surface and that exposure is likely to be highest in areas with low historical climate variation. Last, we show that accounting for changes in the variation and correlation between multiple weather variables can dramatically affect velocity estimates; mean velocity estimates in the continental United States were between 3·1 and 19·0 km yr−1when estimated using climate overlap compared to 1·4 km yr−1 when estimated using traditional methods.Our results suggest that accounting for changes in the means, variation and correlation between multiple weather variables can dramatically affect estimates of climate change exposure and velocity. These climate components are known to affect the ecology and evolution of organisms, but are ignored by most measures of climate change. We conclude with a set of future directions and recommend future work to determine which measures of climate change exposure and velocity are most related to biological responses to climate change.

An examination of predictive variables toward graduation of minority students in science at a selected urban university

NASA Astrophysics Data System (ADS)

Hunter, Evelyn M. Irving

1998-12-01

The purpose of this study was to examine the relationship and predictive power of the variables gender, high school GPA, class rank, SAT scores, ACT scores, and socioeconomic status on the graduation rates of minority college students majoring in the sciences at a selected urban university. Data was examined on these variables as they related to minority students majoring in science. The population consisted of 101 minority college students who had majored in the sciences from 1986 to 1996 at an urban university in the southwestern region of Texas. A non-probability sampling procedure was used in this study. The non-probability sampling procedure in this investigation was incidental sampling technique. A profile sheet was developed to record the information regarding the variables. The composite scores from SAT and ACT testing were used in the study. The dichotomous variables gender and socioeconomic status were dummy coded for analysis. For the gender variable, zero (0) indicated male, and one (1) indicated female. Additionally, zero (0) indicated high SES, and one (1) indicated low SES. Two parametric procedures were used to analyze the data in this investigation. They were the multiple correlation and multiple regression procedures. Multiple correlation is a statistical technique that indicates the relationship between one variable and a combination of two other variables. The variables socioeconomic status and GPA were found to contribute significantly to the graduation rates of minority students majoring in all sciences when combined with chemistry (Hypotheses Two and Four). These variables accounted for 7% and 15% of the respective variance in the graduation rates of minority students in the sciences and in chemistry. Hypotheses One and Three, the predictor variables gender, high school GPA, SAT Total Scores, class rank, and socioeconomic status did not contribute significantly to the graduation rates of minority students in biology and pharmacy.

An integrated, ethically driven environmental model of clinical decision making in emergency settings.

PubMed

Wolf, Lisa

2013-02-01

To explore the relationship between multiple variables within a model of critical thinking and moral reasoning. A quantitative descriptive correlational design using a purposive sample of 200 emergency nurses. Measured variables were accuracy in clinical decision-making, moral reasoning, perceived care environment, and demographics. Analysis was by bivariate correlation using Pearson's product-moment correlation coefficients, chi square and multiple linear regression analysis. The elements as identified in the integrated ethically-driven environmental model of clinical decision-making (IEDEM-CD) corrected depict moral reasoning and environment of care as factors significantly affecting accuracy in decision-making. The integrated, ethically driven environmental model of clinical decision making is a framework useful for predicting clinical decision making accuracy for emergency nurses in practice, with further implications in education, research and policy. A diagnostic and therapeutic framework for identifying and remediating individual and environmental challenges to accurate clinical decision making. © 2012, The Author. International Journal of Nursing Knowledge © 2012, NANDA International.

Multiple jet study data correlations. [data correlation for jet mixing flow of air jets

NASA Technical Reports Server (NTRS)

Walker, R. E.; Eberhardt, R. G.

1975-01-01

Correlations are presented which allow determination of penetration and mixing of multiple cold air jets injected normal to a ducted subsonic heated primary air stream. Correlations were obtained over jet-to-primary stream momentum flux ratios of 6 to 60 for locations from 1 to 30 jet diameters downstream of the injection plane. The range of geometric and operating variables makes the correlations relevant to gas turbine combustors. Correlations were obtained for the mixing efficiency between jets and primary stream using an energy exchange parameter. Also jet centerplane velocity and temperature trajectories were correlated and centerplane dimensionless temperature distributions defined. An assumption of a Gaussian vertical temperature distribution at all stations is shown to result in a reasonable temperature field model. Data are presented which allow comparison of predicted and measured values over the range of conditions specified above.

Latin Hypercube Sampling (LHS) UNIX Library/Standalone

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

2004-05-13

The LHS UNIX Library/Standalone software provides the capability to draw random samples from over 30 distribution types. It performs the sampling by a stratified sampling method called Latin Hypercube Sampling (LHS). Multiple distributions can be sampled simultaneously, with user-specified correlations amongst the input distributions, LHS UNIX Library/ Standalone provides a way to generate multi-variate samples. The LHS samples can be generated either as a callable library (e.g., from within the DAKOTA software framework) or as a standalone capability. LHS UNIX Library/Standalone uses the Latin Hypercube Sampling method (LHS) to generate samples. LHS is a constrained Monte Carlo sampling scheme. Inmore » LHS, the range of each variable is divided into non-overlapping intervals on the basis of equal probability. A sample is selected at random with respect to the probability density in each interval, If multiple variables are sampled simultaneously, then values obtained for each are paired in a random manner with the n values of the other variables. In some cases, the pairing is restricted to obtain specified correlations amongst the input variables. Many simulation codes have input parameters that are uncertain and can be specified by a distribution, To perform uncertainty analysis and sensitivity analysis, random values are drawn from the input parameter distributions, and the simulation is run with these values to obtain output values. If this is done repeatedly, with many input samples drawn, one can build up a distribution of the output as well as examine correlations between input and output variables.« less

The Propagation of Movement Variability in Time: A Methodological Approach for Discrete Movements with Multiple Degrees of Freedom.

PubMed

Krüger, Melanie; Straube, Andreas; Eggert, Thomas

2017-01-01

In recent years, theory-building in motor neuroscience and our understanding of the synergistic control of the redundant human motor system has significantly profited from the emergence of a range of different mathematical approaches to analyze the structure of movement variability. Approaches such as the Uncontrolled Manifold method or the Noise-Tolerance-Covariance decomposition method allow to detect and interpret changes in movement coordination due to e.g., learning, external task constraints or disease, by analyzing the structure of within-subject, inter-trial movement variability. Whereas, for cyclical movements (e.g., locomotion), mathematical approaches exist to investigate the propagation of movement variability in time (e.g., time series analysis), similar approaches are missing for discrete, goal-directed movements, such as reaching. Here, we propose canonical correlation analysis as a suitable method to analyze the propagation of within-subject variability across different time points during the execution of discrete movements. While similar analyses have already been applied for discrete movements with only one degree of freedom (DoF; e.g., Pearson's product-moment correlation), canonical correlation analysis allows to evaluate the coupling of inter-trial variability across different time points along the movement trajectory for multiple DoF-effector systems, such as the arm. The theoretical analysis is illustrated by empirical data from a study on reaching movements under normal and disturbed proprioception. The results show increased movement duration, decreased movement amplitude, as well as altered movement coordination under ischemia, which results in a reduced complexity of movement control. Movement endpoint variability is not increased under ischemia. This suggests that healthy adults are able to immediately and efficiently adjust the control of complex reaching movements to compensate for the loss of proprioceptive information. Further, it is shown that, by using canonical correlation analysis, alterations in movement coordination that indicate changes in the control strategy concerning the use of motor redundancy can be detected, which represents an important methodical advance in the context of neuromechanics.

The Impact of Selected Academic and Demographic Variables on Mathematics College Readiness Predicted by ACT

ERIC Educational Resources Information Center

Smith, Marcia

2013-01-01

The purpose of the study was to determine the degree to which academic and demographic variables affected the ACT results used in determining college readiness. This quantitative research study followed a non-experimental correlational design. A multiple regression was used to analyze archival data to determine the impact the combined Arkansas…

Diffusion-weighted magnetic resonance imaging in the characterization of testicular germ cell neoplasms: Effect of ROI methods on apparent diffusion coefficient values and interobserver variability.

PubMed

Tsili, Athina C; Ntorkou, Alexandra; Astrakas, Loukas; Xydis, Vasilis; Tsampalas, Stavros; Sofikitis, Nikolaos; Argyropoulou, Maria I

2017-04-01

To evaluate the difference in apparent diffusion coefficient (ADC) measurements at diffusion-weighted (DW) magnetic resonance imaging of differently shaped regions-of-interest (ROIs) in testicular germ cell neoplasms (TGCNS), the diagnostic ability of differently shaped ROIs in differentiating seminomas from nonseminomatous germ cell neoplasms (NSGCNs) and the interobserver variability. Thirty-three TGCNs were retrospectively evaluated. Patients underwent MR examinations, including DWI on a 1.5-T MR system. Two observers measured mean tumor ADCs using four distinct ROI methods: round, square, freehand and multiple small, round ROIs. The interclass correlation coefficient was analyzed to assess interobserver variability. Statistical analysis was used to compare mean ADC measurements among observers, methods and histologic types. All ROI methods showed excellent interobserver agreement, with excellent correlation (P<0.001). Multiple, small ROIs provided the lower mean ADC in TGCNs. Seminomas had lower mean ADC compared to NSGCNs for each ROI method (P<0.001). Round ROI proved the most accurate method in characterizing TGCNS. Interobserver variability in ADC measurement is excellent, irrespective of the ROI shape. Multiple, small round ROIs and round ROI proved the more accurate methods for ADC measurement in the characterization of TGCNs and in the differentiation between seminomas and NSGCNs, respectively. Copyright © 2017 Elsevier B.V. All rights reserved.

Weighted Fuzzy Risk Priority Number Evaluation of Turbine and Compressor Blades Considering Failure Mode Correlations

NASA Astrophysics Data System (ADS)

Gan, Luping; Li, Yan-Feng; Zhu, Shun-Peng; Yang, Yuan-Jian; Huang, Hong-Zhong

2014-06-01

Failure mode, effects and criticality analysis (FMECA) and Fault tree analysis (FTA) are powerful tools to evaluate reliability of systems. Although single failure mode issue can be efficiently addressed by traditional FMECA, multiple failure modes and component correlations in complex systems cannot be effectively evaluated. In addition, correlated variables and parameters are often assumed to be precisely known in quantitative analysis. In fact, due to the lack of information, epistemic uncertainty commonly exists in engineering design. To solve these problems, the advantages of FMECA, FTA, fuzzy theory, and Copula theory are integrated into a unified hybrid method called fuzzy probability weighted geometric mean (FPWGM) risk priority number (RPN) method. The epistemic uncertainty of risk variables and parameters are characterized by fuzzy number to obtain fuzzy weighted geometric mean (FWGM) RPN for single failure mode. Multiple failure modes are connected using minimum cut sets (MCS), and Boolean logic is used to combine fuzzy risk priority number (FRPN) of each MCS. Moreover, Copula theory is applied to analyze the correlation of multiple failure modes in order to derive the failure probabilities of each MCS. Compared to the case where dependency among multiple failure modes is not considered, the Copula modeling approach eliminates the error of reliability analysis. Furthermore, for purpose of quantitative analysis, probabilities importance weight from failure probabilities are assigned to FWGM RPN to reassess the risk priority, which generalize the definition of probability weight and FRPN, resulting in a more accurate estimation than that of the traditional models. Finally, a basic fatigue analysis case drawn from turbine and compressor blades in aeroengine is used to demonstrate the effectiveness and robustness of the presented method. The result provides some important insights on fatigue reliability analysis and risk priority assessment of structural system under failure correlations.

[Factors associated with incidence of dengue in Costa Rica].

PubMed

Mena, Nelson; Troyo, Adriana; Bonilla-Carrión, Roger; Calderón-Arguedas, Olger

2011-04-01

Determine the extent to which socioeconomic, demographic, geographic, and climate variables affected the incidence of dengue and dengue hemorrhagic fever (D/DH) in Costa Rica during the period 1999-2007. A correlational epidemiologic study was conducted that analyzed the cumulative incidence of D/DH from 1999 to 2007 and its association with different variables in the country's 81 cantons. Information was obtained from secondary sources, and the independent variables used for the analysis were selected on the basis of their representativeness in terms of sociodemographic, environmental, and health coverage factors that affect the epidemiology of D/DH. These variables were divided into four groups of indicators: demographic, socioeconomic, housing, and climate and geographical. The data were analyzed by means of simple and multiple Poisson regressions. The Costa Rican cantons with a higher incidence of D/DH were located primarily near the coast, coinciding with some of the variables studied. Temperature, altitude, and the human poverty index were the most relevant variables in explaining the incidence of D/DH, while temperature was the most significant variable in the multiple analyses. The analyses made it possible to correlate a higher incidence of D/DH with lower-altitude cantons, higher temperature, and a high human poverty index ranking. This information is relevant as a first step toward prioritizing and optimizing actions for the prevention and control of this disease.

Quantitative Assessment of Cervical Vertebral Maturation Using Cone Beam Computed Tomography in Korean Girls

PubMed Central

Byun, Bo-Ram; Kim, Yong-Il; Maki, Koutaro; Son, Woo-Sung

2015-01-01

This study was aimed to examine the correlation between skeletal maturation status and parameters from the odontoid process/body of the second vertebra and the bodies of third and fourth cervical vertebrae and simultaneously build multiple regression models to be able to estimate skeletal maturation status in Korean girls. Hand-wrist radiographs and cone beam computed tomography (CBCT) images were obtained from 74 Korean girls (6–18 years of age). CBCT-generated cervical vertebral maturation (CVM) was used to demarcate the odontoid process and the body of the second cervical vertebra, based on the dentocentral synchondrosis. Correlation coefficient analysis and multiple linear regression analysis were used for each parameter of the cervical vertebrae (P < 0.05). Forty-seven of 64 parameters from CBCT-generated CVM (independent variables) exhibited statistically significant correlations (P < 0.05). The multiple regression model with the greatest R 2 had six parameters (PH2/W2, UW2/W2, (OH+AH2)/LW2, UW3/LW3, D3, and H4/W4) as independent variables with a variance inflation factor (VIF) of <2. CBCT-generated CVM was able to include parameters from the second cervical vertebral body and odontoid process, respectively, for the multiple regression models. This suggests that quantitative analysis might be used to estimate skeletal maturation status. PMID:25878721

Maternal factors predicting cognitive and behavioral characteristics of children with fetal alcohol spectrum disorders.

PubMed

May, Philip A; Tabachnick, Barbara G; Gossage, J Phillip; Kalberg, Wendy O; Marais, Anna-Susan; Robinson, Luther K; Manning, Melanie A; Blankenship, Jason; Buckley, David; Hoyme, H Eugene; Adnams, Colleen M

2013-06-01

To provide an analysis of multiple predictors of cognitive and behavioral traits for children with fetal alcohol spectrum disorders (FASDs). Multivariate correlation techniques were used with maternal and child data from epidemiologic studies in a community in South Africa. Data on 561 first-grade children with fetal alcohol syndrome (FAS), partial FAS (PFAS), and not FASD and their mothers were analyzed by grouping 19 maternal variables into categories (physical, demographic, childbearing, and drinking) and used in structural equation models (SEMs) to assess correlates of child intelligence (verbal and nonverbal) and behavior. A first SEM using only 7 maternal alcohol use variables to predict cognitive/behavioral traits was statistically significant (B = 3.10, p < .05) but explained only 17.3% of the variance. The second model incorporated multiple maternal variables and was statistically significant explaining 55.3% of the variance. Significantly correlated with low intelligence and problem behavior were demographic (B = 3.83, p < .05) (low maternal education, low socioeconomic status [SES], and rural residence) and maternal physical characteristics (B = 2.70, p < .05) (short stature, small head circumference, and low weight). Childbearing history and alcohol use composites were not statistically significant in the final complex model and were overpowered by SES and maternal physical traits. Although other analytic techniques have amply demonstrated the negative effects of maternal drinking on intelligence and behavior, this highly controlled analysis of multiple maternal influences reveals that maternal demographics and physical traits make a significant enabling or disabling contribution to child functioning in FASD.

Serum Albumin and Disease Severity of Non-Cystic Fibrosis Bronchiectasis.

PubMed

Lee, Seung Jun; Kim, Hyo-Jung; Kim, Ju-Young; Ju, Sunmi; Lim, Sujin; Yoo, Jung Wan; Nam, Sung-Jin; Lee, Gi Dong; Cho, Hyun Seop; Kim, Rock Bum; Cho, Yu Ji; Jeong, Yi Yeong; Kim, Ho Cheol; Lee, Jong Deog

2017-08-01

A clinical classification system has been developed to define the severity and predict the prognosis of subjects with non-cystic fibrosis (CF) bronchiectasis. We aimed to identify laboratory parameters that are correlated with the bronchiectasis severity index (BSI) and FACED score. The medical records of 107 subjects with non-CF bronchiectasis for whom BSI and FACED scores could be calculated were retrospectively reviewed. The correlations between the laboratory parameters and BSI or FACED score were assessed, and multiple-linear regression analysis was performed to identify variables independently associated with BSI and FACED score. An additional subgroup analysis was performed according to sex. Among all of the enrolled subjects, 49 (45.8%) were male and 58 (54.2%) were female. The mean BSI and FACED scores were 9.43 ± 3.81 and 1.92 ± 1.59, respectively. The serum albumin level (r = -0.49), bilirubin level (r = -0.31), C-reactive protein level (r = 0.22), hemoglobin level (r = -0.2), and platelet/lymphocyte ratio (r = 0.31) were significantly correlated with BSI. Meanwhile, serum albumin (r = -0.37) and bilirubin level (r = -0.25) showed a significant correlation with the FACED score. Multiple-linear regression analysis showed that the serum bilirubin level was independently associated with BSI, and the serum albumin level was independently associated with both scoring systems. Subgroup analysis revealed that the level of uric acid was also a significant variable independently associated with the BSI in male bronchiectasis subjects. Several laboratory variables were identified as possible prognostic factors for non-CF bronchiectasis. Among them, the serum albumin level exhibited the strongest correlation and was identified as an independent variable associated with the BSI and FACED scores. Copyright © 2017 by Daedalus Enterprises.

Effect of Ankle Range of Motion (ROM) and Lower-Extremity Muscle Strength on Static Balance Control Ability in Young Adults: A Regression Analysis

PubMed Central

Kim, Seong-Gil

2018-01-01

Background The purpose of this study was to investigate the effect of ankle ROM and lower-extremity muscle strength on static balance control ability in young adults. Material/Methods This study was conducted with 65 young adults, but 10 young adults dropped out during the measurement, so 55 young adults (male: 19, female: 36) completed the study. Postural sway (length and velocity) was measured with eyes open and closed, and ankle ROM (AROM and PROM of dorsiflexion and plantarflexion) and lower-extremity muscle strength (flexor and extensor of hip, knee, and ankle joint) were measured. Pearson correlation coefficient was used to examine the correlation between variables and static balance ability. Simple linear regression analysis and multiple linear regression analysis were used to examine the effect of variables on static balance ability. Results In correlation analysis, plantarflexion ROM (AROM and PROM) and lower-extremity muscle strength (except hip extensor) were significantly correlated with postural sway (p<0.05). In simple correlation analysis, all variables that passed the correlation analysis procedure had significant influence (p<0.05). In multiple linear regression analysis, plantar flexion PROM with eyes open significantly influenced sway length (B=0.681) and sway velocity (B=0.011). Conclusions Lower-extremity muscle strength and ankle plantarflexion ROM influenced static balance control ability, with ankle plantarflexion PROM showing the greatest influence. Therefore, both contractile structures and non-contractile structures should be of interest when considering static balance control ability improvement. PMID:29760375

Effect of Ankle Range of Motion (ROM) and Lower-Extremity Muscle Strength on Static Balance Control Ability in Young Adults: A Regression Analysis.

PubMed

Kim, Seong-Gil; Kim, Wan-Soo

2018-05-15

BACKGROUND The purpose of this study was to investigate the effect of ankle ROM and lower-extremity muscle strength on static balance control ability in young adults. MATERIAL AND METHODS This study was conducted with 65 young adults, but 10 young adults dropped out during the measurement, so 55 young adults (male: 19, female: 36) completed the study. Postural sway (length and velocity) was measured with eyes open and closed, and ankle ROM (AROM and PROM of dorsiflexion and plantarflexion) and lower-extremity muscle strength (flexor and extensor of hip, knee, and ankle joint) were measured. Pearson correlation coefficient was used to examine the correlation between variables and static balance ability. Simple linear regression analysis and multiple linear regression analysis were used to examine the effect of variables on static balance ability. RESULTS In correlation analysis, plantarflexion ROM (AROM and PROM) and lower-extremity muscle strength (except hip extensor) were significantly correlated with postural sway (p<0.05). In simple correlation analysis, all variables that passed the correlation analysis procedure had significant influence (p<0.05). In multiple linear regression analysis, plantar flexion PROM with eyes open significantly influenced sway length (B=0.681) and sway velocity (B=0.011). CONCLUSIONS Lower-extremity muscle strength and ankle plantarflexion ROM influenced static balance control ability, with ankle plantarflexion PROM showing the greatest influence. Therefore, both contractile structures and non-contractile structures should be of interest when considering static balance control ability improvement.

Multicollinearity in associations between multiple environmental features and body weight and abdominal fat: using matching techniques to assess whether the associations are separable.

PubMed

Leal, Cinira; Bean, Kathy; Thomas, Frédérique; Chaix, Basile

2012-06-01

Because of the strong correlations among neighborhoods' characteristics, it is not clear whether the associations of specific environmental exposures (e.g., densities of physical features and services) with obesity can be disentangled. Using data from the RECORD (Residential Environment and Coronary Heart Disease) Cohort Study (Paris, France, 2007-2008), the authors investigated whether neighborhood characteristics related to the sociodemographic, physical, service-related, and social-interactional environments were associated with body mass index and waist circumference. The authors developed an original neighborhood characteristic-matching technique (analyses within pairs of participants similarly exposed to an environmental variable) to assess whether or not these associations could be disentangled. After adjustment for individual/neighborhood socioeconomic variables, body mass index/waist circumference was negatively associated with characteristics of the physical/service environments reflecting higher densities (e.g., proportion of built surface, densities of shops selling fruits/vegetables, and restaurants). Multiple adjustment models and the neighborhood characteristic-matching technique were unable to identify which of these neighborhood variables were driving the associations because of high correlations between the environmental variables. Overall, beyond the socioeconomic environment, the physical and service environments may be associated with weight status, but it is difficult to disentangle the effects of strongly correlated environmental dimensions, even if they imply different causal mechanisms and interventions.

An investigation of the effect of seasonal activity levels on avian censusing

Treesearch

C. John Ralph

1981-01-01

Intensive variable distance circular-plot censuses and timed activity budget data were used to compare the effects of conspicuousness upon census results. In six of ten species no correlation was found, suggesting that all birds within the "Effective Detection Distance" (EDD) were seen. In four species there were significant correlations. Multiple regression...

Systematic Review of Correlates and Determinants of Physical Activity in Persons With Multiple Sclerosis.

PubMed

Streber, René; Peters, Stefan; Pfeifer, Klaus

2016-04-01

To review the current evidence regarding correlates and determinants of physical activity (PA) in persons with multiple sclerosis (pwMS). PubMed and Scopus (1980 to January 2015) and reference lists of eligible studies. Eligible studies include adults with multiple sclerosis; have a cross-sectional or prospective observational design; or examine the effect of a theory-based intervention trial on PA, including a mediation analysis. Eligible studies also apply a quantitative assessment of PA and correlates or proposed mediators and are published in English or German language. Two reviewers independently evaluated the risk of bias, extracted data, and categorized variables according to the International Classification of Functioning, Disability and Health. Consistency and the direction of associations were evaluated with a semiquantitative approach. Fifty-six publications with data from observational studies and 2 interventional studies provided evidence for 86 different variables. Consistent correlates of PA were the disability level, walking limitations in particular, PA-related self-efficacy, self-regulation constructs, employment status, and educational level. One interventional study provided evidence for a causal relation between self-regulation and PA. However, 59 of the 86 investigated variables in observational studies are based on 1 or 2 study findings, and most results stem from cross-sectional designs. Beside the importance of the general disability level and walking limitations, the results highlight the importance of personal factors (eg, PA-related self-efficacy, self-regulatory constructs, sociodemographic factors). Limitations and implications of the current review are discussed. Research that is more rigorous is needed to better understand what affects PA in pwMS. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Novel Index (Hepatic Receptor: IHR) to Evaluate Hepatic Functional Reserve Using (99m)Tc-GSA Scintigraphy.

PubMed

Hasegawa, Daisuke; Onishi, Hideo; Matsutomo, Norikazu

2016-02-01

This study aimed to evaluate the novel index of hepatic receptor (IHR) on the regression analysis derived from time activity curve of the liver for hepatic functional reserve. Sixty patients had undergone (99m)Tc-galactosyl serum albumin ((99m)Tc-GSA) scintigraphy in the retrospective clinical study. Time activity curves for liver were obtained by region of interest (ROI) on the whole liver. A novel hepatic functional predictor was calculated with multiple regression analysis of time activity curves. In the multiple regression function, the objective variables were the indocyanine green (ICG) retention rate at 15 min, and the explanatory variables were the liver counts in 3-min intervals until end from beginning. Then, this result was defined by IHR, and we analyzed the correlation between IHR and ICG, uptake ratio of the heart at 15 minutes to that at 3 minutes (HH15), uptake ratio of the liver to the liver plus heart at 15 minutes (LHL15), and index of convexity (IOC). Regression function of IHR was derived as follows: IHR=0.025×L(6)-0.052×L(12)+0.027×L(27). The multiple regression analysis indicated that liver counts at 6 min, 12 min, and 27 min were significantly related to objective variables. The correlation coefficient between IHR and ICG was 0.774, and the correlation coefficient between ICG and conventional indices (HH15, LHL15, and IOC) were 0.837, 0.773, and 0.793, respectively. IHR had good correlation with HH15, LHL15, and IOC. The finding results suggested that IHR would provide clinical benefit for hepatic functional assessment in the (99m)Tc-GSA scintigraphy.

Multiple-input multiple-output causal strategies for gene selection.

PubMed

Bontempi, Gianluca; Haibe-Kains, Benjamin; Desmedt, Christine; Sotiriou, Christos; Quackenbush, John

2011-11-25

Traditional strategies for selecting variables in high dimensional classification problems aim to find sets of maximally relevant variables able to explain the target variations. If these techniques may be effective in generalization accuracy they often do not reveal direct causes. The latter is essentially related to the fact that high correlation (or relevance) does not imply causation. In this study, we show how to efficiently incorporate causal information into gene selection by moving from a single-input single-output to a multiple-input multiple-output setting. We show in synthetic case study that a better prioritization of causal variables can be obtained by considering a relevance score which incorporates a causal term. In addition we show, in a meta-analysis study of six publicly available breast cancer microarray datasets, that the improvement occurs also in terms of accuracy. The biological interpretation of the results confirms the potential of a causal approach to gene selection. Integrating causal information into gene selection algorithms is effective both in terms of prediction accuracy and biological interpretation.

A Link between Variability of the Semidiurnal Tide and Planetary Waves in the Opposite Hemisphere

NASA Technical Reports Server (NTRS)

Smith, Anne K.; Pancheva, Dora V.; Mitchell, Nicholas J.; Marsh, Daniel R.; Russell, James M., III; Mlynczak, Martin G.

2007-01-01

Horizontal wind observations over four years from the meteor radar at Esrange (68 deg N) are analyzed to determine the variability of the semidiurnal tide. Simultaneous global observations of temperature and geopotential from the SABER satellite instrument are used to construct time series of planetary wave amplitudes and geostrophic mean zonal wind. During NH summer and fall, the temporal variability of the semidiurnal tide at Esrange is found to be well correlated with the amplitude of planetary wavenumber 1 in the stratosphere in high southern latitudes (i.e., in the opposite hemisphere). The correlations indicate that a significant part of the tidal variations at Esrange is due to dynamical interactions in the Southern Hemisphere. Other times of the year do not indicate a corresponding robust correlation pattern for the Esrange tides over multiple years.

Concurrent generation of multivariate mixed data with variables of dissimilar types.

PubMed

Amatya, Anup; Demirtas, Hakan

2016-01-01

Data sets originating from wide range of research studies are composed of multiple variables that are correlated and of dissimilar types, primarily of count, binary/ordinal and continuous attributes. The present paper builds on the previous works on multivariate data generation and develops a framework for generating multivariate mixed data with a pre-specified correlation matrix. The generated data consist of components that are marginally count, binary, ordinal and continuous, where the count and continuous variables follow the generalized Poisson and normal distributions, respectively. The use of the generalized Poisson distribution provides a flexible mechanism which allows under- and over-dispersed count variables generally encountered in practice. A step-by-step algorithm is provided and its performance is evaluated using simulated and real-data scenarios.

Modeling chlorophyll-a and dissolved oxygen concentration in tropical floodplain lakes (Paraná River, Brazil).

PubMed

Rocha, R R A; Thomaz, S M; Carvalho, P; Gomes, L C

2009-06-01

The need for prediction is widely recognized in limnology. In this study, data from 25 lakes of the Upper Paraná River floodplain were used to build models to predict chlorophyll-a and dissolved oxygen concentrations. Akaike's information criterion (AIC) was used as a criterion for model selection. Models were validated with independent data obtained in the same lakes in 2001. Predictor variables that significantly explained chlorophyll-a concentration were pH, electrical conductivity, total seston (positive correlation) and nitrate (negative correlation). This model explained 52% of chlorophyll variability. Variables that significantly explained dissolved oxygen concentration were pH, lake area and nitrate (all positive correlations); water temperature and electrical conductivity were negatively correlated with oxygen. This model explained 54% of oxygen variability. Validation with independent data showed that both models had the potential to predict algal biomass and dissolved oxygen concentration in these lakes. These findings suggest that multiple regression models are valuable and practical tools for understanding the dynamics of ecosystems and that predictive limnology may still be considered a powerful approach in aquatic ecology.

Cognitive and Behavioural Correlates of Non-Adherence to HIV Anti-Retroviral Therapy: Theoretical and Practical Insight for Clinical Psychology and Health Psychology

ERIC Educational Resources Information Center

Begley, Kim; McLaws, Mary-Louise; Ross, Michael W.; Gold, Julian

2008-01-01

This cross-sectional study identified variables associated with protease inhibitor (PI) non-adherence in 179 patients taking anti-retroviral therapy. Univariate analyses identified 11 variables associated with PI non-adherence. Multiple logistic regression modelling identified three predictors of PI non-adherence: low adherence self-efficacy and…

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.

Total energy expenditure in adults with cerebral palsy as assessed by doubly labeled water.

PubMed

Johnson, R K; Hildreth, H G; Contompasis, S H; Goran, M I

1997-09-01

To characterize total energy expenditure (TEE) in free-living adults with cerebral palsy (CP) using the doubly labeled water technique, and to determine those physiologic variables and characteristics of CP that were markers of TEE in adults with CP. TEE was measured using the doubly labeled water technique in 30 free-living adults with CP (12 women, 18 men). To determine the best markers of TEE, the following factors were examined: CP status, resting metabolic rate (RMR), anthropometric characteristics and body composition by means of dual-energy x-ray absorptiometry (DXA) and skinfold thickness measurements, energy cost of leisure-time activities, and oral-motor impairment. Means +/- standard deviations, t tests, Pearson product-moment correlation coefficients, Spearman rank correlation coefficients, chi 2, stepwise multiple-correlation regression analysis, and analysis of covariance were used to examine the relationships among variables of interest. TEE was highly variable in the sample (mean = 2,455 +/- 622 kcal/day for men and 1,986 +/- 363 kcal/day for women). Stepwise regression analysis showed that TEE was best predicted in the sample by RMR, percentage body fat determined by DXA, ambulation status, and sex (multiple R = .68, P = .003). When practical, easily measured variables were used, TEE was best predicted by height, ambulation status, percentage body fat by skinfold thickness measurements, and sex (multiple R = .61, P. = 018). The contribution of energy expended in physical activity to TEE was significantly higher in the ambulatory subjects than the nonambulatory subjects (25% vs 16%, respectively; P = .009). The high degree of variability in TEE, largely attributable to high interindividual variation in energy expended in physical activity, makes it difficult to provide general guidelines for energy requirements for adults with CP. Because ambulation status was an important predictor of TEE, it must be accounted for in estimating energy requirements in this population.

Biomechanical, anthropometric, and psychological determinants of barbell back squat strength.

PubMed

Vigotsky, Andrew D; Bryanton, Megan A; Nuckols, Greg; Beardsley, Chris; Contreras, Bret; Evans, Jessica; Schoenfeld, Brad J

2018-02-27

Previous investigations of strength have only focused on biomechanical or psychological determinants, while ignoring the potential interplay and relative contributions of these variables. The purpose of this study was to investigate the relative contributions of biomechanical, anthropometric, and psychological variables to the prediction of maximum parallel barbell back squat strength. Twenty-one college-aged participants (male = 14; female = 7; age = 23 ± 3 years) reported to the laboratory for two visits. The first visit consisted of anthropometric, psychometric, and parallel barbell back squat one-repetition maximum (1RM) testing. On the second visit, participants performed isometric dynamometry testing for the knee, hip, and spinal extensors in a sticking point position-specific manner. Multiple linear regression and correlations were used to investigate the combined and individual relationships between biomechanical, anthropometric, and psychological variables and squat 1RM. Multiple regression revealed only one statistically predictive determinant: fat free mass normalized to height (standardized estimate ± SE = 0.6 ± 0.3; t(16) = 2.28; p = 0.037). Correlation coefficients for individual variables and squat 1RM ranged from r = -0.79-0.83, with biomechanical, anthropometric, experiential, and sex predictors showing the strongest relationships, and psychological variables displaying the weakest relationships. These data suggest that back squat strength in a heterogeneous population is multifactorial and more related to physical rather than psychological variables.

What variables can influence clinical reasoning?

PubMed

Ashoorion, Vahid; Liaghatdar, Mohammad Javad; Adibi, Peyman

2012-12-01

Clinical reasoning is one of the most important competencies that a physician should achieve. Many medical schools and licensing bodies try to predict it based on some general measures such as critical thinking, personality, and emotional intelligence. This study aimed at providing a model to design the relationship between the constructs. Sixty-nine medical students participated in this study. A battery test devised that consist four parts: Clinical reasoning measures, personality NEO inventory, Bar-On EQ inventory, and California critical thinking questionnaire. All participants completed the tests. Correlation and multiple regression analysis consumed for data analysis. There is low to moderate correlations between clinical reasoning and other variables. Emotional intelligence is the only variable that contributes clinical reasoning construct (r=0.17-0.34) (R(2) chnage = 0.46, P Value = 0.000). Although, clinical reasoning can be considered as a kind of thinking, no significant correlation detected between it and other constructs. Emotional intelligence (and its subscales) is the only variable that can be used for clinical reasoning prediction.

The Role of C-Peptide as Marker of Cardiometabolic Risk in Women With Polycystic Ovary Syndrome: A Controlled Study

PubMed Central

de Medeiros, Sebastiao Freitas; Angelo, Laura Camila Antunes; de Medeiros, Matheus Antonio Souto; Banhara, Camila Regis; Barbosa, Bruna Barcelo; Yamamoto, Marcia Marly Winck

2018-01-01

Background The aim of this study was to examine the role of C-peptide as a biological marker of cardiometabolic risk in polycystic ovary syndrome (PCOS). Methods This case-control study enrolled 385 PCOS patients and 240 normal cycling women. Anthropometric and clinical variables were taken at first visit. Fasting C-peptide, glucose, lipids, and hormone measurements were performed. Simple and multiple correlations between C-peptide and other variables associated with dysmetabolism and cardiovascular disease were examined. Results C-peptide was well correlated with several anthropometric, metabolic, and endocrine parameters. In PCOS patients, stepwise multiple regression including C-peptide as the criterion variable and other predictors of cardiovascular disease risk provided a significant model in which the fasting C-peptide/glucose ratio, glucose, body weight, and free estrogen index (FEI) were retained (adjusted R2 = 0.988, F = 7.161, P = 0.008). Conclusion C-peptide levels alone or combined with C-peptide/glucose ratio, glucose, body weight, and FEI provided a significant model to identify PCOS patients with higher risk of future cardiometabolic diseases. PMID:29416587

Personal growth, symptoms, and uncertainty in community-residing adults with heart failure.

PubMed

Overbaugh, Kristen J; Parshall, Mark B

Personal growth has not been studied extensively in heart failure (HF). To characterize personal growth in HF and its relationships with symptom burden, uncertainty, and demographic and clinical factors. Associations among personal growth, uncertainty, symptom burden, and clinical and demographic variables were examined in adult outpatients with HF using bivariate correlations and multiple regressions. Participants (N = 103; 76% male, mean age = 74 years, 97% New York Heart Association classes II and III) reported moderate levels of personal growth, uncertainty, and symptom burden. Personal growth was weakly correlated with age and symptom burden but not with other study variables. In a regression model, age, sex, ethnicity, disease severity, time since diagnosis, symptom burden, and uncertainty were not significant independent correlates of personal growth. Community-residing patients with HF report moderate personal growth that is not explained by uncertainty, symptom burden, or demographic and clinical variables. Copyright © 2016 Elsevier Inc. All rights reserved.

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables.

PubMed

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C; Downing, James R; Lamba, Jatinder

2009-08-15

In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org.

Maternal Factors Predicting Cognitive and Behavioral Characteristics of Children with Fetal Alcohol Spectrum Disorders

PubMed Central

May, Philip A.; Tabachnick, Barbara G.; Gossage, J. Phillip; Kalberg, Wendy O.; Marais, Anna-Susan; Robinson, Luther K.; Manning, Melanie A.; Blankenship, Jason; Buckley, David; Hoyme, H. Eugene; Adnams, Colleen M.

2013-01-01

Objective To provide an analysis of multiple predictors of cognitive and behavioral traits for children with fetal alcohol spectrum disorders (FASD). Method Multivariate correlation techniques were employed with maternal and child data from epidemiologic studies in a community in South Africa. Data on 561 first grade children with fetal alcohol syndrome (FAS), partial FAS (PFAS), and not FASD and their mothers were analyzed by grouping 19 maternal variables into categories (physical, demographic, childbearing, and drinking) and employed in structural equation models (SEM) to assess correlates of child intelligence (verbal and non-verbal) and behavior. Results A first SEM utilizing only seven maternal alcohol use variables to predict cognitive/behavioral traits was statistically significant (B = 3.10, p < .05), but explained only 17.3% of the variance. The second model incorporated multiple maternal variables and was statistically significant explaining 55.3% of the variance. Significantly correlated with low intelligence and problem behavior were demographic (B = 3.83, p < .05) (low maternal education, low socioeconomic status (SES), and rural residence) and maternal physical characteristics (B = 2.70, p < .05) (short stature, small head circumference, and low weight). Childbearing history and alcohol use composites were not statistically significant in the final complex model, and were overpowered by SES and maternal physical traits. Conclusions While other analytic techniques have amply demonstrated the negative effects of maternal drinking on intelligence and behavior, this highly-controlled analysis of multiple maternal influences reveals that maternal demographics and physical traits make a significant enabling or disabling contribution to child functioning in FASD. PMID:23751886

[Keys to preventing accidents in children in the school context].

PubMed

Gabari Gambarte, M Inés; Sáenz Mendía, Raquel

2016-11-02

To learn about children's perception of the causes and prevention strategies involved in school accidents. The sample included 584 school children aged 8-9 years from Navarra. A mixed design was chosen by questionnaire with three open-response questions and one multiple-choice assessment. Analysis was performed in two phases: 1) qualitative development of categories and dimensions of the responses of narrative content, and 2) quantitative variables for recoding correlational analysis. 22 categories emerged, which make up three perceptual dimensions: 1) attribution of causality (5), 2) identification of mechanisms of avoidance (11), and 3) development of coping strategies (6). The correlation intra-variables portray varying degrees: on the one hand, moderate positive numbers (r>0.5) in allocating and identifying causality avoidance mechanisms and, on the other hand, high positive correlation values (r>0.7) referred to developing coping strategies. Children are able to identify accidents as a health problem. They question the multiplicity of elements involved and relate the origin and kind of accident to prevention and support mechanisms. Copyright © 2016 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

The detection of cheating in multiple choice examinations

NASA Astrophysics Data System (ADS)

Richmond, Peter; Roehner, Bertrand M.

2015-10-01

Cheating in examinations is acknowledged by an increasing number of organizations to be widespread. We examine two different approaches to assess their effectiveness at detecting anomalous results, suggestive of collusion, using data taken from a number of multiple-choice examinations organized by the UK Radio Communication Foundation. Analysis of student pair overlaps of correct answers is shown to give results consistent with more orthodox statistical correlations for which confidence limits as opposed to the less familiar "Bonferroni method" can be used. A simulation approach is also developed which confirms the interpretation of the empirical approach. Then the variables Xi =(1 -Ui) Yi +Ui Z are a system of symmetric dependent binary variables (0 , 1 ; p) whose correlation matrix is ρij = r. The proof is easy and given in the paper. Let us add two remarks. • We used the expression "symmetric variables" to reflect the fact that all Xi play the same role. The expression "exchangeable variables" is often used with the same meaning. • The correlation matrix has only positive elements. This is of course imposed by the symmetry condition. ρ12 < 0 and ρ23 < 0 would imply ρ13 > 0, thus violating the symmetry requirement. In the following subsections we will be concerned with the question of uniqueness of the set of Xi generated above. Needless to say, it is useful to know whether the proposition gives the answer or only one among many. More precisely, the problem can be stated as follows.

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

PubMed

Graffelman, Jan; van Eeuwijk, Fred

2005-12-01

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

Community characteristics that attract physicians in Japan: a cross-sectional analysis of community demographic and economic factors.

PubMed

Matsumoto, Masatoshi; Inoue, Kazuo; Noguchi, Satomi; Toyokawa, Satoshi; Kajii, Eiji

2009-02-18

In many countries, there is a surplus of physicians in some communities and a shortage in others. Population size is known to be correlated with the number of physicians in a community, and is conventionally considered to represent the power of communities to attract physicians. However, associations between other demographic/economic variables and the number of physicians in a community have not been fully evaluated. This study seeks other parameters that correlate with the physician population and show which characteristics of a community determine its "attractiveness" to physicians. Associations between the number of physicians and selected demographic/economic/life-related variables of all of Japan's 3132 municipalities were examined. In order to exclude the confounding effect of community size, correlations between the physician-to-population ratio and other variable-to-population ratios or variable-to-area ratios were evaluated with simple correlation and multiple regression analyses. The equity of physician distribution against each variable was evaluated by the orenz curve and Gini index. Among the 21 variables selected, the service industry workers-to-population ratio (0.543), commercial land price (0.527), sales of goods per person (0.472), and daytime population density (0.451) were better correlated with the physician-to-population ratio than was population density (0.409). Multiple regression analysis showed that the service industry worker-to-population ratio, the daytime population density, and the elderly rate were each independently correlated with the physician-to-population ratio (standardized regression coefficient 0.393, 0.355, 0.089 respectively; each p<0.001). Equity of physician distribution was higher against service industry population (Gini index=0.26) and daytime population (0.28) than against population (0.33). Daytime population and service industry population in a municipality are better parameters of community attractiveness to physicians than population. Because attractiveness is supposed to consist of medical demand and the amenities of urban life, the two parameters may represent the amount of medical demand and/or the extent of urban amenities of the community more precisely than population does. The conventional demand-supply analysis based solely on population as the demand parameter may overestimate the inequity of the physician distribution among communities.

Patient activation, knowledge, and health literacy association with self-management behaviors in persons with heart failure.

PubMed

Jacobson, Ann F; Sumodi, Veronica; Albert, Nancy M; Butler, Robert S; DeJohn, Lori; Walker, Donna; Dion, Kelly; Tai, Hua-Li Lin; Ross, Donna M

2018-06-14

More evidence is needed about factors that influence self-management behaviors in persons with heart failure. To test a correlational mediation model of the independent variables of health literacy, patient activation, and heart failure knowledge with heart failure self-management behaviors. The study used a prospective, cross-sectional, correlational design. Correlation and multiple regression were used to analyze associations among variables. Of 151 participants, 57% were male, and mean age was 68 years. Heart failure self-management behaviors was positively correlated with patient activation level (p = .0008), but not with health literacy or heart failure knowledge. Persons with heart failure may better manage their condition if sufficiently activated, regardless of their level of health literacy or knowledge of heart failure disease and management processes. Copyright © 2018 Elsevier Inc. All rights reserved.

Sound System Engineering & Optimization: The effects of multiple arrivals on the intelligibility of reinforced speech

NASA Astrophysics Data System (ADS)

Ryan, Timothy James

The effects of multiple arrivals on the intelligibility of speech produced by live-sound reinforcement systems are examined. The intent is to determine if correlations exist between the manipulation of sound system optimization parameters and the subjective attribute speech intelligibility. Given the number, and wide range, of variables involved, this exploratory research project attempts to narrow the focus of further studies. Investigated variables are delay time between signals arriving from multiple elements of a loudspeaker array, array type and geometry and the two-way interactions of speech-to-noise ratio and array geometry with delay time. Intelligibility scores were obtained through subjective evaluation of binaural recordings, reproduced via headphone, using the Modified Rhyme Test. These word-score results are compared with objective measurements of Speech Transmission Index (STI). Results indicate that both variables, delay time and array geometry, have significant effects on intelligibility. Additionally, it is seen that all three of the possible two-way interactions have significant effects. Results further reveal that the STI measurement method overestimates the decrease in intelligibility due to short delay times between multiple arrivals.

Exploring correlates of diabetes-related stress among adults with Type 1 diabetes in the T1D exchange clinic registry.

PubMed

Boden, Matthew Tyler; Gala, Sasha

2018-04-01

To explore relations between diabetes-related stress and multiple sociodemographic, diabetes health, other health, and treatment-related variables among a large sample of adults with Type 1 Diabetes (T1D). The sample consisted of 10,821 adults (over 18 years old) enrolled in the T1D Exchange Clinic Registry. The T1D Exchange clinic network consists of 67 diabetes clinical centers throughout the United States selected to broadly represent pediatric and adult patients with T1D. Variables were assessed through participant self-report and extraction of clinic chart data. Univariate and multiple linear regression (with simultaneous entry of all predictors) analyses were conducted. Robustly associated with increased diabetes-related stress across analyses were multiple sociodemographic (female [vs. male], native Hawaiian/other Pacific islander [vs. white/Caucasian], decreased age and diabetes duration), diabetes health (higher HbA1c), other health (lower general health, presence of major life stress and depression, less physical activity), and treatment related variables (use of injections/pen or combination injection/pen/pump [vs. pump], use of CGM, increased frequency of missing insulin doses and BG checking, decreased frequency of BG checking prior to bolus, receipt of mental health treatment). We replicated and extended research demonstrating that diabetes-related stress among people with T1D occurs at higher levels among those with particular sociodemographic characteristics and is associated with a range poorer diabetes health and other health variables, and multiple treatment-related variables. The strong incremental prediction of diabetes-related stress by multiple variables in our study suggests that a multi-variable, personalized approach may increase the effectiveness of treatments for diabetes-related stress. Published by Elsevier B.V.

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.

Multiple GISS AGCM Hindcasts and MSU Versions of 1979-1998

NASA Technical Reports Server (NTRS)

Shah, Kathryn Pierce; Rind, David; Druyan, Leonard; Lonergan, Patrick; Chandler, Mark

1998-01-01

Multiple realizations of the 1979-1998 time period have been simulated by the Goddard Institute for Space Studies Atmospheric General Circulation Model (GISS AGCM) to explore its responsiveness to accumulated forcings, particularly over sensitive agricultural regions. A microwave radiative transfer postprocessor has produced the AGCM's lower tropospheric, tropospheric and lower stratospheric brightness temperature (Tb) time series for correlations with the various Microwave Sounding Unit (MSU) time series available. MSU maps of monthly means and anomalies were also used to assess the AGCM's mean annual cycle and regional variability. Seven realizations by the AGCM were forced by observed sea surface temperatures (sst) through 1992 to gather rough standard deviations associated with internal model variability. Subsequent runs hindcast January 1979 through April 1998 with an accumulation of forcings: observed ssts, greenhouse gases, stratospheric volcanic aerosols. stratospheric and tropospheric ozone and tropospheric sulfate and black carbon aerosols. The goal of narrowing gaps between AGCM and MSU time series was complicated by MSU time series, by Tb simulation concerns and by unforced climatic variability in the AGCM and in the real world. Lower stratospheric Tb correlations between the AGCM and MSU for 1979-1998 reached as high as 0.91 +/-0.16 globally with sst, greenhouse gases, volcanic aerosol, stratospheric ozone forcings and tropospheric aerosols. Mid-tropospheric Tb correlations reached as high as 0.66 +/-.04 globally and 0.84 +/-.02 in the tropics. Oceanic lower tropospheric Tb correlations similarly reached 0.61 +/-.06 globally and 0.79 +/-.02 in the tropics. Of the sensitive agricultural areas considered, Nordeste in northeastern Brazil was simulated best with mid-tropospheric Tb correlations up to 0.75 +/- .03. The two other agricultural regions, in Africa and in the northern mid-latitudes, suffered from higher levels of non-sst variability. Zimbabwe had a maximum mid-tropospheric correlation of 0.54 +/- 0.11 while the U.S. Cornbelt had only 0.25 +/- .10. Precipitation and surface temperature performance are also examined over these regions. Correlations of MSU and AGCM time series mostly improved with addition of explicit atmospheric forcings in zonal bands but not in agricultural regional bins each encompassing only six AGCM gridcells.

[Long-term outcome following multiple trauma in working age : A prospective study in a Swiss trauma center].

PubMed

Gross, T; Amsler, F

2016-11-01

Given the lack of data in the available literature, we were interested in the disability rate and corresponding insurance costs following multiple trauma in Switzerland. The possible impact of demographic, traumatic and hospital process factors as well as subjective and objective longer-term outcome variables on insurance data acquired were examined. Following multiple trauma the clinical and socioeconomic parameters in 145 survivors of working age were investigated over 2 and 4 years post-injury at a Swiss trauma center (University Hospital Basel). The correlation with the corresponding data provided by the largest Swiss accident insurance company (Suva, n = 63) was tested by univariate and multivariate analysis and patients insured at Suva were compared with those insured elsewhere (n = 82). The mean level of disability in this cohort of multiple trauma patients insured at Suva was 43 %. The insurer expected costs of more than 1 million Swiss Francs per multiply injured patient. In univariate analysis, only discrete correlations (maximum r = 0.37) were found with resulting disability, but significant correlations were found in subsequent multivariate testing most of all for age and the sequential organ failure assessment (SOFA 11 % and 15 % predictive capacity, p = 0.001; corrected R 2  = 0.26). Among variables of longer-term outcome the Euro Quality of Life Group health-related quality of life in five dimensions (EQ-5D) correlated almost as highly with the objective extent of disability as did the reduced capacity to work declared by the patients (0.64 and 0.7, respectively). The estimation of long-term disability following multiple trauma based on primary data following injury appears to be possible only to a limited extent. Given the clinical and socioeconomic relevance, comparable analyses are necessary by including all insurance providers involved.

A multiple deficit model of reading disability and attention-deficit/hyperactivity disorder: searching for shared cognitive deficits.

PubMed

McGrath, Lauren M; Pennington, Bruce F; Shanahan, Michelle A; Santerre-Lemmon, Laura E; Barnard, Holly D; Willcutt, Erik G; Defries, John C; Olson, Richard K

2011-05-01

This study tests a multiple cognitive deficit model of reading disability (RD), attention-deficit/hyperactivity disorder (ADHD), and their comorbidity. A structural equation model (SEM) of multiple cognitive risk factors and symptom outcome variables was constructed. The model included phonological awareness as a unique predictor of RD and response inhibition as a unique predictor of ADHD. Processing speed, naming speed, and verbal working memory were modeled as potential shared cognitive deficits. Model fit indices from the SEM indicated satisfactory fit. Closer inspection of the path weights revealed that processing speed was the only cognitive variable with significant unique relationships to RD and ADHD dimensions, particularly inattention. Moreover, the significant correlation between reading and inattention was reduced to non-significance when processing speed was included in the model, suggesting that processing speed primarily accounted for the phenotypic correlation (or comorbidity) between reading and inattention. This study illustrates the power of a multiple deficit approach to complex developmental disorders and psychopathologies, particularly for exploring comorbidities. The theoretical role of processing speed in the developmental pathways of RD and ADHD and directions for future research are discussed. © 2010 The Authors. Journal of Child Psychology and Psychiatry © 2010 Association for Child and Adolescent Mental Health.

Clinical Variables Correlated with Numbers of Intra-arterial Nimodipine Infusion in Patients with Medically Refractory Cerebral Vasospasm

PubMed Central

Kim, Sang-Young; Kim, Ki-Hong; Cho, Jae-Hoon

2015-01-01

Objective The objective of this study was to find out the clinical variables correlated with repeated intra-arterial (IA) nimodipine infusions in patients with medically refractory cerebral vasospasm (CV) following subarachnoid hemorrhage (SAH). Materials and Methods During the 36 months between January 2011 and December 2013, 275 patients were treated at our institute for SAH due to a ruptured intracranial aneurysm. Of the 275 patients, 26 patients (9.5%) met the inclusion criteria. For each patient, a retrospective review of their medical records was conducted. Results Eleven patients underwent a single IA nimodipine infusion and 15 patients underwent more than two IA nimodipine infusions. Multiple IA nimodipine infusion patients had poor improvement (2 of 15 patients, 13.3%) in Glasgow coma scale (GCS) scores after the first IA nimodipine infusion compared to patients of single IA nimodipine infusion (6 of 11 patients, 54.6%) (p = 0.038). The mean middle cerebral artery (MCA) Lindegaard ratio of multiple IA nimodipine infusion patients was 4.3 ± 1.1 after the first IA nimodipine infusion (p = 0.039). In multiple IA nimodipine infusion patients, CV occurred more often bilaterally (p = 0.035) and distally (p = 0.001). More vessel segments were affected in multiple IA nimodipine infusion patients (3.1 ± 1.0) (p < 0.001). Conclusion The following factors correlated with multiple IA nimodipine infusions: 1) no improvement in GCS after the IA nimodipine infusion; 2) no decrease of MCA velocity on transcranial doppler over 50 cm/s or Lindegaard ratio over 4.3 after the IA nimodipine infusion; 3) distal, bilateral, or diffuse involvement of CV. PMID:26523251

Learning style and concept acquisition of community college students in introductory biology

NASA Astrophysics Data System (ADS)

Bobick, Sandra Burin

This study investigated the influence of learning style on concept acquisition within a sample of community college students in a general biology course. There are two subproblems within the larger problem: (1) the influence of demographic variables (age, gender, number of college credits, prior exposure to scientific information) on learning style, and (2) the correlations between prior scientific knowledge, learning style and student understanding of the concept of the gene. The sample included all students enrolled in an introductory general biology course during two consecutive semesters at an urban community college. Initial data was gathered during the first week of the semester, at which time students filled in a short questionnaire (age, gender, number of college credits, prior exposure to science information either through reading/visual sources or a prior biology course). Subjects were then given the Inventory of Learning Processes-Revised (ILP-R) which measures general preferences in five learning styles; Deep Learning; Elaborative Learning, Agentic Learning, Methodical Learning and Literal Memorization. Subjects were then given the Gene Conceptual Knowledge pretest: a 15 question objective section and an essay section. Subjects were exposed to specific concepts during lecture and laboratory exercises. At the last lab, students were given the Genetics Conceptual Knowledge Posttest. Pretest/posttest gains were correlated with demographic variables and learning styles were analyzed for significant correlations. Learning styles, as the independent variable in a simultaneous multiple regression, were significant predictors of results on the gene assessment tests, including pretest, posttest and gain. Of the learning styles, Deep Learning accounted for the greatest positive predictive value of pretest essay and pretest objective results. Literal Memorization was a significant negative predictor for posttest essay, essay gain and objective gain. Simultaneous multiple regression indicated that demographic variables were significant positive predictors for Methodical, Deep and Elaborative Learning Styles. Stepwise multiple regression resulted in number of credits, Read Science and gender (female) as significant predictors of learning styles. The findings of this study emphasize the importance of learning styles in conceptual understanding of the gene and the correlation of nonformal exposure to science information with learning style and conceptual understanding.

Relationships between reef fish communities and remotely sensed rugosity measurements in Biscayne National Park, Florida, USA

USGS Publications Warehouse

Kuffner, Ilsa B.; Brock, John C.; Grober-Dunsmore, Rikki; Bonito, Victor E.; Hickey, T. Donald; Wright, C. Wayne

2007-01-01

The realization that coral reef ecosystem management must occur across multiple spatial scales and habitat types has led scientists and resource managers to seek variables that are easily measured over large areas and correlate well with reef resources. Here we investigate the utility of new technology in airborne laser surveying (NASA Experimental Advanced Airborne Research Lidar (EAARL)) in assessing topographical complexity (rugosity) to predict reef fish community structure on shallow (n = 10–13 per reef). Rugosity at each station was assessed in situ by divers using the traditional chain-transect method (10-m scale), and remotely using the EAARL submarine topography data at multiple spatial scales (2, 5, and 10 m). The rugosity and biological datasets were analyzed together to elucidate the predictive power of EAARL rugosity in describing the variance in reef fish community variables and to assess the correlation between chain-transect and EAARL rugosity. EAARL rugosity was not well correlated with chain-transect rugosity, or with species richness of fishes (although statistically significant, the amount of variance explained by the model was very low). Variance in reef fish community attributes was better explained in reef-by-reef variability than by physical variables. However, once the reef-by-reef variability was taken into account in a two-way analysis of variance, the importance of rugosity could be seen on individual reefs. Fish species richness and abundance were statistically higher at high rugosity stations compared to medium and low rugosity stations, as predicted by prior ecological research. The EAARL shows promise as an important mapping tool for reef resource managers as they strive to inventory and protect coral reef resources.

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables

PubMed Central

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R.; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C.; Downing, James R.; Lamba, Jatinder

2009-01-01

Motivation: In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Results: Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Availability: Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org. Contact: stanley.pounds@stjude.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19528086

Testing Group Mean Differences of Latent Variables in Multilevel Data Using Multiple-Group Multilevel CFA and Multilevel MIMIC Modeling.

PubMed

Kim, Eun Sook; Cao, Chunhua

2015-01-01

Considering that group comparisons are common in social science, we examined two latent group mean testing methods when groups of interest were either at the between or within level of multilevel data: multiple-group multilevel confirmatory factor analysis (MG ML CFA) and multilevel multiple-indicators multiple-causes modeling (ML MIMIC). The performance of these methods were investigated through three Monte Carlo studies. In Studies 1 and 2, either factor variances or residual variances were manipulated to be heterogeneous between groups. In Study 3, which focused on within-level multiple-group analysis, six different model specifications were considered depending on how to model the intra-class group correlation (i.e., correlation between random effect factors for groups within cluster). The results of simulations generally supported the adequacy of MG ML CFA and ML MIMIC for multiple-group analysis with multilevel data. The two methods did not show any notable difference in the latent group mean testing across three studies. Finally, a demonstration with real data and guidelines in selecting an appropriate approach to multilevel multiple-group analysis are provided.

The Relationship Between Gratitude and Loneliness: The Potential Benefits of Gratitude for Promoting Social Bonds.

PubMed

Caputo, Andrea

2015-05-01

This paper explores the potential role of gratitude on the reduction of loneliness feelings, even controlling for several variables related to social desirability, well-being (subjective happiness and life satisfaction) and socio-demographic characteristics. Through a web-based survey a convenience sample of 197 participants completed an online questionnaire including these measures. Correlation analyses and four-step hierarchical multiple regression analyses were conducted. The results show a negative correlation between gratitude and loneliness; specifically, gratitude succeeds in accounting for up to almost one-fifth of the total variability of loneliness even controlling for further variables. Being female, not having a stable and consolidated relationship and not participating in the labor force represent some risk factors affecting loneliness which should be taken into account in further research.

The Relationship Between Gratitude and Loneliness: The Potential Benefits of Gratitude for Promoting Social Bonds

PubMed Central

Caputo, Andrea

2015-01-01

This paper explores the potential role of gratitude on the reduction of loneliness feelings, even controlling for several variables related to social desirability, well-being (subjective happiness and life satisfaction) and socio-demographic characteristics. Through a web-based survey a convenience sample of 197 participants completed an online questionnaire including these measures. Correlation analyses and four-step hierarchical multiple regression analyses were conducted. The results show a negative correlation between gratitude and loneliness; specifically, gratitude succeeds in accounting for up to almost one-fifth of the total variability of loneliness even controlling for further variables. Being female, not having a stable and consolidated relationship and not participating in the labor force represent some risk factors affecting loneliness which should be taken into account in further research. PMID:27247660

Methodology to develop crash modification functions for road safety treatments with fully specified and hierarchical models.

PubMed

Chen, Yongsheng; Persaud, Bhagwant

2014-09-01

Crash modification factors (CMFs) for road safety treatments are developed as multiplicative factors that are used to reflect the expected changes in safety performance associated with changes in highway design and/or the traffic control features. However, current CMFs have methodological drawbacks. For example, variability with application circumstance is not well understood, and, as important, correlation is not addressed when several CMFs are applied multiplicatively. These issues can be addressed by developing safety performance functions (SPFs) with components of crash modification functions (CM-Functions), an approach that includes all CMF related variables, along with others, while capturing quantitative and other effects of factors and accounting for cross-factor correlations. CM-Functions can capture the safety impact of factors through a continuous and quantitative approach, avoiding the problematic categorical analysis that is often used to capture CMF variability. There are two formulations to develop such SPFs with CM-Function components - fully specified models and hierarchical models. Based on sample datasets from two Canadian cities, both approaches are investigated in this paper. While both model formulations yielded promising results and reasonable CM-Functions, the hierarchical model was found to be more suitable in retaining homogeneity of first-level SPFs, while addressing CM-Functions in sub-level modeling. In addition, hierarchical models better capture the correlations between different impact factors. Copyright © 2014 Elsevier Ltd. All rights reserved.

Improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis.

PubMed

Tam, Roger C; Traboulsee, Anthony; Riddehough, Andrew; Li, David K B

2012-01-01

The change in T 1-hypointense lesion ("black hole") volume is an important marker of pathological progression in multiple sclerosis (MS). Black hole boundaries often have low contrast and are difficult to determine accurately and most (semi-)automated segmentation methods first compute the T 2-hyperintense lesions, which are a superset of the black holes and are typically more distinct, to form a search space for the T 1w lesions. Two main potential sources of measurement noise in longitudinal black hole volume computation are partial volume and variability in the T 2w lesion segmentation. A paired analysis approach is proposed herein that uses registration to equalize partial volume and lesion mask processing to combine T 2w lesion segmentations across time. The scans of 247 MS patients are used to compare a selected black hole computation method with an enhanced version incorporating paired analysis, using rank correlation to a clinical variable (MS functional composite) as the primary outcome measure. The comparison is done at nine different levels of intensity as a previous study suggests that darker black holes may yield stronger correlations. The results demonstrate that paired analysis can strongly improve longitudinal correlation (from -0.148 to -0.303 in this sample) and may produce segmentations that are more sensitive to clinically relevant changes.

Estimation of Causal Mediation Effects for a Dichotomous Outcome in Multiple-Mediator Models using the Mediation Formula

PubMed Central

Nelson, Suchitra; Albert, Jeffrey M.

2013-01-01

Mediators are intermediate variables in the causal pathway between an exposure and an outcome. Mediation analysis investigates the extent to which exposure effects occur through these variables, thus revealing causal mechanisms. In this paper, we consider the estimation of the mediation effect when the outcome is binary and multiple mediators of different types exist. We give a precise definition of the total mediation effect as well as decomposed mediation effects through individual or sets of mediators using the potential outcomes framework. We formulate a model of joint distribution (probit-normal) using continuous latent variables for any binary mediators to account for correlations among multiple mediators. A mediation formula approach is proposed to estimate the total mediation effect and decomposed mediation effects based on this parametric model. Estimation of mediation effects through individual or subsets of mediators requires an assumption involving the joint distribution of multiple counterfactuals. We conduct a simulation study that demonstrates low bias of mediation effect estimators for two-mediator models with various combinations of mediator types. The results also show that the power to detect a non-zero total mediation effect increases as the correlation coefficient between two mediators increases, while power for individual mediation effects reaches a maximum when the mediators are uncorrelated. We illustrate our approach by applying it to a retrospective cohort study of dental caries in adolescents with low and high socioeconomic status. Sensitivity analysis is performed to assess the robustness of conclusions regarding mediation effects when the assumption of no unmeasured mediator-outcome confounders is violated. PMID:23650048

Estimation of causal mediation effects for a dichotomous outcome in multiple-mediator models using the mediation formula.

PubMed

Wang, Wei; Nelson, Suchitra; Albert, Jeffrey M

2013-10-30

Mediators are intermediate variables in the causal pathway between an exposure and an outcome. Mediation analysis investigates the extent to which exposure effects occur through these variables, thus revealing causal mechanisms. In this paper, we consider the estimation of the mediation effect when the outcome is binary and multiple mediators of different types exist. We give a precise definition of the total mediation effect as well as decomposed mediation effects through individual or sets of mediators using the potential outcomes framework. We formulate a model of joint distribution (probit-normal) using continuous latent variables for any binary mediators to account for correlations among multiple mediators. A mediation formula approach is proposed to estimate the total mediation effect and decomposed mediation effects based on this parametric model. Estimation of mediation effects through individual or subsets of mediators requires an assumption involving the joint distribution of multiple counterfactuals. We conduct a simulation study that demonstrates low bias of mediation effect estimators for two-mediator models with various combinations of mediator types. The results also show that the power to detect a nonzero total mediation effect increases as the correlation coefficient between two mediators increases, whereas power for individual mediation effects reaches a maximum when the mediators are uncorrelated. We illustrate our approach by applying it to a retrospective cohort study of dental caries in adolescents with low and high socioeconomic status. Sensitivity analysis is performed to assess the robustness of conclusions regarding mediation effects when the assumption of no unmeasured mediator-outcome confounders is violated. Copyright © 2013 John Wiley & Sons, Ltd.

The predictors of chemistry achievement of 12th grade students in secondary schools in the United Arab Emirates

NASA Astrophysics Data System (ADS)

Khalaf, Ali Khalfan

2000-10-01

The purpose of this study is to explore variables related to chemistry achievement of 12th grade science students in the United Arab Emirates (UAE). The focus is to identify student, teacher, and school variables that predict chemistry achievement. The analysis sample included 204 males and 252 females in 66 classes in 60 schools from 10 districts or bureaus of education in the UAE. Thirty-two male and 33 female chemistry teachers and 60 school principals were included. The Khalaf Chemistry Achievement Test, GALT, the Student Questionnaire, Teacher Questionnaire, and School Information Questionnaire were administered. Descriptive statistics, correlations, analyses of variance, factor analysis, and stepwise multiple linear regression analyses were done. The results indicate that demographic, home environment, prior knowledge, scholastic ability, attitudes and perceptions related to chemistry and science, and student perception of instructional practices variables correlated with student chemistry achievement. The amount of help teachers received from the supervisor, class size, and courses in geology were teacher variables that correlated with class chemistry achievement. Nine school variables involving school, division, and class sizes correlated with school chemistry achievement. Analyses of variance revealed significant interaction effects: district by school size and district by student gender. In two districts, students in small schools achieved better than those in large schools. Generally female students achieved equal to or better than males. Three factors from the factor analysis: School Size, Prior Student Achievement, and Student Perception of Teacher Effectiveness, correlated with school chemistry achievement. The results of the multiple linear regression indicated that the factors of Prior Student Achievement, Student Perception of Teacher Effectiveness, and Teacher Experience and Expertise accounted for 45% of the variance in school chemistry achievement. Results indicate that the strongest predictors of chemistry achievement are prior achievement in science, Arabic language, and mathematics; student perception of teacher effectiveness; and teacher experience and expertise. Females tend to achieve better in chemistry than males. No nationality differences were found and the relationship of school size to chemistry achievement was inconclusive. Recommendations related to chemistry and science are presented. These include curriculum, school practice, teacher professional development, and future research.

What variables can influence clinical reasoning?

PubMed Central

Ashoorion, Vahid; Liaghatdar, Mohammad Javad; Adibi, Peyman

2012-01-01

Background: Clinical reasoning is one of the most important competencies that a physician should achieve. Many medical schools and licensing bodies try to predict it based on some general measures such as critical thinking, personality, and emotional intelligence. This study aimed at providing a model to design the relationship between the constructs. Materials and Methods: Sixty-nine medical students participated in this study. A battery test devised that consist four parts: Clinical reasoning measures, personality NEO inventory, Bar-On EQ inventory, and California critical thinking questionnaire. All participants completed the tests. Correlation and multiple regression analysis consumed for data analysis. Results: There is low to moderate correlations between clinical reasoning and other variables. Emotional intelligence is the only variable that contributes clinical reasoning construct (r=0.17-0.34) (R2 chnage = 0.46, P Value = 0.000). Conclusion: Although, clinical reasoning can be considered as a kind of thinking, no significant correlation detected between it and other constructs. Emotional intelligence (and its subscales) is the only variable that can be used for clinical reasoning prediction. PMID:23853636

A quantitative study of factors influencing quality of life in rural Mexican women diagnosed with HIV.

PubMed

Holtz, Carol; Sowell, Richard; VanBrackle, Lewis; Velasquez, Gabriela; Hernandez-Alonso, Virginia

2014-01-01

This quantitative study explored the level of Quality of Life (QoL) in indigenous Mexican women and identified psychosocial factors that significantly influenced their QoL, using face-to-face interviews with 101 women accessing care in an HIV clinic in Oaxaca, Mexico. Variables included demographic characteristics, levels of depression, coping style, family functioning, HIV-related beliefs, and QoL. Descriptive statistics were used to analyze participant characteristics, and women's scores on data collection instruments. Pearson's R correlational statistics were used to determine the level of significance between study variables. Multiple regression analysis examined all variables that were significantly related to QoL. Pearson's correlational analysis of relationships between Spirituality, Educating Self about HIV, Family Functioning, Emotional Support, Physical Care, and Staying Positive demonstrated positive correlation to QoL. Stigma, depression, and avoidance coping were significantly and negatively associated with QoL. The final regression model indicated that depression and avoidance coping were the best predictor variables for QoL. Copyright © 2014 Association of Nurses in AIDS Care. Published by Elsevier Inc. All rights reserved.

Predictive ability of a comprehensive incremental test in mountain bike marathon.

PubMed

Ahrend, Marc-Daniel; Schneeweiss, Patrick; Martus, Peter; Niess, Andreas M; Krauss, Inga

2018-01-01

Traditional performance tests in mountain bike marathon (XCM) primarily quantify aerobic metabolism and may not describe the relevant capacities in XCM. We aimed to validate a comprehensive test protocol quantifying its intermittent demands. Forty-nine athletes (38.8±9.1 years; 38 male; 11 female) performed a laboratory performance test, including an incremental test, to determine individual anaerobic threshold (IAT), peak power output (PPO) and three maximal efforts (10 s all-out sprint, 1 min maximal effort and 5 min maximal effort). Within 2 weeks, the athletes participated in one of three XCM races (n=15, n=9 and n=25). Correlations between test variables and race times were calculated separately. In addition, multiple regression models of the predictive value of laboratory outcomes were calculated for race 3 and across all races (z-transformed data). All variables were correlated with race times 1, 2 and 3: 10 s all-out sprint (r=-0.72; r=-0.59; r=-0.61), 1 min maximal effort (r=-0.85; r=-0.84; r=-0.82), 5 min maximal effort (r=-0.57; r=-0.85; r=-0.76), PPO (r=-0.77; r=-0.73; r=-0.76) and IAT (r=-0.71; r=-0.67; r=-0.68). The best-fitting multiple regression models for race 3 (r 2 =0.868) and across all races (r 2 =0.757) comprised 1 min maximal effort, IAT and body weight. Aerobic and intermittent variables correlated least strongly with race times. Their use in a multiple regression model confirmed additional explanatory power to predict XCM performance. These findings underline the usefulness of the comprehensive incremental test to predict performance in that sport more precisely.

Comparison of Penalty Functions for Sparse Canonical Correlation Analysis

PubMed Central

Chalise, Prabhakar; Fridley, Brooke L.

2011-01-01

Canonical correlation analysis (CCA) is a widely used multivariate method for assessing the association between two sets of variables. However, when the number of variables far exceeds the number of subjects, such in the case of large-scale genomic studies, the traditional CCA method is not appropriate. In addition, when the variables are highly correlated the sample covariance matrices become unstable or undefined. To overcome these two issues, sparse canonical correlation analysis (SCCA) for multiple data sets has been proposed using a Lasso type of penalty. However, these methods do not have direct control over sparsity of solution. An additional step that uses Bayesian Information Criterion (BIC) has also been suggested to further filter out unimportant features. In this paper, a comparison of four penalty functions (Lasso, Elastic-net, SCAD and Hard-threshold) for SCCA with and without the BIC filtering step have been carried out using both real and simulated genotypic and mRNA expression data. This study indicates that the SCAD penalty with BIC filter would be a preferable penalty function for application of SCCA to genomic data. PMID:21984855

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

PubMed

Cleophas, Ton J

2016-01-01

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

Automated Real-Time Behavioral and Physiological Data Acquisition and Display Integrated with Stimulus Presentation for fMRI

PubMed Central

Voyvodic, James T.; Glover, Gary H.; Greve, Douglas; Gadde, Syam

2011-01-01

Functional magnetic resonance imaging (fMRI) is based on correlating blood oxygen-level dependent (BOLD) signal fluctuations in the brain with other time-varying signals. Although the most common reference for correlation is the timing of a behavioral task performed during the scan, many other behavioral and physiological variables can also influence fMRI signals. Variations in cardiac and respiratory functions in particular are known to contribute significant BOLD signal fluctuations. Variables such as skin conduction, eye movements, and other measures that may be relevant to task performance can also be correlated with BOLD signals and can therefore be used in image analysis to differentiate multiple components in complex brain activity signals. Combining real-time recording and data management of multiple behavioral and physiological signals in a way that can be routinely used with any task stimulus paradigm is a non-trivial software design problem. Here we discuss software methods that allow users control of paradigm-specific audio–visual or other task stimuli combined with automated simultaneous recording of multi-channel behavioral and physiological response variables, all synchronized with sub-millisecond temporal accuracy. We also discuss the implementation and importance of real-time display feedback to ensure data quality of all recorded variables. Finally, we discuss standards and formats for storage of temporal covariate data and its integration into fMRI image analysis. These neuroinformatics methods have been adopted for behavioral task control at all sites in the Functional Biomedical Informatics Research Network (FBIRN) multi-center fMRI study. PMID:22232596

Empirical predictive models of daily relativistic electron flux at geostationary orbit: Multiple regression analysis

DOE PAGES

Simms, Laura E.; Engebretson, Mark J.; Pilipenko, Viacheslav; ...

2016-04-07

The daily maximum relativistic electron flux at geostationary orbit can be predicted well with a set of daily averaged predictor variables including previous day's flux, seed electron flux, solar wind velocity and number density, AE index, IMF Bz, Dst, and ULF and VLF wave power. As predictor variables are intercorrelated, we used multiple regression analyses to determine which are the most predictive of flux when other variables are controlled. Empirical models produced from regressions of flux on measured predictors from 1 day previous were reasonably effective at predicting novel observations. Adding previous flux to the parameter set improves the predictionmore » of the peak of the increases but delays its anticipation of an event. Previous day's solar wind number density and velocity, AE index, and ULF wave activity are the most significant explanatory variables; however, the AE index, measuring substorm processes, shows a negative correlation with flux when other parameters are controlled. This may be due to the triggering of electromagnetic ion cyclotron waves by substorms that cause electron precipitation. VLF waves show lower, but significant, influence. The combined effect of ULF and VLF waves shows a synergistic interaction, where each increases the influence of the other on flux enhancement. Correlations between observations and predictions for this 1 day lag model ranged from 0.71 to 0.89 (average: 0.78). Furthermore, a path analysis of correlations between predictors suggests that solar wind and IMF parameters affect flux through intermediate processes such as ring current ( Dst), AE, and wave activity.« less

Empirical predictive models of daily relativistic electron flux at geostationary orbit: Multiple regression analysis

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

Simms, Laura E.; Engebretson, Mark J.; Pilipenko, Viacheslav

The daily maximum relativistic electron flux at geostationary orbit can be predicted well with a set of daily averaged predictor variables including previous day's flux, seed electron flux, solar wind velocity and number density, AE index, IMF Bz, Dst, and ULF and VLF wave power. As predictor variables are intercorrelated, we used multiple regression analyses to determine which are the most predictive of flux when other variables are controlled. Empirical models produced from regressions of flux on measured predictors from 1 day previous were reasonably effective at predicting novel observations. Adding previous flux to the parameter set improves the predictionmore » of the peak of the increases but delays its anticipation of an event. Previous day's solar wind number density and velocity, AE index, and ULF wave activity are the most significant explanatory variables; however, the AE index, measuring substorm processes, shows a negative correlation with flux when other parameters are controlled. This may be due to the triggering of electromagnetic ion cyclotron waves by substorms that cause electron precipitation. VLF waves show lower, but significant, influence. The combined effect of ULF and VLF waves shows a synergistic interaction, where each increases the influence of the other on flux enhancement. Correlations between observations and predictions for this 1 day lag model ranged from 0.71 to 0.89 (average: 0.78). Furthermore, a path analysis of correlations between predictors suggests that solar wind and IMF parameters affect flux through intermediate processes such as ring current ( Dst), AE, and wave activity.« less

The gait standard deviation, a single measure of kinematic variability.

PubMed

Sangeux, Morgan; Passmore, Elyse; Graham, H Kerr; Tirosh, Oren

2016-05-01

Measurement of gait kinematic variability provides relevant clinical information in certain conditions affecting the neuromotor control of movement. In this article, we present a measure of overall gait kinematic variability, GaitSD, based on combination of waveforms' standard deviation. The waveform standard deviation is the common numerator in established indices of variability such as Kadaba's coefficient of multiple correlation or Winter's waveform coefficient of variation. Gait data were collected on typically developing children aged 6-17 years. Large number of strides was captured for each child, average 45 (SD: 11) for kinematics and 19 (SD: 5) for kinetics. We used a bootstrap procedure to determine the precision of GaitSD as a function of the number of strides processed. We compared the within-subject, stride-to-stride, variability with the, between-subject, variability of the normative pattern. Finally, we investigated the correlation between age and gait kinematic, kinetic and spatio-temporal variability. In typically developing children, the relative precision of GaitSD was 10% as soon as 6 strides were captured. As a comparison, spatio-temporal parameters required 30 strides to reach the same relative precision. The ratio stride-to-stride divided by normative pattern variability was smaller in kinematic variables (the smallest for pelvic tilt, 28%) than in kinetic and spatio-temporal variables (the largest for normalised stride length, 95%). GaitSD had a strong, negative correlation with age. We show that gait consistency may stabilise only at, or after, skeletal maturity. Copyright © 2016 Elsevier B.V. All rights reserved.

Lower extremity kinematics during walking and elliptical training in individuals with and without traumatic brain injury.

PubMed

Buster, Thad; Burnfield, Judith; Taylor, Adam P; Stergiou, Nicholas

2013-12-01

Elliptical training may be an option for practicing walking-like activity for individuals with traumatic brain injuries (TBI). Understanding similarities and differences between participants with TBI and neurologically healthy individuals during elliptical trainer use and walking may help guide clinical applications incorporating elliptical trainers. Ten participants with TBI and a comparison group of 10 neurologically healthy participants underwent 2 familiarization sessions and 1 data collection session. Kinematic data were collected as participants walked on a treadmill or on an elliptical trainer. Gait-related measures, including coefficient of multiple correlations (a measure of similarity between ensemble joint movement profiles; coefficient of multiple correlations [CMCs]), critical event joint angles, variability of peak critical event joint angles (standard deviations [SDs]) of peak critical event joint angles, and maximum Lyapunov exponents (a measure of the organization of the variability [LyEs]) were compared between groups and conditions. Coefficient of multiple correlations values comparing the similarity in ensemble motion profiles between the TBI and comparison participants exceeded 0.85 for the hip, knee, and ankle joints. The only critical event joint angle that differed significantly between participants with TBI and comparison participants was the ankle during terminal stance. Variability was higher for the TBI group (6 of 11 comparisons significant) compared with comparison participants. Hip and knee joint movement patterns of both participants with TBI and comparison participants on the elliptical trainer were similar to walking (CMCs ≥ 0.87). Variability was higher during elliptical trainer usage compared with walking (5 of 11 comparisons significant). Hip LyEs were higher during treadmill walking. Ankle LyEs were greater during elliptical trainer usage. Movement patterns of participants with TBI were similar to, but more variable than, those of comparison participants while using both the treadmill and the elliptical trainer. If incorporation of complex movements similar to walking is a goal of rehabilitation, elliptical training is a reasonable alternative to treadmill-based training.Video Abstract available (see Video, Supplemental Digital Content 1, http://links.lww.com/JNPT/A65) for more insights from the authors.

Female homicide in Rio Grande do Sul, Brazil.

PubMed

Leites, Gabriela Tomedi; Meneghel, Stela Nazareth; Hirakata, Vania Noemi

2014-01-01

This study aimed to assess the female homicide rate due to aggression in Rio Grande do Sul, Brazil, using this as a "proxy" of femicide. This was an ecological study which correlated the female homicide rate due to aggression in Rio Grande do Sul, according to the 35 microregions defined by the Brazilian Institute of Geography and Statistics (IBGE), with socioeconomic and demographic variables access and health indicators. Pearson's correlation test was performed with the selected variables. After this, multiple linear regressions were performed with variables with p < 0.20. The standardized average of female homicide rate due to aggression in the period from 2003 to 2007 was 3.1 obits per 100 thousand. After multiple regression analysis, the final model included male mortality due to aggression (p = 0.016), the percentage of hospital admissions for alcohol (p = 0.005) and the proportion of ill-defined deaths (p = 0.015). The model have an explanatory power of 39% (adjusted r2 = 0.391). The results are consistent with other studies and indicate a strong relationship between structural violence in society and violence against women, in addition to a higher incidence of female deaths in places with high alcohol hospitalization.

Relapse May Serve as a Mediator Variable in Longitudinal Outcomes in Multiple Sclerosis.

PubMed

Stone, Lael Anne; Cutter, Gary Raymond; Fisher, Elizabeth; Richert, Nancy; McCartin, Jennifer; Ohayon, Joan; Bash, Craig; McFarland, Henry

2016-05-01

Contrast-enhancing lesions (CEL) on magnetic resonance imaging (MRI) are believed to represent inflammatory disease activity in multiple sclerosis (MS), but their relationship to subsequent long-term disability and progression is unclear, particularly at longer time periods such as 8-10 years. Between 1989 and 1994, 111 MS patients were seen at the National Institutes of Health for clinical evaluations and 3 monthly contrast-enhanced MRI scans. Of these, 94 patients were re-evaluated a mean of 8 years later (range 6.1-10.5 years) with a single MRI scan and clinical evaluation. CEL number and volume were determined at baseline and follow-up. The number of relapses was ascertained over the follow-up period and annualized relapse rates were calculated. Other MRI parameters, such as T2 hyperintensity volume, T1 volume, and brain parenchymal fraction, were also calculated. While there was no direct correlation between CEL number or volume at baseline and disability status at follow-up, CEL measures at baseline did correlate with number of relapses observed in the subsequent years, and the number of relapses in turn correlated with subsequent disability as well as transition to progressive MS. While number and volume of CEL at baseline do not directly correlate with disability in the longer term in MS, our data suggest that 1 route to disability involves relapses as a mediator variable in the causal sequence of MS progression from CEL to disability. Further studies using relapse as a mediator variable in a larger data set may be warranted. Copyright © 2015 by the American Society of Neuroimaging.

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

USGS Publications Warehouse

Dembkowski, Daniel J.; Miranda, Leandro E.

2014-01-01

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

A latent variable approach to study gene-environment interactions in the presence of multiple correlated exposures.

PubMed

Sánchez, Brisa N; Kang, Shan; Mukherjee, Bhramar

2012-06-01

Many existing cohort studies initially designed to investigate disease risk as a function of environmental exposures have collected genomic data in recent years with the objective of testing for gene-environment interaction (G × E) effects. In environmental epidemiology, interest in G × E arises primarily after a significant effect of the environmental exposure has been documented. Cohort studies often collect rich exposure data; as a result, assessing G × E effects in the presence of multiple exposure markers further increases the burden of multiple testing, an issue already present in both genetic and environment health studies. Latent variable (LV) models have been used in environmental epidemiology to reduce dimensionality of the exposure data, gain power by reducing multiplicity issues via condensing exposure data, and avoid collinearity problems due to presence of multiple correlated exposures. We extend the LV framework to characterize gene-environment interaction in presence of multiple correlated exposures and genotype categories. Further, similar to what has been done in case-control G × E studies, we use the assumption of gene-environment (G-E) independence to boost the power of tests for interaction. The consequences of making this assumption, or the issue of how to explicitly model G-E association has not been previously investigated in LV models. We postulate a hierarchy of assumptions about the LV model regarding the different forms of G-E dependence and show that making such assumptions may influence inferential results on the G, E, and G × E parameters. We implement a class of shrinkage estimators to data adaptively trade-off between the most restrictive to most flexible form of G-E dependence assumption and note that such class of compromise estimators can serve as a benchmark of model adequacy in LV models. We demonstrate the methods with an example from the Early Life Exposures in Mexico City to Neuro-Toxicants Study of lead exposure, iron metabolism genes, and birth weight. © 2011, The International Biometric Society.

Integrated Central-Autonomic Multifractal Complexity in the Heart Rate Variability of Healthy Humans

PubMed Central

Lin, D. C.; Sharif, A.

2012-01-01

Purpose of Study: The aim of this study was to characterize the central-autonomic interaction underlying the multifractality in heart rate variability (HRV) of healthy humans. Materials and Methods: Eleven young healthy subjects participated in two separate ~40 min experimental sessions, one in supine (SUP) and one in, head-up-tilt (HUT), upright (UPR) body positions. Surface scalp electroencephalography (EEG) and electrocardiogram (ECG) were collected and fractal correlation of brain and heart rate data was analyzed based on the idea of relative multifractality. The fractal correlation was further examined with the EEG, HRV spectral measures using linear regression of two variables and principal component analysis (PCA) to find clues for the physiological processing underlying the central influence in fractal HRV. Results: We report evidence of a central-autonomic fractal correlation (CAFC) where the HRV multifractal complexity varies significantly with the fractal correlation between the heart rate and brain data (P = 0.003). The linear regression shows significant correlation between CAFC measure and EEG Beta band spectral component (P = 0.01 for SUP and P = 0.002 for UPR positions). There is significant correlation between CAFC measure and HRV LF component in the SUP position (P = 0.04), whereas the correlation with the HRV HF component approaches significance (P = 0.07). The correlation between CAFC measure and HRV spectral measures in the UPR position is weak. The PCA results confirm these findings and further imply multiple physiological processes underlying CAFC, highlighting the importance of the EEG Alpha, Beta band, and the HRV LF, HF spectral measures in the supine position. Discussion and Conclusion: The findings of this work can be summarized into three points: (i) Similar fractal characteristics exist in the brain and heart rate fluctuation and the change toward stronger fractal correlation implies the change toward more complex HRV multifractality. (ii) CAFC is likely contributed by multiple physiological mechanisms, with its central elements mainly derived from the EEG Alpha, Beta band dynamics. (iii) The CAFC in SUP and UPR positions is qualitatively different, with a more predominant central influence in the fractal HRV of the UPR position. PMID:22403548

College Tuition and Perceptions of Private University Quality

ERIC Educational Resources Information Center

Tang, Thomas Li-Ping; Tang, David Shin-Hsiung; Tang, Cindy Shin-Yi

2004-01-01

This research employs institutional characteristics and market-related factors to predict undergraduate students' tuition at 190 private colleges and universities in the USA. Results showed that the strongest correlations among variables for college tuition were reputation ranking and SAT scores. Results of a hierarchical multiple regression…

Partial Least Square Analyses of Landscape and Surface Water Biota Associations in the Savannah River Basin

EPA Science Inventory

Ecologists are often faced with problem of small sample size, correlated and large number of predictors, and high noise-to-signal relationships. This necessitates excluding important variables from the model when applying standard multiple or multivariate regression analyses. In ...

Ridge: a computer program for calculating ridge regression estimates

Treesearch

Donald E. Hilt; Donald W. Seegrist

1977-01-01

Least-squares coefficients for multiple-regression models may be unstable when the independent variables are highly correlated. Ridge regression is a biased estimation procedure that produces stable estimates of the coefficients. Ridge regression is discussed, and a computer program for calculating the ridge coefficients is presented.

[Upper extremity kinetics and energy expenditure during walker-assisted gait in children with cerebral palsy].

PubMed

Konop, Katherine A; Strifling, Kelly M B; Wang, Mei; Cao, Kevin; Eastwood, Daniel; Jackson, Scott; Ackman, Jeffrey; Altiok, Haluk; Schwab, Jeffrey; Harris, Gerald F

2009-01-01

We evaluated the relationships between upper extremity (UE) kinetics and the energy expenditure index during anterior and posterior walker-assisted gait in children with spastic diplegic cerebral palsy (CP). Ten children (3 boys, 7 girls; mean age 12.1 years; range 8 to 18 years) with spastic diplegic CP, who ambulated with a walker underwent gait analyses that included UE kinematics and kinetics. Upper extremity kinetics were obtained using instrumented walker handles. Energy expenditure index was obtained using the heart rate method (EEIHR) by subtracting resting heart rate from walking heart rate, and dividing by the walking speed. Correlations were sought between the kinetic variables and the EEIHR and temporal and stride parameters. In general, anterior walker use was associated with a higher EEIHR. Several kinetic variables correlated well with temporal and stride parameters, as well as the EEIHR. All of the significant correlations (r>0.80; p<0.005) occurred during anterior walker use and involved joint reaction forces (JRF) rather than moments. Some variables showed multiple strong correlations during anterior walker use, including the medial JRF in the wrist, the posterior JRF in the elbow, and the inferior and superior JRFs in the shoulder. The observed correlations may indicate a relationship between the force used to advance the body forward within the walker frame and an increased EEIHR. More work is needed to refine the correlations, and to explore relationships with other variables, including the joint kinematics.

Workplace support, discrimination, and person-organization fit: tests of the theory of work adjustment with LGB individuals.

PubMed

Velez, Brandon L; Moradi, Bonnie

2012-07-01

The present study explored the links of 2 workplace contextual variables--perceptions of workplace heterosexist discrimination and lesbian, gay, and bisexual (LGB)-supportive climates--with job satisfaction and turnover intentions in a sample of LGB employees. An extension of the theory of work adjustment (TWA) was used as the conceptual framework for the study; as such, perceived person-organization (P-O) fit was tested as a mediator of the relations between the workplace contextual variables and job outcomes. Data were analyzed from 326 LGB employees. Zero-order correlations indicated that perceptions of workplace heterosexist discrimination and LGB-supportive climates were correlated in expected directions with P-O fit, job satisfaction, and turnover intentions. Structural equation modeling (SEM) was used to compare multiple alternative measurement models evaluating the discriminant validity of the 2 workplace contextual variables relative to one another, and the 3 TWA job variables relative to one another; SEM was also used to test the hypothesized mediation model. Comparisons of multiple alternative measurement models supported the construct distinctiveness of the variables of interest. The test of the hypothesized structural model revealed that only LGB-supportive climates (and not workplace heterosexist discrimination) had a unique direct positive link with P-O fit and, through the mediating role of P-O fit, had significant indirect positive and negative relations with job satisfaction and turnover intentions, respectively. Moreover, P-O fit had a significant indirect negative link with turnover intentions through job satisfaction.

Predicting punching acceleration from selected strength and power variables in elite karate athletes: a multiple regression analysis.

PubMed

Loturco, Irineu; Artioli, Guilherme Giannini; Kobal, Ronaldo; Gil, Saulo; Franchini, Emerson

2014-07-01

This study investigated the relationship between punching acceleration and selected strength and power variables in 19 professional karate athletes from the Brazilian National Team (9 men and 10 women; age, 23 ± 3 years; height, 1.71 ± 0.09 m; and body mass [BM], 67.34 ± 13.44 kg). Punching acceleration was assessed under 4 different conditions in a randomized order: (a) fixed distance aiming to attain maximum speed (FS), (b) fixed distance aiming to attain maximum impact (FI), (c) self-selected distance aiming to attain maximum speed, and (d) self-selected distance aiming to attain maximum impact. The selected strength and power variables were as follows: maximal dynamic strength in bench press and squat-machine, squat and countermovement jump height, mean propulsive power in bench throw and jump squat, and mean propulsive velocity in jump squat with 40% of BM. Upper- and lower-body power and maximal dynamic strength variables were positively correlated to punch acceleration in all conditions. Multiple regression analysis also revealed predictive variables: relative mean propulsive power in squat jump (W·kg-1), and maximal dynamic strength 1 repetition maximum in both bench press and squat-machine exercises. An impact-oriented instruction and a self-selected distance to start the movement seem to be crucial to reach the highest acceleration during punching execution. This investigation, while demonstrating strong correlations between punching acceleration and strength-power variables, also provides important information for coaches, especially for designing better training strategies to improve punching speed.

Motor control differs for increasing and releasing force

PubMed Central

Park, Seoung Hoon; Kwon, MinHyuk; Solis, Danielle; Lodha, Neha

2016-01-01

Control of the motor output depends on our ability to precisely increase and release force. However, the influence of aging on force increase and release remains unknown. The purpose of this study, therefore, was to determine whether force control differs while increasing and releasing force in young and older adults. Sixteen young adults (22.5 ± 4 yr, 8 females) and 16 older adults (75.7 ± 6.4 yr, 8 females) increased and released force at a constant rate (10% maximum voluntary contraction force/s) during an ankle dorsiflexion isometric task. We recorded the force output and multiple motor unit activity from the tibialis anterior (TA) muscle and quantified the following outcomes: 1) variability of force using the SD of force; 2) mean discharge rate and variability of discharge rate of multiple motor units; and 3) power spectrum of the multiple motor units from 0–4, 4–10, 10–35, and 35–60 Hz. Participants exhibited greater force variability while releasing force, independent of age (P < 0.001). Increased force variability during force release was associated with decreased modulation of multiple motor units from 35 to 60 Hz (R2 = 0.38). Modulation of multiple motor units from 35 to 60 Hz was further correlated to the change in mean discharge rate of multiple motor units (r = 0.66) and modulation from 0 to 4 Hz (r = −0.64). In conclusion, these findings suggest that force control is altered while releasing due to an altered modulation of the motor units. PMID:26961104

Multiscale power analysis for heart rate variability

NASA Astrophysics Data System (ADS)

Zeng, Peng; Liu, Hongxing; Ni, Huangjing; Zhou, Jing; Xia, Lan; Ning, Xinbao

2015-06-01

We first introduce multiscale power (MSP) method to assess the power distribution of physiological signals on multiple time scales. Simulation on synthetic data and experiments on heart rate variability (HRV) are tested to support the approach. Results show that both physical and psychological changes influence power distribution significantly. A quantitative parameter, termed power difference (PD), is introduced to evaluate the degree of power distribution alteration. We find that dynamical correlation of HRV will be destroyed completely when PD>0.7.

White Blood Cells, Neutrophils, and Reactive Oxygen Metabolites among Asymptomatic Subjects.

PubMed

Kotani, Kazuhiko; Sakane, Naoki

2012-06-01

Chronic inflammation and oxidative stress are associated with health and the disease status. The objective of the present study was to investigate the association among white blood cell (WBC) counts, neutrophil counts as a WBC subpopulation, and diacron reactive oxygen metabolites (d-ROMs) levels in an asymptomatic population. The clinical data, including general cardiovascular risk variables and high-sensitivity C-reactive protein (hs-CRP), were collected from 100 female subjects (mean age, 62 years) in outpatient clinics. The correlation of the d-ROMs with hs-CRP, WBC, and neutrophil counts was examined. The mean/median levels were WBC counts 5.9 × 10(9)/L, neutrophil counts 3.6 × 10(9)/L, hs-CRP 0.06 mg/dL, and d-ROMs 359 CURR U. A simple correlation analysis showed a significant positive correlation of the d-ROMs with the WBC counts, neutrophil counts, or hs-CRP levels. The correlation between d-ROMs and neutrophil counts (β = 0.22, P < 0.05), as well as that between d-ROMs and hs-CRP (β = 0.28, P < 0.01), remained significant and independent in a multiple linear regression analysis adjusted for other variables. A multiple linear regression analysis showed that WBC counts had only a positive correlation tendency to the d-ROMs. Neutrophils may be slightly but more involved in the oxidative stress status, as assessed by d-ROMs, in comparison to the overall WBC. Further studies are needed to clarify the biologic mechanism(s) of the observed relationship.

[Final clinical indications and etiology in 1,023 enucleations. Descriptive databank evaluation with SPSS software in variable response mode with dummy variables].

PubMed

Becker, H; Bialasiewicz, A A; Schaudig, U; Schäfer, H; von Domarus, D

2002-05-01

A new data bank developed for ophthalmopathology using a computer-generated, multidigital data code is expected to be able to accomplish complex clinicopathologic correlations of diagnoses and signs, as provided by (multiple) clinical events and histopathologically proven etiologies, and to facilitate the documentation of new data. In the ophthalmopathology laboratory 2890 eyes were examined between January 20, 1975 and December 12, 1996. The main diagnoses and patient data from this 22-year period were recorded. To facilitate the presentation of data, a 10-year period with eyes of 976 patients enucleated from December, 1986 to December, 1996 was chosen. Principal and secondary diagnoses served for establishing the data bank. The frequencies of successive histologic and clinical diagnoses were evaluated by a descriptive computing program using an SPSS-multi-response mode with dummy variables and a categorical variable listing of the software (SPSS version 10.0) classified as (a) non-filtered random, (b) filtered by multiple etiologies, and (c) filtered by multiple events. The principal groups (e.g., histologic diagnoses concerning etiology) and subgroups (e.g., trauma, neoplasia, surgery, systemic diseases, and inflammations) were defined and correlated with 798 separate diagnoses. From 11 diagnoses/events ascribed to the clinical cases, 11,198 namings resulted. Thus, a comparative study of complex etiologies and events leading to enucleation in different hospitals of a specific area may be performed using this electronic ophthalmopathologic data bank system. The complexity of rare disease and integration into a superimposed structure can be managed with this custom-made data bank. A chronologically and demographically oriented consideration of reasons for enucleation is thus feasible.

Variable criteria sequential stopping rule: Validity and power with repeated measures ANOVA, multiple correlation, MANOVA and relation to Chi-square distribution.

PubMed

Fitts, Douglas A

2017-09-21

The variable criteria sequential stopping rule (vcSSR) is an efficient way to add sample size to planned ANOVA tests while holding the observed rate of Type I errors, α o , constant. The only difference from regular null hypothesis testing is that criteria for stopping the experiment are obtained from a table based on the desired power, rate of Type I errors, and beginning sample size. The vcSSR was developed using between-subjects ANOVAs, but it should work with p values from any type of F test. In the present study, the α o remained constant at the nominal level when using the previously published table of criteria with repeated measures designs with various numbers of treatments per subject, Type I error rates, values of ρ, and four different sample size models. New power curves allow researchers to select the optimal sample size model for a repeated measures experiment. The criteria held α o constant either when used with a multiple correlation that varied the sample size model and the number of predictor variables, or when used with MANOVA with multiple groups and two levels of a within-subject variable at various levels of ρ. Although not recommended for use with χ 2 tests such as the Friedman rank ANOVA test, the vcSSR produces predictable results based on the relation between F and χ 2 . Together, the data confirm the view that the vcSSR can be used to control Type I errors during sequential sampling with any t- or F-statistic rather than being restricted to certain ANOVA designs.

Langevin dynamics for vector variables driven by multiplicative white noise: A functional formalism

NASA Astrophysics Data System (ADS)

Moreno, Miguel Vera; Arenas, Zochil González; Barci, Daniel G.

2015-04-01

We discuss general multidimensional stochastic processes driven by a system of Langevin equations with multiplicative white noise. In particular, we address the problem of how time reversal diffusion processes are affected by the variety of conventions available to deal with stochastic integrals. We present a functional formalism to build up the generating functional of correlation functions without any type of discretization of the Langevin equations at any intermediate step. The generating functional is characterized by a functional integration over two sets of commuting variables, as well as Grassmann variables. In this representation, time reversal transformation became a linear transformation in the extended variables, simplifying in this way the complexity introduced by the mixture of prescriptions and the associated calculus rules. The stochastic calculus is codified in our formalism in the structure of the Grassmann algebra. We study some examples such as higher order derivative Langevin equations and the functional representation of the micromagnetic stochastic Landau-Lifshitz-Gilbert equation.

Spruce Budworm Fecundity and Foliar Chemistry: Influence of Site

Treesearch

M.D.C. Schmitt; M.M. Czapowskyj; D.C.  Allen; E.H.  White

1983-01-01

Two Maine spruce-fir stands having different soils were sampled to determine the relationship between spruce budworm weight (fecundity) and foliage quality. Although much of the variation in budworm weight was attributable to other factors, significant correlations between budworm weight and multiple foliar nutrient concentration variables suggest that foliage quality...

Psychosocial and demographic predictors of fruit, juice and vegetable consumption among 11-14-year-old Boy Scouts

USDA-ARS?s Scientific Manuscript database

Psychosocial and demographic correlates of fruit, juice, and vegetable (FJV) consumption were investigated to guide how to increase FJV intake. Experimental design consisted of hierarchical multiple regression analysis of FJV consumption on demographics and psychosocial variables. Subjects were boys...

Environmental factors affecting understory diversity in second-growth deciduous forests

Treesearch

Cynthia D. Huebner; J.C. Randolph; G.R. Parker

1995-01-01

The purpose of this study was to determine the most important nonanthropogenic factors affecting understory (herbs, shrubs and low-growing vines) diversity in forested landscapes of southern Indiana. Fourteen environmental variables were measured for 46 sites. Multiple regression analysis showed significant positive correlation between understory diversity and tree...

Correlation and simple linear regression.

PubMed

Eberly, Lynn E

2007-01-01

This chapter highlights important steps in using correlation and simple linear regression to address scientific questions about the association of two continuous variables with each other. These steps include estimation and inference, assessing model fit, the connection between regression and ANOVA, and study design. Examples in microbiology are used throughout. This chapter provides a framework that is helpful in understanding more complex statistical techniques, such as multiple linear regression, linear mixed effects models, logistic regression, and proportional hazards regression.

Stress and the multiple-role woman: taking a closer look at the "superwoman".

PubMed

Sumra, Monika K; Schillaci, Michael A

2015-01-01

In the academic literature there is debate as to whether women who engage in multiple social roles experience more or less stress than women in fewer roles. For the present research we examined the relationship between levels of engagement in seven distinct roles and perceived stress and life satisfaction in a small non-random sample of women in North America (N = 308). We did not find a significant correlation between role engagement and perceived stress, though we did find a small but significant positive correlation between role engagement and life satisfaction. Similarly, in a subset of the participants (N = 31), there was not a significant relationship between the level of role engagement and physiological stress as measured by hair or urinary cortisol levels. We found a significant negative correlation between perceived stress and life satisfaction, and role satisfaction. The results from multiple regression models did not identify the level of role engagement as a significant predictor of either perceived stress or life satisfaction. Role satisfaction in addition to several life style variables such as the frequency of sex and exercise were identified as significant predictors of both outcome variables. We also examined the popularized notion of the "superwoman", which we defined as women who fell within the 4th quartile of role engagement, or those engaged in the wife/mother/worker/homemaker role combination. Based on popular discourses surrounding the superwoman we expected that superwomen would exhibit higher levels of perceived stress. Our results revealed that superwomen do not experience a significantly higher level of perceived stress than non-superwomen. The results of our study therefore suggest that multiple role engagement in women, even at a relatively high level as experienced by "superwomen", is not associated with significantly higher stress, or reduced life satisfaction.

Inter-individual cognitive variability in children with Asperger's syndrome

PubMed Central

Gonzalez-Gadea, Maria Luz; Tripicchio, Paula; Rattazzi, Alexia; Baez, Sandra; Marino, Julian; Roca, Maria; Manes, Facundo; Ibanez, Agustin

2014-01-01

Multiple studies have tried to establish the distinctive profile of individuals with Asperger's syndrome (AS). However, recent reports suggest that adults with AS feature heterogeneous cognitive profiles. The present study explores inter-individual variability in children with AS through group comparison and multiple case series analysis. All participants completed an extended battery including measures of fluid and crystallized intelligence, executive functions, theory of mind, and classical neuropsychological tests. Significant group differences were found in theory of mind and other domains related to global information processing. However, the AS group showed high inter-individual variability (both sub- and supra-normal performance) on most cognitive tasks. Furthermore, high fluid intelligence correlated with less general cognitive impairment, high cognitive flexibility, and speed of motor processing. In light of these findings, we propose that children with AS are characterized by a distinct, uneven pattern of cognitive strengths and weaknesses. PMID:25132817

Spiritual Well-Being and Its Relationship with Mindfulness, Self-Compassion and Satisfaction with Life in Baccalaureate Nursing Students: A Correlation Study.

PubMed

Mathad, Monali D; Rajesh, S K; Pradhan, Balaram

2017-12-06

The present study aimed to explore the correlates and predictors of spiritual well-being among nursing students. One hundred and forty-five BSc nursing students were recruited from three nursing colleges in Bangalore, Karnataka, India. Data were collected using SHALOM, FMI, SCS-SF and SWLS questionnaires and analysed by the Pearson correlation test and multiple regression analysis. The results of our study revealed a significant correlation between variables, and a considerable amount of variance was explained by self-compassion, mindfulness and satisfaction with life on personal, communal, environmental and transcendental domains of spiritual well-being.

Development and validation of the neck dissection impairment index: a quality of life measure.

PubMed

Taylor, Rodney J; Chepeha, Judith C; Teknos, Theodoros N; Bradford, Carol R; Sharma, Pramod K; Terrell, Jeffrey E; Hogikyan, Norman D; Wolf, Gregory T; Chepeha, Douglas B

2002-01-01

To validate a health-related quality-of-life (QOL) instrument for patients following neck dissection and to identify the factors that affect QOL following neck dissection. Cross-sectional validation study. The outpatient clinic of a tertiary care cancer center. Convenience sample of 54 patients previously treated for head and neck cancer who underwent a selective neck dissection or modified radical neck dissection (64 total neck dissections). Patients had a minimum postoperative convalescence of 11 months. Thirty-two underwent accessory nerve-sparing modified radical neck dissection, and 32 underwent selective neck dissection. A 10-item, self-report instrument, the Neck Dissection Impairment Index (NDII), was developed and validated. Reliability was evaluated with test-retest correlation and internal consistency using the Cronbach alpha coefficient. Convergent validity was assessed using the 36-Item Short-Form Health Survey (SF-36) and the Constant Shoulder Scale, a shoulder function test. Multiple variable regression was used to determine variables that most affected QOL following neck dissection The 10-item NDII test-retest correlation was 0.91 (P<.001) with an internal consistency Cronbach alpha coefficient of.95. The NDII correlated with the Constant Shoulder Scale (r = 0.85, P<.001) and with the SF-36 physical functioning (r = 0.50, P<.001) and role-physical functioning (r = 0.60, P<.001) domains. Using multiple variable regression, the variables that contributed most to QOL score were patient's age and weight, radiation treatment, and neck dissection type. The NDII is a valid, reliable instrument for assessing neck dissection impairment. Patient's age, weight, radiation treatment, and neck dissection type were important factors that affect QOL following neck dissection.

Correlation of USMLE Step 1 scores with performance on dermatology in-training examinations.

PubMed

Fening, Katherine; Vander Horst, Anthony; Zirwas, Matthew

2011-01-01

Although United States Medical Licensing Examination (USMLE) Step 1 was not designed to predict resident performance, scores are used to compare residency applicants. Multiple studies have displayed a significant correlation among Step 1 scores, in-training examination (ITE) scores, and board passage, although no such studies have been performed in dermatology. The purpose of this study is to determine if this correlation exists in dermatology, and how much of the variability in ITE scores is a result of differences in Step 1 scores. This study also seeks to determine if it is appropriate to individualize expectations for resident ITE performance. This project received institutional review board exemption. From 5 dermatology residency programs (86 residents), we collected Step 1 and ITE scores for each of the 3 years of dermatology residency, and recorded passage/failure on boards. Bivariate Pearson correlation analysis was used to assess correlation between USMLE and ITE scores. Ordinary least squares regression was computed to determine how much USMLE scores contribute to ITE variability. USMLE and ITE score correlations were highly significant (P < .001). Correlation coefficients with USMLE were: 0.467, 0.541, and 0.527 for ITE in years 1, 2, and 3, respectively. Variability in ITE scores caused by differences in USMLE scores were: ITE first-year residency = 21.8%, ITE second-year residency = 29.3%, and ITE third-year residency = 27.8%. This study had a relatively small sample size, with data from only 5 programs. There is a moderate correlation between USMLE and ITE scores, with USMLE scores explaining ∼26% of the variability in ITE scores. Copyright © 2009 American Academy of Dermatology, Inc. Published by Mosby, Inc. All rights reserved.

Dietary intake of nutrients and its correlation with fatigue in multiple sclerosis patients

PubMed Central

Bitarafan, Sama; Harirchian, Mohammad-Hossein; Nafissi, Shahriar; Sahraian, Mohammad-Ali; Togha, Mansoureh; Siassi, Fereydoun; Saedisomeolia, Ahmad; Alipour, Elham; Mohammadpour, Nakisa; Chamary, Maryam; Honarvar, Niyaz Mohammadzadeh

2014-01-01

Background The role of nutrition in the progression of multiple sclerosis (MS) and related complications such as fatigue has been reported by several studies. The aim of this study is the assessment of nutritional status and its relationship with fatigue in multiple sclerosis patients. Methods This is a cross-sectional study, in which 101 relapsing-remitting MS patients were enrolled. The fatigue status was determined using the validated Persian version of of the Modified Fatigue Impact Scale (MFIS). Dietary intake was assessed using a 3-day food record questionnaire and compared to dietary reference intake (DRI) values. Association between variables was determined using Pearson Correlation Coefficient. Results In the preset study, 25 men and 76 women (total = 101) were enrolled. Analysis of dietary intake showed that daily intake of vitamin D, folate, calcium, and magnesium were significantly lower than DRI in all of patients. In men, zinc intake was significantly lower than DRI; while, in women, iron was significantly below the DRI level. After adjusting for energy, MFIS and its physical subscale were highly correlated with intake of folate and magnesium. Conclusion Our findings support that lower magnesium and folate diets are correlated with higher fatigue scores in MS patients. PMID:24800044

Correlating Solar Wind Modulation with Ionospheric Variability at Mars from MEX and MAVEN Observations

NASA Astrophysics Data System (ADS)

Kopf, A. J.; Morgan, D. D.; Halekas, J. S.; Ruhunusiri, S.; Gurnett, D. A.; Connerney, J. E. P.

2017-12-01

The synthesis of observations by the Mars Express and Mars Atmosphere and Volatiles Evolution (MAVEN) spacecraft allows for a unique opportunity to study variability in the Martian ionosphere from multiple perspectives. One major source for this variability is the solar wind. Due to its elliptical orbit which precesses over time, MAVEN periodically spends part of its orbit outside the Martian bow shock, allowing for direct measurements of the solar wind impacting the Martian plasma environment. When the Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) instrument aboard Mars Express is simultaneously sounding the ionosphere, the influence from changes in the solar wind can be observed. Previous studies have suggested a positive correlation, connecting ionospheric density to the solar wind proton flux, but depended on Earth-based measurements for solar wind conditions. More recently, research has indicated that observations of ionospheric variability from these two spacecraft can be connected in special cases, such as shock wave impacts or specific solar wind magnetic field orientations. Here we extend this to more general solar wind conditions and examine how changes in the solar wind properties measured by MAVEN instruments correlate with ionospheric structure and dynamics observed simultaneously in MARSIS remote and local measurements.

On measures of association among genetic variables

PubMed Central

Gianola, Daniel; Manfredi, Eduardo; Simianer, Henner

2012-01-01

Summary Systems involving many variables are important in population and quantitative genetics, for example, in multi-trait prediction of breeding values and in exploration of multi-locus associations. We studied departures of the joint distribution of sets of genetic variables from independence. New measures of association based on notions of statistical distance between distributions are presented. These are more general than correlations, which are pairwise measures, and lack a clear interpretation beyond the bivariate normal distribution. Our measures are based on logarithmic (Kullback-Leibler) and on relative ‘distances’ between distributions. Indexes of association are developed and illustrated for quantitative genetics settings in which the joint distribution of the variables is either multivariate normal or multivariate-t, and we show how the indexes can be used to study linkage disequilibrium in a two-locus system with multiple alleles and present applications to systems of correlated beta distributions. Two multivariate beta and multivariate beta-binomial processes are examined, and new distributions are introduced: the GMS-Sarmanov multivariate beta and its beta-binomial counterpart. PMID:22742500

Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time

PubMed Central

Zhang, Yeqing; Wang, Meiling; Li, Yafeng

2018-01-01

For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90–94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7–5.6% per millisecond, with most satellites acquired successfully. PMID:29495301

Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time.

PubMed

Zhang, Yeqing; Wang, Meiling; Li, Yafeng

2018-02-24

For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90-94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7-5.6% per millisecond, with most satellites acquired successfully.

Improving Prediction Accuracy for WSN Data Reduction by Applying Multivariate Spatio-Temporal Correlation

PubMed Central

Carvalho, Carlos; Gomes, Danielo G.; Agoulmine, Nazim; de Souza, José Neuman

2011-01-01

This paper proposes a method based on multivariate spatial and temporal correlation to improve prediction accuracy in data reduction for Wireless Sensor Networks (WSN). Prediction of data not sent to the sink node is a technique used to save energy in WSNs by reducing the amount of data traffic. However, it may not be very accurate. Simulations were made involving simple linear regression and multiple linear regression functions to assess the performance of the proposed method. The results show a higher correlation between gathered inputs when compared to time, which is an independent variable widely used for prediction and forecasting. Prediction accuracy is lower when simple linear regression is used, whereas multiple linear regression is the most accurate one. In addition to that, our proposal outperforms some current solutions by about 50% in humidity prediction and 21% in light prediction. To the best of our knowledge, we believe that we are probably the first to address prediction based on multivariate correlation for WSN data reduction. PMID:22346626

Elastic-net regularization approaches for genome-wide association studies of rheumatoid arthritis.

PubMed

Cho, Seoae; Kim, Haseong; Oh, Sohee; Kim, Kyunga; Park, Taesung

2009-12-15

The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genome. However, many challenges exist in detecting disease-causing genes among the thousands of SNPs. Examples include multicollinearity and multiple testing issues, especially when a large number of correlated SNPs are simultaneously tested. Multicollinearity can often occur when predictor variables in a multiple regression model are highly correlated, and can cause imprecise estimation of association. In this study, we propose a simple stepwise procedure that identifies disease-causing SNPs simultaneously by employing elastic-net regularization, a variable selection method that allows one to address multicollinearity. At Step 1, the single-marker association analysis was conducted to screen SNPs. At Step 2, the multiple-marker association was scanned based on the elastic-net regularization. The proposed approach was applied to the rheumatoid arthritis (RA) case-control data set of Genetic Analysis Workshop 16. While the selected SNPs at the screening step are located mostly on chromosome 6, the elastic-net approach identified putative RA-related SNPs on other chromosomes in an increased proportion. For some of those putative RA-related SNPs, we identified the interactions with sex, a well known factor affecting RA susceptibility.

Development of in vitro-in vivo correlation for extended-release niacin after administration of hypromellose-based matrix formulations to healthy volunteers.

PubMed

Kesisoglou, Filippos; Rossenu, Stefaan; Farrell, Colm; Van Den Heuvel, Michiel; Prohn, Marita; Fitzpatrick, Shaun; De Kam, Pieter-Jan; Vargo, Ryan

2014-11-01

Development of in vitro-in vivo correlations (IVIVCs) for extended-release (ER) products is commonly pursued during pharmaceutical development to increase product understanding, set release specifications, and support biowaivers. This manuscript details the development of Level C and Level A IVIVCs for ER formulations of niacin, a highly variable and extensively metabolized compound. Three ER formulations were screened in a cross-over study against immediate-release niacin. A Multiple Level C IVIVC was established for both niacin and its primary metabolite nicotinuric acid (NUA) as well as total niacin metabolites urinary excretion. For NUA, but not for niacin, Level A IVIVC models with acceptable prediction errors were achievable via a modified IVIVC rather than a traditional deconvolution/convolution approach. Hence, this is in contradiction with current regulatory guidelines that suggest that when a Multiple Level C IVIVC is established, Level A models should also be readily achievable. We demonstrate that for a highly variable, highly metabolized compound such as niacin, development of a Level A IVIVC model fully validated according to agency guidelines may be challenging. However, Multiple Level C models are achievable and could be used to guide release specifications and formulation/manufacturing changes. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

Assessment of blood donation intention among medical students in Pakistan--An application of theory of planned behavior.

PubMed

Faqah, Anadil; Moiz, Bushra; Shahid, Fatima; Ibrahim, Mariam; Raheem, Ahmed

2015-12-01

Theory of Planned Behavior proposes a model which can measure how human actions are guided. It has been successfully utilized in the context of blood donation. We employed a decision-making framework to determine the intention of blood donation among medical students who have never donated blood before the study. Survey responses were collected from 391 medical students from four various universities on a defined questionnaire. The tool composed of 20 questions that were formulated to explain donation intention based on theory of planned behavior. The construct included questions related to attitude, subjective norm and perceived behavior control, descriptive norm, moral norm, anticipated regret, donation anxiety and religious norm. Pearson's correlational relationships were measured between independent and dependent variables of intention to donate blood. ANOVA was applied to observe the model fit; a value of 0.000 was considered statistically significant. A multiple regression analysis was conducted to explore the relative importance of the main independent variables in the prediction of intention. Multi-collinearity was also evaluated to determine that various independent variables determine the intention. The reliability of measures composed of two items was assessed using inter-item correlations. Three hundred and ninety-one medical students (M:F; 1:2.2) with mean age of 21.96 years ± 1.95 participated in this study. Mean item score was 3.8 ± 0.83. Multiple regression analysis suggested that perceived behavioral control, anticipated regret and attitude were the most influential factors in determining intention of blood donation. Donation anxiety was least correlated and in fact bore a negative correlation with intention. ANOVA computed an F value of 199.082 with a p-value of 0.000 indicating fitness of model. The value of R square and adjusted R square was 0.811 and 0.807 respectively indicating strong correlation between various independent and dependent variables. Medical students as novice blood donors showed a positive attitude toward blood donation. Theory of planned behavior can be successfully utilized in determining the antecedents toward blood donation behavior. Copyright © 2015 Elsevier Ltd. All rights reserved.

Reassessment of the relationship between M-protein decrement and survival in multiple myeloma.

PubMed

Palmer, M; Belch, A; Hanson, J; Brox, L

1989-01-01

The relationship between percentage M-protein decrement and survival is assessed in 134 multiple myeloma patients. The correlation did not achieve statistical significance (P = 0.069). Multivariate analysis using the Cox proportional hazards model, including a number of previously recognised prognostic factors, showed only percentage M-protein decrement, creatinine and haemoglobin to be significantly correlated with survival. However, the R'-statistic for each of these variables was low, indicating that their prognostic power is weak. We conclude that neither the percentage M-protein decrement nor the response derived from it can be used as an accurate means of assessing the efficacy of treatment in myeloma. Mature survival data alone should be used for this purpose.

Reassessment of the relationship between M-protein decrement and survival in multiple myeloma.

PubMed Central

Palmer, M.; Belch, A.; Hanson, J.; Brox, L.

1989-01-01

The relationship between percentage M-protein decrement and survival is assessed in 134 multiple myeloma patients. The correlation did not achieve statistical significance (P = 0.069). Multivariate analysis using the Cox proportional hazards model, including a number of previously recognised prognostic factors, showed only percentage M-protein decrement, creatinine and haemoglobin to be significantly correlated with survival. However, the R'-statistic for each of these variables was low, indicating that their prognostic power is weak. We conclude that neither the percentage M-protein decrement nor the response derived from it can be used as an accurate means of assessing the efficacy of treatment in myeloma. Mature survival data alone should be used for this purpose. PMID:2757916

What is the relationship between renal function and visit-to-visit blood pressure variability in primary care? Retrospective cohort study from routinely collected healthcare data.

PubMed

Lasserson, Daniel S; Scherpbier de Haan, Nynke; de Grauw, Wim; van der Wel, Mark; Wetzels, Jack F; O'Callaghan, Christopher A

2016-06-10

To determine the relationship between renal function and visit-to-visit blood pressure (BP) variability in a cohort of primary care patients. Retrospective cohort study from routinely collected healthcare data. Primary care in Nijmegen, the Netherlands, from 2007 to 2012. 19 175 patients who had a measure of renal function, and 7 separate visits with BP readings in the primary care record. Visit-to-visit variability in systolic BP, calculated from the first 7 office measurements, including SD, successive variation, absolute real variation and metrics of variability shown to be independent of mean. Multiple linear regression was used to analyse the influence of estimated glomerular filtration rate (eGFR) on BP variability measures with adjustment for age, sex, diabetes, mean BP, proteinuria, cardiovascular disease, time interval between measures and antihypertensive use. In the patient cohort, 57% were women, mean (SD) age was 65.5 (12.3) years, mean (SD) eGFR was 75.6 (18.0) mL/min/1.73m(2) and SD systolic BP 148.3 (21.4) mm Hg. All BP variability measures were negatively correlated with eGFR and positively correlated with age. However, multiple linear regressions demonstrated consistent, small magnitude negative relationships between eGFR and all measures of BP variability adjusting for confounding variables. Worsening renal function is associated with small increases in measures of visit-to-visit BP variability after adjustment for confounding factors. This is seen across the spectrum of renal function in the population, and provides a mechanism whereby chronic kidney disease may raise the risk of cardiovascular events. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Sensitivity Analysis of Multiple Informant Models When Data are Not Missing at Random

PubMed Central

Blozis, Shelley A.; Ge, Xiaojia; Xu, Shu; Natsuaki, Misaki N.; Shaw, Daniel S.; Neiderhiser, Jenae; Scaramella, Laura; Leve, Leslie; Reiss, David

2014-01-01

Missing data are common in studies that rely on multiple informant data to evaluate relationships among variables for distinguishable individuals clustered within groups. Estimation of structural equation models using raw data allows for incomplete data, and so all groups may be retained even if only one member of a group contributes data. Statistical inference is based on the assumption that data are missing completely at random or missing at random. Importantly, whether or not data are missing is assumed to be independent of the missing data. A saturated correlates model that incorporates correlates of the missingness or the missing data into an analysis and multiple imputation that may also use such correlates offer advantages over the standard implementation of SEM when data are not missing at random because these approaches may result in a data analysis problem for which the missingness is ignorable. This paper considers these approaches in an analysis of family data to assess the sensitivity of parameter estimates to assumptions about missing data, a strategy that may be easily implemented using SEM software. PMID:25221420

Self-transcendence and depression in middle-age adults.

PubMed

Ellermann, C R; Reed, P G

2001-11-01

Self-transcendence has been found to be an important correlate of mental health in older adults and adults facing the end of life. This study extends current theory by examining the relationship of transcendence and other transcendence variables to depression in middle-age adults (N = 133). Reed's Self-Transcendence Scale, the Center for Epidemiological Studies-Depression Scale, and measures of parenting, acceptance and spirituality were administered. Findings indicating significant inverse correlations between self-transcendence and depression, as well as between other measures of transcendence and depression support Reed's (1991b) theory. Multiple regression analysis indicated that acceptance may be another significant correlate of depression. Significant gender differences and age-related patterns of increased levels of self-transcendence were found. Study results illuminate the need to continue research into developmentally based transcendence variables related to various experiences of health and well-being across the life span.

Evaluating and Quantifying the Climate-Driven Interannual Variability in Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) at Global Scales

NASA Technical Reports Server (NTRS)

Zeng, Fanwei; Collatz, George James; Pinzon, Jorge E.; Ivanoff, Alvaro

2013-01-01

Satellite observations of surface reflected solar radiation contain informationabout variability in the absorption of solar radiation by vegetation. Understanding thecauses of variability is important for models that use these data to drive land surface fluxesor for benchmarking prognostic vegetation models. Here we evaluated the interannualvariability in the new 30.5-year long global satellite-derived surface reflectance index data,Global Inventory Modeling and Mapping Studies normalized difference vegetation index(GIMMS NDVI3g). Pearsons correlation and multiple linear stepwise regression analyseswere applied to quantify the NDVI interannual variability driven by climate anomalies, andto evaluate the effects of potential interference (snow, aerosols and clouds) on the NDVIsignal. We found ecologically plausible strong controls on NDVI variability by antecedent precipitation and current monthly temperature with distinct spatial patterns. Precipitation correlations were strongest for temperate to tropical water limited herbaceous systemswhere in some regions and seasons 40 of the NDVI variance could be explained byprecipitation anomalies. Temperature correlations were strongest in northern mid- to-high-latitudes in the spring and early summer where up to 70 of the NDVI variance was explained by temperature anomalies. We find that, in western and central North America,winter-spring precipitation determines early summer growth while more recent precipitation controls NDVI variability in late summer. In contrast, current or prior wetseason precipitation anomalies were correlated with all months of NDVI in sub-tropical herbaceous vegetation. Snow, aerosols and clouds as well as unexplained phenomena still account for part of the NDVI variance despite corrections. Nevertheless, this study demonstrates that GIMMS NDVI3g represents real responses of vegetation to climate variability that are useful for global models.

Multivariate analysis of scale-dependent associations between bats and landscape structure

USGS Publications Warehouse

Gorresen, P.M.; Willig, M.R.; Strauss, R.E.

2005-01-01

The assessment of biotic responses to habitat disturbance and fragmentation generally has been limited to analyses at a single spatial scale. Furthermore, methods to compare responses between scales have lacked the ability to discriminate among patterns related to the identity, strength, or direction of associations of biotic variables with landscape attributes. We present an examination of the relationship of population- and community-level characteristics of phyllostomid bats with habitat features that were measured at multiple spatial scales in Atlantic rain forest of eastern Paraguay. We used a matrix of partial correlations between each biotic response variable (i.e., species abundance, species richness, and evenness) and a suite of landscape characteristics to represent the multifaceted associations of bats with spatial structure. Correlation matrices can correspond based on either the strength (i.e., magnitude) or direction (i.e., sign) of association. Therefore, a simulation model independently evaluated correspondence in the magnitude and sign of correlations among scales, and results were combined via a meta-analysis to provide an overall test of significance. Our approach detected both species-specific differences in response to landscape structure and scale dependence in those responses. This matrix-simulation approach has broad applicability to ecological situations in which multiple intercorrelated factors contribute to patterns in space or time. ?? 2005 by the Ecological Society of America.

A twelve-year profile of students' SAT scores, GPAs, and MCAT scores from a small university's premedical program.

PubMed

Montague, J R; Frei, J K

1993-04-01

To determine whether significant correlations existed among quantitative and qualitative predictors of students' academic success and quantitative outcomes of such success over a 12-year period in a small university's premedical program. A database was assembled from information on the 199 graduates who earned BS degrees in biology from Barry University's School of Natural and Health Sciences from 1980 through 1991. The quantitative variables were year of BS degree, total score on the Scholastic Aptitude Test (SAT), various measures of undergraduate grade-point averages (GPAs), and total score on the Medical College Admission Test (MCAT); and the qualitative variables were minority (54% of the students) or majority status and transfer (about one-third of the students) or nontransfer status. The statistical methods were multiple analysis of variance and stepwise multiple regression. Statistically significant positive correlations were found among SAT total scores, final GPAs, biology GPAs versus nonbiology GPAs, and MCAT total scores. These correlations held for transfer versus nontransfer students and for minority versus majority students. Over the 12-year period there were significant fluctuations in mean MCAT scores. The students' SAT scores and GPAs proved to be statistically reliable predictors of MCAT scores, but the minority or majority status and the transfer or nontransfer status of the students were statistically insignificant.

Quantifying relationships between abundances of cold-water coral Lophelia pertusa and terrain features: A case study on the Norwegian margin

NASA Astrophysics Data System (ADS)

Tong, Ruiju; Purser, Autun; Guinan, Janine; Unnithan, Vikram; Yu, Jinsongdi; Zhang, Chengcheng

2016-03-01

An understanding of how terrain features influence abundance of a particular species greatly aids in the development of accurate predictive habitat suitability models. In this study, we investigated the observed seafloor coverage of cold-water coral Lophelia pertusa in relation to seabed topography at the Sotbakken and Røst Reefs on the Norwegian margin. The primary terrain features at the study sites are a SW-NE stretching mound at Sotbakken Reef and SW-NE running ridges at Røst Reef, located at depths of ~300-400 m and ~250-320 m respectively. Ship-borne multibeam bathymetry data, JAGO dive video data and JAGO positioning data were used in this study. Terrain variables were calculated at scales of 30 m, 90 m and 170 m based on the bathymetry data. Additionally, we investigated the relationships between the terrain variables at multiple scales using the Unweighted Pair Group Method. The observed L. pertusa coverage at both reefs was found to be significantly correlated with most investigated terrain variables, with correlations increasing in strength with increase in analysis scale, suggesting that large scale terrain features likely play an important role in influencing L. pertusa distribution. Small scale terrain variations appear less important in determining the suitability of a region of seafloor for L. pertusa colonization. We conclude that bathymetric position index and curvature, as well as seabed aspect, most strongly correlate with coral coverage, indicating that local topographic highs, with an orientation into inflowing bottom currents, are most suitable for L. pertusa habitation. These results indicate that developing habitat suitability models for L. pertusa will benefit from inclusion of particular key terrain variables (e.g. aspect, plan curvature, mean curvature and slope) and that these should ideally be computed at multiple spatial scales with a greater gap in scales than we used in this study, to maximize the inclusion of the key variables in the model whilst minimizing redundancy.

Simulation of Plant Physiological Process Using Fuzzy Variables

Treesearch

Daniel L. Schmoldt

1991-01-01

Qualitative modelling can help us understand and project effects of multiple stresses on trees. It is not practical to collect and correlate empirical data for all combinations of plant/environments and human/climate stresses, especially for mature trees in natural settings. Therefore, a mechanistic model was developed to describe ecophysiological processes. This model...

Determination of Habitat Requirements For Birds in Suburban Areas

Treesearch

Jack Ward Thomas; Richard M. DeGraaf; Joseph C. Mawson

1977-01-01

Songbird populations can be related to habitat components by a method that allows the simultaneous determination of habitat requirements for a variety of species . Through correlation and multiple-regression analyses, 10 bird species were studied in a suburban habitat, which was stratified according to human density. Variables used to account for bird distribution...

Associations between Academic Achievement and Psychosocial Variables in Adolescents with Cystic Fibrosis

ERIC Educational Resources Information Center

Grieve, Adam J.; Tluczek, Audrey; Racine-Gilles, Caroline N.; Laxova, Anita; Albers, Craig A.; Farrell, Philip M.

2011-01-01

Background: Cystic fibrosis (CF) is a chronic genetic disease that leads to the accumulation of thick mucus in multiple organ systems, leading to chronic lung infection and affecting the body's ability to absorb nutrients necessary for growth and development. This cross-sectional, correlational study examined the potential effects of CF on…

Correlation Study of Physics Achievement, Learning Strategy, Attitude and Gender in an Introductory Physics Course

ERIC Educational Resources Information Center

Sezgin Selcuk, Gamze

2010-01-01

This study investigates the relationship between multiple predictors of physics achievement including reported use of four learning strategy clusters (elaboration, organization, comprehension monitoring and rehearsal), attitudes towards physics (sense of care and sense of interest) and a demographic variable (gender) in order to determine the…

Clustering of metabolic and cardiovascular risk factors in the polycystic ovary syndrome: a principal component analysis.

PubMed

Stuckey, Bronwyn G A; Opie, Nicole; Cussons, Andrea J; Watts, Gerald F; Burke, Valerie

2014-08-01

Polycystic ovary syndrome (PCOS) is a prevalent condition with heterogeneity of clinical features and cardiovascular risk factors that implies multiple aetiological factors and possible outcomes. To reduce a set of correlated variables to a smaller number of uncorrelated and interpretable factors that may delineate subgroups within PCOS or suggest pathogenetic mechanisms. We used principal component analysis (PCA) to examine the endocrine and cardiometabolic variables associated with PCOS defined by the National Institutes of Health (NIH) criteria. Data were retrieved from the database of a single clinical endocrinologist. We included women with PCOS (N = 378) who were not taking the oral contraceptive pill or other sex hormones, lipid lowering medication, metformin or other medication that could influence the variables of interest. PCA was performed retaining those factors with eigenvalues of at least 1.0. Varimax rotation was used to produce interpretable factors. We identified three principal components. In component 1, the dominant variables were homeostatic model assessment (HOMA) index, body mass index (BMI), high density lipoprotein (HDL) cholesterol and sex hormone binding globulin (SHBG); in component 2, systolic blood pressure, low density lipoprotein (LDL) cholesterol and triglycerides; in component 3, total testosterone and LH/FSH ratio. These components explained 37%, 13% and 11% of the variance in the PCOS cohort respectively. Multiple correlated variables from patients with PCOS can be reduced to three uncorrelated components characterised by insulin resistance, dyslipidaemia/hypertension or hyperandrogenaemia. Clustering of risk factors is consistent with different pathogenetic pathways within PCOS and/or differing cardiometabolic outcomes. Copyright © 2014 Elsevier Inc. All rights reserved.

Relationships among multiple aspects of agriculture's environmental impact and productivity: a meta-analysis to guide sustainable agriculture.

PubMed

German, Richard N; Thompson, Catherine E; Benton, Tim G

2017-05-01

Given the pressures on land to produce ever more food, doing it 'sustainably' is growing in importance. However, 'sustainable agriculture' is complex to define, not least because agriculture impacts in many different ways and it is not clear how different aspects of sustainability may be in synergy or trade off against each other. We conducted a meta-analysis to assess the relationships between multiple measures of sustainability using novel analytical methods, based around defining the efficiency frontier in the relationship between variables, as well as using correlation analysis. We define 20 grouped variables of agriculture's impact (e.g. on soil, greenhouse gas, water, biodiversity) and find evidence of both strong positive and negative correlations between them. Analysis based on the efficiency frontier suggests that trade-offs can be 'softened' by exploiting the natural between-study variation that arises from a combination of farming best practice and context. Nonetheless, the literature provides strong evidence of the relationship between yields and the negative externalities created by farming across a range of measures. © 2016 Cambridge Philosophical Society.

Influence of ozone and meteorological parameters on levels of polycyclic aromatic hydrocarbons in the air

NASA Astrophysics Data System (ADS)

Pehnec, Gordana; Jakovljević, Ivana; Šišović, Anica; Bešlić, Ivan; Vađić, Vladimira

2016-04-01

Concentrations of ten polycyclic aromatic hydrocarbons (PAHs) in the PM10 particle fraction were measured together with ozone and meteorological parameters at an urban site (Zagreb, Croatia) over a one-year period. Data were subjected to regression analysis in order to determine the relationship between the measured pollutants and selected meteorological variables. All of the PAHs showed seasonal variations with high concentrations in winter and autumn and very low concentrations during summer and spring. All of the ten PAHs concentrations also correlated well with each other. A statistically significant negative correlation was found between the concentrations of PAHs and ozone concentrations and concentrations of PAHs and temperature, as well as a positive correlation between concentrations of PAHs and PM10 mass concentration and relative humidity. Multiple regression analysis showed that concentrations of PM10 and ozone, temperature, relative humidity and pressure accounted for 43-70% of PAHs variability. Concentrations of PM10 and temperature were significant variables for all of the measured PAH's concentrations in all seasons. Ozone concentrations were significant for only some of the PAHs, particularly 6-ring PAHs.

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

Predictive ability of a comprehensive incremental test in mountain bike marathon

PubMed Central

Schneeweiss, Patrick; Martus, Peter; Niess, Andreas M; Krauss, Inga

2018-01-01

Objectives Traditional performance tests in mountain bike marathon (XCM) primarily quantify aerobic metabolism and may not describe the relevant capacities in XCM. We aimed to validate a comprehensive test protocol quantifying its intermittent demands. Methods Forty-nine athletes (38.8±9.1 years; 38 male; 11 female) performed a laboratory performance test, including an incremental test, to determine individual anaerobic threshold (IAT), peak power output (PPO) and three maximal efforts (10 s all-out sprint, 1 min maximal effort and 5 min maximal effort). Within 2 weeks, the athletes participated in one of three XCM races (n=15, n=9 and n=25). Correlations between test variables and race times were calculated separately. In addition, multiple regression models of the predictive value of laboratory outcomes were calculated for race 3 and across all races (z-transformed data). Results All variables were correlated with race times 1, 2 and 3: 10 s all-out sprint (r=−0.72; r=−0.59; r=−0.61), 1 min maximal effort (r=−0.85; r=−0.84; r=−0.82), 5 min maximal effort (r=−0.57; r=−0.85; r=−0.76), PPO (r=−0.77; r=−0.73; r=−0.76) and IAT (r=−0.71; r=−0.67; r=−0.68). The best-fitting multiple regression models for race 3 (r2=0.868) and across all races (r2=0.757) comprised 1 min maximal effort, IAT and body weight. Conclusion Aerobic and intermittent variables correlated least strongly with race times. Their use in a multiple regression model confirmed additional explanatory power to predict XCM performance. These findings underline the usefulness of the comprehensive incremental test to predict performance in that sport more precisely. PMID:29387445

A UV multifunctional Raman lidar system for the observation and analysis of atmospheric temperature, humidity, aerosols and their conveying characteristics over Xi'an

NASA Astrophysics Data System (ADS)

Yufeng, Wang; Qiang, Fu; Meina, Zhao; Fei, Gao; Huige, Di; Yuehui, Song; Dengxin, Hua

2018-01-01

To monitor the variability and the correlation of multiple atmospheric parameters in the whole troposphere and the lower stratosphere, a ground-based ultraviolet multifunctional Raman lidar system was established to simultaneously measure the atmospheric parameters in Xi'an (34.233°N, 108.911°E). A set of dichroic mirrors (DMs) and narrow-band interference filters (IFs) with narrow angles of incidence were utilized to construct a high-efficiency 5-channel polychromator. A series of high-quality data obtained from October 2013 to December 2015 under different weather conditions were used to investigate the functionality of the Raman lidar system and to study the variability of multiple atmospheric parameters in the whole stratosphere. Their conveying characteristics are also investigated using back trajectories with a hybrid single-particle Lagrangian integrated trajectory model (HYSPLIT). The lidar system can be operated efficiently under weather conditions with a cloud backscattering ratio of less than 18 and an atmospheric visibility of 3 km. We observed an obvious temperature inversion phenomenon at the tropopause height of 17-18 km and occasional temperature inversion layers below the boundary layer. The rapidly changing atmospheric water vapor is mostly concentrated at the lower troposphere, below ∼4-5 km, accounting for ∼90% of the total water vapor content at 0.5-10 km. The back trajectory analysis shows that the air flow from the northwest and the west mainly contributes to the transport of aerosols and water vapor over Xi'an. The simultaneous continuous observational results demonstrate the variability and correlation among the multiple atmospheric parameters, and the accumulated water vapor density in the bottom layer causes an increase in the aerosol extinction coefficient and enhances the relative humidity in the early morning. The long-term observations provide a large amount of reliable atmospheric data below the lower stratosphere, and can be used to study their correlation and to improve local climate change research.

Psychosocial and cognitive factors associated with adherence to dietary and fluid restriction regimens by people on chronic haemodialysis.

PubMed

Sensky, T; Leger, C; Gilmour, S

1996-01-01

Failure by people on chronic haemodialysis to adhere adequately to dietary and fluid restrictions can have serious medical consequences. Numerous psychosocial factors possibly associated with adherence have been investigated in previous research. However, most previous studies have examined one or a few variables in isolation, and have tended to focus on sociodemographic variables not easily amenable to intervention. Much previous work has tended to ignore potential differences in adherence between male and female dialysands. Sociodemographic and psychosocial factors associated with adherence to dietary and fluid restrictions were investigated in 45 people on haemodialysis attending one renal unit, excluding those with a residual urine volume > 500 ml/day. Multiple regression analyses were used to estimate the contribution to adherence of a range of variables, including gender, age, duration of dialysis, affective disturbance, past psychiatric history, health locus of control, social adjustment and social supports. Adherence to diet (measured by predialysis serum potassium) and to fluid restriction (interdialysis weight gain) were not linked, and had different psychosocial correlates. Regression models of four different aspects of adherence revealed very distinct psychosocial correlates, with contributions to adherence from complex interactions between psychosocial and cognitive variables, notably gender, age, social adjustment, health locus of control, and depression. The findings cast doubt on the results of many previous studies which have used simple models of adherence. Adherence is likely to be influenced in a complex manner by multiple factors including age, gender, locus of control, social adjustment, and past psychiatric history.

How easily can omission of patients, or selection amongst poorly-reproducible measurements, create artificial correlations? Methods for detection and implications for observational research design in cardiology.

PubMed

Francis, Darrel P

2013-07-15

When reported correlation coefficients seem too high to be true, does investigative verification of source data provide suitable reassurance? This study tests how easily omission of patients or selection amongst irreproducible measurements generate fictitious strong correlations, without data fabrication. Two forms of manipulation are applied to a pair of normally-distributed, uncorrelated variables: first, exclusion of patients least favourable to a hypothesised association and, second, making multiple poorly-reproducible measurements per patient and choosing the most supportive. Excluding patients raises correlations powerfully, from 0.0 ± 0.11 (no patients omitted) to 0.40 ± 0.11 (one-fifth omitted), 0.59 ± 0.08 (one-third omitted) and 0.78 ± 0.05 (half omitted). Study size offers no protection: omitting just one-fifth of 75 patients (i.e. publishing 60) makes 92% of correlations statistically significant. Worse, simply selecting the most favourable amongst several measurements raises correlations from 0.0 ± 0.12 (single measurement of each variable) to 0.73 ± 0.06 (best of 2), and 0.90 ± 0.03 (best of 4). 100% of correlation coefficients become statistically significant. Scatterplots may reveal a telltale "shave sign" or "bite sign". Simple statistical tests are presented for these suspicious signatures in single or multiple studies. Correlations are vulnerable to data manipulation. Cardiology is especially vulnerable to patient deletion (because cardiologists ourselves might completely control enrolment and measurement), and selection of "best" measurements (because alternative heartbeats are numerous, and some modalities poorly reproducible). Source data verification cannot detect these but tests might highlight suspicious data and--aggregating across studies--unreliable laboratories or research fields. Cardiological correlation research needs adequately-informed planning and guarantees of integrity, with teeth. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Stability of hand force production. I. Hand level control variables and multifinger synergies.

PubMed

Reschechtko, Sasha; Latash, Mark L

2017-12-01

We combined the theory of neural control of movement with referent coordinates and the uncontrolled manifold hypothesis to explore synergies stabilizing the hand action in accurate four-finger pressing tasks. In particular, we tested a hypothesis on two classes of synergies, those among the four fingers and those within a pair of control variables, stabilizing hand action under visual feedback and disappearing without visual feedback. Subjects performed four-finger total force and moment production tasks under visual feedback; the feedback was later partially or completely removed. The "inverse piano" device was used to lift and lower the fingers smoothly at the beginning and at the end of each trial. These data were used to compute pairs of hypothetical control variables. Intertrial analysis of variance within the finger force space was used to quantify multifinger synergies stabilizing both force and moment. A data permutation method was used to quantify synergies among control variables. Under visual feedback, synergies in the spaces of finger forces and hypothetical control variables were found to stabilize total force. Without visual feedback, the subjects showed a force drift to lower magnitudes and a moment drift toward pronation. This was accompanied by disappearance of the four-finger synergies and strong attenuation of the control variable synergies. The indexes of the two types of synergies correlated with each other. The findings are interpreted within the scheme with multiple levels of abundant variables. NEW & NOTEWORTHY We extended the idea of hierarchical control with referent spatial coordinates for the effectors and explored two types of synergies stabilizing multifinger force production tasks. We observed synergies among finger forces and synergies between hypothetical control variables that stabilized performance under visual feedback but failed to stabilize it after visual feedback had been removed. Indexes of two types of synergies correlated with each other. The data suggest the existence of multiple mechanisms stabilizing motor actions. Copyright © 2017 the American Physiological Society.

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.

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

NASA Astrophysics Data System (ADS)

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

2013-06-01

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

Two-dimensional correlation spectroscopy — Biannual survey 2007-2009

NASA Astrophysics Data System (ADS)

Noda, Isao

2010-06-01

The publication activities in the field of 2D correlation spectroscopy are surveyed with the emphasis on papers published during the last two years. Pertinent review articles and conference proceedings are discussed first, followed by the examination of noteworthy developments in the theory and applications of 2D correlation spectroscopy. Specific topics of interest include Pareto scaling, analysis of randomly sampled spectra, 2D analysis of data obtained under multiple perturbations, evolution of 2D spectra along additional variables, comparison and quantitative analysis of multiple 2D spectra, orthogonal sample design to eliminate interfering cross peaks, quadrature orthogonal signal correction and other data transformation techniques, data pretreatment methods, moving window analysis, extension of kernel and global phase angle analysis, covariance and correlation coefficient mapping, variant forms of sample-sample correlation, and different display methods. Various static and dynamic perturbation methods used in 2D correlation spectroscopy, e.g., temperature, composition, chemical reactions, H/D exchange, physical phenomena like sorption, diffusion and phase transitions, optical and biological processes, are reviewed. Analytical probes used in 2D correlation spectroscopy include IR, Raman, NIR, NMR, X-ray, mass spectrometry, chromatography, and others. Application areas of 2D correlation spectroscopy are diverse, encompassing synthetic and natural polymers, liquid crystals, proteins and peptides, biomaterials, pharmaceuticals, food and agricultural products, solutions, colloids, surfaces, and the like.

Fatigue, emotional functioning, and executive dysfunction in pediatric multiple sclerosis.

PubMed

Holland, Alice Ann; Graves, Donna; Greenberg, Benjamin M; Harder, Lana L

2014-01-01

Fatigue, depression, anxiety, and executive dysfunction are associated with multiple sclerosis (MS) in adults. Existing research suggests similar problems in pediatric MS, but relationships between these variables have not been investigated. This study investigates the associations between executive functioning and fatigue, emotional functioning, age of onset, and disease duration in pediatric MS. Twenty-six MS or Clinically Isolated Syndrome (CIS) patients, ages 7 to 18, were evaluated through a multidisciplinary demyelinating diseases clinic. Participants completed neuropsychological screening including Verbal Fluency, Digit Span, and Trail-Making Test. Parents completed rating forms of behavioral, emotional, and executive functioning. Patients and parents completed questionnaires related to the patient's quality of life and fatigue. Pearson's correlation coefficients were calculated to investigate relationships between fatigue, emotional functioning, and executive functioning, as well as to examine correlations between parent and child reports of fatigue. Rates of parent-reported anxiety, depression, fatigue, and executive dysfunction varied widely. Means were below average on the Trail-Making Test and average on Verbal Fluency and Digit Span, though scores varied widely. Various fatigue and emotional functioning indices-but not age of onset or disease duration-significantly correlated with various performance-based measures of executive functioning. Results indicate pediatric MS is associated with some degree of fatigue, emotional difficulties, and executive dysfunction, the latter of which is associated with the two former. Notably, age of onset and disease duration did not significantly correlate with executive functioning. Results advance understanding of psychological and clinical variables related to neurocognitive outcomes in pediatric MS.

Correlates of children and parents being physically active together.

PubMed

Lee, Sarah M; Nihiser, Allison; Strouse, Darcy; Das, Barnali; Michael, Shannon; Huhman, Marian

2010-11-01

Co-physical activity (between parents and children), as an outcome variable, and its correlates have not been examined previously. The purpose of this study was to investigate correlates of co-physical activity among a nationally representative sample of 9- to 13-year-old children and their parents. Data were from the 2004 Youth Media Campaign Longitudinal Survey, a national survey of 5177 child-parent dyads. Parents of 9- to 13-year-old children were asked to report co-physical activity. Parents and children responded to a series of sociodemographic, behavioral, and psychosocial measures. Co-physical activity was treated as a dichotomous variable (ie, some or none). Logistic regression was used to assess associations of correlates directly and possible interactions between correlates. More than three-quarters of parents reported co-physical activity at least 1 day in the prior week. Age, race/ethnicity, sports team participation, eating meals together, parental confidence to influence the child's organized activity, and the child's perception of parental support were significantly associated with co-physical activity. The majority of respondents reported participating in co-physical activity, and multiple sociodemographic, behavioral, and psychosocial correlates were significantly associated with co-physical activity. This study provides insight for physical activity interventions that might involve parents.

A model for the flux-r.m.s. correlation in blazar variability or the minijets-in-a-jet statistical model

NASA Astrophysics Data System (ADS)

Biteau, J.; Giebels, B.

2012-12-01

Very high energy gamma-ray variability of blazar emission remains of puzzling origin. Fast flux variations down to the minute time scale, as observed with H.E.S.S. during flares of the blazar PKS 2155-304, suggests that variability originates from the jet, where Doppler boosting can be invoked to relax causal constraints on the size of the emission region. The observation of log-normality in the flux distributions should rule out additive processes, such as those resulting from uncorrelated multiple-zone emission models, and favour an origin of the variability from multiplicative processes not unlike those observed in a broad class of accreting systems. We show, using a simple kinematic model, that Doppler boosting of randomly oriented emitting regions generates flux distributions following a Pareto law, that the linear flux-r.m.s. relation found for a single zone holds for a large number of emitting regions, and that the skewed distribution of the total flux is close to a log-normal, despite arising from an additive process.

On the Genetic and Environmental Correlations between Trait Emotional Intelligence and Vocational Interest Factors.

PubMed

Schermer, Julie Aitken; Petrides, Konstantinos V; Vernon, Philip A

2015-04-01

The phenotypic (observed), genetic, and environmental correlations were examined in a sample of adult twins between the four factors and global score of the trait emotional intelligence questionnaire (TEIQue) and the seven vocational interest factors of the Jackson Career Explorer (JCE). Multiple significant correlations were found involving the work style vocational interest factor (consisting of job security, stamina, accountability, planfulness, and interpersonal confidence) and the social vocational interest factor (which included interests in the social sciences, personal services, teaching, social services, and elementary education), both of which correlated significantly with all of the TEIQue variables (well-being, self-control, emotionality, sociability, and global trait EI). Following bivariate genetic analyses, most of the significant phenotypic correlations were found to also have significant genetic correlations as well as significant non-shared (unique) environmental correlations.

Relationship between balance performance in the elderly and some anthropometric variables.

PubMed

Fabunmi, A A; Gbiri, C A

2008-12-01

Ability to maintain either static or dynamic balance has been found to be influenced by many factors such as height and weight in the elderly. The relationship between other anthropometric variables and balance performance among elderly Nigerians has not been widely studied. The aim of this study was to investigate the relationship between these other anthropometric variables and balance performance among old individuals aged >60 years in Ibadan, Nigeria. The study used the ex-post facto design and involved two hundred and three apparently healthy (103 males and 100 females) elderly participants with ages between 60 years and 74 years, selected using multiple step-wise sampling techniques from churches, mosques and market place within Ibadan. They were without history of neurological problem, postural hypotension, orthopeadic conditions or injury to the back and/or upper and lower extremities within the past one year. Selected anthropometric variables were measured, Sharpened Romberg Test (SRT) and Functional Reach Test (FRT) was used to assess static balance and dynamic balance respectively. All data were summarized using range, mean and standard deviation. Pearson's product moment correlation coefficient was used to determine the relationship between the physical characteristics, anthropometric variables and performance on each of the two balance tests. The results showed that there were low but significant positive correlations between performance on FRT and each of height, weight, trunk length, foot length, shoulder girth and hip girth. (p<0.05). There was low significant and positive correlation between SRT with eyes closed and arm length, foot length and shoulder girth. (p<0.05) and there was low but significant positive correlation between SRT with eyes opened and shoulder girth and foot length (P<0.05). Anthropometric variables affect balance performances in apparently healthy elderly.

School-Related Variables in the Dimensions of Anger in High School Students in Turkey

ERIC Educational Resources Information Center

Siyez, Digdem M.

2018-01-01

The study aimed to examine the effects of perceived social support from teachers, expectation of academic achievement, school control, and gender on anger dimensions in high school students in Izmir, Turkey. In total, 446 high school students (234 girls, 212 boys) participated in the study. Pearson's correlation and multiple regression analyses…

Methods for Improving Information from "Undesigned" Human Factors Experiments. Technical Report No. p75-287.

ERIC Educational Resources Information Center

Simon, Charles W.

An "undesigned" experiment is one in which the predictor variables are correlated, either due to a failure to complete a design or because the investigator was unable to select or control relevant experimental conditions. The traditional method of analyzing this class of experiment--multiple regression analysis based on a least squares…

Multiple Regression with Varying Levels of Correlation among Predictors: Monte Carlo Sampling from Normal and Non-Normal Populations.

ERIC Educational Resources Information Center

Vasu, Ellen Storey

1978-01-01

The effects of the violation of the assumption of normality in the conditional distributions of the dependent variable, coupled with the condition of multicollinearity upon the outcome of testing the hypothesis that the regression coefficient equals zero, are investigated via a Monte Carlo study. (Author/JKS)

Toward an Index of Well-Being for the Fifty U.S. States

ERIC Educational Resources Information Center

Pesta, Bryan J.; McDaniel, Michael A.; Bertsch, Sharon

2010-01-01

Well-being is a construct spanning multiple disciplines including psychology, economics, health, and public policy. In many ways, well-being is a nexus of inter-correlated variables, much like the "g" nexus. Here, we created an index of well-being for the geographical and political subdivisions of the United States (i.e., states). The…

Frontal parenchymal atrophy measures in multiple sclerosis.

PubMed

Locatelli, Laura; Zivadinov, Robert; Grop, Attilio; Zorzon, Marino

2004-10-01

The aim of this study was to establish whether, in a cross-sectional study, the normalized measures of whole and regional brain atrophy correlate better with tests assessing the cognitive function than the absolute brain atrophy measures. The neuropsychological performances and disability have been assessed in 39 patients with relapsing-remitting multiple sclerosis (MS). T1- and T2-lesion load (LL) of total brain and frontal lobes (FLs) were measured using a reproducible semiautomated technique. The whole brain volume and the regional brain parenchymal volume (RBPV) of FLs were obtained using a computerized interactive program, which incorporates semiautomated and automated segmentation processes. Normalized measures of brain atrophy, i.e., brain parenchymal fraction (BPF) and regional brain parenchymal fraction (RBPF) of FLs, were calculated. The scan-rescan, inter- and intrarater coefficient of variation (COV) and intraclass correlation coefficient (ICC) have been estimated. The RBPF of FLs showed an acceptable level of reproducibility which ranged from 1.7% for intrarater variability to 3.2% for scan-rescan variability. The mean ICC was 0.88 (CI 0.82-0.93). The RBPF of FLs demonstrated stronger magnitudes of correlation with neuropsychological functioning, disability and quantitative MRI lesion measures than RBPV. These differences were statistically significant: P<0.001 for Stroop Color Word Interference test, P<0.001 for Paced Auditory Serial Addition Test, P=0.04 for Standard Raven Progressive Matrices, P=0.049 for Expanded Disability Status Scale, P=0.01 for T2-LL of FLs and P<0.001 for T1-LL of FLs. BPF demonstrated significant correlations with tests assessing cognitive functions, whereas BPAV did not. The correlation analysis results were supported by the results of multiple regression analysis which showed that only the normalized brain atrophy measures were associated with tests exploring the cognitive functions. These data suggest that RBPF is a reproducible and sensitive method for measuring frontal parenchymal atrophy. The normalized measures of whole and regional brain parenchymal atrophy should be preferred to absolute measures in future studies that correlate neuropsychological performances and brain atrophy measures in patients with MS.

Cerebrospinal fluid anti-Epstein-Barr virus specific oligoclonal IgM and IgG bands in patients with clinically isolated and Guillain-Barré syndrome.

PubMed

Ferraro, Diana; Galli, Veronica; Simone, Anna Maria; Bedin, Roberta; Vitetta, Francesca; Merelli, Elisa; Nichelli, Paolo Frigio; Sola, Patrizia

2017-04-01

Epstein-Barr virus (EBV) has been implicated in multiple sclerosis (MS) pathogenesis. We aimed to assess the frequency of EBV-specific IgG and IgM oligoclonal bands (OCB) in cerebrospinal fluid (CSF) of 50 patients with clinically isolated syndrome (CIS) and in 27 controls with Guillain-Barré syndrome (GBS). Furthermore, we assessed correlations between the presence of OCB and CIS patients' CSF, MRI, and clinical variables. There was no difference in the proportion of CIS and GB patients with positivity for anti-EBV-specific IgG/IgM OCB. There were no correlations between OCB and analyzed variables, nor were they predictive of a higher disability at 3 years.

Does weather shape rodents? Climate related changes in morphology of two heteromyid species

NASA Astrophysics Data System (ADS)

Wolf, Mosheh; Friggens, Michael; Salazar-Bravo, Jorge

2009-01-01

Geographical variation in morphometric characters in heteromyid rodents has often correlated with climate gradients. Here, we used the long-term database of rodents trapped in the Sevilleta National Wildlife Refuge in New Mexico, USA to test whether significant annual changes in external morphometric characters are observed in a region with large variations in temperature and precipitation. We looked at the relationships between multiple temperature and precipitation variables and a number of morphological traits (body mass, body, tail, hind leg, and ear length) for two heteromyid rodents, Dipodomys merriami and Perognathus flavescens. Because these rodents can live multiple years in the wild, the climate variables for the year of the capture and the previous 2 years were included in the analyses. Using multiple linear regressions, we found that all of our morphometric traits, with the exception of tail length in D. merriami, had a significant relationship with one or more of the climate variables used. Our results demonstrate that effects of climate change on morphological traits occur over short periods, even in noninsular mammal populations. It is unclear, though, whether these changes are the result of morphological plasticity or natural selection.

The correlation between calcaneal valgus angle and asymmetrical thoracic-lumbar rotation angles in patients with adolescent scoliosis.

PubMed

Park, Jaeyong; Lee, Sang Gil; Bae, Jongjin; Lee, Jung Chul

2015-12-01

[Purpose] This study aimed to provide a predictable evaluation method for the progression of scoliosis in adolescents based on quick and reliable measurements using the naked eye, such as the calcaneal valgus angle of the foot, which can be performed at public facilities such as schools. [Subjects and Methods] Idiopathic scoliosis patients with a Cobb's angle of 10° or more (96 females, 22 males) were included in this study. To identify relationships between factors, Pearson's product-moment correlation coefficient was computed. The degree of scoliosis was set as a dependent variable to predict thoracic and lumbar scoliosis using ankle angle and physique factors. Height, weight, and left and right calcaneal valgus angles were set as independent variables; thereafter, multiple regression analysis was performed. This study extracted variables at a significance level (α) of 0.05 by applying a stepwise method, and calculated a regression equation. [Results] Negative correlation (R=-0.266) was shown between lumbar lordosis and asymmetrical lumbar rotation angles. A correlation (R=0.281) was also demonstrated between left calcaneal valgus angles and asymmetrical thoracic rotation angles. [Conclusion] Prediction of scoliosis progress was revealed to be possible through ocular inspection of the calcaneus and Adams forward bending test and the use of a scoliometer.

Quality of life among people with multiple sclerosis: Replication of a three-factor prediction model.

PubMed

Bishop, Malachy; Rumrill, Phillip D; Roessler, Richard T

2015-01-01

This article presents a replication of Rumrill, Roessler, and Fitzgerald's 2004 analysis of a three-factor model of the impact of multiple sclerosis (MS) on quality of life (QOL). The three factors in the original model included illness-related, employment-related, and psychosocial adjustment factors. To test hypothesized relationships between QOL and illness-related, employment-related, and psychosocial variables using data from a survey of the employment concerns of Americans with MS (N = 1,839). An ex post facto, multiple correlational design was employed incorporating correlational and multiple regression analyses. QOL was positively related to educational level, employment status, job satisfaction, and job-match, and negatively related to number of symptoms, severity of symptoms, and perceived stress level. The three-factor model explained approximately 37 percent of the variance in QOL scores. The results of this replication confirm the continuing value of the three-factor model for predicting the QOL of adults with MS, and demonstrate the importance of medical, mental health, and vocational rehabilitation interventions and services in promoting QOL.

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.

Automated gait and balance parameters diagnose and correlate with severity in Parkinson disease.

PubMed

Dewey, D Campbell; Miocinovic, Svjetlana; Bernstein, Ira; Khemani, Pravin; Dewey, Richard B; Querry, Ross; Chitnis, Shilpa; Dewey, Richard B

2014-10-15

To assess the suitability of instrumented gait and balance measures for diagnosis and estimation of disease severity in PD. Each subject performed iTUG (instrumented Timed-Up-and-Go) and iSway (instrumented Sway) using the APDM(®) Mobility Lab. MDS-UPDRS parts II and III, a postural instability and gait disorder (PIGD) score, the mobility subscale of the PDQ-39, and Hoehn & Yahr stage were measured in the PD cohort. Two sets of gait and balance variables were defined by high correlation with diagnosis or disease severity and were evaluated using multiple linear and logistic regressions, ROC analyses, and t-tests. 135 PD subjects and 66 age-matched controls were evaluated in this prospective cohort study. We found that both iTUG and iSway variables differentiated PD subjects from controls (area under the ROC curve was 0.82 and 0.75 respectively) and correlated with all PD severity measures (R(2) ranging from 0.18 to 0.61). Objective exam-based scores correlated more strongly with iTUG than iSway. The chosen set of iTUG variables was abnormal in very mild disease. Age and gender influenced gait and balance parameters and were therefore controlled in all analyses. Our study identified sets of iTUG and iSway variables which correlate with PD severity measures and differentiate PD subjects from controls. These gait and balance measures could potentially serve as markers of PD progression and are under evaluation for this purpose in the ongoing NIH Parkinson Disease Biomarker Program. Copyright © 2014 Elsevier B.V. All rights reserved.

Automated Gait and Balance Parameters Diagnose and Correlate with Severity in Parkinson Disease

PubMed Central

Dewey, Daniel C.; Miocinovic, Svjetlana; Bernstein, Ira; Khemani, Pravin; Dewey, Richard B.; Querry, Ross; Chitnis, Shilpa; Dewey, Richard B.

2014-01-01

Objective To assess the suitability of instrumented gait and balance measures for diagnosis and estimation of disease severity in PD. Methods Each subject performed iTUG (instrumented Timed-Up-and-Go) and iSway (instrumented Sway) using the APDM® Mobility Lab. MDS-UPDRS parts II and III, a postural instability and gait disorder (PIGD) score, the mobility subscale of the PDQ-39, and Hoehn & Yahr stage were measured in the PD cohort. Two sets of gait and balance variables were defined by high correlation with diagnosis or disease severity and were evaluated using multiple linear and logistic regressions, ROC analyses, and t-tests. Results 135 PD subjects and 66 age-matched controls were evaluated in this prospective cohort study. We found that both iTUG and iSway variables differentiated PD subjects from controls (area under the ROC curve was 0.82 and 0.75 respectively) and correlated with all PD severity measures (R2 ranging from 0.18 to 0.61). Objective exam-based scores correlated more strongly with iTUG than iSway. The chosen set of iTUG variables was abnormal in very mild disease. Age and gender influenced gait and balance parameters and were therefore controlled in all analyses. Interpretation Our study identified sets of iTUG and iSway variables which correlate with PD severity measures and differentiate PD subjects from controls. These gait and balance measures could potentially serve as markers of PD progression and are under evaluation for this purpose in the ongoing NIH Parkinson Disease Biomarker Program. PMID:25082782

Spatial path models with multiple indicators and multiple causes: mental health in US counties.

PubMed

Congdon, Peter

2011-06-01

This paper considers a structural model for the impact on area mental health outcomes (poor mental health, suicide) of spatially structured latent constructs: deprivation, social capital, social fragmentation and rurality. These constructs are measured by multiple observed effect indicators, with the constructs allowed to be correlated both between and within areas. However, in the scheme developed here, particular latent constructs may also be influenced by known variables, or, via path sequences, by other constructs, possibly nonlinearly. For example, area social capital may be measured by effect indicators (e.g. associational density, charitable activity), but influenced as causes by other constructs (e.g. area deprivation), and by observed features of the socio-ethnic structure of areas. A model incorporating these features is applied to suicide mortality and the prevalence of poor mental health in 3141 US counties, which are related to the latent spatial constructs and to observed variables (e.g. county ethnic mix). Copyright © 2011 Elsevier Ltd. All rights reserved.

Miniature Loop Heat Pipe with Multiple Evaporators for Thermal Control of Small Spacecraft

NASA Technical Reports Server (NTRS)

Ku, Jentung; Ottenstein, Laura; Douglas, Denya; Pauken, Michael; Birur, Gajanana

2005-01-01

This paper presents an advanced miniature heat transport system for thermal control of small spacecraft. The thermal system consists of a loop heat pipe (LHP) with multiple evaporators and multiple deployable radiators for heat transfer, and variable emittance coatings on the radiators for performance enhancement. Thermoelectric coolers are used to control the loop operating temperature. The thermal system combines the functions of variable conductance heat pipes, thermal switches, thermal diodes, and the state-of-the-art LHPs into a single integrated thermal system. It retains all the performance characteristics of state-of-the-art LHPs and offers additional advantages to enhance the functionality, performance, versatility, and reliability of the system. Steady state and transient analytical models have been developed, and scaling criteria have also been established. A breadboard unit has been built for functional testing in laboratory and thermal vacuum environments. Experimental results show excellent performance of the thermal system and correlate very well with theoretical predictions.

Relation of pH and other soil variables to concentrations of Pb, Cu, Zn, Cd, and Se in earthworms

USGS Publications Warehouse

Beyer, W.N.; Hensler, G.L.; Moore, J.

1987-01-01

Various soil treatments (clay, composted peat, superphosphate, sulfur, calcium carbonate, calcium chloride, zinc chloride, selenous acid) were added to experimental field plots to test the effect of different soil variables on the concentrations of 5 elements in earthworms (Pb, Cu, Zn, Cd, Se). Concentrations of the 5 elements were related to 9 soil variables (soil Pb, soil Cu, soil Zn, pH, organic matter, P, K, Mg, and Ca) with linear multiple regression. Lead concentrations in earthworms were positively correlated with soil Pb and soil organic matter, and negatively correlated with soil pH and soil Mg, with an R2 of 64%. Se concentrations were higher in earthworms from plots amended with Se, and Zn concentrations were higher in earthworms from plots amended with Zn. However, none of the other soil variables had important effects on the concentrations of Cu, Zn, Cd and Se in earthworms. Although some significant statistical relations were demonstrated, the values of r2 of all relations (> 20%) were so low that they had little predictive value.

Air Pollutants, Climate, and the Prevalence of Pediatric Asthma in Urban Areas of China

PubMed Central

Zhang, Juanjuan; Yan, Li; Fu, Wenlong; Yi, Jing; Chen, Yuzhi; Liu, Chuanhe; Xu, Dongqun; Wang, Qiang

2016-01-01

Background. Prevalence of childhood asthma varies significantly among regions, while its reasons are not clear yet with only a few studies reporting relevant causes for this variation. Objective. To investigate the potential role of city-average levels of air pollutants and climatic factors in order to distinguish differences in asthma prevalence in China and explain their reasons. Methods. Data pertaining to 10,777 asthmatic patients were obtained from the third nationwide survey of childhood asthma in China's urban areas. Annual mean concentrations of air pollutants and other climatic factors were obtained for the same period from several government departments. Data analysis was implemented with descriptive statistics, Pearson correlation coefficient, and multiple regression analysis. Results. Pearson correlation analysis showed that the situation of childhood asthma was strongly linked with SO2, relative humidity, and hours of sunshine (p < 0.05). Multiple regression analysis indicated that, among the predictor variables in the final step, SO2 was found to be the most powerful predictor variable amongst all (β = −19.572, p < 0.05). Furthermore, results had shown that hours of sunshine (β = −0.014, p < 0.05) was a significant component summary predictor variable. Conclusion. The findings of this study do not suggest that air pollutants or climate, at least in terms of children, plays a major role in explaining regional differences in asthma prevalence in China. PMID:27556031

Grip pressure distributions and associated variability in golf: a two-club comparison.

PubMed

Langlais, Sean M; Broker, Jeffrey P

2014-06-01

Teaching and playing professionals offer multiple theories concerning the manner in which forces should be applied to the handle of the club during the golf swing. This study extends recent research concerning grip pressures and forces in golf, with the purpose of exploring the similarities and differences between force profiles for a 7-iron and driver swung by proficient golfers. A secondary purpose was to further analyze the way that golfers use grip forces to manipulate the club. Grip forces were measured on eight low handicap golfers (USGA indexes 0 to 7) swinging their own 7-irons and drivers. In total, lead-hand and trail-hand grip forces were isolated as well as anatomically specific forces within the hands. Force profile variability across multiple swings for each golfer and between golfers characterized consistencies and important differences. Correlations between 7-iron and driver force profiles characterized force 'signatures.' The data highlight large fluctuations in grip forces during the swing. Marked differences between participants were observed, involving force magnitudes and phasing. Dominant forces arose primarily from the lead hand, specifically the last three fingers. Force profiles were highly repeatable across swings for a golfer (standard deviations < 7% of total force) and force profile correlations between 7-iron and driver for a golfer were remarkably high (r2 = 0.86). Notably, within swing force variability was greatest during club acceleration, but dramatically decreased at impact.

Quality of life in multiple sclerosis (MS) and role of fatigue, depression, anxiety, and stress: A bicenter study from north of Iran.

PubMed

Salehpoor, Ghasem; Rezaei, Sajjad; Hosseininezhad, Mozaffar

2014-11-01

Although studies have demonstrated significant negative relationships between quality of life (QOL), fatigue, and the most common psychological symptoms (depression, anxiety, stress), the main ambiguity of previous studies on QOL is in the relative importance of these predictors. Also, there is lack of adequate knowledge about the actual contribution of each of them in the prediction of QOL dimensions. Thus, the main objective of this study is to assess the role of fatigue, depression, anxiety, and stress in relation to QOL of multiple sclerosis (MS) patients. One hundred and sixty-two MS patients completed the questionnaire on demographic variables, and then they were evaluated by the Persian versions of Short-Form Health Survey Questionnaire (SF-36), Fatigue Survey Scale (FSS), and Depression, Anxiety, Stress Scale-21 (DASS-21). Data were analyzed by Pearson correlation coefficient and hierarchical regression. Correlation analysis showed a significant relationship between QOL elements in SF-36 (physical component summary and mental component summary) and depression, fatigue, stress, and anxiety (P < 0.01). Hierarchical regression analysis indicated that among the predictor variables in the final step, fatigue, depression, and anxiety were identified as the physical component summary predictor variables. Anxiety was found to be the most powerful predictor variable amongst all (β = -0.46, P < 0.001). Furthermore, results have shown depression as the only significant mental component summary predictor variable (β = -0.39, P < 0.001). This study has highlighted the role of anxiety, fatigue, and depression in physical dimensions and the role of depression in psychological dimensions of the lives of MS patients. In addition, the findings of this study indirectly suggest that psychological interventions for reducing fatigue, depression, and anxiety can lead to improved QOL of MS patients.

Prediction of rectal temperature using non-invasive physiologic variable measurements in hair pregnant ewes subjected to natural conditions of heat stress.

PubMed

Vicente-Pérez, Ricardo; Avendaño-Reyes, Leonel; Mejía-Vázquez, Ángel; Álvarez-Valenzuela, F Daniel; Correa-Calderón, Abelardo; Mellado, Miguel; Meza-Herrera, Cesar A; Guerra-Liera, Juan E; Robinson, P H; Macías-Cruz, Ulises

2016-01-01

Rectal temperature (RT) is the foremost physiological variable indicating if an animal is suffering hyperthermia. However, this variable is traditionally measured by invasive methods, which may compromise animal welfare. Models to predict RT have been developed for growing pigs and lactating dairy cows, but not for pregnant heat-stressed ewes. Our aim was to develop a prediction equation for RT using non-invasive physiological variables in pregnant ewes under heat stress. A total of 192 records of respiratory frequency (RF) and hair coat temperature in various body regions (i.e., head, rump, flank, shoulder, and belly) obtained from 24 Katahdin × Pelibuey pregnant multiparous ewes were collected during the last third of gestation (i.e., d 100 to lambing) with a 15 d sampling interval. Hair coat temperatures were taken using infrared thermal imaging technology. Initially, a Pearson correlation analysis examined the relationship among variables, and then multiple linear regression analysis was used to develop the prediction equations. All predictor variables were positively correlated (P<0.01; r=0.59-0.67) with RT. The adjusted equation which best predicted RT (P<0.01; Radj(2)=56.15%; CV=0.65%) included as predictors RF and head and belly temperatures. Comparison of predicted and observed values for RT indicates a suitable agreement (P<0.01) between them with moderate accuracy (Radj(2)=56.15%) when RT was calculated with the adjusted equation. In general, the final equation does not violate any assumption of multiple regression analysis. The RT in heat-stressed pregnant ewes can be predicted with an adequate accuracy using non-invasive physiologic variables, and the final equation was: RT=35.57+0.004 (RF)+0.067 (heat temperature)+0.028 (belly temperature). Copyright © 2015 Elsevier Ltd. All rights reserved.

Community Air Sensor Network (CAIRSENSE) project: evaluation of low-cost sensor performance in a suburban environment in the southeastern United States

NASA Astrophysics Data System (ADS)

Jiao, Wan; Hagler, Gayle; Williams, Ronald; Sharpe, Robert; Brown, Ryan; Garver, Daniel; Judge, Robert; Caudill, Motria; Rickard, Joshua; Davis, Michael; Weinstock, Lewis; Zimmer-Dauphinee, Susan; Buckley, Ken

2016-11-01

Advances in air pollution sensor technology have enabled the development of small and low-cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring networks with additional geographic and temporal measurement resolution, if the data quality were sufficient. To understand the capability of emerging air sensor technology, the Community Air Sensor Network (CAIRSENSE) project deployed low-cost, continuous, and commercially available air pollution sensors at a regulatory air monitoring site and as a local sensor network over a surrounding ˜ 2 km area in the southeastern United States. Collocation of sensors measuring oxides of nitrogen, ozone, carbon monoxide, sulfur dioxide, and particles revealed highly variable performance, both in terms of comparison to a reference monitor as well as the degree to which multiple identical sensors produced the same signal. Multiple ozone, nitrogen dioxide, and carbon monoxide sensors revealed low to very high correlation with a reference monitor, with Pearson sample correlation coefficient (r) ranging from 0.39 to 0.97, -0.25 to 0.76, and -0.40 to 0.82, respectively. The only sulfur dioxide sensor tested revealed no correlation (r < 0.5) with a reference monitor and erroneously high concentration values. A wide variety of particulate matter (PM) sensors were tested with variable results - some sensors had very high agreement (e.g., r = 0.99) between identical sensors but moderate agreement with a reference PM2.5 monitor (e.g., r = 0.65). For select sensors that had moderate to strong correlation with reference monitors (r > 0.5), step-wise multiple linear regression was performed to determine if ambient temperature, relative humidity (RH), or age of the sensor in number of sampling days could be used in a correction algorithm to improve the agreement. Maximum improvement in agreement with a reference, incorporating all factors, was observed for an NO2 sensor (multiple correlation coefficient R2adj-orig = 0.57, R2adj-final = 0.81); however, other sensors showed no apparent improvement in agreement. A four-node sensor network was successfully able to capture ozone (two nodes) and PM (four nodes) data for an 8-month period of time and show expected diurnal concentration patterns, as well as potential ozone titration due to nearby traffic emissions. Overall, this study demonstrates the performance of emerging air quality sensor technologies in a real-world setting; the variable agreement between sensors and reference monitors indicates that in situ testing of sensors against benchmark monitors should be a critical aspect of all field studies.

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.

Stimulated peripheral production of interferon-gamma is related to fatigue and depression in multiple sclerosis.

PubMed

Pokryszko-Dragan, A; Frydecka, I; Kosmaczewska, A; Ciszak, L; Bilińska, M; Gruszka, E; Podemski, R; Frydecka, D

2012-10-01

The aim of the study was to evaluate the stimulated production of interferon-gamma (IFNγ) by peripheral CD3+CD4+ T lymphocytes in patients with multiple sclerosis (MS) with regard to the degree of fatigue, and to investigate relationships between immunological parameters, level of depression and clinical variables. Forty MS patients (30 women, 10 men, aged 22-60 years): 20 fatigued and 20 non-fatigued were involved in the study. Fatigue was evaluated using the Fatigue Severity Scale (FSS) and Modified Fatigue Impact Scale (MFIS), depression level - using Beck Depression Inventory (BDI). Production of IFNγ by stimulated peripheral blood CD3+CD4+ T lymphocytes, assessed using flow cytometry, was compared between MS patients with different levels of fatigue and controls. Correlations were searched out between immunological findings and BDI, age, duration and course of MS, relapse rate, disability (assessed in Expanded Disability Status Scale - EDSS) and its progression. Stimulated production of IFNγ by CD3+CD4+ T lymphocytes was higher in severely fatigued patients in comparison with non-fatigued ones and controls, tended to correlate with FSS and MFIS, and correlated with BDI. No relationships were found between immunological findings and disease-related variables. Stimulated production of IFNγ by peripheral CD3+CD4+ T lymphocytes is related to fatigue and depression in MS patients. Copyright © 2012 Elsevier B.V. All rights reserved.

Weather Variability Associated with Aedes (Stegomyia) aegypti (Dengue Vector) Oviposition Dynamics in Northwestern Argentina

PubMed Central

Estallo, Elizabet L.; Ludueña-Almeida, Francisco F.; Introini, María V.; Zaidenberg, Mario; Almirón, Walter R.

2015-01-01

This study aims to develop a forecasting model by assessing the weather variability associated with seasonal fluctuation of Aedes aegypti oviposition dynamic at a city level in Orán, in northwestern Argentina. Oviposition dynamics were assessed by weekly monitoring of 90 ovitraps in the urban area during 2005-2007. Correlations were performed between the number of eggs collected weekly and weather variables (rainfall, photoperiod, vapor pressure of water, temperature, and relative humidity) with and without time lags (1 to 6 weeks). A stepwise multiple linear regression analysis was performed with the set of meteorological variables from the first year of study with the variables in the time lags that best correlated with the oviposition. Model validation was conducted using the data from the second year of study (October 2006- 2007). Minimum temperature and rainfall were the most important variables. No eggs were found at temperatures below 10°C. The most significant time lags were 3 weeks for minimum temperature and rains, 3 weeks for water vapor pressure, and 6 weeks for maximum temperature. Aedes aegypti could be expected in Orán three weeks after rains with adequate min temperatures. The best-fit forecasting model for the combined meteorological variables explained 70 % of the variance (adj. R2). The correlation between Ae. aegypti oviposition observed and estimated by the forecasting model resulted in rs = 0.80 (P < 0.05). The forecasting model developed would allow prediction of increases and decreases in the Ae. aegypti oviposition activity based on meteorological data for Orán city and, according to the meteorological variables, vector activity can be predicted three or four weeks in advance. PMID:25993415

Model assessment using a multi-metric ranking technique

NASA Astrophysics Data System (ADS)

Fitzpatrick, P. J.; Lau, Y.; Alaka, G.; Marks, F.

2017-12-01

Validation comparisons of multiple models presents challenges when skill levels are similar, especially in regimes dominated by the climatological mean. Assessing skill separation will require advanced validation metrics and identifying adeptness in extreme events, but maintain simplicity for management decisions. Flexibility for operations is also an asset. This work postulates a weighted tally and consolidation technique which ranks results by multiple types of metrics. Variables include absolute error, bias, acceptable absolute error percentages, outlier metrics, model efficiency, Pearson correlation, Kendall's Tau, reliability Index, multiplicative gross error, and root mean squared differences. Other metrics, such as root mean square difference and rank correlation were also explored, but removed when the information was discovered to be generally duplicative to other metrics. While equal weights are applied, weights could be altered depending for preferred metrics. Two examples are shown comparing ocean models' currents and tropical cyclone products, including experimental products. The importance of using magnitude and direction for tropical cyclone track forecasts instead of distance, along-track, and cross-track are discussed. Tropical cyclone intensity and structure prediction are also assessed. Vector correlations are not included in the ranking process, but found useful in an independent context, and will be briefly reported.

Multivariate research in areas of phosphorus cast-iron brake shoes manufacturing using the statistical analysis and the multiple regression equations

NASA Astrophysics Data System (ADS)

Kiss, I.; Cioată, V. G.; Alexa, V.; Raţiu, S. A.

2017-05-01

The braking system is one of the most important and complex subsystems of railway vehicles, especially when it comes for safety. Therefore, installing efficient safe brakes on the modern railway vehicles is essential. Nowadays is devoted attention to solving problems connected with using high performance brake materials and its impact on thermal and mechanical loading of railway wheels. The main factor that influences the selection of a friction material for railway applications is the performance criterion, due to the interaction between the brake block and the wheel produce complex thermos-mechanical phenomena. In this work, the investigated subjects are the cast-iron brake shoes, which are still widely used on freight wagons. Therefore, the cast-iron brake shoes - with lamellar graphite and with a high content of phosphorus (0.8-1.1%) - need a special investigation. In order to establish the optimal condition for the cast-iron brake shoes we proposed a mathematical modelling study by using the statistical analysis and multiple regression equations. Multivariate research is important in areas of cast-iron brake shoes manufacturing, because many variables interact with each other simultaneously. Multivariate visualization comes to the fore when researchers have difficulties in comprehending many dimensions at one time. Technological data (hardness and chemical composition) obtained from cast-iron brake shoes were used for this purpose. In order to settle the multiple correlation between the hardness of the cast-iron brake shoes, and the chemical compositions elements several model of regression equation types has been proposed. Because a three-dimensional surface with variables on three axes is a common way to illustrate multivariate data, in which the maximum and minimum values are easily highlighted, we plotted graphical representation of the regression equations in order to explain interaction of the variables and locate the optimal level of each variable for maximal response. For the calculation of the regression coefficients, dispersion and correlation coefficients, the software Matlab was used.

Correlates of suicide ideation and attempts in children and adolescents with eating disorders.

PubMed

Mayes, Susan Dickerson; Fernandez-Mendoza, Julio; Baweja, Raman; Calhoun, Susan; Mahr, Fauzia; Aggarwal, Richa; Arnold, Mariah

2014-01-01

This is the first study determining correlates of suicide behavior in children with eating disorders using multiple sleep, psychological, and demographic variables. Mothers rated suicide ideation and attempts in 90 children ages 7-18 with bulimia nervosa or anorexia nervosa. Suicide ideation was more prevalent in children with bulimia nervosa (43%) than children with anorexia nervosa (20%). All children with bulimia nervosa who experienced ideation attempted suicide, whereas only 3% of children with anorexia nervosa attempted suicide. Correlates of ideation were externalizing behavior problems and sleep disturbances. Correlates of attempts were bulimia nervosa, self-induced vomiting, nightmares, and physical or sexual abuse. These problems should be assessed and targeted for intervention because of their association with suicide behavior.

Model for predicting the injury severity score.

PubMed

Hagiwara, Shuichi; Oshima, Kiyohiro; Murata, Masato; Kaneko, Minoru; Aoki, Makoto; Kanbe, Masahiko; Nakamura, Takuro; Ohyama, Yoshio; Tamura, Jun'ichi

2015-07-01

To determine the formula that predicts the injury severity score from parameters that are obtained in the emergency department at arrival. We reviewed the medical records of trauma patients who were transferred to the emergency department of Gunma University Hospital between January 2010 and December 2010. The injury severity score, age, mean blood pressure, heart rate, Glasgow coma scale, hemoglobin, hematocrit, red blood cell count, platelet count, fibrinogen, international normalized ratio of prothrombin time, activated partial thromboplastin time, and fibrin degradation products, were examined in those patients on arrival. To determine the formula that predicts the injury severity score, multiple linear regression analysis was carried out. The injury severity score was set as the dependent variable, and the other parameters were set as candidate objective variables. IBM spss Statistics 20 was used for the statistical analysis. Statistical significance was set at P  < 0.05. To select objective variables, the stepwise method was used. A total of 122 patients were included in this study. The formula for predicting the injury severity score (ISS) was as follows: ISS = 13.252-0.078(mean blood pressure) + 0.12(fibrin degradation products). The P -value of this formula from analysis of variance was <0.001, and the multiple correlation coefficient (R) was 0.739 (R 2  = 0.546). The multiple correlation coefficient adjusted for the degrees of freedom was 0.538. The Durbin-Watson ratio was 2.200. A formula for predicting the injury severity score in trauma patients was developed with ordinary parameters such as fibrin degradation products and mean blood pressure. This formula is useful because we can predict the injury severity score easily in the emergency department.

Stress and the Multiple-Role Woman: Taking a Closer Look at the “Superwoman”

PubMed Central

Sumra, Monika K.; Schillaci, Michael A.

2015-01-01

In the academic literature there is debate as to whether women who engage in multiple social roles experience more or less stress than women in fewer roles. For the present research we examined the relationship between levels of engagement in seven distinct roles and perceived stress and life satisfaction in a small non-random sample of women in North America (N = 308). We did not find a significant correlation between role engagement and perceived stress, though we did find a small but significant positive correlation between role engagement and life satisfaction. Similarly, in a subset of the participants (N = 31), there was not a significant relationship between the level of role engagement and physiological stress as measured by hair or urinary cortisol levels. We found a significant negative correlation between perceived stress and life satisfaction, and role satisfaction. The results from multiple regression models did not identify the level of role engagement as a significant predictor of either perceived stress or life satisfaction. Role satisfaction in addition to several life style variables such as the frequency of sex and exercise were identified as significant predictors of both outcome variables. We also examined the popularized notion of the “superwoman”, which we defined as women who fell within the 4th quartile of role engagement, or those engaged in the wife/mother/worker/homemaker role combination. Based on popular discourses surrounding the superwoman we expected that superwomen would exhibit higher levels of perceived stress. Our results revealed that superwomen do not experience a significantly higher level of perceived stress than non-superwomen. The results of our study therefore suggest that multiple role engagement in women, even at a relatively high level as experienced by “superwomen”, is not associated with significantly higher stress, or reduced life satisfaction. PMID:25816317

[Impact of air pollution in paediatric consultations in Primary Health Care: Ecological study].

PubMed

Martín Martín, Raquel; Sánchez Bayle, Marciano

2017-08-09

To study the correlation between the levels of environmental pollutants and the number of paediatric consultations related to respiratory disease in Primary Health Care. An ecological study is performed, in which the dependent variable analysed was the number of paediatric consultations in an urban Primary Health Care centre in Madrid over a 3 year period (2013-2015), and specifically the consultations related to bronchiolitis, recurrent bronchospasm, and upper respiratory diseases. The independent variables analysed were the levels of environmental pollutants. Coefficients of correlation and multiple lineal regressions were calculated. An analysis has been carried out comparing the average of paediatric consultations when the levels of nitrogen dioxide (NO 2 ) were higher and lower than 40μg/m 3. RESULTS: During the period of the study, there were a total of 52,322 paediatric consultations in the health centre, of which 6,473 (12.37%) were related to respiratory diseases. A positive correlation was found between SO 2 , CO, NOx and NO 2 and benzene levels and paediatric consultations related to respiratory diseases, and a negative correlation with temperature. The number of consultations was significantly higher when NO 2 levels exceeded 40μg/m 3 . In the multiple lineal regression (P=.0001), the correlation was only positive between consultations and NO 2 levels (3.630, 95% CI: 0.691-6.570), and negative with temperature (-5,957, 95% CI: -8.665 to -3.248). NO 2 environmental pollution is related to an increase in respiratory diseases in children. Paediatricians should contribute to promote an improvement in urban air quality as a significant preventive measure. Copyright © 2017. Publicado por Elsevier España, S.L.U.

Bibliometric Analysis of Manuscript Characteristics That Influence Citations: A Comparison of Six Major Radiology Journals.

PubMed

Shekhani, Haris Naseem; Shariff, Shoaib; Bhulani, Nizar; Khosa, Faisal; Hanna, Tarek Noel

2017-12-01

The objective of our study was to investigate radiology manuscript characteristics that influence citation rate, capturing features of manuscript construction that are discrete from study design. Consecutive articles published from January 2004 to June 2004 were collected from the six major radiology journals with the highest impact factors: Radiology (impact factor, 5.076), Investigative Radiology (2.320), American Journal of Neuroradiology (AJNR) (2.384), RadioGraphics (2.494), European Radiology (2.364), and American Journal of Roentgenology (2.406). The citation count for these articles was retrieved from the Web of Science, and 29 article characteristics were tabulated manually. A point-biserial correlation, Spearman rank-order correlation, and multiple regression model were performed to predict citation number from the collected variables. A total of 703 articles-211 published in Radiology, 48 in Investigative Radiology, 106 in AJNR, 52 in RadioGraphics, 129 in European Radiology, and 157 in AJR-were evaluated. Punctuation was included in the title in 55% of the articles and had the highest statistically significant positive correlation to citation rate (point-biserial correlation coefficient [r pb ] = 0.85, p < 0.05). Open access status provided a low-magnitude, but significant, correlation to citation rate (r pb = 0.140, p < 0.001). The following variables created a significant multiple regression model to predict citation count (p < 0.005, R 2 = 0.186): study findings in the title, abstract word count, abstract character count, total number of words, country of origin, and all authors in the field of radiology. Using bibliometric knowledge, authors can craft a title, abstract, and text that may enhance visibility and citation count over what they would otherwise experience.

High-speed limnology: using advanced sensors to investigate spatial variability in biogeochemistry and hydrology.

PubMed

Crawford, John T; Loken, Luke C; Casson, Nora J; Smith, Colin; Stone, Amanda G; Winslow, Luke A

2015-01-06

Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h(-1)) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial-aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.

High-speed limnology: Using advanced sensors to investigate spatial variability in biogeochemistry and hydrology

USGS Publications Warehouse

Crawford, John T.; Loken, Luke C.; Casson, Nora J.; Smith, Collin; Stone, Amanda G.; Winslow, Luke A.

2015-01-01

Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h–1) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial–aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.

Balancing precision and risk: should multiple detection methods be analyzed separately in N-mixture models?

USGS Publications Warehouse

Graves, Tabitha A.; Royle, J. Andrew; Kendall, Katherine C.; Beier, Paul; Stetz, Jeffrey B.; Macleod, Amy C.

2012-01-01

Using multiple detection methods can increase the number, kind, and distribution of individuals sampled, which may increase accuracy and precision and reduce cost of population abundance estimates. However, when variables influencing abundance are of interest, if individuals detected via different methods are influenced by the landscape differently, separate analysis of multiple detection methods may be more appropriate. We evaluated the effects of combining two detection methods on the identification of variables important to local abundance using detections of grizzly bears with hair traps (systematic) and bear rubs (opportunistic). We used hierarchical abundance models (N-mixture models) with separate model components for each detection method. If both methods sample the same population, the use of either data set alone should (1) lead to the selection of the same variables as important and (2) provide similar estimates of relative local abundance. We hypothesized that the inclusion of 2 detection methods versus either method alone should (3) yield more support for variables identified in single method analyses (i.e. fewer variables and models with greater weight), and (4) improve precision of covariate estimates for variables selected in both separate and combined analyses because sample size is larger. As expected, joint analysis of both methods increased precision as well as certainty in variable and model selection. However, the single-method analyses identified different variables and the resulting predicted abundances had different spatial distributions. We recommend comparing single-method and jointly modeled results to identify the presence of individual heterogeneity between detection methods in N-mixture models, along with consideration of detection probabilities, correlations among variables, and tolerance to risk of failing to identify variables important to a subset of the population. The benefits of increased precision should be weighed against those risks. The analysis framework presented here will be useful for other species exhibiting heterogeneity by detection method.

Are Predictive Equations for Estimating Resting Energy Expenditure Accurate in Asian Indian Male Weightlifters?

PubMed

Joseph, Mini; Gupta, Riddhi Das; Prema, L; Inbakumari, Mercy; Thomas, Nihal

2017-01-01

The accuracy of existing predictive equations to determine the resting energy expenditure (REE) of professional weightlifters remains scarcely studied. Our study aimed at assessing the REE of male Asian Indian weightlifters with indirect calorimetry and to compare the measured REE (mREE) with published equations. A new equation using potential anthropometric variables to predict REE was also evaluated. REE was measured on 30 male professional weightlifters aged between 17 and 28 years using indirect calorimetry and compared with the eight formulas predicted by Harris-Benedicts, Mifflin-St. Jeor, FAO/WHO/UNU, ICMR, Cunninghams, Owen, Katch-McArdle, and Nelson. Pearson correlation coefficient, intraclass correlation coefficient, and multiple linear regression analysis were carried out to study the agreement between the different methods, association with anthropometric variables, and to formulate a new prediction equation for this population. Pearson correlation coefficients between mREE and the anthropometric variables showed positive significance with suprailiac skinfold thickness, lean body mass (LBM), waist circumference, hip circumference, bone mineral mass, and body mass. All eight predictive equations underestimated the REE of the weightlifters when compared with the mREE. The highest mean difference was 636 kcal/day (Owen, 1986) and the lowest difference was 375 kcal/day (Cunninghams, 1980). Multiple linear regression done stepwise showed that LBM was the only significant determinant of REE in this group of sportspersons. A new equation using LBM as the independent variable for calculating REE was computed. REE for weightlifters = -164.065 + 0.039 (LBM) (confidence interval -1122.984, 794.854]. This new equation reduced the mean difference with mREE by 2.36 + 369.15 kcal/day (standard error = 67.40). The significant finding of this study was that all the prediction equations underestimated the REE. The LBM was the sole determinant of REE in this population. In the absence of indirect calorimetry, the REE equation developed by us using LBM is a better predictor for calculating REE of professional male weightlifters of this region.

Tumble Graphs: Avoiding Misleading End Point Extrapolation When Graphing Interactions From a Moderated Multiple Regression Analysis

ERIC Educational Resources Information Center

Bodner, Todd E.

2016-01-01

This article revisits how the end points of plotted line segments should be selected when graphing interactions involving a continuous target predictor variable. Under the standard approach, end points are chosen at ±1 or 2 standard deviations from the target predictor mean. However, when the target predictor and moderator are correlated or the…

Probabilistic Based Modeling and Simulation Assessment

DTIC Science & Technology

2010-06-01

different crash and blast scenarios. With the integration of the high fidelity neck and head model, a methodology to calculate the probability of injury...variability, correlation, and multiple (often competing) failure metrics. Important scenarios include vehicular collisions, blast /fragment impact, and...first area of focus is to develop a methodology to integrate probabilistic analysis into finite element analysis of vehicle collisions and blast . The

Probabilistic-Based Modeling and Simulation Assessment

DTIC Science & Technology

2010-06-01

developed to determine the relative importance of structural components of the vehicle under differnet crash and blast scenarios. With the integration of...the vehicle under different crash and blast scenarios. With the integration of the high fidelity neck and head model, a methodology to calculate the...parameter variability, correlation, and multiple (often competing) failure metrics. Important scenarios include vehicular collisions, blast /fragment

Stature estimation from the lengths of the growing foot-a study on North Indian adolescents.

PubMed

Krishan, Kewal; Kanchan, Tanuj; Passi, Neelam; DiMaggio, John A

2012-12-01

Stature estimation is considered as one of the basic parameters of the investigation process in unknown and commingled human remains in medico-legal case work. Race, age and sex are the other parameters which help in this process. Stature estimation is of the utmost importance as it completes the biological profile of a person along with the other three parameters of identification. The present research is intended to formulate standards for stature estimation from foot dimensions in adolescent males from North India and study the pattern of foot growth during the growing years. 154 male adolescents from the Northern part of India were included in the study. Besides stature, five anthropometric measurements that included the length of the foot from each toe (T1, T2, T3, T4, and T5 respectively) to pternion were measured on each foot. The data was analyzed statistically using Student's t-test, Pearson's correlation, linear and multiple regression analysis for estimation of stature and growth of foot during ages 13-18 years. Correlation coefficients between stature and all the foot measurements were found to be highly significant and positively correlated. Linear regression models and multiple regression models (with age as a co-variable) were derived for estimation of stature from the different measurements of the foot. Multiple regression models (with age as a co-variable) estimate stature with greater accuracy than the regression models for 13-18 years age group. The study shows the growth pattern of feet in North Indian adolescents and indicates that anthropometric measurements of the foot and its segments are valuable in estimation of stature in growing individuals of that population. Copyright © 2012 Elsevier Ltd. All rights reserved.

Epigenetic Variation in the Mu-opioid Receptor Gene in Infants with Neonatal Abstinence Syndrome

PubMed Central

Wachman, Elisha M; Hayes, Marie J; Lester, Barry M; Terrin, Norma; Brown, Mark S; Nielsen, David A; Davis, Jonathan M

2014-01-01

Objective Neonatal abstinence syndrome (NAS) from in utero opioid exposure is highly variable with genetic factors appearing to play an important role. Epigenetic changes in cytosine:guanine (CpG) dinucleotide methylation can occur after drug exposure and may help to explain NAS variability. We correlated DNA methylation levels in the mu-opioid receptor (OPRM1) promoter in opioid-exposed infants and correlate them with NAS outcomes. Study design DNA samples from cord blood or saliva were analyzed for 86 infants being treated for NAS according to institutional protocol. Methylation levels at 16 OPRM1 CpG sites were determined and correlated with NAS outcome measures, including need for treatment, treatment with >2 medications, and length of hospital stay. We adjusted for co-variates and multiple genetic testing. Results Sixty-five percent of infants required treatment for NAS, and 24% required ≥2 medications. Hypermethylation of the OPRM1 promoter was measured at the −10 CpG in treated versus non-treated infants [adjusted difference δ=3.2% (95% CI 0.3–6.0%), p=0.03; NS after multiple testing correction]. There was hypermethylation at the −14 [δ=4.9% (95% CI 1.8–8.1%), p=0.003], −10 [δ=5.0% (95% CI 2.3–7.7%), p=0.0005)], and +84 [δ=3.5% (95% CI 0.6 – 6.4), p=0.02] CpG sites in infants requiring ≥2 medications which remained significant for −14 and −10 after multiple testing correction. Conclusions Increased methylation within the OPRM1 promoter is associated with worse NAS outcomes, consistent with gene silencing. PMID:24996986

Bayesian Group Bridge for Bi-level Variable Selection.

PubMed

Mallick, Himel; Yi, Nengjun

2017-06-01

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

Basic properties and variability

NASA Technical Reports Server (NTRS)

Querci, Francois R.

1987-01-01

Giant and supergiant M, S, and C stars are discussed in this survey of research. Basic properties as determined by spectra, chemical composition, photometry, or variability type are discussed. Space motions and space distributions of cool giants are described. Distribution of these stars in our galaxy and those nearby is discussed. Mira variables in particular are surveyed with emphasis on the following topics: (1) phase lag phenomenon; (2) Mira light curves; (3) variations in color indices; (4) determination of multiple periods; (5) correlations between quantities such as period length, light-curve shape, infrared (IR) excess, and visible and IR color diagram; (6) semiregular (SR) variables and different time scales in SR light variations; (7) irregular variable Lb and Lc stars; (8) different time-scale light variations; (9) hydrogen-deficient carbon (HdC) stars, in particular RCB stars; and (10) irreversible changes and rapid evolution in red variable stars.

Perceptual Decision-Making as Probabilistic Inference by Neural Sampling.

PubMed

Haefner, Ralf M; Berkes, Pietro; Fiser, József

2016-05-04

We address two main challenges facing systems neuroscience today: understanding the nature and function of cortical feedback between sensory areas and of correlated variability. Starting from the old idea of perception as probabilistic inference, we show how to use knowledge of the psychophysical task to make testable predictions for the influence of feedback signals on early sensory representations. Applying our framework to a two-alternative forced choice task paradigm, we can explain multiple empirical findings that have been hard to account for by the traditional feedforward model of sensory processing, including the task dependence of neural response correlations and the diverging time courses of choice probabilities and psychophysical kernels. Our model makes new predictions and characterizes a component of correlated variability that represents task-related information rather than performance-degrading noise. It demonstrates a normative way to integrate sensory and cognitive components into physiologically testable models of perceptual decision-making. Copyright © 2016 Elsevier Inc. All rights reserved.

Influence of weather and climate on subjective symptom intensity in atopic eczema

NASA Astrophysics Data System (ADS)

Vocks, E.; Busch, R.; Fröhlich, C.; Borelli, S.; Mayer, H.; Ring, J.

The frequent clinical observation that the course of atopic eczema, a skin disease involving a disturbed cutaneous barrier function, is influenced by climate and weather motivated us to analyse these relationships biometrically. In the Swiss high-mountain area of Davos the intensity of itching experienced by patients with atopic eczema was evaluated and compared to 15 single meteorological variables recorded daily during an entire 7-year observation period. By means of univariate analyses and multiple regressions, itch intensity was found to be correlated with some meteorological variables. A clear-cut inverse correlation exists with air temperature (coefficient of correlation: -0.235, P<0.001), but the effects of water vapour pressure, air pressure and hours of sunshine are less pronounced. The results show that itching in atopic eczema is significantly dependent on meteorological conditions. The data suggest that, in patients with atopic eczema, a certain range of thermo-hygric atmospheric conditions with a balance of heat and water loss on the skin surface is essential for the skin to feel comfortable.

[Correlations Between Joint Proprioception, Muscle Strength, and Functional Ability in Patients with Knee Osteoarthritis].

PubMed

Chen, Yoa; Yu, Yong; He, Cheng-qi

2015-11-01

To establish correlations between joint proprioception, muscle flexion and extension peak torque, and functional ability in patients with knee osteoarthritis (OA). Fifty-six patients with symptomatic knee OA were recruited in this study. Both proprioceptive acuity and muscle strength were measured using the isomed-2000 isokinetic dynamometer. Proprioceptive acuity was evaluated by establishing the joint motion detection threshold (JMDT). Muscle strength was evaluated by Max torque (Nm) and Max torque/weight (Nm/ kg). Functional ability was assessed by the Western Ontario and McMaster Universities Osteoarthritis Index physical function (WOMAC-PF) questionnaire. Correlational analyses were performed between proprioception, muscle strength, and functional ability. A multiple stepwise regression model was established, with WOMAC-PF as dependent variable and patient age, body mass index (BMI), visual analogue scale (VAS)-score, mean grade for Kellgren-Lawrance of both knees, mean strength for quadriceps and hamstring muscles of both knees, and mean JMDT of both knees as independent variables. Poor proprioception (high JMDT) was negatively correlated with muscle strength (P<0.05). There was no significant correlation between knee proprioception (high JMDT) and joint pain (WOMAC pain score), and between knee proprioception (high JMDT) and joint stiffness (WOMAC stiffness score). Poor proprioception (high JMDT) was correlated with limitation in functional ability (WOMAC physical function score r=0.659, P<0.05). WOMAC score was correlated with poor muscle strength (quadriceps muscle strength r = -0.511, P<0.05, hamstring muscle strength r = -0.408, P<0.05). The multiple stepwise regression model showed that high JMDT C standard partial regression coefficient (B) = 0.385, P<0.50 and high VAS-scale score (B=0.347, P<0.05) were significant predictors of WOMAC-PF score. Patients with poor proprioception is associated with poor muscle strength and limitation in functional ability. Patients with symptomatic OA of knees commonly endure with moderate to considerable dysfunction, which is associated with poor proprioception (high JMDT) and high VAS-scale score.

Multiple endocrine neoplasia type 1: analysis of germline MEN1 mutations in the Italian multicenter MEN1 patient database.

PubMed

Marini, Francesca; Giusti, Francesca; Fossi, Caterina; Cioppi, Federica; Cianferotti, Luisella; Masi, Laura; Boaretto, Francesca; Zovato, Stefania; Cetani, Filomena; Colao, Annamaria; Davì, Maria Vittoria; Faggiano, Antongiulio; Fanciulli, Giuseppe; Ferolla, Piero; Ferone, Diego; Loli, Paola; Mantero, Franco; Marcocci, Claudio; Opocher, Giuseppe; Beck-Peccoz, Paolo; Persani, Luca; Scillitani, Alfredo; Guizzardi, Fabiana; Spada, Anna; Tomassetti, Paola; Tonelli, Francesco; Brandi, Maria Luisa

2018-03-01

Multiple endocrine neoplasia type 1 (MEN1) is caused by germline inactivating mutations of the MEN1 gene. Currently, no direct genotype-phenotype correlation is identified. We aim to analyze MEN1 mutation site and features, and possible correlations between the mutation type and/or the affected menin functional domain and clinical presentation in patients from the Italian multicenter MEN1 database, one of the largest worldwide MEN1 mutation series published to date. The study included the analysis of MEN1 mutation profile in 410 MEN1 patients [370 familial cases from 123 different pedigrees (48 still asymptomatic at the time of this study) and 40 single cases]. We identified 99 different mutations: 41 frameshift [small intra-exon deletions (28) or insertions (13)], 13 nonsense, 26 missense and 11 splicing site mutations, 4 in-frame small deletions, and 4 intragenic large deletions spanning more than one exon. One family had two different inactivating MEN1 mutations on the same allele. Gastro-entero-pancreatic tumors resulted more frequent in patients with a nonsense mutation, and thoracic neuroendocrine tumors in individuals bearing a splicing-site mutation. Our data regarding mutation type frequency and distribution are in accordance with previously published data: MEN1 mutations are scattered through the entire coding region, and truncating mutations are the most common in MEN1 syndrome. A specific direct correlation between MEN1 genotype and clinical phenotype was not found in all our families, and wide intra-familial clinical variability and variable disease penetrance were both confirmed, suggesting a role for modifying, still undetermined, factors, explaining the variable MEN1 tumorigenesis.

Intrinsic vs. spurious long-range memory in high-frequency records of environmental radioactivity. Critical re-assessment and application to indoor 222Rn concentrations from Coimbra, Portugal

NASA Astrophysics Data System (ADS)

Donner, R. V.; Potirakis, S. M.; Barbosa, S. M.; Matos, J. A. O.; Pereira, A. J. S. C.; Neves, L. J. P. F.

2015-05-01

The presence or absence of long-range correlations in the environmental radioactivity fluctuations has recently attracted considerable interest. Among a multiplicity of practically relevant applications, identifying and disentangling the environmental factors controlling the variable concentrations of the radioactive noble gas radon is important for estimating its effect on human health and the efficiency of possible measures for reducing the corresponding exposition. In this work, we present a critical re-assessment of a multiplicity of complementary methods that have been previously applied for evaluating the presence of long-range correlations and fractal scaling in environmental radon variations with a particular focus on the specific properties of the underlying time series. As an illustrative case study, we subsequently re-analyze two high-frequency records of indoor radon concentrations from Coimbra, Portugal, each of which spans several weeks of continuous measurements at a high temporal resolution of five minutes.Our results reveal that at the study site, radon concentrations exhibit complex multi-scale dynamics with qualitatively different properties at different time-scales: (i) essentially white noise in the high-frequency part (up to time-scales of about one hour), (ii) spurious indications of a non-stationary, apparently long-range correlated process (at time scales between some hours and one day) arising from marked periodic components, and (iii) low-frequency variability indicating a true long-range dependent process. In the presence of such multi-scale variability, common estimators of long-range memory in time series are prone to fail if applied to the raw data without previous separation of time-scales with qualitatively different dynamics.

The Geomagnetic Field and Correlations with Multiple Sclerosis: A Possible Etiology of Disease

NASA Astrophysics Data System (ADS)

Wade, Brett

Multiple sclerosis (MS) is a complex autoimmune disease that results in a demyelinating process of the central nervous system. It is the most common, progressive, neurological disease affecting young adults, and there is no cure. A curious feature of MS is its distinct global prevalence with high rates of occurrence between 40 and 60 degrees latitude. While genetics may partially explain this phenomenon, studies have shown that the influence of genetics is modest. Many non-genetic variables, such as viruses, vitamin D, smoking, diet, hormones, etc., have been shown to be related to the expression of MS but none of these variables have been determined to be necessarily strong enough to exclude other factors. The geomagnetic field, which is a non-uniform, three dimensional entity which protects all living things from ionizing radiation, is suggested in this research to be related to global MS prevalence. This study hypothesized that either the total field, the vertical field, or the horizontal field strength of the geomagnetic field will be correlated with MS. Using secondary sources of prevalence studies (N=131) and geomagnetic data, the results supported all three hypotheses with the strongest correlation being an inverse relationship between the horizontal field and MS (r = -.607). The explanation for the inverse relationship being most strongly correlated with MS prevalence is explained by the fact that the horizontal aspect of the geomagnetic field has a protective effect from incoming cosmic radiation. Chronic exposure to high levels of background radiation can have deleterious health effects. This research suggests that living in areas of a weak horizontal field increases a person's exposure to ionizing radiation and therefore increases the risk for developing MS. While it was not the intention of this research, it became clear that an explanation which explained the results of this research and also attempted to unify the mechanisms of all non-genetic variables was prudent. A Unified Theory of MS Disease Expression is presented in this research.

Sources of variability in satellite-derived estimates of phytoplankton production in the eastern tropical Pacific

NASA Technical Reports Server (NTRS)

Banse, Karl; Yong, Marina

1990-01-01

As a proxy for satellite CZCS observations and concurrent measurements of primary production rates, data from 138 stations occupied seasonally during 1967-1968 in the offshore eastern tropical Pacific were analyzed in terms of six temporal groups and our current regimes. Multiple linear regressions on column production Pt show that simulated satellite pigment is generally weakly correlated, but sometimes not correlated with Pt, and that incident irradiance, sea surface temperature, nitrate, transparency, and depths of mixed layer or nitracline assume little or no importance. After a proxy for the light-saturated chlorophyll-specific photosynthetic rate P(max) is added, the coefficient of determination ranges from 0.55 to 0.91 (median of 0.85) for the 10 cases. In stepwise multiple linear regressions the P(max) proxy is the best predictor for Pt.

Prediction of hearing outcomes by multiple regression analysis in patients with idiopathic sudden sensorineural hearing loss.

PubMed

Suzuki, Hideaki; Tabata, Takahisa; Koizumi, Hiroki; Hohchi, Nobusuke; Takeuchi, Shoko; Kitamura, Takuro; Fujino, Yoshihisa; Ohbuchi, Toyoaki

2014-12-01

This study aimed to create a multiple regression model for predicting hearing outcomes of idiopathic sudden sensorineural hearing loss (ISSNHL). The participants were 205 consecutive patients (205 ears) with ISSNHL (hearing level ≥ 40 dB, interval between onset and treatment ≤ 30 days). They received systemic steroid administration combined with intratympanic steroid injection. Data were examined by simple and multiple regression analyses. Three hearing indices (percentage hearing improvement, hearing gain, and posttreatment hearing level [HLpost]) and 7 prognostic factors (age, days from onset to treatment, initial hearing level, initial hearing level at low frequencies, initial hearing level at high frequencies, presence of vertigo, and contralateral hearing level) were included in the multiple regression analysis as dependent and explanatory variables, respectively. In the simple regression analysis, the percentage hearing improvement, hearing gain, and HLpost showed significant correlation with 2, 5, and 6 of the 7 prognostic factors, respectively. The multiple correlation coefficients were 0.396, 0.503, and 0.714 for the percentage hearing improvement, hearing gain, and HLpost, respectively. Predicted values of HLpost calculated by the multiple regression equation were reliable with 70% probability with a 40-dB-width prediction interval. Prediction of HLpost by the multiple regression model may be useful to estimate the hearing prognosis of ISSNHL. © The Author(s) 2014.

Fast and Accurate Approximation to Significance Tests in Genome-Wide Association Studies

PubMed Central

Zhang, Yu; Liu, Jun S.

2011-01-01

Genome-wide association studies commonly involve simultaneous tests of millions of single nucleotide polymorphisms (SNP) for disease association. The SNPs in nearby genomic regions, however, are often highly correlated due to linkage disequilibrium (LD, a genetic term for correlation). Simple Bonferonni correction for multiple comparisons is therefore too conservative. Permutation tests, which are often employed in practice, are both computationally expensive for genome-wide studies and limited in their scopes. We present an accurate and computationally efficient method, based on Poisson de-clumping heuristics, for approximating genome-wide significance of SNP associations. Compared with permutation tests and other multiple comparison adjustment approaches, our method computes the most accurate and robust p-value adjustments for millions of correlated comparisons within seconds. We demonstrate analytically that the accuracy and the efficiency of our method are nearly independent of the sample size, the number of SNPs, and the scale of p-values to be adjusted. In addition, our method can be easily adopted to estimate false discovery rate. When applied to genome-wide SNP datasets, we observed highly variable p-value adjustment results evaluated from different genomic regions. The variation in adjustments along the genome, however, are well conserved between the European and the African populations. The p-value adjustments are significantly correlated with LD among SNPs, recombination rates, and SNP densities. Given the large variability of sequence features in the genome, we further discuss a novel approach of using SNP-specific (local) thresholds to detect genome-wide significant associations. This article has supplementary material online. PMID:22140288

Temporal and spatial patterns of wetland extent influence variability of surface water connectivity in the Prairie Pothole Region, United States

USGS Publications Warehouse

Vanderhoof, Melanie; Alexander, Laurie C.; Todd, Jason

2016-01-01

Context. Quantifying variability in landscape-scale surface water connectivity can help improve our understanding of the multiple effects of wetlands on downstream waterways. Objectives. We examined how wetland merging and the coalescence of wetlands with streams varied both spatially (among ecoregions) and interannually (from drought to deluge) across parts of the Prairie Pothole Region. Methods. Wetland extent was derived over a time series (1990-2011) using Landsat imagery. Changes in landscape-scale connectivity, generated by the physical coalescence of wetlands with other surface water features, were quantified by fusing static wetland and stream datasets with Landsat-derived wetland extent maps, and related to multiple wetness indices. The usage of Landsat allows for decadal-scale analysis, but limits the types of surface water connections that can be detected. Results. Wetland extent correlated positively with the merging of wetlands and wetlands with streams. Wetness conditions, as defined by drought indices and runoff, were positively correlated with wetland extent, but less consistently correlated with measures of surface water connectivity. The degree of wetland-wetland merging was found to depend less on total wetland area or density, and more on climate conditions, as well as the threshold for how wetland/upland was defined. In contrast, the merging of wetlands with streams was positively correlated with stream density, and inversely related to wetland density. Conclusions. Characterizing the degree of surface water connectivity within the Prairie Pothole Region in North America requires consideration of 1) climate-driven variation in wetness conditions and 2) within-region variation in wetland and stream spatial arrangements.

Multiple regression equations modelling of groundwater of Ajmer-Pushkar railway line region, Rajasthan (India).

PubMed

Mathur, Praveen; Sharma, Sarita; Soni, Bhupendra

2010-01-01

In the present work, an attempt is made to formulate multiple regression equations using all possible regressions method for groundwater quality assessment of Ajmer-Pushkar railway line region in pre- and post-monsoon seasons. Correlation studies revealed the existence of linear relationships (r 0.7) for electrical conductivity (EC), total hardness (TH) and total dissolved solids (TDS) with other water quality parameters. The highest correlation was found between EC and TDS (r = 0.973). EC showed highly significant positive correlation with Na, K, Cl, TDS and total solids (TS). TH showed highest correlation with Ca and Mg. TDS showed significant correlation with Na, K, SO4, PO4 and Cl. The study indicated that most of the contamination present was water soluble or ionic in nature. Mg was present as MgCl2; K mainly as KCl and K2SO4, and Na was present as the salts of Cl, SO4 and PO4. On the other hand, F and NO3 showed no significant correlations. The r2 values and F values (at 95% confidence limit, alpha = 0.05) for the modelled equations indicated high degree of linearity among independent and dependent variables. Also the error % between calculated and experimental values was contained within +/- 15% limit.

Population Analysis of Disabled Children by Departments in France

NASA Astrophysics Data System (ADS)

Meidatuzzahra, Diah; Kuswanto, Heri; Pech, Nicolas; Etchegaray, Amélie

2017-06-01

In this study, a statistical analysis is performed by model the variations of the disabled about 0-19 years old population among French departments. The aim is to classify the departments according to their profile determinants (socioeconomic and behavioural profiles). The analysis is focused on two types of methods: principal component analysis (PCA) and multiple correspondences factorial analysis (MCA) to review which one is the best methods for interpretation of the correlation between the determinants of disability (independent variable). The PCA is the best method for interpretation of the correlation between the determinants of disability (independent variable). The PCA reduces 14 determinants of disability to 4 axes, keeps 80% of total information, and classifies them into 7 classes. The MCA reduces the determinants to 3 axes, retains only 30% of information, and classifies them into 4 classes.

The Relationship of Clinical Nurses' Perceptions of Structural and Psychological Empowerment and Engagement on Their Unit.

PubMed

DiNapoli, Jean Marie; O'Flaherty, Deirdre; Musil, Carol; Clavelle, Joanne T; Fitzpatrick, Joyce J

2016-02-01

The purpose of this study was to describe relationships between structural empowerment, psychological empowerment, and engagement among clinical nurses. Empowerment and engagement are key drivers of retention and quality in healthcare. Creating an empowering culture and an engaged staff supports initiatives that are essential for positive work environments. A survey of 280 nurses in a national conference was conducted using the Conditions of Work Effectiveness, Psychological Empowerment Instrument, and the Utrecht Work Engagement Scale. Pearson correlation coefficients and multiple regression analysis were used to determine relationships between demographic data and study variables. Overall, nurses had high perceptions of structural empowerment and psychological empowerment and were moderately engaged. Also, significant positive relationships were found between the key study variables. Results show positive correlations between empowerment and perceived engagement among clinical nurses.

Temporal Patterns and Environmental Correlates of Macroinvertebrate Communities in Temporary Streams.

PubMed

Botwe, Paul K; Barmuta, Leon A; Magierowski, Regina; McEvoy, Paul; Goonan, Peter; Carver, Scott

2015-01-01

Temporary streams are characterised by short periods of seasonal or annual stream flow after which streams contract into waterholes or pools of varying hydrological connectivity and permanence. Although these streams are widespread globally, temporal variability of their ecology is understudied, and understanding the processes that structure community composition in these systems is vital for predicting and managing the consequences of anthropogenic impacts. We used multivariate and univariate approaches to investigate temporal variability in macroinvertebrate compositional data from 13 years of sampling across multiple sites from autumn and spring, in South Australia, the driest state in the driest inhabited continent in the world. We examined the potential of land-use, geographic and environmental variables to predict the temporal variability in macroinvertebrate assemblages, and also identified indicator taxa, that is, those highly correlated with the most significantly associated physical variables. Temporal trajectories of macroinvertebrate communities varied within site in both seasons and across years. A combination of land-use, geographic and environmental variables accounted for 24% of the variation in community structure in autumn and 27% in spring. In autumn, community composition among sites were more closely clustered together relative to spring suggesting that communities were more similar in autumn than in spring. In both seasons, community structure was most strongly correlated with conductivity and latitude, and community structure was more associated with cover by agriculture than urban land-use. Maintaining temporary streams will require improved catchment management aimed at sustaining seasonal flows and critical refuge habitats, while also limiting the damaging effects from increased agriculture and urban developments.

Temporal Patterns and Environmental Correlates of Macroinvertebrate Communities in Temporary Streams

PubMed Central

Botwe, Paul K.; Barmuta, Leon A.; Magierowski, Regina; McEvoy, Paul; Goonan, Peter; Carver, Scott

2015-01-01

Temporary streams are characterised by short periods of seasonal or annual stream flow after which streams contract into waterholes or pools of varying hydrological connectivity and permanence. Although these streams are widespread globally, temporal variability of their ecology is understudied, and understanding the processes that structure community composition in these systems is vital for predicting and managing the consequences of anthropogenic impacts. We used multivariate and univariate approaches to investigate temporal variability in macroinvertebrate compositional data from 13 years of sampling across multiple sites from autumn and spring, in South Australia, the driest state in the driest inhabited continent in the world. We examined the potential of land-use, geographic and environmental variables to predict the temporal variability in macroinvertebrate assemblages, and also identified indicator taxa, that is, those highly correlated with the most significantly associated physical variables. Temporal trajectories of macroinvertebrate communities varied within site in both seasons and across years. A combination of land-use, geographic and environmental variables accounted for 24% of the variation in community structure in autumn and 27% in spring. In autumn, community composition among sites were more closely clustered together relative to spring suggesting that communities were more similar in autumn than in spring. In both seasons, community structure was most strongly correlated with conductivity and latitude, and community structure was more associated with cover by agriculture than urban land-use. Maintaining temporary streams will require improved catchment management aimed at sustaining seasonal flows and critical refuge habitats, while also limiting the damaging effects from increased agriculture and urban developments. PMID:26556711

Science Teaching Efficacy of Preservice Elementary Teachers: Examination of the Multiple Factors Reported as Influential

NASA Astrophysics Data System (ADS)

Taştan Kırık, Özgecan

2013-12-01

This study explores the science teaching efficacy beliefs of pr-service elementary teachers and the relationship between efficacy beliefs and multiple factors such as antecedent factors (participation in extracurricular activities and number of science and science teaching methods courses taken), conceptual understanding, classroom management beliefs and science teaching attitudes. Science education majors ( n = 71) and elementary education majors ( n = 262) were compared with respect to these variables. Finally, the predictors of two constructs of science teaching efficacy beliefs, personal science teaching efficacy (PSTE) and science teaching outcome expectancy (STOE), were examined by multiple linear regression analysis. According to the results, participation in extracurricular activities has a significant but low correlation with science concept knowledge, science teaching attitudes, PSTE and STOE. In addition, there is a small but significant correlation between science concept knowledge and outcome expectancy, which leads the idea that preservice elementary teachers' conceptual understanding in science contributes to their science teaching self-efficacy. This study reveals a moderate correlation between science teaching attitudes and STOE and a high correlation between science teaching attitudes and PSTE. Additionally, although the correlation coefficient is low, the number of methodology courses was found to be one of the correlates of science teaching attitudes. Furthermore, students of both majors generally had positive self-efficacy beliefs on both the STOE and PSTE. Specifically, science education majors had higher science teaching self-efficacy than elementary education majors. Regression results showed that science teaching attitude is the major factor in predicting both PSTE and STOE for both groups.

Determinants of Lifestyle Behavior in Iranian Adults with Prediabetes: Applying the Theory of Planned Behavior.

PubMed

Rahmati-Najarkolaei, Fatemeh; Pakpour, Amir H; Saffari, Mohsen; Hosseini, Mahboobeh Sadat; Hajizadeh, Fereshteh; Chen, Hui; Yekaninejad, Mir Saeed

2017-04-01

Prediabetic condition can lead to development of type 2 diabetes, especially in individuals who do not adhere to a healthy lifestyle. The aim of the present study was to investigate the socio-cognitive factors using the Theory of Planned Behavior (TPB) that may be associated with the choice of lifestyle in prediabetic patients. A prospective study with one-month follow up was designed to collect data from 350 individuals with prediabetic conditions. A questionnaire was used to collect the information, including demographic variables, exercise behavior, food consumption, as well as the constructs of the TPB (attitude, subjective norms, perceived behavioral control, and behavioral intention) regarding physical activity and dietary choice. The correlations between TPB variables and the dependent variables (dietary choice, physical activity) were assessed using Spearman correlation and multiple regression models. In total, 303 people participated. The mean age of the participants was 53.0 (SD 11.5) years and 42% were males. Significant correlations were found between all TPB constructs and both dependent variables (healthy eating and exercise behaviors) both at baseline and after one month (P < 0.01). The predictive validity of the TPB over time was proved for both dependent variables where past and future behaviors were significantly correlated with the constructs. Nearly 87% of the variance in exercise behavior and 72% of the variance in healthy eating behavior were explainable by TPB constructs. The TPB may be a useful model to predict behaviors of physical activity and dietary choice among prediabetic people. Therefore, it may be used to monitor lifestyle modification to prevent development of diabetes among people with prediabetic conditions.

Clinical Performance and Admission Variables as Predictors of Passage of the National Physical Therapy Examination.

PubMed

Meiners, Kelly M; Rush, Douglas K

2017-01-01

Prior studies have explored variables that had predictive relationships with National Physical Therapy Examination (NPTE) score or NPTE failure. The purpose of this study was to explore whether certain variables were predictive of test-takers' first-time score on the NPTE. The population consisted of 134 students who graduated from the university's Professional DPT Program in 2012 to 2014. This quantitative study used a retrospective design. Two separate data analyses were conducted. First, hierarchical linear multiple regression (HMR) analysis was performed to determine which variables were predictive of first-time NPTE score. Second, a correlation analysis was performed on all 18 Physical Therapy Clinical Performance Instrument (PT CPI) 2006 category scores obtained during the first long-term clinical rotation, overall PT CPI 2006 score, and NPTE passage. With all variables entered, the HMR model predicted 39% of the variance seen in NPTE scores. The HMR results showed that physical therapy program first-year GPA (1PTGPA) was the strongest predictor and explained 24% of the variance in NPTE scores (b=0.572, p<0.001). The correlational analysis found no statistically significant correlation between the 18 PT CPI 2006 category scores, overall PT CPI 2006 score, and NPTE passage. As 1PTGPA had the most significant contribution to prediction of NPTE scores, programs need to monitor first-year students who display academic difficulty. PT CPI version 2006 scores were significantly correlated with each other, but not with NPTE score or NPTE passage. Both tools measure many of the same professional requirements but use different modes of assessment, and they may be considered complementary tools to gain a full picture of both the student's ability and skills.

Multi-scale variability and long-range memory in indoor Radon concentrations from Coimbra, Portugal

NASA Astrophysics Data System (ADS)

Donner, Reik V.; Potirakis, Stelios; Barbosa, Susana

2014-05-01

The presence or absence of long-range correlations in the variations of indoor Radon concentrations has recently attracted considerable interest. As a radioactive gas naturally emitted from the ground in certain geological settings, understanding environmental factors controlling Radon concentrations and their dynamics is important for estimating its effect on human health and the efficiency of possible measures for reducing the corresponding exposition. In this work, we re-analyze two high-resolution records of indoor Radon concentrations from Coimbra, Portugal, each of which spans several months of continuous measurements. In order to evaluate the presence of long-range correlations and fractal scaling, we utilize a multiplicity of complementary methods, including power spectral analysis, ARFIMA modeling, classical and multi-fractal detrended fluctuation analysis, and two different estimators of the signals' fractal dimensions. Power spectra and fluctuation functions reveal some complex behavior with qualitatively different properties on different time-scales: white noise in the high-frequency part, indications of some long-range correlated process dominating time scales of several hours to days, and pronounced low-frequency variability associated with tidal and/or meteorological forcing. In order to further decompose these different scales of variability, we apply two different approaches. On the one hand, applying multi-resolution analysis based on the discrete wavelet transform allows separately studying contributions on different time scales and characterize their specific correlation and scaling properties. On the other hand, singular system analysis (SSA) provides a reconstruction of the essential modes of variability. Specifically, by considering only the first leading SSA modes, we achieve an efficient de-noising of our environmental signals, highlighting the low-frequency variations together with some distinct scaling on sub-daily time-scales resembling the properties of a long-range correlated process.

The Schaake shuffle: A method for reconstructing space-time variability in forecasted precipitation and temperature fields

USGS Publications Warehouse

Clark, M.R.; Gangopadhyay, S.; Hay, L.; Rajagopalan, B.; Wilby, R.

2004-01-01

A number of statistical methods that are used to provide local-scale ensemble forecasts of precipitation and temperature do not contain realistic spatial covariability between neighboring stations or realistic temporal persistence for subsequent forecast lead times. To demonstrate this point, output from a global-scale numerical weather prediction model is used in a stepwise multiple linear regression approach to downscale precipitation and temperature to individual stations located in and around four study basins in the United States. Output from the forecast model is downscaled for lead times up to 14 days. Residuals in the regression equation are modeled stochastically to provide 100 ensemble forecasts. The precipitation and temperature ensembles from this approach have a poor representation of the spatial variability and temporal persistence. The spatial correlations for downscaled output are considerably lower than observed spatial correlations at short forecast lead times (e.g., less than 5 days) when there is high accuracy in the forecasts. At longer forecast lead times, the downscaled spatial correlations are close to zero. Similarly, the observed temporal persistence is only partly present at short forecast lead times. A method is presented for reordering the ensemble output in order to recover the space-time variability in precipitation and temperature fields. In this approach, the ensemble members for a given forecast day are ranked and matched with the rank of precipitation and temperature data from days randomly selected from similar dates in the historical record. The ensembles are then reordered to correspond to the original order of the selection of historical data. Using this approach, the observed intersite correlations, intervariable correlations, and the observed temporal persistence are almost entirely recovered. This reordering methodology also has applications for recovering the space-time variability in modeled streamflow. ?? 2004 American Meteorological Society.

Body size as a latent variable in a structural equation model: thermal acclimation and energetics of the leaf-eared mouse.

PubMed

Nespolo, Roberto F; Arim, Matías; Bozinovic, Francisco

2003-07-01

Body size is one of the most important determinants of energy metabolism in mammals. However, the usual physiological variables measured to characterize energy metabolism and heat dissipation in endotherms are strongly affected by thermal acclimation, and are also correlated among themselves. In addition to choosing the appropriate measurement of body size, these problems create additional complications when analyzing the relationships among physiological variables such as basal metabolism, non-shivering thermogenesis, thermoregulatory maximum metabolic rate and minimum thermal conductance, body size dependence, and the effect of thermal acclimation on them. We measured these variables in Phyllotis darwini, a murid rodent from central Chile, under conditions of warm and cold acclimation. In addition to standard statistical analyses to determine the effect of thermal acclimation on each variable and the body-mass-controlled correlation among them, we performed a Structural Equation Modeling analysis to evaluate the effects of three different measurements of body size (body mass, m(b); body length, L(b) and foot length, L(f)) on energy metabolism and thermal conductance. We found that thermal acclimation changed the correlation among physiological variables. Only cold-acclimated animals supported our a priori path models, and m(b) appeared to be the best descriptor of body size (compared with L(b) and L(f)) when dealing with energy metabolism and thermal conductance. However, while m(b) appeared to be the strongest determinant of energy metabolism, there was an important and significant contribution of L(b) (but not L(f)) to thermal conductance. This study demonstrates how additional information can be drawn from physiological ecology and general organismal studies by applying Structural Equation Modeling when multiple variables are measured in the same individuals.

Left Atrial Volume Determinants in Patients with Non-Ischemic Dilated Cardiomyopathy

PubMed Central

Mancuso, Frederico José Neves; Moisés, Valdir Ambrósio; Almeida, Dirceu Rodrigues; Poyares, Dalva; Storti, Luciana Julio; Oliveira, Wércules Antonio; Brito, Flavio Souza; de Paola, Angelo Amato Vincenzo; Carvalho, Antonio Carlos Camargo; Campos, Orlando

2015-01-01

Background Left atrial volume (LAV) is a predictor of prognosis in patients with heart failure. Objective We aimed to evaluate the determinants of LAV in patients with dilated cardiomyopathy (DCM). Methods Ninety patients with DCM and left ventricular (LV) ejection fraction ≤ 0.50 were included. LAV was measured with real-time three-dimensional echocardiography (eco3D). The variables evaluated were heart rate, systolic blood pressure, LV end-diastolic volume and end-systolic volume and ejection fraction (eco3D), mitral inflow E wave, tissue Doppler e´ wave, E/e´ ratio, intraventricular dyssynchrony, 3D dyssynchrony index and mitral regurgitation vena contracta. Pearson´s coefficient was used to identify the correlation of the LAV with the assessed variables. A multiple linear regression model was developed that included LAV as the dependent variable and the variables correlated with it as the predictive variables. Results Mean age was 52 ± 11 years-old, LV ejection fraction: 31.5 ± 8.0% (16-50%) and LAV: 39.2±15.7 ml/m2. The variables that correlated with the LAV were LV end-diastolic volume (r = 0.38; p < 0.01), LV end-systolic volume (r = 0.43; p < 0.001), LV ejection fraction (r = -0.36; p < 0.01), E wave (r = 0.50; p < 0.01), E/e´ ratio (r = 0.51; p < 0.01) and mitral regurgitation (r = 0.53; p < 0.01). A multivariate analysis identified the E/e´ ratio (p = 0.02) and mitral regurgitation (p = 0.02) as the only independent variables associated with LAV increase. Conclusion The LAV is independently determined by LV filling pressures (E/e´ ratio) and mitral regurgitation in DCM. PMID:25993483

Left Atrial Volume Determinants in Patients with Non-Ischemic Dilated Cardiomyopathy.

PubMed

Mancuso, Frederico José Neves; Moisés, Valdir Ambrósio; Almeida, Dirceu Rodrigues; Poyares, Dalva; Storti, Luciana Julio; Oliveira, Wércules Antonio; Brito, Flavio Souza; Paola, Angelo Amato Vincenzo de; Carvalho, Antonio Carlos Camargo; Campos, Orlando

2015-07-01

Left atrial volume (LAV) is a predictor of prognosis in patients with heart failure. We aimed to evaluate the determinants of LAV in patients with dilated cardiomyopathy (DCM). Ninety patients with DCM and left ventricular (LV) ejection fraction ≤ 0.50 were included. LAV was measured with real-time three-dimensional echocardiography (eco3D). The variables evaluated were heart rate, systolic blood pressure, LV end-diastolic volume and end-systolic volume and ejection fraction (eco3D), mitral inflow E wave, tissue Doppler e' wave, E/e' ratio, intraventricular dyssynchrony, 3D dyssynchrony index and mitral regurgitation vena contracta. Pearson's coefficient was used to identify the correlation of the LAV with the assessed variables. A multiple linear regression model was developed that included LAV as the dependent variable and the variables correlated with it as the predictive variables. Mean age was 52 ± 11 years-old, LV ejection fraction: 31.5 ± 8.0% (16-50%) and LAV: 39.2±15.7 ml/m2. The variables that correlated with the LAV were LV end-diastolic volume (r = 0.38; p < 0.01), LV end-systolic volume (r = 0.43; p < 0.001), LV ejection fraction (r = -0.36; p < 0.01), E wave (r = 0.50; p < 0.01), E/e' ratio (r = 0.51; p < 0.01) and mitral regurgitation (r = 0.53; p < 0.01). A multivariate analysis identified the E/e' ratio (p = 0.02) and mitral regurgitation (p = 0.02) as the only independent variables associated with LAV increase. The LAV is independently determined by LV filling pressures (E/e' ratio) and mitral regurgitation in DCM.

Social cognitive correlates of physical activity among persons with multiple sclerosis: Influence of depressive symptoms.

PubMed

Ensari, Ipek; Kinnett-Hopkins, Dominique; Motl, Robert W

2017-10-01

Physical inactivity and elevated depressive symptoms are both highly prevalent and correlated among persons with multiple sclerosis (MS). Variables from Social Cognitive Theory (SCT) might be differentially correlated with physical activity in persons with MS who have elevated depressive symptoms. This study investigated the influence of elevated depressive symptoms on correlates of physical activity based on SCT in persons with MS. Participants (mean age = 50.3 years, 87% female, 69% Caucasian) completed questionnaires on physical activity, depressive symptoms, self-efficacy, social support, outcome expectations, functional limitations, and goal setting. The questionnaires were delivered and returned through the U.S. Postal Service. The sample (N = 551) was divided into 2 subgroups (i.e., elevated vs non-elevated levels of depressive symptoms) for statistical analyses. Bivariate correlations and stepwise multiple regressions were conducted using SPSS. Self-efficacy (r = 0.16), functional limitations (r = 0.22) and goal-setting (r = 0.42) were significantly (p < 0.05) associated with physical activity among the elevated depressive sample. The regression analysis indicated that self-efficacy predicted physical activity in Step 1 (β = 0.16, p < 0.05), but was no longer significant when goal-setting (β = 0.06, p > 0.05) entered the model. All social cognitive variables were significantly associated with physical activity levels (r = 0.16-0.40, p < 0.001) among the non-elevated depressive sample. Self-efficacy predicted physical activity in Step 1 (β = 0.24, p < 0.001), but it was no longer significant once goal-setting, functional limitations, and self-evaluative outcome expectations entered the model. Based on SCT, self-efficacy and goal-setting represent possible targets of behavior interventions for increasing physical activity among persons with MS who have elevated depressive symptoms. There is a larger set of targets among those with MS who do not have elevated symptoms. Copyright © 2017 Elsevier Inc. All rights reserved.

Contrasting species-environment relationships in communities of testate amoebae, bryophytes and vascular plants along the fen-bog gradient.

PubMed

Lamentowicz, Mariusz; Lamentowicz, Lukasz; van der Knaap, Willem O; Gabka, Maciej; Mitchell, Edward A D

2010-04-01

We studied the vegetation, testate amoebae and abiotic variables (depth of the water table, pH, electrical conductivity, Ca and Mg concentrations of water extracted from mosses) along the bog to extremely rich fen gradient in sub-alpine peatlands of the Upper Engadine (Swiss Alps). Testate amoeba diversity was correlated to that of mosses but not of vascular plants. Diversity peaked in rich fen for testate amoebae and in extremely rich fen for mosses, while for testate amoebae and mosses it was lowest in bog but for vascular plants in extremely rich fen. Multiple factor and redundancy analyses (RDA) revealed a stronger correlation of testate amoebae than of vegetation to water table and hydrochemical variables and relatively strong correlation between testate amoeba and moss community data. In RDA, hydrochemical variables explained a higher proportion of the testate amoeba and moss data than water table depth. Abiotic variables explained a higher percentage of the species data for testate amoebae (30.3% or 19.5% for binary data) than for mosses (13.4%) and vascular plants (10%). These results show that (1) vascular plant, moss and testate amoeba communities respond differently to ecological gradients in peatlands and (2) testate amoebae are more strongly related than vascular plants to the abiotic factors at the mire surface. These differences are related to vertical trophic gradients and associated niche differentiation.

Anthropometric Survey of US Army Personnel (1988): Correlation Coefficients and Regression Equations. Part 5. Stepwise and Standard Multiple Regression Tables

DTIC Science & Technology

1990-05-01

0.759 0.744 0.768 0.753 106 (THUMBBR) THUMB BREADTH -0.652 -0.673 -0.539 -0.663 217 (LIPLGTHH) LIP LENGTH HEADBOARD 0.017 0.019 0.020 51 (FTBRHOR) FOOT...DEPENDENT VARIABLE: (106) THUMB BREADTH (THUBBR) MODEL INDEPENDENT VARIABLE 1 2 3 4 5 INTERCEPT 6.621 5.016 6.267 5.697 4.528 59 (HANDCIRC) HAND...95 (SLLSPEL) SLEEVE LENGTH: SPINE-ELBOW -0.020 -0.019 -C.018 9 (BLFTCIRC) BALL OF FOOT CIRCUMFERENCE -0.032 -0.039 106 (THUMBBR) THUMB BREADTH 0.228

The correlation between symptomatic fatigue to definite measures of gait in people with multiple sclerosis.

PubMed

Kalron, Alon

2016-02-01

There is a general consensus relating to the multidimensional aspects of fatigue in people with multiple sclerosis (PwMS), however, the exact impact of this symptom on gait is not fully understood. Our primary aim was to examine the relationship between definite parameters of gait with self-reported symptomatic fatigue in PwMS according to their level of neurological impairment. Spatio-temporal parameters of gait were studied using an electronic walkway. The Multiple Sclerosis Walking Scale (MSWS-12) questionnaire, a patient-rated measure of walking ability was collected. The Modified Fatigue Impact Scale (MFIS) questionnaire was used to determine the level of symptomatic fatigue. One hundred and one PwMS (61 women) were included in the study analysis. Subjects were divided into mild and moderate neurological impaired groups. Fatigue was correlated with 5 (out of 14) spatiotemporal parameters. However, correlation scores were all <0.35, thus considered as weak correlations. In the mild group, the double support period was the only variable positively correlated to fatigue (Spearman's rho=0.28, P=0.05). In the moderate group, step and stride length were solely negatively correlated to fatigue (Spearman's rho=0.32, P=0.03). In contrast to the definite gait parameters, the MSWS-12 self-questionnaire was moderately positively correlated to the level of fatigue. Scores for the total, mild and moderate groups were 0.54, 0.57 and 0.51; P<0.01, respectively. The present results indicate that modifications in spatio-temporal parameters of gait are not closely related to symptomatic fatigue in PwMS. On the contrary, the self-reported MSWS-12 questionnaire is predisposed to level of fatigue in PwMS. Copyright © 2015 Elsevier B.V. All rights reserved.

Estimation of streamflow, base flow, and nitrate-nitrogen loads in Iowa using multiple linear regression models

USGS Publications Warehouse

Schilling, K.E.; Wolter, C.F.

2005-01-01

Nineteen variables, including precipitation, soils and geology, land use, and basin morphologic characteristics, were evaluated to develop Iowa regression models to predict total streamflow (Q), base flow (Qb), storm flow (Qs) and base flow percentage (%Qb) in gauged and ungauged watersheds in the state. Discharge records from a set of 33 watersheds across the state for the 1980 to 2000 period were separated into Qb and Qs. Multiple linear regression found that 75.5 percent of long term average Q was explained by rainfall, sand content, and row crop percentage variables, whereas 88.5 percent of Qb was explained by these three variables plus permeability and floodplain area variables. Qs was explained by average rainfall and %Qb was a function of row crop percentage, permeability, and basin slope variables. Regional regression models developed for long term average Q and Qb were adapted to annual rainfall and showed good correlation between measured and predicted values. Combining the regression model for Q with an estimate of mean annual nitrate concentration, a map of potential nitrate loads in the state was produced. Results from this study have important implications for understanding geomorphic and land use controls on streamflow and base flow in Iowa watersheds and similar agriculture dominated watersheds in the glaciated Midwest. (JAWRA) (Copyright ?? 2005).

A method for analyzing temporal patterns of variability of a time series from Poincare plots.

PubMed

Fishman, Mikkel; Jacono, Frank J; Park, Soojin; Jamasebi, Reza; Thungtong, Anurak; Loparo, Kenneth A; Dick, Thomas E

2012-07-01

The Poincaré plot is a popular two-dimensional, time series analysis tool because of its intuitive display of dynamic system behavior. Poincaré plots have been used to visualize heart rate and respiratory pattern variabilities. However, conventional quantitative analysis relies primarily on statistical measurements of the cumulative distribution of points, making it difficult to interpret irregular or complex plots. Moreover, the plots are constructed to reflect highly correlated regions of the time series, reducing the amount of nonlinear information that is presented and thereby hiding potentially relevant features. We propose temporal Poincaré variability (TPV), a novel analysis methodology that uses standard techniques to quantify the temporal distribution of points and to detect nonlinear sources responsible for physiological variability. In addition, the analysis is applied across multiple time delays, yielding a richer insight into system dynamics than the traditional circle return plot. The method is applied to data sets of R-R intervals and to synthetic point process data extracted from the Lorenz time series. The results demonstrate that TPV complements the traditional analysis and can be applied more generally, including Poincaré plots with multiple clusters, and more consistently than the conventional measures and can address questions regarding potential structure underlying the variability of a data set.

Synthesizing trait correlations and functional relationships across multiple scales: A Hierarchical Bayes approach

NASA Astrophysics Data System (ADS)

Shiklomanov, A. N.; Cowdery, E.; Dietze, M.

2016-12-01

Recent syntheses of global trait databases have revealed that although the functional diversity among plant species is immense, this diversity is constrained by trade-offs between plant strategies. However, the use of among-trait and trait-environment correlations at the global scale for both qualitative ecological inference and land surface modeling has several important caveats. An alternative approach is to preserve the existing PFT-based model structure while using statistical analyses to account for uncertainty and variability in model parameters. In this study, we used a hierarchical Bayesian model of foliar traits in the TRY database to test the following hypotheses: (1) Leveraging the covariance between foliar traits will significantly constrain our uncertainty in their distributions; and (2) Among-trait covariance patterns are significantly different among and within PFTs, reflecting differences in trade-offs associated with biome-level evolution, site-level community assembly, and individual-level ecophysiological acclimation. We found that among-trait covariance significantly constrained estimates of trait means, and the additional information provided by across-PFT covariance led to more constraint still, especially for traits and PFTs with low sample sizes. We also found that among-trait correlations were highly variable among PFTs, and were generally inconsistent with correlations within PFTs. The hierarchical multivariate framework developed in our study can readily be enhanced with additional levels of hierarchy to account for geographic, species, and individual-level variability.

Workers exposed to low levels of benzene present in urban air: Assessment of peripheral blood count variations.

PubMed

Casale, Teodorico; Sacco, Carmina; Ricci, Serafino; Loreti, Beatrice; Pacchiarotti, Alessandro; Cupelli, Vincenzo; Arcangeli, Giulio; Mucci, Nicola; Antuono, Vittorio; De Marco, Federica; Tomei, Gianfranco; Tomei, Francesco; Rosati, Maria Valeria

2016-06-01

Few studies in the literature have examined the effects of benzene on blood cells. The aim of this study was to evaluate the possible correlation between the blood benzene levels and the blood cell counts. From a population of 2658 workers, we studied a group of 215 subjects. Each worker underwent blood sampling for the assessment of the blood benzene levels and the blood cell counts. The Mann-Whitney U test for two-mode variables and the Kruskal-Wallis test for more-than-two-mode variables were performed on all subjects. We estimated the Pearson correlation index between the variables in the total sample and the subgroups divided according to sex, the smoking habit, and job. After the main confounding factors were evaluated, multiple linear regression was performed on both the total sample and the subgroups. A significant inverse correlation was found among the blood benzene levels and the white blood cells, lymphocytes, and neutrophils in traffic policemen, motorcyclists, and other outdoor workers. We did not find any significant correlation with any other parameters of blood cell count. Our results, which must be considered preliminary, indicate that increased blood benzene levels in outdoor workers lead to decreased counts of white blood cells, neutrophils, and lymphocytes, because of possible immune effects. These are worth investigating in the future by specific immune tests. Copyright © 2016. Published by Elsevier Ltd.

Possible antecedents and consequences of self-esteem in persons with multiple sclerosis: preliminary evidence from a cross-sectional analysis.

PubMed

Dlugonski, Deirdre; Motl, Robert W

2012-02-01

Persons with multiple sclerosis (MS) have consistently reported lower levels of self-esteem compared with the general population. Despite this, very little is known about the antecedents and consequences of self-esteem in persons with MS. To examine (1) physical activity and social support as potentially modifiable correlates (i.e., antecedents) of self-esteem and (2) physical and psychological health-related quality of life as possible consequences of self-esteem in persons with MS. Participants (N = 46) wore an Actigraph accelerometer for 7 days and then completed a battery of questionnaires, including the Rosenberg Self-Esteem Scale (RSES), Multiple Sclerosis Impact Scale (MSIS-29), and Social Provisions Scale (SPS). The data were analyzed using PASW Statistics 18. Bivariate correlation analysis indicated that average daily step counts (r = .298, p = .026) and social support (r = .366, p = .007) were significantly correlated with self-esteem. Multiple linear regression analysis indicated that only social support was a significant predictor of self-esteem scores (β = .411, p = .004); pedometer steps approached significance as a predictor of self-esteem (β = .178, p = .112). Bivariate correlation analysis further indicated significant negative associations between self-esteem and physical (r = -.391, p = .004) and psychological (r = -.540, p = .0001) domains of health-related quality of life (HRQOL), indicating that higher self-esteem was associated with more positive HRQOL. Social support is a potentially modifiable variable that may be important to target when designing interventions to improve self-esteem and this might have implications for improving physical and psychological HRQOL in persons with MS.

Integrative Exploratory Analysis of Two or More Genomic Datasets.

PubMed

Meng, Chen; Culhane, Aedin

2016-01-01

Exploratory analysis is an essential step in the analysis of high throughput data. Multivariate approaches such as correspondence analysis (CA), principal component analysis, and multidimensional scaling are widely used in the exploratory analysis of single dataset. Modern biological studies often assay multiple types of biological molecules (e.g., mRNA, protein, phosphoproteins) on a same set of biological samples, thereby creating multiple different types of omics data or multiassay data. Integrative exploratory analysis of these multiple omics data is required to leverage the potential of multiple omics studies. In this chapter, we describe the application of co-inertia analysis (CIA; for analyzing two datasets) and multiple co-inertia analysis (MCIA; for three or more datasets) to address this problem. These methods are powerful yet simple multivariate approaches that represent samples using a lower number of variables, allowing a more easily identification of the correlated structure in and between multiple high dimensional datasets. Graphical representations can be employed to this purpose. In addition, the methods simultaneously project samples and variables (genes, proteins) onto the same lower dimensional space, so the most variant variables from each dataset can be selected and associated with samples, which can be further used to facilitate biological interpretation and pathway analysis. We applied CIA to explore the concordance between mRNA and protein expression in a panel of 60 tumor cell lines from the National Cancer Institute. In the same 60 cell lines, we used MCIA to perform a cross-platform comparison of mRNA gene expression profiles obtained on four different microarray platforms. Last, as an example of integrative analysis of multiassay or multi-omics data we analyzed transcriptomic, proteomic, and phosphoproteomic data from pluripotent (iPS) and embryonic stem (ES) cell lines.

An analysis of the influence of the local effects of climatic and hydrological factors affecting new malaria cases in riverine areas along the Rio Negro and surrounding Puraquequara Lake, Amazonas, Brazil.

PubMed

Coutinho, Paulo Eduardo Guzzo; Candido, Luiz Antonio; Tadei, Wanderli Pedro; da Silva Junior, Urbano Lopes; Correa, Honorly Katia Mestre

2018-04-26

A study was conducted at three sampling regions along the Rio Negro and surrounding Puraquequara Lake, Amazonas, Brazil. The aim was to determine the influence of the local effects of climatic and hydrological variables on new malaria cases. Data was gathered on the river level, precipitation, air temperature, and the number of new cases of autochthonous malaria between January 2003 and December 2013. Monthly averages, time series decompositions, cross-correlations, and multiple regressions revealed different relationships at each location. The sampling region in the upper Rio Negro indicated no statistically significant results. However, monthly averages suggest that precipitation and air temperature correlate positively with the occurrence of new cases of malaria. In the mid Rio Negro and Puraquequara Lake, the river level positively correlated, and temperature negatively correlated with new transmissions, while precipitation correlated negatively in the mid Rio Negro and positively on the lake. Overall, the river level is a key variable affecting the formation of breeding sites, while precipitation may either develop or damage them. A negative temperature correlation is associated with the occurrence of new annual post-peak cases of malaria, when the monthly average exceeds 28.5 °C. This suggests that several factors contribute to the occurrence of new malaria cases as higher temperatures are reached at the same time as precipitation and the river levels are lowest. Differences between signals and correlation lags indicate that local characteristics have an impact on how different variables influence the disease vector's life cycle, pathogens, and consequently, new cases of malaria.

ERP correlates of word production predictors in picture naming: a trial by trial multiple regression analysis from stimulus onset to response.

PubMed

Valente, Andrea; Bürki, Audrey; Laganaro, Marina

2014-01-01

A major effort in cognitive neuroscience of language is to define the temporal and spatial characteristics of the core cognitive processes involved in word production. One approach consists in studying the effects of linguistic and pre-linguistic variables in picture naming tasks. So far, studies have analyzed event-related potentials (ERPs) during word production by examining one or two variables with factorial designs. Here we extended this approach by investigating simultaneously the effects of multiple theoretical relevant predictors in a picture naming task. High density EEG was recorded on 31 participants during overt naming of 100 pictures. ERPs were extracted on a trial by trial basis from picture onset to 100 ms before the onset of articulation. Mixed-effects regression models were conducted to examine which variables affected production latencies and the duration of periods of stable electrophysiological patterns (topographic maps). Results revealed an effect of a pre-linguistic variable, visual complexity, on an early period of stable electric field at scalp, from 140 to 180 ms after picture presentation, a result consistent with the proposal that this time period is associated with visual object recognition processes. Three other variables, word Age of Acquisition, Name Agreement, and Image Agreement influenced response latencies and modulated ERPs from ~380 ms to the end of the analyzed period. These results demonstrate that a topographic analysis fitted into the single trial ERPs and covering the entire processing period allows one to associate the cost generated by psycholinguistic variables to the duration of specific stable electrophysiological processes and to pinpoint the precise time-course of multiple word production predictors at once.

The Dental Hygiene Aptitude Tests and the American College Testing Program Tests as Predictors of Scores on the National Board Dental Hygiene Examination.

ERIC Educational Resources Information Center

Longenbecker, Sueann; Wood, Peter H.

1984-01-01

Scores from the National Board Dental Hygiene Examination (NBDHE) served as the criterion variable in a comparison of the predictive validity of the Dental Hygiene Aptitude Tests (DHAT) and the ACT Assessment tests. The DHAT-Science and Verbal tests combined to produce the highest multiple correlation with NBDHE scores. (Author/DWH)

Meteorological adjustment of yearly mean values for air pollutant concentration comparison

NASA Technical Reports Server (NTRS)

Sidik, S. M.; Neustadter, H. E.

1976-01-01

Using multiple linear regression analysis, models which estimate mean concentrations of Total Suspended Particulate (TSP), sulfur dioxide, and nitrogen dioxide as a function of several meteorologic variables, two rough economic indicators, and a simple trend in time are studied. Meteorologic data were obtained and do not include inversion heights. The goodness of fit of the estimated models is partially reflected by the squared coefficient of multiple correlation which indicates that, at the various sampling stations, the models accounted for about 23 to 47 percent of the total variance of the observed TSP concentrations. If the resulting model equations are used in place of simple overall means of the observed concentrations, there is about a 20 percent improvement in either: (1) predicting mean concentrations for specified meteorological conditions; or (2) adjusting successive yearly averages to allow for comparisons devoid of meteorological effects. An application to source identification is presented using regression coefficients of wind velocity predictor variables.

Modeling relationships between catchment attributes and river water quality in southern catchments of the Caspian Sea.

PubMed

Hasani Sangani, Mohammad; Jabbarian Amiri, Bahman; Alizadeh Shabani, Afshin; Sakieh, Yousef; Ashrafi, Sohrab

2015-04-01

Increasing land utilization through diverse forms of human activities, such as agriculture, forestry, urban growth, and industrial development, has led to negative impacts on the water quality of rivers. To find out how catchment attributes, such as land use, hydrologic soil groups, and lithology, can affect water quality variables (Ca(2+), Mg(2+), Na(+), Cl(-), HCO 3 (-) , pH, TDS, EC, SAR), a spatio-statistical approach was applied to 23 catchments in southern basins of the Caspian Sea. All input data layers (digital maps of land use, soil, and lithology) were prepared using geographic information system (GIS) and spatial analysis. Relationships between water quality variables and catchment attributes were then examined by Spearman rank correlation tests and multiple linear regression. Stepwise approach-based multiple linear regressions were developed to examine the relationship between catchment attributes and water quality variables. The areas (%) of marl, tuff, or diorite, as well as those of good-quality rangeland and bare land had negative effects on all water quality variables, while those of basalt, forest land cover were found to contribute to improved river water quality. Moreover, lithological variables showed the greatest most potential for predicting the mean concentration values of water quality variables, and noting that measure of EC and TDS have inversely associated with area (%) of urban land use.

Bottom-up and Top-down Input Augment the Variability of Cortical Neurons

PubMed Central

Nassi, Jonathan J.; Kreiman, Gabriel; Born, Richard T.

2016-01-01

SUMMARY Neurons in the cerebral cortex respond inconsistently to a repeated sensory stimulus, yet they underlie our stable sensory experiences. Although the nature of this variability is unknown, its ubiquity has encouraged the general view that each cell produces random spike patterns that noisily represent its response rate. In contrast, here we show that reversibly inactivating distant sources of either bottom-up or top-down input to cortical visual areas in the alert primate reduces both the spike train irregularity and the trial-to-trial variability of single neurons. A simple model in which a fraction of the pre-synaptic input is silenced can reproduce this reduction in variability, provided that there exist temporal correlations primarily within, but not between, excitatory and inhibitory input pools. A large component of the variability of cortical neurons may therefore arise from synchronous input produced by signals arriving from multiple sources. PMID:27427459

Predicting hydrological response to forest changes by simple statistical models: the selection of the best indicator of forest changes with a hydrological perspective

NASA Astrophysics Data System (ADS)

Ning, D.; Zhang, M.; Ren, S.; Hou, Y.; Yu, L.; Meng, Z.

2017-01-01

Forest plays an important role in hydrological cycle, and forest changes will inevitably affect runoff across multiple spatial scales. The selection of a suitable indicator for forest changes is essential for predicting forest-related hydrological response. This study used the Meijiang River, one of the headwaters of the Poyang Lake as an example to identify the best indicator of forest changes for predicting forest change-induced hydrological responses. Correlation analysis was conducted first to detect the relationships between monthly runoff and its predictive variables including antecedent monthly precipitation and indicators for forest changes (forest coverage, vegetation indices including EVI, NDVI, and NDWI), and by use of the identified predictive variables that were most correlated with monthly runoff, multiple linear regression models were then developed. The model with best performance identified in this study included two independent variables -antecedent monthly precipitation and NDWI. It indicates that NDWI is the best indicator of forest change in hydrological prediction while forest coverage, the most commonly used indicator of forest change is insignificantly related to monthly runoff. This highlights the use of vegetation index such as NDWI to indicate forest changes in hydrological studies. This study will provide us with an efficient way to quantify the hydrological impact of large-scale forest changes in the Meijiang River watershed, which is crucial for downstream water resource management and ecological protection in the Poyang Lake basin.

Consistent patterns of variation in macrobenthic assemblages and environmental variables over multiple spatial scales using taxonomic and functional approaches.

PubMed

Veiga, Puri; Torres, Ana Catarina; Aneiros, Fernando; Sousa-Pinto, Isabel; Troncoso, Jesús S; Rubal, Marcos

2016-09-01

Spatial variability of environmental factors and macrobenthos, using species and functional groups, was examined over the same scales (100s of cm to >100 km) in intertidal sediments of two transitional water systems. The objectives were to test if functional groups were a good species surrogate and explore the relationship between environmental variables and macrobenthos. Environmental variables, diversity and the multivariate assemblage structure showed the highest variability at the scale of 10s of km. However, abundance was more variable at 10s of m. Consistent patterns were achieved using species and functional groups therefore, these may be a good species surrogate. Total carbon, salinity and silt/clay were the strongest correlated with macrobenthic assemblages. Results are valuable for design and interpretation of future monitoring programs including detection of anthropogenic disturbances in transitional systems and propose improvements in environmental variable sampling to refine the assessment of their relationship with biological data across spatial scales. Copyright © 2016 Elsevier Ltd. All rights reserved.

Prompt optical emission from gamma-ray bursts with multiple timescale variability of central engine activities

NASA Astrophysics Data System (ADS)

Xu, Si-Yao; Li, Zhuo

2014-04-01

Complete high-resolution light curves of GRB 080319B observed by Swift present an opportunity for detailed temporal analysis of prompt optical emission. With a two-component distribution of initial Lorentz factors, we simulate the dynamical process of shells being ejected from the central engine in the framework of the internal shock model. The emitted radiations are decomposed into different frequency ranges for a temporal correlation analysis between the light curves in different energy bands. The resulting prompt optical and gamma-ray emissions show similar temporal profiles, with both showing a superposition of a component with slow variability and a component with fast variability, except that the gamma-ray light curve is much more variable than its optical counterpart. The variability in the simulated light curves and the strong correlation with a time lag between the optical and gamma-ray emissions are in good agreement with observations of GRB 080319B. Our simulations suggest that the variations seen in the light curves stem from the temporal structure of the shells injected from the central engine of gamma-ray bursts. Future observations with high temporal resolution of prompt optical emission from GRBs, e.g., by UFFO-Pathfinder and SVOM-GWAC, will provide a useful tool for investigating the central engine activity.

A simple solution for model comparison in bold imaging: the special case of reward prediction error and reward outcomes.

PubMed

Erdeniz, Burak; Rohe, Tim; Done, John; Seidler, Rachael D

2013-01-01

Conventional neuroimaging techniques provide information about condition-related changes of the BOLD (blood-oxygen-level dependent) signal, indicating only where and when the underlying cognitive processes occur. Recently, with the help of a new approach called "model-based" functional neuroimaging (fMRI), researchers are able to visualize changes in the internal variables of a time varying learning process, such as the reward prediction error or the predicted reward value of a conditional stimulus. However, despite being extremely beneficial to the imaging community in understanding the neural correlates of decision variables, a model-based approach to brain imaging data is also methodologically challenging due to the multicollinearity problem in statistical analysis. There are multiple sources of multicollinearity in functional neuroimaging including investigations of closely related variables and/or experimental designs that do not account for this. The source of multicollinearity discussed in this paper occurs due to correlation between different subjective variables that are calculated very close in time. Here, we review methodological approaches to analyzing such data by discussing the special case of separating the reward prediction error signal from reward outcomes.

Unique Associations Between Big Five Personality Aspects and Multiple Dimensions of Well-Being.

PubMed

Sun, Jessie; Kaufman, Scott Barry; Smillie, Luke D

2018-04-01

Personality traits are associated with well-being, but the precise correlates vary across well-being dimensions and within each Big Five domain. This study is the first to examine the unique associations between the Big Five aspects (rather than facets) and multiple well-being dimensions. Two samples of U.S. participants (total N = 706; M age  = 36.17; 54% female) recruited via Amazon's Mechanical Turk completed measures of the Big Five aspects and subjective, psychological, and PERMA well-being. One aspect within each domain was more strongly associated with well-being variables. Enthusiasm and Withdrawal were strongly associated with a broad range of well-being variables, but other aspects of personality also had idiosyncratic associations with distinct forms of positive functioning (e.g., Compassion with positive relationships, Industriousness with accomplishment, and Intellect with personal growth). An aspect-level analysis provides an optimal (i.e., parsimonious yet sufficiently comprehensive) framework for describing the relation between personality traits and multiple ways of thriving in life. © 2016 Wiley Periodicals, Inc.

Sustained attention to response task (SART) shows impaired vigilance in a spectrum of disorders of excessive daytime sleepiness.

PubMed

Van Schie, Mojca K M; Thijs, Roland D; Fronczek, Rolf; Middelkoop, Huub A M; Lammers, Gert Jan; Van Dijk, J Gert

2012-08-01

The sustained attention to response task comprises withholding key presses to one in nine of 225 target stimuli; it proved to be a sensitive measure of vigilance in a small group of narcoleptics. We studied sustained attention to response task results in 96 patients from a tertiary narcolepsy referral centre. Diagnoses according to ICSD-2 criteria were narcolepsy with (n=42) and without cataplexy (n=5), idiopathic hypersomnia without long sleep time (n=37), and obstructive sleep apnoea syndrome (n=12). The sustained attention to response task was administered prior to each of five multiple sleep latency test sessions. Analysis concerned error rates, mean reaction time, reaction time variability and post-error slowing, as well as the correlation of sustained attention to response task results with mean latency of the multiple sleep latency test and possible time of day influences. Median sustained attention to response task error scores ranged from 8.4 to 11.1, and mean reaction times from 332 to 366ms. Sustained attention to response task error score and mean reaction time did not differ significantly between patient groups. Sustained attention to response task error score did not correlate with multiple sleep latency test sleep latency. Reaction time was more variable as the error score was higher. Sustained attention to response task error score was highest for the first session. We conclude that a high sustained attention to response task error rate reflects vigilance impairment in excessive daytime sleepiness irrespective of its cause. The sustained attention to response task and the multiple sleep latency test reflect different aspects of sleep/wakefulness and are complementary. © 2011 European Sleep Research Society.

Inflammation, homocysteine and carotid intima-media thickness.

PubMed

Baptista, Alexandre P; Cacdocar, Sanjiva; Palmeiro, Hugo; Faísca, Marília; Carrasqueira, Herménio; Morgado, Elsa; Sampaio, Sandra; Cabrita, Ana; Silva, Ana Paula; Bernardo, Idalécio; Gome, Veloso; Neves, Pedro L

2008-01-01

Cardiovascular disease is the main cause of morbidity and mortality in chronic renal patients. Carotid intima-media thickness (CIMT) is one of the most accurate markers of atherosclerosis risk. In this study, the authors set out to evaluate a population of chronic renal patients to determine which factors are associated with an increase in intima-media thickness. We included 56 patients (F=22, M=34), with a mean age of 68.6 years, and an estimated glomerular filtration rate of 15.8 ml/min (calculated by the MDRD equation). Various laboratory and inflammatory parameters (hsCRP, IL-6 and TNF-alpha) were evaluated. All subjects underwent measurement of internal carotid artery intima-media thickness by high-resolution real-time B-mode ultrasonography using a 10 MHz linear transducer. Intima-media thickness was used as a dependent variable in a simple linear regression model, with the various laboratory parameters as independent variables. Only parameters showing a significant correlation with CIMT were evaluated in a multiple regression model: age (p=0.001), hemoglobin (p=00.3), logCRP (p=0.042), logIL-6 (p=0.004) and homocysteine (p=0.002). In the multiple regression model we found that age (p=0.001) and homocysteine (p=0.027) were independently correlated with CIMT. LogIL-6 did not reach statistical significance (p=0.057), probably due to the small population size. The authors conclude that age and homocysteine correlate with carotid intima-media thickness, and thus can be considered as markers/risk factors in chronic renal patients.

An integrated brain-behavior model for working memory.

PubMed

Moser, D A; Doucet, G E; Ing, A; Dima, D; Schumann, G; Bilder, R M; Frangou, S

2017-12-05

Working memory (WM) is a central construct in cognitive neuroscience because it comprises mechanisms of active information maintenance and cognitive control that underpin most complex cognitive behavior. Individual variation in WM has been associated with multiple behavioral and health features including demographic characteristics, cognitive and physical traits and lifestyle choices. In this context, we used sparse canonical correlation analyses (sCCAs) to determine the covariation between brain imaging metrics of WM-network activation and connectivity and nonimaging measures relating to sensorimotor processing, affective and nonaffective cognition, mental health and personality, physical health and lifestyle choices derived from 823 healthy participants derived from the Human Connectome Project. We conducted sCCAs at two levels: a global level, testing the overall association between the entire imaging and behavioral-health data sets; and a modular level, testing associations between subsets of the two data sets. The behavioral-health and neuroimaging data sets showed significant interdependency. Variables with positive correlation to the neuroimaging variate represented higher physical endurance and fluid intelligence as well as better function in multiple higher-order cognitive domains. Negatively correlated variables represented indicators of suboptimal cardiovascular and metabolic control and lifestyle choices such as alcohol and nicotine use. These results underscore the importance of accounting for behavioral-health factors in neuroimaging studies of WM and provide a neuroscience-informed framework for personalized and public health interventions to promote and maintain the integrity of the WM network.Molecular Psychiatry advance online publication, 5 December 2017; doi:10.1038/mp.2017.247.

Two SPSS programs for interpreting multiple regression results.

PubMed

Lorenzo-Seva, Urbano; Ferrando, Pere J; Chico, Eliseo

2010-02-01

When multiple regression is used in explanation-oriented designs, it is very important to determine both the usefulness of the predictor variables and their relative importance. Standardized regression coefficients are routinely provided by commercial programs. However, they generally function rather poorly as indicators of relative importance, especially in the presence of substantially correlated predictors. We provide two user-friendly SPSS programs that implement currently recommended techniques and recent developments for assessing the relevance of the predictors. The programs also allow the user to take into account the effects of measurement error. The first program, MIMR-Corr.sps, uses a correlation matrix as input, whereas the second program, MIMR-Raw.sps, uses the raw data and computes bootstrap confidence intervals of different statistics. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from http://brm.psychonomic-journals.org/content/supplemental.

Influence of the Separation of Prescription and Dispensation of Medicine on Its Cost in Japanese Prefectures

PubMed Central

Yokoi, Masayuki; Tashiro, Takao

2014-01-01

We studied how the separation of dispensing and prescribing of medicines between pharmacies and clinics (the “separation system”) can reduce internal medicine costs. To do so, we obtained publicly available data by searching electronic databases and official web pages of the Japanese government and non-profit public service corporations on the Internet. For Japanese medical institutions, participation in the separation system is optional. Consequently, the expansion rate of the separation system for each of the administrative districts is highly variable. The data were subjected to multiple regression analysis; daily internal medicines were the objective variable and expansion rate of the separation system was the explanatory variable. A multiple regression analysis revealed that the expansion rate of the separation system and the rate of replacing brand name medicine with generic medicine showed a significant negative partial correlation with daily internal medicine costs. Thus, the separation system was as effective in reducing medicine costs as the use of generic medicines. Because of its medical economic efficiency, the separation system should be expanded, especially in Asian countries in which the system is underdeveloped. PMID:24999122

Influence of the separation of prescription and dispensation of medicine on its cost in Japanese prefectures.

PubMed

Yokoi, Masayuki; Tashiro, Takao

2014-04-07

We studied how the separation of dispensing and prescribing of medicines between pharmacies and clinics (the "separation system") can reduce internal medicine costs. To do so, we obtained publicly available data by searching electronic databases and official web pages of the Japanese government and non-profit public service corporations on the Internet. For Japanese medical institutions, participation in the separation system is optional. Consequently, the expansion rate of the separation system for each of the administrative districts is highly variable. The data were subjected to multiple regression analysis; daily internal medicines were the objective variable and expansion rate of the separation system was the explanatory variable. A multiple regression analysis revealed that the expansion rate of the separation system and the rate of replacing brand name medicine with generic medicine showed a significant negative partial correlation with daily internal medicine costs. Thus, the separation system was as effective in reducing medicine costs as the use of generic medicines. Because of its medical economic efficiency, the separation system should be expanded, especially in Asian countries in which the system is underdeveloped.

Potential use of multiple surveillance data in the forecast of hospital admissions

PubMed Central

Lau, Eric H.Y.; Ip, Dennis K.M.; Cowling, Benjamin J.

2013-01-01

Objective This paper describes the potential use of multiple influenza surveillance data to forecast hospital admissions for respiratory diseases. Introduction A sudden surge in hospital admissions in public hospital during influenza peak season has been a challenge to healthcare and manpower planning. In Hong Kong, the timing of influenza peak seasons are variable and early short-term indication of possible surge may facilitate preparedness which could be translated into strategies such as early discharge or reallocation of extra hospital beds. In this study we explore the potential use of multiple routinely collected syndromic data in the forecast of hospital admissions. Methods A multivariate dynamic linear time series model was fitted to multiple syndromic data including influenza-like illness (ILI) rates among networks of public and private general practitioners (GP), and school absenteeism rates, plus drop-in fever count data from designated flu clinics (DFC) that were created during the pandemic. The latent process derived from the model has been used as a measure of the influenza activity [1]. We compare the cross-correlations between estimated influenza level based on multiple surveillance data and GP ILI data, versus accident and emergency hospital admissions with principal diagnoses of respiratory diseases and pneumonia & influenza (P&I). Results The estimated influenza activity has higher cross-correlation with respiratory and P&I admissions (ρ=0.66 and 0.73 respectively) compared to that of GP ILI rates (Table 1). Cross correlations drop distinctly after lag 2 for both estimated influenza activity and GP ILI rates. Conclusions The use of a multivariate method to integrate information from multiple sources of influenza surveillance data may have the potential to improve forecasting of admission surge of respiratory diseases.

Deriving the Intrahepatic Arteriovenous Shunt Rate from CT Images and Biochemical Data Instead of from Arterial Perfusion Scintigraphy in Hepatic Arterial Infusion Chemotherapy

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

Ozaki, Toshiro, E-mail: ganronbun@amail.plala.or.jp; Seki, Hiroshi; Shiina, Makoto

2009-09-15

The purpose of the present study was to elucidate a method for predicting the intrahepatic arteriovenous shunt rate from computed tomography (CT) images and biochemical data, instead of from arterial perfusion scintigraphy, because adverse exacerbated systemic effects may be induced in cases where a high shunt rate exists. CT and arterial perfusion scintigraphy were performed in patients with liver metastases from gastric or colorectal cancer. Biochemical data and tumor marker levels of 33 enrolled patients were measured. The results were statistically verified by multiple regression analysis. The total metastatic hepatic tumor volume (V{sub metastasized}), residual hepatic parenchyma volume (V{sub residual};more » calculated from CT images), and biochemical data were treated as independent variables; the intrahepatic arteriovenous (IHAV) shunt rate (calculated from scintigraphy) was treated as a dependent variable. The IHAV shunt rate was 15.1 {+-} 11.9%. Based on the correlation matrixes, the best correlation coefficient of 0.84 was established between the IHAV shunt rate and V{sub metastasized} (p < 0.01). In the multiple regression analysis with the IHAV shunt rate as the dependent variable, the coefficient of determination (R{sup 2}) was 0.75, which was significant at the 0.1% level with two significant independent variables (V{sub metastasized} and V{sub residual}). The standardized regression coefficients ({beta}) of V{sub metastasized} and V{sub residual} were significant at the 0.1 and 5% levels, respectively. Based on this result, we can obtain a predicted value of IHAV shunt rate (p < 0.001) using CT images. When a high shunt rate was predicted, beneficial and consistent clinical monitoring can be initiated in, for example, hepatic arterial infusion chemotherapy.« less

Association between non-cholesterol sterol concentrations and Achilles tendon thickness in patients with genetic familial hypercholesterolemia.

PubMed

Baila-Rueda, Lucía; Lamiquiz-Moneo, Itziar; Jarauta, Estíbaliz; Mateo-Gallego, Rocío; Perez-Calahorra, Sofía; Marco-Benedí, Victoria; Bea, Ana M; Cenarro, Ana; Civeira, Fernando

2018-01-15

Familial hypercholesterolemia (FH) is a genetic disorder that result in abnormally high low-density lipoprotein cholesterol levels, markedly increased risk of coronary heart disease (CHD) and tendon xanthomas (TX). However, the clinical expression is highly variable. TX are present in other metabolic diseases that associate increased sterol concentration. If non-cholesterol sterols are involved in the development of TX in FH has not been analyzed. Clinical and biochemical characteristics, non-cholesterol sterols concentrations and Aquilles tendon thickness were determined in subjects with genetic FH with (n = 63) and without (n = 40) TX. Student-t test o Mann-Whitney test were used accordingly. Categorical variables were compared using a Chi square test. ANOVA and Kruskal-Wallis tests were performed to multiple independent variables comparison. Post hoc adjusted comparisons were performed with Bonferroni correction when applicable. Correlations of parameters in selected groups were calculated applying the non-parametric Spearman correlation procedure. To identify variables associated with Achilles tendon thickness changes, multiple linear regression were applied. Patients with TX presented higher concentrations of non-cholesterol sterols in plasma than patients without xanthomas (P = 0.006 and 0.034, respectively). Furthermore, there was a significant association between 5α-cholestanol, β-sitosterol, desmosterol, 24S-hydroxycholesterol and 27-hydroxycholesterol concentrations and Achilles tendon thickness (p = 0.002, 0.012, 0.020, 0.045 and 0.040, respectively). Our results indicate that non-cholesterol sterol concentrations are associated with the presence of TX. Since cholesterol and non-cholesterol sterols are present in the same lipoproteins, further studies would be needed to elucidate their potential role in the development of TX.

The contribution of hydroxylamine content to spatial variability of N2O formation in soil of a Norway spruce forest

NASA Astrophysics Data System (ADS)

Liu, Shurong; Herbst, Michael; Bol, Roland; Gottselig, Nina; Pütz, Thomas; Weymann, Daniel; Wiekenkamp, Inge; Vereecken, Harry; Brüggemann, Nicolas

2016-04-01

Hydroxylamine (NH2OH), a reactive intermediate of several microbial nitrogen turnover processes, is a potential precursor of nitrous oxide (N2O) formation in the soil. However, the contribution of soil NH2OH to soil N2O emission rates in natural ecosystems is unclear. Here, we determined the spatial variability of NH2OH content and potential N2O emission rates of organic (Oh) and mineral (Ah) soil layers of a Norway spruce forest, using a recently developed analytical method for the determination of soil NH2OH content, combined with a geostatistical Kriging approach. Potential soil N2O emission rates were determined by laboratory incubations under oxic conditions, followed by gas chromatographic analysis and complemented by ancillary measurements of soil characteristics. Stepwise multiple regressions demonstrated that the potential N2O emission rates, NH2OH and nitrate (NO3-) content were spatially highly correlated, with hotspots for all three parameters observed in the headwater of a small creek flowing through the sampling area. In contrast, soil ammonium (NH4+) was only weakly correlated with potential N2O emission rates, and was excluded from the multiple regression models. While soil NH2OH content explained the potential soil N2O emission rates best for both layers, also NO3- and Mn content turned out to be significant parameters explaining N2O formation in both soil layers. The Kriging approach was improved markedly by the addition of the co-variable information of soil NH2OH and NO3- content. The results indicate that determination of soil NH2OH content could provide crucial information for the prediction of the spatial variability of soil N2O emissions.

Factors related to achievement in sophomore organic chemistry at the University of Arkansas

NASA Astrophysics Data System (ADS)

Lindsay, Harriet Arlene

The purpose of this study was to identify the significant cognitive and non-cognitive variables that related to achievement in the first semester of organic chemistry at the University of Arkansas. Cognitive variables included second semester general chemistry grade, ACT composite score, ACT English, mathematics, reading, and science reasoning subscores, and spatial ability. Non-cognitive variables included anxiety, confidence, effectance motivation, and usefulness. Using a correlation research design, the individual relationships between organic chemistry achievement and each of the cognitive variables and non-cognitive variables were assessed. In addition, the relationships between organic chemistry achievement and combinations of these independent variables were explored. Finally, gender- and instructor-related differences in the relationships between organic chemistry achievement and the independent variables were investigated. The samples consisted of volunteers from the Fall 1999 and Fall 2000 sections of Organic Chemistry I at the University of Arkansas. All students in each section were asked to participate. Data for spatial ability and non-cognitive independent variables were collected using the Purdue Visualization of Rotations test and the modified Fennema-Sherman Attitude Scales. Data for other independent variables, including ACT scores and second semester general chemistry grades, were obtained from the Office of Institutional Research. The dependent variable, organic chemistry achievement, was measured by each student's accumulated points in the course and consisted of scores on quizzes and exams in the lecture section only. These totals were obtained from the lecture instructor at the end of each semester. Pearson correlation and stepwise multiple regression analyses were used to measure the relationships between organic chemistry achievement and the independent variables. Prior performance in chemistry as measured by second semester general chemistry grade was the best indicator of performance in organic chemistry. The importance of other independent variables in explaining organic chemistry achievement varied between instructors. In addition, gender differences were found in the explanations of organic chemistry achievement variance provided by this study. In general, males exhibited stronger correlations between independent variables and organic chemistry achievement than females. The report contains 19 tables detailing the statistical analyses. Suggestions for improved practice and further research are also included

Dysfunctional Metacognitive Beliefs in Body Dysmorphic Disorder

PubMed Central

Zeinodini, Zahra; Sedighi, Sahar; Rahimi, Mandana Baghertork; Noorbakhsh, Simasadat; Esfahani, Sepideh Rajezi

2016-01-01

The present study aims to examine the correlation of body dysmorphic disorder, with metacognitive subscales, metaworry and thought-fusion. The study was conducted in a correlation framework. Sample included 155 high school students in Isfahan, Iran in 2013-2014, gathered through convenience sampling. To gather data about BDD, Yale-Brown Obsessive Compulsive Scale Modified for BDD was applied. Then, Meta Cognitive Questionnaire, Metaworry Questionnaire, and Thought-Fusion Inventory were used to assess metacognitive subscales, metaworry and thought-fusion. Data obtained from this study were analyzed using Pearson correlation and multiple regressions in SPSS 18. Result indicated YBOCS-BDD scores had a significant correlation with scores from MCQ (P<0.05), MWG (P<0.05), and TFI (P<0.05). Also, multiple regressions were run to predict YBOCS from TFI, MWQ, and MCQ-30. These variables significantly predicted YBOCS [F (3,151) =32.393, R2=0.57]. Findings indicated that body dysmorphic disorder was significantly related to metacognitive subscales, metaworry, and thought fusion in high school students in Isfahan, which is in line with previous studies. A deeper understanding of these processes can broaden theory and treatment of BDD, thereby improve the lives of sufferers and potentially protect others from developing this devastating disorder. PMID:26493420

Characterizing regional soil mineral composition using spectroscopyand geostatistics

USGS Publications Warehouse

Mulder, V.L.; de Bruin, S.; Weyermann, J.; Kokaly, Raymond F.; Schaepman, M.E.

2013-01-01

This work aims at improving the mapping of major mineral variability at regional scale using scale-dependent spatial variability observed in remote sensing data. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data and statistical methods were combined with laboratory-based mineral characterization of field samples to create maps of the distributions of clay, mica and carbonate minerals and their abundances. The Material Identification and Characterization Algorithm (MICA) was used to identify the spectrally-dominant minerals in field samples; these results were combined with ASTER data using multinomial logistic regression to map mineral distributions. X-ray diffraction (XRD)was used to quantify mineral composition in field samples. XRD results were combined with ASTER data using multiple linear regression to map mineral abundances. We testedwhether smoothing of the ASTER data to match the scale of variability of the target sample would improve model correlations. Smoothing was donewith Fixed Rank Kriging (FRK) to represent the mediumand long-range spatial variability in the ASTER data. Stronger correlations resulted using the smoothed data compared to results obtained with the original data. Highest model accuracies came from using both medium and long-range scaled ASTER data as input to the statistical models. High correlation coefficients were obtained for the abundances of calcite and mica (R2 = 0.71 and 0.70, respectively). Moderately-high correlation coefficients were found for smectite and kaolinite (R2 = 0.57 and 0.45, respectively). Maps of mineral distributions, obtained by relating ASTER data to MICA analysis of field samples, were found to characterize major soil mineral variability (overall accuracies for mica, smectite and kaolinite were 76%, 89% and 86% respectively). The results of this study suggest that the distributions of minerals and their abundances derived using FRK-smoothed ASTER data more closely match the spatial variability of soil and environmental properties at regional scale.

Some environmental and attitudinal characteristics as predictors of mathematical creativity

NASA Astrophysics Data System (ADS)

Kanhai, Abhishek; Singh, Bhoodev

2017-04-01

There are many things which can be made more useful and interesting through the application of creativity. Self-concept in mathematics and some school environmental factors such as resource adequacy, teachers' support to the students, teachers' classroom control, creative stimulation by the teachers, etc. were selected in the study. The sample of the study comprised 770 seventh grade students. Pearson correlation, multiple correlation, regression equation and multiple discriminant function analyses of variance were used to analyse the data. The result of the study showed that the relationship between mathematical creativity and each attitudinal and environmental characteristic was found to be positive and significant. Index of forecasting efficiency reveals that mathematical creativity may be best predicted by self-concept in mathematics. Environmental factors, resource adequacy and creative stimulation by the teachers' are found to be the most important factors for predicting mathematical creativity, while social-intellectual involvement among students and educational administration of the schools are to be suppressive factors. The multiple correlation between mathematical creativity and attitudinal and school environmental characteristic suggests that the combined contribution of these variables plays a significant role in the development of mathematical creativity. Mahalanobis analysis indicates that self-concept in mathematics and total school environment were found to be contributing significantly to the development of mathematical creativity.

Velocity landscape correlation resolves multiple flowing protein populations from fluorescence image time series.

PubMed

Pandžić, Elvis; Abu-Arish, Asmahan; Whan, Renee M; Hanrahan, John W; Wiseman, Paul W

2018-02-16

Molecular, vesicular and organellar flows are of fundamental importance for the delivery of nutrients and essential components used in cellular functions such as motility and division. With recent advances in fluorescence/super-resolution microscopy modalities we can resolve the movements of these objects at higher spatio-temporal resolutions and with better sensitivity. Previously, spatio-temporal image correlation spectroscopy has been applied to map molecular flows by correlation analysis of fluorescence fluctuations in image series. However, an underlying assumption of this approach is that the sampled time windows contain one dominant flowing component. Although this was true for most of the cases analyzed earlier, in some situations two or more different flowing populations can be present in the same spatio-temporal window. We introduce an approach, termed velocity landscape correlation (VLC), which detects and extracts multiple flow components present in a sampled image region via an extension of the correlation analysis of fluorescence intensity fluctuations. First we demonstrate theoretically how this approach works, test the performance of the method with a range of computer simulated image series with varying flow dynamics. Finally we apply VLC to study variable fluxing of STIM1 proteins on microtubules connected to the plasma membrane of Cystic Fibrosis Bronchial Epithelial (CFBE) cells. Copyright © 2018 Elsevier Inc. All rights reserved.

An ecological study on suicide and homicide in Brazil.

PubMed

Bando, Daniel Hideki; Lester, David

2014-04-01

The objective was to evaluate correlations between suicide, homicide and socio-demographic variables by an ecological study. Mortality and socio-demographic data were collected from official records of the Ministry of Health and IBGE (2010), aggregated by state (27). The data were analyzed using correlation techniques, factor analysis, principal component analysis with a varimax rotation and multiple linear regression. Suicide age-adjusted rates for the total population, men and women were 5.0, 8.0, and 2.2 per 100,000 inhabitants respectively. The suicide rates ranged from 2.7 in Pará to 9.1 in Rio Grande do Sul. Homicide for the total population, men and women were 27.2, 50.8, and 4.5 per 100,000, respectively. The homicide rates ranged from 13.0 in Santa Catarina to 68.9 in Alagoas. Suicide and homicide were negatively associated, the significance persisted among men. Unemployment was negatively correlated with suicide and positively with homicide. Different socio-demographic variables were found to correlate with suicide and homicide in the regressions. Suicide showed a pattern suggesting that, in Brazil, it is related to high socioeconomic status. Homicide seemed to follow the pattern found in other countries, associated with lower social and economic status.

Unravelling the architecture of functional variability in wild populations of Polygonum viviparum L

PubMed Central

Boucher, Florian C.; Thuiller, Wilfried; Arnoldi, Cindy; Albert, Cécile H.; Lavergne, Sébastien

2014-01-01

SUMMARY Functional variability (FV) of populations can be decomposed into three main features: the individual variability of multiple traits, the strength of correlations between those traits and the main direction of these correlations, the latter two being known as ‘phenotypic integration’. Evolutionary biology has long recognized that FV in natural populations is key to determining potential evolutionary responses, but this topic has been little studied in functional ecology. Here we focus on the arctico-alpine perennial plant species Polygonum viviparum L.. We used a comprehensive sampling of seven functional traits in 29 wild populations covering the whole environmental niche of the species. The niche of the species was captured by a temperature gradient, which separated alpine stressful habitats from species-rich, competitive sub-alpine ones. We seeked to assess the relative roles of abiotic stress and biotic interactions in shaping different aspects of functional variation within and among populations, that is, the multi-trait variability, the strength of correlations between traits, and the main directions of functional trade-offs. Populations with the highest extent of functional variability were found in the warm end of the gradient whereas populations exhibiting the strongest degree of phenotypic integration were located in sites with intermediate temperatures. This could reveal both the importance of environmental filtering and population demography in structuring FV. Interestingly, we found that the main axes of multivariate functional variation were radically different within and across population. Although the proximate causes of FV structure remain uncertain, our study presents a robust methodology for the quantitative study of functional variability in connection with species’ niches. It also opens up new perspectives for the conceptual merging of intraspecific functional patterns with community ecology. PMID:24790285

The influence of daily stress and resilience on successful ageing.

PubMed

Byun, J; Jung, D

2016-09-01

The aim of this study was to identify the effects of daily stress and resilience on successful ageing among community-dwelling older adults. Ageing can be a positive experience if there is good adaptation to ageing processes. Positive ageing needs to be a basis of nursing care, health promotion and education within community settings. Data were collected in March and April of 2014 from 262 older adults living in Seoul and Jeju, South Korea. We used a four-part survey consisting of demographic data, daily stress, resilience and successful ageing scales, in total 91 items. Data were analysed using descriptive statistics, t-test, one-way ANOVA, Tukey HSD test, Pearson's correlation coefficient and hierarchical multiple regression analysis to identify the influence of variables on successful ageing. Successful ageing had a significant negative correlation with daily stress and a positive correlation with resilience. Daily stress had a negative correlation with resilience. Findings of hierarchical multiple regression analysis indicated that resilience and subjective economic status had an effect on successful ageing. Furthermore, these variables accounted for 41.6% of the variance in successful ageing. Data were collected in only two cities of Korea based on convenience sampling. The findings of the study suggest that daily stress and resilience have a statistically significant relationship with successful ageing. Furthermore, resilience is an important influential factor and a much-needed personal characteristic for one's successful ageing. Nurses can advocate joining with health and social policy makers to implement policies on healthy ageing, including evaluation of stress, education programmes and implementation of self-help groups to enhance resilience in older people. © 2016 International Council of Nurses.

Correlation of geographic distributions of haptoglobin alleles with prevalence of multiple sclerosis (MS) - a narrative literature review.

PubMed

Bamm, Vladimir V; Geist, Arielle M; Harauz, George

2017-02-01

We have proposed that the myelin damage observed in multiple sclerosis (MS) may be partly mediated through the long-term release and degradation of extracellular hemoglobin (Hb) and the products of its oxidative degradation [Cellular and Molecular Life Sciences, 71, 1789-1798, 2014]. The protein haptoglobin (Hpt) binds extracellular Hb as a first line of defense, and can serve as a vascular antioxidant. Humans have two different Hpt alleles: Hpt1 and Hpt2, giving either homozygous Hpt1-1 or Hpt2-2 phenotypes, or a heterozygous Hpt1-2 phenotype. We questioned whether those geographic regions with higher frequency of the Hpt2 allele (conversely, lower frequency of Hpt1 allele) would correlate with an increased incidence of MS, because different Hpt phenotypes will have variable anti-oxidative potentials in protecting myelin from damage inflicted by extracellular Hb and its degradation products. To test this hypothesis, we undertook a systematic analysis of the literature on reported geographic distributions of Hpt alleles to compare them with data reported in the World Health Organization Atlas of worldwide MS prevalence. We found the frequency of the Hpt1 allele to be low in European and North American countries with a high prevalence of MS, consistent with our hypothesis. However, this correlation was not observed in China and India, countries with the lowest Hpt1 frequencies, yet low reported prevalence of MS. Nevertheless, this work shows the need for continued refinement of geographic patterns of MS prevalence, including data on ethnic or racial origin, and for new clinical studies to probe the observed correlation and evaluate Hpt phenotype as a predictor of disease variability and progression, severity, and/or comorbidity with cardiovascular disorders.

Cross-national evidence for the clustering and psychosocial correlates of adolescent risk behaviours in 27 countries.

PubMed

de Looze, Margaretha; Ter Bogt, Tom F M; Raaijmakers, Quinten A W; Pickett, William; Kuntsche, Emmanuel; Vollebergh, Wilma A M

2015-02-01

According to Jessor's Problem Behaviour Theory (PBT) and Moffitt's theory of adolescence-limited antisocial behaviour, adolescent risk behaviours cluster and can be predicted by various psychosocial factors including parent, peer and school attachment. This study tested the potential influence of the sociocultural, or macro-level, environment on the clustering and correlates of adolescent risk behaviour across 27 European and North American countries. Analyses were based on data from the 2009-10 Health Behaviour in School-aged Children (HBSC) study. Participants compromised 56,090 adolescents (M(age) = 15.5 years) who self-reported on substance use (tobacco, alcohol, cannabis) and early sexual activity as well as on psychosocial factors (parent, peer and school attachment). Multiple group confirmatory factor analyses (with country as grouping variable) showed that substance use and early sexual activity loaded on a single underlying factor across countries. In addition, multiple group path analyses (with country as grouping variable) showed that associations between this factor and parent, peer and school attachment were identical across countries. Cross-national consistencies exist in the clustering and psychosocial correlates of substance use and early sexual activity across western countries. While Jessor's PBT stresses the problematic aspects of adolescent risk behaviours, Moffitt emphasizes their normative character. Although the problematic nature of risk behaviours overall receives more attention in the literature, it is important to consider both perspectives to fully understand why they cluster and correlate with psychosocial factors. This is essential for the development and implementation of prevention programmes aimed at reducing adolescent risk behaviours across Europe and North America. © The Author 2014. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Effect of knee osteoarthritis on the perception of quality of life in Venezuelan patients.

PubMed

Chacón, José G; González, Nancy E; Véliz, Aleida; Losada, Benito R; Paul, Hernando; Santiago, Luís G; Antúnez, Ana; Finol, Yelitza; González, María E; Granados, Isabel; Maldonado, Irama; Maldonado, Teolinda; Marín, Francisco; Zambrano, Gisela; Rodríguez, Martín A

2004-06-15

To measure the perception of quality of life in Venezuelan patients with knee osteoarthritis and to identify those variables that may influence it. A multicenter, cross-sectional study of 126 mestizo patients with knee osteoarthritis recruited from 8 rheumatology centers in Venezuela. We used a Spanish-translated version of the Arthritis Impact Measurement Scales (AIMS), as adapted in Venezuela. One-way analysis of variance was used to compare the AIMS mean total score among subgroups of knee pain, anatomic stage, and socioeconomic status (SES); a post-hoc test was performed to identify significant intragroup differences. Pearson's correlation coefficient was used to examine correlations between age, body mass index (BMI), disease duration, knee pain, and AIMS score. Associations between radiologic stage, SES, and AIMS scores were examined using Spearman's rank correlation. Multiple regression analysis was used to estimate predictor factors of AIMS scores. A significant correlation was found between total AIMS scores and knee pain, age, and socioeconomic status, but not with BMI, disease duration, or anatomic stage. Patients with severe knee pain differed from those with mild and moderate pain, and the highest AIMS mean total score was seen in patients within the severe knee pain subset. Patients in the highest socioeconomic levels differed from those within lowest categories. Patients classified as being at the levels of relative and critical poverty showed the highest AIMS scores. Multiple regression analysis showed that knee pain was the only variable that exerted an independent effect on the quality of life in our patients. The perception of quality of life is negatively affected by increasing levels of joint pain, old age, and low socioeconomic status in Venezuelan patients with knee osteoarthritis. Our study supports the need for an early and vigorous approach to treat pain in this group of patients.

Comparisons of Office and 24-Hour Ambulatory Blood Pressure Monitoring in Children with Obstructive Sleep Apnea.

PubMed

Kang, Kun-Tai; Chiu, Shuenn-Nan; Weng, Wen-Chin; Lee, Pei-Lin; Hsu, Wei-Chung

2017-03-01

To compare office blood pressure (BP) and 24-hour ambulatory BP (ABP) monitoring to facilitate the diagnosis and management of hypertension in children with obstructive sleep apnea (OSA). Children aged 4-16 years with OSA-related symptoms were recruited from a tertiary referral medical center. All children underwent overnight polysomnography, office BP, and 24-hour ABP studies. Multiple linear regression analyses were applied to elucidate the association between the apnea-hypopnea index and BP. Correlation and consistency between office BP and 24-hour ABP were measured by Pearson correlation, intraclass correlation, and Bland-Altman analyses. In the 163 children enrolled (mean age, 8.2 ± 3.3 years; 67% male). The prevalence of systolic hypertension at night was significantly higher in children with moderate-to-severe OSA than in those with primary snoring (44.9% vs 16.1%, P = .006). Pearson correlation and intraclass correlation analyses revealed associations between office BP and 24-hour BP, and Bland-Altman analysis indicated an agreement between office and 24-hour BP measurements. However, multiple linear regression analyses demonstrated that 24-hour BP (nighttime systolic BP and mean arterial pressure), unlike office BP, was independently associated with the apnea-hypopnea index, after adjustment for adiposity variables. Twenty-four-hour ABP is more strongly correlated with OSA in children, compared with office BP. Copyright © 2016 Elsevier Inc. All rights reserved.

Movement measurements at home for multiple sclerosis: walking speed measured by a novel ambient measurement system.

PubMed

Smith, Victoria Mj; Varsanik, Jonathan S; Walker, Rachel A; Russo, Andrew W; Patel, Kevin R; Gabel, Wendy; Phillips, Glenn A; Kimmel, Zebadiah M; Klawiter, Eric C

2018-01-01

Gait disturbance is a major contributor to clinical disability in multiple sclerosis (MS). A sensor was developed to assess walking speed at home for people with MS using infrared technology in real-time without the use of wearables. To develop continuous in-home outcome measures to assess gait in adults with MS. Movement measurements were collected continuously for 8 months from six people with MS. Average walking speed and peak walking speed were calculated from movement data, then analyzed for variability over time, by room (location), and over the course of the day. In-home continuous gait outcomes and variability were correlated with standard in-clinic gait outcomes. Measured in-home average walking speed of participants ranged from 0.33 m/s to 0.96 m/s and peak walking speed ranged from 0.89 m/s to 1.51 m/s. Mean total within-participant coefficient of variation for daily average walking speed and peak walking speed were 10.75% and 10.93%, respectively. Average walking speed demonstrated a moderately strong correlation with baseline Timed 25-Foot Walk (r s  = 0.714, P  = 0.111). New non-wearable technology provides reliable and continuous in-home assessment of walking speed.

Relationship between Climate Variability, Wildfire Risk, and Wildfire Occurrence in Wildland-Urban Interface of the Southwestern United States

NASA Astrophysics Data System (ADS)

Kafatos, M.; Kim, S. H.; Jia, S.; Nghiem, S. V.

2017-12-01

As housing units in or near wildlands have grown, the wildland-urban interface (WUI) contain at present approximately one-third of all housing in the contiguous US. Wildfires are a part of the natural cycle in the Southwestern United States (SWUS) but the increasing trend of WUI has made wildfires a serious high-risk hazard. The expansion of WUI has elevated wildfire risks by increasing the chance of human caused ignitions and past fire suppression in the area. Previous studies on climate variability have shown that the SWUS region is prone to frequent droughts and has suffered from severe wildfires in the recent decade. Therefore, assessing the increased vulnerability to the wildfire in WUI is crucial for proactive adaptation under climate change. Our previous study has shown that a strong correlation between North Atlantic Oscillation (NAO) and temperature was found during March-June in the SWUS. The abnormally warm and dry spring conditions, combined with suppression of winter precipitation, can cause an early start of a fire season and high fire risk throughout the summer and fall. Therefore, it is crucial to investigate the connections between climate variability and wildfire danger characteristics. This study aims to identify climate variability using multiple climate indices such as NAO, El Niño-Southern Oscillation and the Pacific Decadal Oscillation closely related with droughts in the SWUS region. Correlation between the variability and fire frequency and severity in WUI were examined. Also, we investigated climate variability and its relationship on local wildfire potential using both Keetch-Byram Drought Index (KBDI) and Fire Weather Index (FWI) which have been used to assessing wildfire potential in the U.S.A and Canada, respectively. We examined the long-term variability of the fire potential indices and relationships between the indices and historical occurrence in WUI using multi-decadal reanalysis data sets. Following our analysis, we investigated joint impacts of multiple climate indices on droughts and human activities in the WUI for regional wildfire potential.

Importance of Preserving Cross-correlation in developing Statistically Downscaled Climate Forcings and in estimating Land-surface Fluxes and States

NASA Astrophysics Data System (ADS)

Das Bhowmik, R.; Arumugam, S.

2015-12-01

Multivariate downscaling techniques exhibited superiority over univariate regression schemes in terms of preserving cross-correlations between multiple variables- precipitation and temperature - from GCMs. This study focuses on two aspects: (a) develop an analytical solutions on estimating biases in cross-correlations from univariate downscaling approaches and (b) quantify the uncertainty in land-surface states and fluxes due to biases in cross-correlations in downscaled climate forcings. Both these aspects are evaluated using climate forcings available from both historical climate simulations and CMIP5 hindcasts over the entire US. The analytical solution basically relates the univariate regression parameters, co-efficient of determination of regression and the co-variance ratio between GCM and downscaled values. The analytical solutions are compared with the downscaled univariate forcings by choosing the desired p-value (Type-1 error) in preserving the observed cross-correlation. . For quantifying the impacts of biases on cross-correlation on estimating streamflow and groundwater, we corrupt the downscaled climate forcings with different cross-correlation structure.

Low-resolution brain electromagnetic tomography (LORETA) identifies brain regions linked to psychometric performance under modafinil in narcolepsy.

PubMed

Saletu, Michael; Anderer, Peter; Semlitsch, Heribert V; Saletu-Zyhlarz, Gerda Maria; Mandl, Magdalena; Zeitlhofer, Josef; Saletu, Bernd

2007-01-15

Low-resolution brain electromagnetic tomography (LORETA) showed a functional deterioration of the fronto-temporo-parietal network of the right hemispheric vigilance system in narcolepsy and a therapeutic effect of modafinil. The aim of this study was to determine the effects of modafinil on cognitive and thymopsychic variables in patients with narcolepsy and investigate whether neurophysiological vigilance changes correlate with cognitive and subjective vigilance alterations at the behavioral level. In a double-blind, placebo-controlled crossover design, EEG-LORETA and psychometric data were obtained during midmorning hours in 15 narcoleptics before and after 3 weeks of placebo or 400 mg modafinil. Cognitive investigations included the Pauli Test and complex reaction time. Thymopsychic/psychophysiological evaluation comprised drive, mood, affectivity, wakefulness, depression, anxiety, the Symptom Checklist 90 and critical flicker frequency. The Multiple Sleep Latency Test (MSLT) and the Epworth Sleepiness Scale (ESS) were performed too. Cognitive performance (Pauli Test) was significantly better after modafinil than after placebo. Concerning reaction time and thymopsychic variables, no significant differences were observed. Correlation analyses revealed that a decrease in prefrontal delta, theta and alpha-1 power correlated with an improvement in cognitive performance. Moreover, drowsiness was positively correlated with theta power in parietal and medial prefrontal regions and beta-1 and beta-2 power in occipital regions. A less significant correlation was observed between midmorning EEG LORETA and the MSLT; between EEG LORETA and the ESS, the correlation was even weaker. In conclusion, modafinil did not influence thymopsychic variables in narcolepsy, but it significantly improved cognitive performance, which may be related to medial prefrontal activity processes identified by LORETA.

Longitudinal variability in outdoor, indoor, and personal PM 2.5 exposure in healthy non-smoking adults

NASA Astrophysics Data System (ADS)

Adgate, J. L.; Ramachandran, G.; Pratt, G. C.; Waller, L. A.; Sexton, K.

Multiple 24-h average outdoor, indoor and personal PM 2.5 measurements were made in a population of healthy non-smoking adults from the Minneapolis-St. Paul metropolitan area between April and November 1999. Personal ( P) PM 2.5 concentrations were higher than indoor ( I) concentrations, which were higher than outdoor (O) concentrations. For 28 adults with a median of 9 (range 5-11) measurements per person, the distribution of longitudinal (i.e., within-person) correlation coefficients between P and I was moderate (median r=0.45). The distribution of longitudinal correlation coefficients between I and O concentrations showed that these variables were less strongly associated (median r=0.25; 28 residences; measurement median n=10 per residence, range 7-13), and the distribution of P and O correlation coefficients (median r=0.02; 29 subjects; measurement median n=11 per subject, range 7-15) showed little statistical relation between these two variables for a majority of participants. A sensitivity analysis indicated that correlations did not increase if days with exposure to environmental tobacco smoke or occupational exposures were excluded. On average these adults spent 91% of their time indoors, and the mean of the average PM 2.5 "personal cloud" was 15.3 μg/m 3. Participants who had the largest personal cloud values tended to work outside the home and spent more time outdoors than subjects who did not work outside the home. In this population of healthy non-smoking adults, personal exposure to PM 2.5 does not correlate strongly with outdoor central site PM 2.5 concentrations.

Variability of FUV Emission Line in Classical T Tauri Stars as a Diagnostic for Disc Accretion

NASA Astrophysics Data System (ADS)

Ramkumar, B.; Johns-Krull, C. M.

2005-12-01

We present our results of FUV emission line variability studies done on four classical T Tauri stars. We have used the IUE Final Archive spectra of pre-main sequence stars to analyze the sample of four stars BP Tau, DR Tau, RU Lup and RY Tau where each of these low-resolution (R ˜6 Å) spectra was observed in the IUE short-wavelength band pass (1150--1980Å). Given a broad time line of multiple observations being available from the IUE Final archive, an intrinsic variability study has been possible with this sample. Our results indicate that the transition region lines \\ion{Si}{4} and \\ion{C}{4}, produced near the accretion shocks at ˜105 K, have a strong correlation between them in all four stars except DR Tau. We also observe a strong correlation between \\ion{C}{4} & \\ion{He}{2} on our entire sample with a correlation coefficient of 0.549 (false alarm probability = 7.9 x 10-2) or higher. In addition, \\ion{He}{2} correlates with the molecular hydrogen (1503Å) line in all but RU Lup. If the \\ion{He}{2} lines are produced because of X-ray ionization then the observed molecular hydrogen emission is indeed controlled by X-ray ionization and therefore \\ion{He}{2} could serve as an X-ray proxy for future studies. Also, our correlation results strengthen the fact that \\ion{C}{4} is a good predictor of \\ion{Si}{4} and have a common origin i.e. in accretion shocks in the star formation process.

Should efforts in favor of medical student diversity be focused during admissions or farther upstream?

PubMed

Reiter, Harold I; Lockyer, Jocelyn; Ziola, Barry; Courneya, Carol-Ann; Eva, Kevin

2012-04-01

Traditional medical school admissions assessment tools may be limiting diversity. This study investigates whether the Multiple Mini-Interview (MMI) is diversity-neutral and, if so, whether applying it with greater weight would dilute the anticipated negative impact of diversity-limiting admissions measures. Interviewed applicants to six medical schools in 2008 and 2009 underwent MMI. Predictor variables of MMI scores, grade point average (GPA), and Medical College Admission Test (MCAT) scores were correlated with diversity measures of age, gender, size of community of origin, income level, and self-declared aboriginal status. A subset of the data was then combined with variable weight assigned to predictor variables to determine whether weighting during the applicant selection process would affect diversity among chosen applicants. MMI scores were unrelated to gender, size of community of origin, and income level. They correlated positively with age and negatively with aboriginal status. GPA and MCAT correlated negatively with age and aboriginal status, GPA correlated positively with income level, and MCAT correlated positively with size of community of origin. Even extreme combinations of MMI and GPA weightings failed to increase diversity among applicants who would be selected on the basis of weighted criteria. MMI could not neutralize the diversity-limiting properties of academic scores as selection criteria to interview. Using academic scores in this way causes range restriction, counteracting attempts to enhance diversity using downstream admissions selection measures such as MMI. Diversity efforts should instead be focused upstream. These results lend further support for the development of pipeline programs.

Self-care of patients with diabetes mellitus cared for at an emergency service in Mexico.

PubMed

Baquedano, Irasema Romero; dos Santos, Manoel Antônio; Martins, Tatiane Aparecida; Zanetti, Maria Lúcia

2010-01-01

This study examines the self-care ability of type 2 diabetes mellitus patients and relates it to sociodemographic and clinical variables. The study included 251 patients who were cared for by an emergency service in Mexico, in 2007. Data were obtained through structured interviews held at participants' households, through a form, a questionnaire and the Self-Care Ability Scale. Descriptive and correlation statistics were used for data analysis. The results show that 83 (33.5%) individuals displayed good self-care ability and 168 (66.5%) individuals displayed regular ability. A directly proportional correlation was found between self-care ability and schooling (r=0.124; p<0.05), as well as a negative correlation for religion (rs=-0.435; p<0.05) and duration of disease evolution (r=-0.667; p<0.05). The conclusion is that most of the individuals with type 2 diabetes mellitus displayed regular ability for self-care. Self-care ability is related to multiple variables that should be taken into account by health professionals when suggesting educational programs.

When in doubt, ask the audience: potential users' perceptions of Internet-delivered cognitive behavioural therapy for chronic pain.

PubMed

Schneider, Luke H; Hadjistavropoulos, Heather D

2014-01-01

Although research has demonstrated that Internet-delivered cognitive behavioural therapy (ICBT) for chronic pain helps with adjustment to pain, it remains unclear how this treatment option would initially be perceived by individuals with chronic pain. To explore initial perceptions of ICBT and to examine variables that correlate with an expressed interest in ICBT as a treatment option among individuals with chronic pain. A total of 129 individuals with chronic pain completed a survey assessing perceptions of ICBT and individual difference variables that could be correlated with expressed interest in ICBT (eg, demographic characteristics, pain, computer self-efficacy). Results showed that most participants perceived ICBT as a potentially valuable service with multiple benefits. Being female, having greater pain severity and interference, and having greater computer self-efficacy and lower computer anxiety were positively correlated with interest in receiving ICBT. Combined with previous research on treatment efficacy of ICBT for chronic pain, the results should serve to stimulate further research on integrating ICBT within existing health care services.

Factors Associated with Blood Pressure Variability Based on Ambulatory Blood Pressure Monitoring in Subjects with Hypertension in China.

PubMed

Li, Wei; Yu, YanXia; Liang, Dehong; Jia, En-Zhi

2017-01-01

We examined the factors associated with blood pressure variability in a multi-ethnicity prospective study in China to gain more evidence to guide the prevention and management of hypertension through risk factor intervention. A total of 318 consecutive adult subjects aged 29-94 years with suspected or known hypertension were enrolled in this study. Blood pressure variability measurements were based on ambulatory blood pressure monitoring. To measure short-term reading-to-reading blood pressure variability in this study, we used the standard deviation(SD) of the blood pressure to estimate the blood pressure variability. The SDs of the blood pressure in this study ranged from 5.425 to 32.25, with a median of 10.81 (quartile range, 8.90-12.46). No significant difference regarding the level distribution of blood pressure variability was found across the various ethnicities. Spearman correlation analyses indicated that the SD of blood pressure was positively correlated with DSBP (r=0.302, p=<0.001), NSBP (r=0.383, p=<0.001), NDBP (r=0.230, p=<0.001), and FBG (r=0.129, p=0.023) and was negatively correlated with triglyceride (r=-0.289, p=<0.001), CR (r=-0.242, p=<0.001), HDL-C (r=-0.230, p=<0.001), LDL-C (r=-0.186, p=0.001), and apolipoprotein B levels (r=-0.157, p=0.006). Multiple linear regression analysis indicated that triglycerides (β=-0.217, p=<0.001), NSBP (β=0.174, p=0.003), FBG (β=0.128, p=0.024), DDBP (β=-0.128, p=0.022), and apolipoprotein A (β=-0.116, p=0.036) were significantly and independently associated with the blood pressure variability. In this study, blood pressure variability was significantly associated with not only blood pressure levels but also patient demographic, clinical and biochemical characteristics. © 2017 The Author(s). Published by S. Karger AG, Basel.

Do evoked potentials contribute to the functional follow-up and clinical prognosis of multiple sclerosis?

PubMed

Giffroy, Xavier; Maes, Nathalie; Albert, Adelin; Maquet, Pierre; Crielaard, Jean-Michel; Dive, Dominique

2017-03-01

The clinical variability and complexity of multiple sclerosis (MS) challenges the individual clinical course prognostication. This study aimed to find out whether multimodal evoked potentials (EP) correlate with the motor components of multiple sclerosis functional composite (MSFCm) and predict clinically relevant motor functional deterioration. One hundred MS patients were assessed at baseline (T 0 ) and about 7.5 years later (T 1 ), with visual, somatosensory and motor EP and rated on the Expanded Disability Status Scale (EDSS) and the MSFCm, including the 9 Hole Peg Test and the Timed 25 Foot Walk (T25FW). The Spearman correlation coefficient (r S ) was used to evaluate the cross-sectional and longitudinal relationship between EP Z scores and clinical findings. The predictive value of baseline electrophysiological data for clinical worsening (EDSS, 9-HPT, T25FW, MSFCm) during follow-up was assessed by logistic regression analysis. Unlike longitudinal correlations, cross-sectional correlations between EP Z scores and clinical outcomes were all significant and ranged between 0.22 and 0.67 (p < 0.05). The global EP Z score was systematically predictive of EDSS and MSFCm worsening over time (all p < 0.05). EP latency was a better predictor than amplitude, although weaker than latency and amplitude aggregation in the global EP Z score. The study demonstrates that EP numerical scores can be used for motor function monitoring and outcome prediction in patients with MS.

High school science enrollment of black students

NASA Astrophysics Data System (ADS)

Goggins, Ellen O.; Lindbeck, Joy S.

How can the high school science enrollment of black students be increased? School and home counseling and classroom procedures could benefit from variables identified as predictors of science enrollment. The problem in this study was to identify a set of variables which characterize science course enrollment by black secondary students. The population consisted of a subsample of 3963 black high school seniors from The High School and Beyond 1980 Base-Year Survey. Using multiple linear regression, backward regression, and correlation analyses, the US Census regions and grades mostly As and Bs in English were found to be significant predictors of the number of science courses scheduled by black seniors.

Analysis of the thermal comfort model in an environment of metal mechanical branch.

PubMed

Pinto, N M; Xavier, A A P; do Amaral, Regiane T

2012-01-01

This study aims to identify the correlation between the Predicted Mean Vote (PMV) with the thermal sensation (S) of 55 employees, establishing a linear multiple regression equation. The measurement of environmental variables followed established standards. The survey was conducted in a metal industry located in Ponta Grossa of the State of Parana in Brazil. It was applied the physical model of thermal comfort to the environmental variables and also to the subjective data on the thermal sensations of employees. The survey was conducted from May to November, 2010, with 48 measurements. This study will serve as the basis for a dissertation consisting of 72 measurements.

Quality of life in multiple sclerosis (MS) and role of fatigue, depression, anxiety, and stress: A bicenter study from north of Iran

PubMed Central

Salehpoor, Ghasem; Rezaei, Sajjad; Hosseininezhad, Mozaffar

2014-01-01

Background: Although studies have demonstrated significant negative relationships between quality of life (QOL), fatigue, and the most common psychological symptoms (depression, anxiety, stress), the main ambiguity of previous studies on QOL is in the relative importance of these predictors. Also, there is lack of adequate knowledge about the actual contribution of each of them in the prediction of QOL dimensions. Thus, the main objective of this study is to assess the role of fatigue, depression, anxiety, and stress in relation to QOL of multiple sclerosis (MS) patients. Materials and Methods: One hundred and sixty-two MS patients completed the questionnaire on demographic variables, and then they were evaluated by the Persian versions of Short-Form Health Survey Questionnaire (SF-36), Fatigue Survey Scale (FSS), and Depression, Anxiety, Stress Scale-21 (DASS-21). Data were analyzed by Pearson correlation coefficient and hierarchical regression. Results: Correlation analysis showed a significant relationship between QOL elements in SF-36 (physical component summary and mental component summary) and depression, fatigue, stress, and anxiety (P < 0.01). Hierarchical regression analysis indicated that among the predictor variables in the final step, fatigue, depression, and anxiety were identified as the physical component summary predictor variables. Anxiety was found to be the most powerful predictor variable amongst all (β = −0.46, P < 0.001). Furthermore, results have shown depression as the only significant mental component summary predictor variable (β = −0.39, P < 0.001). Conclusions: This study has highlighted the role of anxiety, fatigue, and depression in physical dimensions and the role of depression in psychological dimensions of the lives of MS patients. In addition, the findings of this study indirectly suggest that psychological interventions for reducing fatigue, depression, and anxiety can lead to improved QOL of MS patients. PMID:25558256

Evaluation of gait kinetics in puppies with coxofemoral joint laxity

PubMed Central

Lopez, Mandi J.; Quinn, Margaret M.; Markel, Mark D.

2007-01-01

Objective To characterize ground reaction forces (GRFs) and determine whether there were correlations between forces and passive coxofemoral joint laxity in puppies. Animals Fifty-one 16-week-old hound-breed dogs. Procedure Force-plate gait evaluation and distraction radiographic imaging were performed. Ground reaction forces evaluated included x (mediolateral), y (craniocaudal breaking and propulsion), and z (vertical) peak force and impulse. Z-plane limb loading and unloading rates, loading interval, and weight distribution and y-plane stance time breaking and propulsion percentages were calculated. One-way ANOVA with the Duncan multiple range test was used to evaluate differences in gait variables among limbs. The relationships of left, right, highest, and mean distraction index (DI) with individual limb data of each dog were evaluated with the Spearman rank correlation. Left and right DIs were compared by means of linear regression analysis. Results Mean ± SEM DI was 0.67 ± 0.02. Left and right DIs were strongly correlated, but there were no significant relationships between DIs and gait variables. Most fore- and hind limb gait variables differed significantly, whereas paired fore- and hind limb gait variables did not. Asymmetry was most pronounced in the x- and y-planes. Conclusions and Clinical Relevance GRFs were consistent with those of clinically normal mature dogs, supporting an absence of association between GRF and DI in young dogs. The GRFs and elucidation of the relationship between GRFs and DI may be useful for future studies in immature dogs. PMID:16454627

Postural response latencies are related to balance control during standing and walking in patients with multiple sclerosis

PubMed Central

Huisinga, Jessie M.; St. George, Rebecca J.; Spain, Rebecca; Overs, Shannon; Horak, Fay B.

2015-01-01

Objective To understand examined the relationship between postural response latencies obtained during postural perturbations and representative measures of balance during standing (sway variables) and during walking (trunk motion). Design Cross-sectional Setting University medical center balance disorders laboratory Participants Forty persons with MS were compared with 20 similar aged control subjects. Twenty subjects with MS had normal walking velocity group and 20 had slow walking velocity based on the 25-foot walk time greater than 5 seconds. Interventions None Main Outcome Measures Postural response latency, sway variables, trunk motion variables Results: We found that subjects with MS with either slow or normal walking velocities had significantly longer postural response latencies than the healthy control group. Postural response latency was not correlated with the 25-ft walk time. Postural response latency was significantly correlated with center of pressure sway variables during quiet standing: root mean square (ρ = 0.334, p=0.040), range (ρ=0.385, p=0.017), mean velocity (ρ=0.337, p=0.038), and total sway area (ρ=0.393, p=0.015). Postural response latency was also significantly correlated with motion of the trunk during walking: sagittal plane range of motion (ρ=0.316, p=0.050) and standard deviation of transverse plane range of motion (ρ=-0.430, p=0.006). Conclusions These findings clearly indicate that slow postural responses to external perturbations in patients with MS contribute to disturbances in balance control, both during standing and walking. PMID:24445088

Prediction equations for maximal respiratory pressures of Brazilian adolescents.

PubMed

Mendes, Raquel E F; Campos, Tania F; Macêdo, Thalita M F; Borja, Raíssa O; Parreira, Verônica F; Mendonça, Karla M P P

2013-01-01

The literature emphasizes the need for studies to provide reference values and equations able to predict respiratory muscle strength of Brazilian subjects at different ages and from different regions of Brazil. To develop prediction equations for maximal respiratory pressures (MRP) of Brazilian adolescents. In total, 182 healthy adolescents (98 boys and 84 girls) aged between 12 and 18 years, enrolled in public and private schools in the city of Natal-RN, were evaluated using an MVD300 digital manometer (Globalmed®) according to a standardized protocol. Statistical analysis was performed using SPSS Statistics 17.0 software, with a significance level of 5%. Data normality was verified using the Kolmogorov-Smirnov test, and descriptive analysis results were expressed as the mean and standard deviation. To verify the correlation between the MRP and the independent variables (age, weight, height and sex), the Pearson correlation test was used. To obtain the prediction equations, stepwise multiple linear regression was used. The variables height, weight and sex were correlated to MRP. However, weight and sex explained part of the variability of MRP, and the regression analysis in this study indicated that these variables contributed significantly in predicting maximal inspiratory pressure, and only sex contributed significantly to maximal expiratory pressure. This study provides reference values and two models of prediction equations for maximal inspiratory and expiratory pressures and sets the necessary normal lower limits for the assessment of the respiratory muscle strength of Brazilian adolescents.

Long time scale hard X-ray variability in Seyfert 1 galaxies

NASA Astrophysics Data System (ADS)

Markowitz, Alex Gary

This dissertation examines the relationship between long-term X-ray variability characteristics, black hole mass, and luminosity of Seyfert 1 Active Galactic Nuclei. High dynamic range power spectral density functions (PSDs) have been constructed for six Seyfert 1 galaxies. These PSDs show "breaks" or characteristic time scales, typically on the order of a few days. There is resemblance to PSDs of lower-mass Galactic X-ray binaries (XRBs), with the ratios of putative black hole masses and variability time scales approximately the same (106--7) between the two classes of objects. The data are consistent with a linear correlation between Seyfert PSD break time scale and black hole mass estimate; the relation extrapolates reasonably well over 6--7 orders of magnitude to XRBs. All of this strengthens the case for a physical similarity between Seyfert galaxies and XRBs. The first six years of RXTE monitoring of Seyfert 1s have been systematically analyzed to probe hard X-ray variability on multiple time scales in a total of 19 Seyfert is in an expansion of the survey of Markowitz & Edelson (2001). Correlations between variability amplitude, luminosity, and black hole mass are explored, the data support the model of PSD movement with black hole mass suggested by the PSD survey. All of the continuum variability results are consistent with relatively more massive black holes hosting larger X-ray emission regions, resulting in 'slower' observed variability. Nearly all sources in the sample exhibit stronger variability towards softer energies, consistent with softening as they brighten. Direct time-resolved spectral fitting has been performed on continuous RXTE monitoring of seven Seyfert is to study long-term spectral variability and Fe Kalpha variability characteristics. The Fe Kalpha line displays a wide range of behavior but varies less strongly than the broadband continuum. Overall, however, there is no strong evidence for correlated variability between the line and continuum, severely challenging models in which the line tracks continuum variations modified only by a light-travel time delay. This experiment yields further support for spectral softening as continuum flux increases.

The association between sexual satisfaction and body image in women.

PubMed

Pujols, Yasisca; Seal, Brooke N; Meston, Cindy M

2010-02-01

Although sexual functioning has been linked to sexual satisfaction, it only partially explains the degree to which women report being sexually satisfied. Other factors include quality of life, relational variables, and individual factors such as body image. Of the few studies that have investigated the link between body image and sexual satisfaction, most have considered body image to be a single construct and have shown mixed results. The present study assessed multiple body image variables in order to better understand which aspects of body image influence multiple domains of sexual satisfaction, including sexual communication, compatibility, contentment, personal concern, and relational concern in a community sample of women. Women between the ages of 18 and 49 years in sexual relationships (N = 154) participated in an Internet survey that assessed sexual functioning, five domains of sexual satisfaction, and several body image variables. Body image variables included the sexual attractiveness, weight concern, and physical condition subscales of the Body Esteem Scale, the appearance-based subscale of the Cognitive Distractions During Sexual Activity Scale, and body mass index. Total score of the Sexual Satisfaction Scale for Women was the main outcome measure. Sexual functioning was measured by a modified Female Sexual Function Index. Consistent with expectations, correlations indicated significant positive relationships between sexual functioning, sexual satisfaction, and all body image variables. A multiple regression analysis revealed that sexual satisfaction was predicted by high body esteem and low frequency of appearance-based distracting thoughts during sexual activity, even after controlling for sexual functioning status. Several aspects of body image, including weight concern, physical condition, sexual attractiveness, and thoughts about the body during sexual activity predict sexual satisfaction in women. The findings suggest that women who experience low sexual satisfaction may benefit from treatments that target these specific aspects of body image.

Correlates of attitudes towards mood stabilizers in individuals with bipolar disorder.

PubMed

Chang, Ching-Wen; Sajatovic, Martha; Tatsuoka, Curtis

2015-02-01

Attitudes towards medication are believed to be important for medication adherence and social factors are believed to have effects on attitudes. Only a limited literature has focused on how attitudes to medication may correlate with social factors relevant to medication adherence among individuals with bipolar disorder (BPD). This secondary analysis of baseline data from a longitudinal study examined the relationships between attitudes towards mood stabilizers and psychosocial variables. Community mental health clinic patients (n = 122) were assessed on the outcome variable of medication attitudes as measured by the Attitudes towards Mood Stabilizers Questionnaire (AMSQ). Independent variables included education as well as standardized measures of psychiatric symptom severity, alcohol and drug problem severity, health locus of control (the belief that one's health is self-determined versus determined by factors outside of one's own control), and psychosocial support. A hierarchical multiple regression model evaluated the relationship between AMSQ and these variables. More positive medication attitudes were seen in individuals with higher levels of social support and in those who held a stronger belief that their health outcomes are determined by others, such as family or clinicians. Education, symptom severity, alcohol problem severity and drug problem severity were not significant attitudinal correlates. Attitudes towards mood stabilizers are correlated with both the support a person receives from others in their social network and how much a person believes others can influence his or her health. Clinicians need to be aware of the importance of the social environment as it relates to medication attitudes and more research is needed on how treatment attitudes may actually translate into medication adherence behavior. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Population dynamics of pond zooplankton, I. Diaptomus pallidus Herrick

USGS Publications Warehouse

Armitage, K.B.; Saxena, B.; Angino, E.E.

1973-01-01

The simultaneous and lag relationships between 27 environmental variables and seven population components of a perennial calanoid copepod were examined by simple and partial correlations and stepwise regression. The analyses consistently explained more than 70% of the variation of a population component. The multiple correlation coefficient (R) usually was highest in no lag or in 3-week or 4-week lag except for clutch size in which R was highest in 1-week lag. Population control, egg-bearing, and clutch size were affected primarily by environmental components categorized as weather; food apparently was relatively minor in affecting population control or reproduction. ?? 1973 Dr. W. Junk B.V. Publishers.

Family caregivers of older adults on home enteral nutrition have multiple unmet task-related training needs and low overall preparedness for caregiving.

PubMed

Silver, Heidi J; Wellman, Nancy S; Galindo-Ciocon, Daisy; Johnson, Paulette

2004-01-01

We used stress process theory to identify family caregiving variables that are salient to the experience of managing older adults' home enteral nutrition. In this article, we describe the specific tasks family caregivers performed and their unique training needs in the context of caregiver preparedness, competence, effectiveness, and health care use. Hospital billing lists from two university-affiliated institutions in Miami, FL, were used to identify older adults who had enteral tubes placed over a 6-month period. Consent was obtained from those older adults discharged for the first time on home enteral nutrition and their family caregivers at the first scheduled outpatient visit. In-home interviews were conducted with a diverse sample of 30 family caregivers (14 white, 8 Hispanic, 7 African-American, 1 Asian) during their first 3 months (mean=1.83+/-0.69 months) of home enteral nutrition caregiving. Descriptive statistics were used to summarize data for all variables; chi(2) analysis was conducted to analyze differences in categorical variables. One-way analysis of variance was used to analyze mean differences among caregivers grouped by ethnicity for total number of hours and tasks performed. Post hoc comparisons were conducted using the Tukey HSD test. The Spearman rho correlations were calculated to assess bivariate associations between quantitative variables. Caregivers reported providing from 6 to 168 hours of care weekly (mean=61.87+/-49.67 hours), in which they performed an average of 19.73+/-8.09 caregiving tasks daily. Training needs identified were greatest for technical and nutrition-related tasks. Preparedness for caregiving scores were low (mean=1.72, maximum=4.0) and positively correlated with caregiver competence (P<.001) and self-rated caregiver effectiveness (P=.004). Preparedness negatively correlated with health care use (P=.03). Caregivers of older adults on home enteral nutrition need training for multiple nutrition-related and caregiving tasks. Multidisciplinary interventions, involving dietitian expertise, are needed to better prepare caregivers to improve both caregiver effectiveness and enteral nutrition outcomes.

Neural correlates of gait variability in people with multiple sclerosis with fall history.

PubMed

Kalron, Alon; Allali, Gilles; Achiron, Anat

2018-05-28

Investigate the association between step time variability and related brain structures in accordance with fall status in people with multiple sclerosis (PwMS). The study included 225 PwMS. A whole-brain MRI was performed by a high-resolution 3.0-Telsa MR scanner in addition to volumetric analysis based on 3D T1-weighted images using the FreeSurfer image analysis suite. Step time variability was measured by an electronic walkway. Participants were defined as "fallers" (at least two falls during the previous year) and "non-fallers". One hundred and five PwMS were defined as fallers and had a greater step time variability compared to non-fallers (5.6% (S.D.=3.4) vs. 3.4% (S.D.=1.5); p=0.001). MS fallers exhibited a reduced volume in the left caudate and both cerebellum hemispheres compared to non-fallers. By using a linear regression analysis no association was found between gait variability and related brain structures in the total cohort and non-fallers group. However, the analysis found an association between the left hippocampus and left putamen volumes with step time variability in the faller group; p=0.031, 0.048, respectively, controlling for total cranial volume, walking speed, disability, age and gender. Nevertheless, according to the hierarchical regression model, the contribution of these brain measures to predict gait variability was relatively small compared to walking speed. An association between low left hippocampal, putamen volumes and step time variability was found in PwMS with a history of falls, suggesting brain structural characteristics may be related to falls and increased gait variability in PwMS. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Londrina Activities of Daily Living Protocol: Reproducibility, Validity, and Reference Values in Physically Independent Adults Age 50 Years and Older.

PubMed

Paes, Thaís; Belo, Letícia Fernandes; da Silva, Diego Rodrigues; Morita, Andrea Akemi; Donária, Leila; Furlanetto, Karina Couto; Sant'Anna, Thaís; Pitta, Fabio; Hernandes, Nidia Aparecida

2017-03-01

It is important to assess activities of daily living (ADL) in older adults due to impairment of independence and quality of life. However, there is no objective and standardized protocol available to assess this outcome. Thus, the aim of this study was to verify the reproducibility and validity of a new protocol for ADL assessment applied in physically independent adults age ≥50 y, the Londrina ADL protocol, and to establish an equation to predict reference values of the Londrina ADL protocol. Ninety-three physically independent adults age ≥50 y had their performance in ADL evaluated by registering the time spent to conclude the protocol. The protocol was performed twice. The 6-min walk test, which assesses functional exercise capacity, was used as a validation criterion. A multiple linear regression model was applied, including anthropometric and demographic variables that correlated with the protocol, to establish an equation to predict the protocol's reference values. In general, the protocol was reproducible (intraclass correlation coefficient 0.91). The average difference between the first and second protocol was 5.3%. The new protocol was valid to assess ADL performance in the studied subjects, presenting a moderate correlation with the 6-min walk test (r = -0.53). The time spent to perform the protocol correlated significantly with age (r = 0.45) but neither with weight (r = -0.17) nor with height (r = -0.17). A model of stepwise multiple regression including sex and age showed that age was the only determinant factor to the Londrina ADL protocol, explaining 21% ( P < .001) of its variability. The derived reference equation was: Londrina ADL protocol pred (s) = 135.618 + (3.102 × age [y]). The Londrina ADL protocol was reproducible and valid in physically independent adults age ≥50 y. A reference equation for the protocol was established including only age as an independent variable (r 2 = 0.21), allowing a better interpretation of the protocol's results in clinical practice. Copyright © 2017 by Daedalus Enterprises.

Examining Preservice Science Teacher Understanding of Nature of Science: Discriminating Variables on the Aspects of Nature of Science

NASA Astrophysics Data System (ADS)

Jones, William I.

This study examined the understanding of nature of science among participants in their final year of a 4-year undergraduate teacher education program at a Midwest liberal arts university. The Logic Model Process was used as an integrative framework to focus the collection, organization, analysis, and interpretation of the data for the purpose of (1) describing participant understanding of NOS and (2) to identify participant characteristics and teacher education program features related to those understandings. The Views of Nature of Science Questionnaire form C (VNOS-C) was used to survey participant understanding of 7 target aspects of Nature of Science (NOS). A rubric was developed from a review of the literature to categorize and score participant understanding of the target aspects of NOS. Participants' high school and college transcripts, planning guides for their respective teacher education program majors, and science content and science teaching methods course syllabi were examined to identify and categorize participant characteristics and teacher education program features. The R software (R Project for Statistical Computing, 2010) was used to conduct an exploratory analysis to determine correlations of the antecedent and transaction predictor variables with participants' scores on the 7 target aspects of NOS. Fourteen participant characteristics and teacher education program features were moderately and significantly ( p < .01) correlated with participant scores on the target aspects of NOS. The 6 antecedent predictor variables were entered into multiple regression analyses to determine the best-fit model of antecedent predictor variables for each target NOS aspect. The transaction predictor variables were entered into separate multiple regression analyses to determine the best-fit model of transaction predictor variables for each target NOS aspect. Variables from the best-fit antecedent and best-fit transaction models for each target aspect of NOS were then combined. A regression analysis for each of the combined models was conducted to determine the relative effect of these variables on the target aspects of NOS. Findings from the multiple regression analyses revealed that each of the fourteen predictor variables was present in the best-fit model for at least 1 of the 7 target aspects of NOS. However, not all of the predictor variables were statistically significant (p < .007) in the models and their effect (beta) varied. Participants in the teacher education program who had higher ACT Math scores, completed more high school science credits, and were enrolled either in the Middle Childhood with a science concentration program major or in the Adolescent/Young Adult Science Education program major were more likely to have an informed understanding on each of the 7 target aspects of NOS. Analyses of the planning guides and the course syllabi in each teacher education program major revealed differences between the program majors that may account for the results.

Confronting weather and climate models with observational data from soil moisture networks over the United States

PubMed Central

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal D.; Balsamo, Gianpaolo; Lawrence, David M.

2018-01-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison. PMID:29645013

Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

NASA Technical Reports Server (NTRS)

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A., Jr.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal Dean;

Confronting weather and climate models with observational data from soil moisture networks over the United States.

PubMed

Dirmeyer, Paul A; Wu, Jiexia; Norton, Holly E; Dorigo, Wouter A; Quiring, Steven M; Ford, Trenton W; Santanello, Joseph A; Bosilovich, Michael G; Ek, Michael B; Koster, Randal D; Balsamo, Gianpaolo; Lawrence, David M

2016-04-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison.

Diagnostic Challenges in Retinitis Pigmentosa: Genotypic Multiplicity and Phenotypic Variability

PubMed Central

Chang, Susie; Vaccarella, Leah; Olatunji, Sunday; Cebulla, Colleen; Christoforidis, John

2011-01-01

Retinitis pigmentosa (RP) is a heterogeneous group of inherited retinal disorders. Diagnosis can be challenging as more than 40 genes are known to cause non-syndromic RP and phenotypic expression can differ significantly resulting in variations in disease severity, age of onset, rate of progression, and clinical findings. We describe the clinical manifestations of RP, the more commonly known causative gene mutations, and the genotypic-phenotypic correlation of RP. PMID:22131872

Relationship of aerobic and anaerobic parameters with 400 m front crawl swimming performance

PubMed Central

Kalva-Filho, CA; Campos, EZ; Andrade, VL; Silva, ASR; Zagatto, AM; Lima, MCS

2015-01-01

The aims of the present study were to investigate the relationship of aerobic and anaerobic parameters with 400 m performance, and establish which variable better explains long distance performance in swimming. Twenty-two swimmers (19.1±1.5 years, height 173.9±10.0 cm, body mass 71.2±10.2 kg; 76.6±5.3% of 400 m world record) underwent a lactate minimum test to determine lactate minimum speed (LMS) (i.e., aerobic capacity index). Moreover, the swimmers performed a 400 m maximal effort to determine mean speed (S400m), peak oxygen uptake (V.O2PEAK) and total anaerobic contribution (CANA). The CANA was assumed as the sum of alactic and lactic contributions. Physiological parameters of 400 m were determined using the backward extrapolation technique (V.O2PEAK and alactic contributions of CANA) and blood lactate concentration analysis (lactic anaerobic contributions of CANA). The Pearson correlation test and backward multiple regression analysis were used to verify the possible correlations between the physiological indices (predictor factors) and S400m (independent variable) (p < 0.05). Values are presented as mean ± standard deviation. Significant correlations were observed between S400m (1.4±0.1 m·s-1) and LMS (1.3±0.1 m·s-1; r = 0.80), V.O2PEAK (4.5±3.9 L·min-1; r = 0.72) and CANA (4.7±1.5 L·O2; r= 0.44). The best model constructed using multiple regression analysis demonstrated that LMS and V.O2PEAK explained 85% of the 400 m performance variance. When backward multiple regression analysis was performed, CANA lost significance. Thus, the results demonstrated that both aerobic parameters (capacity and power) can be used to predict 400 m swimming performance. PMID:28479663

Are social norms associated with smoking in French university students? A survey report on smoking correlates

PubMed Central

Riou França, Lionel; Dautzenberg, Bertrand; Falissard, Bruno; Reynaud, Michel

2009-01-01

Background Knowledge of the correlates of smoking is a first step to successful prevention interventions. The social norms theory hypothesises that students' smoking behaviour is linked to their perception of norms for use of tobacco. This study was designed to test the theory that smoking is associated with perceived norms, controlling for other correlates of smoking. Methods In a pencil-and-paper questionnaire, 721 second-year students in sociology, medicine, foreign language or nursing studies estimated the number of cigarettes usually smoked in a month. 31 additional covariates were included as potential predictors of tobacco use. Multiple imputation was used to deal with missing values among covariates. The strength of the association of each variable with tobacco use was quantified by the inclusion frequencies of the variable in 1000 bootstrap sample backward selections. Being a smoker and the number of cigarettes smoked by smokers were modelled separately. Results We retain 8 variables to predict the risk of smoking and 6 to predict the quantities smoked by smokers. The risk of being a smoker is increased by cannabis use, binge drinking, being unsupportive of smoke-free universities, perceived friends' approval of regular smoking, positive perceptions about tobacco, a high perceived prevalence of smoking among friends, reporting not being disturbed by people smoking in the university, and being female. The quantity of cigarettes smoked by smokers is greater for smokers reporting never being disturbed by smoke in the university, unsupportive of smoke-free universities, perceiving that their friends approve of regular smoking, having more negative beliefs about the tobacco industry, being sociology students and being among the older students. Conclusion Other substance use, injunctive norms (friends' approval) and descriptive norms (friends' smoking prevalence) are associated with tobacco use. University-based prevention campaigns should take multiple substance use into account and focus on the norms most likely to have an impact on student smoking. PMID:19341453

Intrinsic vs. spurious long-range memory in high-frequency records of environmental radioactivity - Critical re-assessment and application to indoor 222Rn concentrations from Coimbra, Portugal

NASA Astrophysics Data System (ADS)

Donner, Reik V.; Potirakis, Stelios M.; Barbosa, Susana M.; Matos, Jose A. O.

2015-04-01

The presence or absence of long-range correlations in environmental radioactivity fluctuations has recently attracted considerable interest. Among a multiplicity of practically relevant applications, identifying and disentangling the environmental factors controlling the variable concentrations of the radioactive noble gas Radon is important for estimating its effect on human health and the efficiency of possible measures for reducing the corresponding exposition. In this work, we present a critical re-assessment of a multiplicity of complementary methods that have been previously applied for evaluating the presence of long-range correlations and fractal scaling in environmental Radon variations with a particular focus on the specific properties of the underlying time series. As an illustrative case study, we subsequently re-analyze two high-frequency records of indoor Radon concentrations from Coimbra, Portugal, each of which spans several months of continuous measurements at a high temporal resolution of five minutes. Our results reveal that at the study site, Radon concentrations exhibit complex multi-scale dynamics with qualitatively different properties at different time-scales: (i) essentially white noise in the high-frequency part (up to time-scales of about one hour), (ii) spurious indications of a non-stationary, apparently long-range correlated process (at time scales between hours and one day) arising from marked periodic components probably related to tidal frequencies, and (iii) low-frequency variability indicating a true long-range dependent process, which might be dominated by a response to meteorological drivers. In the presence of such multi-scale variability, common estimators of long-range memory in time series are necessarily prone to fail if applied to the raw data without previous separation of time-scales with qualitatively different dynamics. We emphasize that similar properties can be found in other types of geophysical time series (for example, tide gauge records), calling for a careful application of time series analysis tools when studying such data.

Instantaneous and Time Averaged Flow Fields of Multiple Vortices in the Tip Region of a Ducted Propulsor

NASA Astrophysics Data System (ADS)

Oweis, Ghanem; Steven, Ceccio

2003-11-01

PIV data of the flow field in the immediate vicinity of the trailing edge of a ducted propeller at the tip revealed the existence of multiple vorticity concentrations. The multiple vortices in each instantaneous PIV field were identified and individually characterized. The measurements of the multiple vortices were combined with a Gaussian vortex model to reconstruct the vorticity and velocity fields. The major features of the original experimental field were recovered, and the correlation between the two fields was good. The time averaged field and velocity fluctuations were also measured. We will discuss why the "typical" instantaneous tip vortex and the tip vortex from the time averaged field are substantially different. We attempt to explain the cause of these differences. Knowledge of the instantaneous flow field variability is used to understand the causes of the measured velocity fluctuations. The results from this study have an impact on the understanding of the roll-up of tip vortices, and the dynamics of multiple vortices.

Latent variable models for gene-environment interactions in longitudinal studies with multiple correlated exposures.

PubMed

Tao, Yebin; Sánchez, Brisa N; Mukherjee, Bhramar

2015-03-30

Many existing cohort studies designed to investigate health effects of environmental exposures also collect data on genetic markers. The Early Life Exposures in Mexico to Environmental Toxicants project, for instance, has been genotyping single nucleotide polymorphisms on candidate genes involved in mental and nutrient metabolism and also in potentially shared metabolic pathways with the environmental exposures. Given the longitudinal nature of these cohort studies, rich exposure and outcome data are available to address novel questions regarding gene-environment interaction (G × E). Latent variable (LV) models have been effectively used for dimension reduction, helping with multiple testing and multicollinearity issues in the presence of correlated multivariate exposures and outcomes. In this paper, we first propose a modeling strategy, based on LV models, to examine the association between repeated outcome measures (e.g., child weight) and a set of correlated exposure biomarkers (e.g., prenatal lead exposure). We then construct novel tests for G × E effects within the LV framework to examine effect modification of outcome-exposure association by genetic factors (e.g., the hemochromatosis gene). We consider two scenarios: one allowing dependence of the LV models on genes and the other assuming independence between the LV models and genes. We combine the two sets of estimates by shrinkage estimation to trade off bias and efficiency in a data-adaptive way. Using simulations, we evaluate the properties of the shrinkage estimates, and in particular, we demonstrate the need for this data-adaptive shrinkage given repeated outcome measures, exposure measures possibly repeated and time-varying gene-environment association. Copyright © 2014 John Wiley & Sons, Ltd.

Knee-Extension Torque Variability and Subjective Knee Function in Patients with a History of Anterior Cruciate Ligament Reconstruction.

PubMed

Goetschius, John; Hart, Joseph M

2016-01-01

When returning to physical activity, patients with a history of anterior cruciate ligament reconstruction (ACL-R) often experience limitations in knee-joint function that may be due to chronic impairments in quadriceps motor control. Assessment of knee-extension torque variability may demonstrate underlying impairments in quadriceps motor control in patients with a history of ACL-R. To identify differences in maximal isometric knee-extension torque variability between knees that have undergone ACL-R and healthy knees and to determine the relationship between knee-extension torque variability and self-reported knee function in patients with a history of ACL-R. Descriptive laboratory study. Laboratory. A total of 53 individuals with primary, unilateral ACL-R (age = 23.4 ± 4.9 years, height = 1.7 ± 0.1 m, mass = 74.6 ± 14.8 kg) and 50 individuals with no history of substantial lower extremity injury or surgery who served as controls (age = 23.3 ± 4.4 years, height = 1.7 ± 0.1 m, mass = 67.4 ± 13.2 kg). Torque variability, strength, and central activation ratio (CAR) were calculated from 3-second maximal knee-extension contraction trials (90° of flexion) with a superimposed electrical stimulus. All participants completed the International Knee Documentation Committee (IKDC) Subjective Knee Evaluation Form, and we determined the number of months after surgery. Group differences were assessed using independent-samples t tests. Correlation coefficients were calculated among torque variability, strength, CAR, months after surgery, and IKDC scores. Torque variability, strength, CAR, and months after surgery were regressed on IKDC scores using stepwise, multiple linear regression. Torque variability was greater and strength, CAR, and IKDC scores were lower in the ACL-R group than in the control group (P < .05). Torque variability and strength were correlated with IKDC scores (P < .05). Torque variability, strength, and CAR were correlated with each other (P < .05). Torque variability alone accounted for 14.3% of the variance in IKDC scores. The combination of torque variability and number of months after surgery accounted for 21% of the variance in IKDC scores. Strength and CAR were excluded from the regression model. Knee-extension torque variability was moderately associated with IKDC scores in patients with a history of ACL-R. Torque variability combined with months after surgery predicted 21% of the variance in IKDC scores in these patients.

The influence of physical and cognitive factors on reactive agility performance in men basketball players.

PubMed

Scanlan, Aaron; Humphries, Brendan; Tucker, Patrick S; Dalbo, Vincent

2014-01-01

This study explored the influence of physical and cognitive measures on reactive agility performance in basketball players. Twelve men basketball players performed multiple sprint, Change of Direction Speed Test, and Reactive Agility Test trials. Pearson's correlation analyses were used to determine relationships between the predictor variables (stature, mass, body composition, 5-m, 10-m and 20-m sprint times, peak speed, closed-skill agility time, response time and decision-making time) and reactive agility time (response variable). Simple and stepwise regression analyses determined the individual influence of each predictor variable and the best predictor model for reactive agility time. Morphological (r = -0.45 to 0.19), sprint (r = -0.40 to 0.41) and change-of-direction speed measures (r = 0.43) had small to moderate correlations with reactive agility time. Response time (r = 0.76, P = 0.004) and decision-making time (r = 0.58, P = 0.049) had large to very large relationships with reactive agility time. Response time was identified as the sole predictor variable for reactive agility time in the stepwise model (R(2) = 0.58, P = 0.004). In conclusion, cognitive measures had the greatest influence on reactive agility performance in men basketball players. These findings suggest reaction and decision-making drills should be incorporated in basketball training programmes.

Purposes of Internet use and problematic Internet use among Turkish high school students.

PubMed

Demirer, Veysel; Bozoglan, Bahadir

2016-12-01

After the emergence of the Internet, the sudden increase in its use soon attracted attention to this phenomenon. Studies have shown that there is a relationship between problematic Internet use (PIU) and the purposes of Internet use. The aims of this study are to examine the purposes of Internet use among Turkish high school students according to their gender, frequency of Internet use (FIU), grade point average (GPA) and family income (F-income), and to investigate whether all these variables predict PIU. The participants in the study were 375 high school students (185 girls and 190 boys), and verbal consent was obtained from the subjects before application. The participants' ages ranged between 14 and 18 (Mean = 15.6, SD = 1.26). One-way analysis of variance was used to identify the purposes of Internet use in terms of demographic variables. Also, hierarchical multiple regression analyses were conducted to explore whether demographic variables and purposes of Internet use affected PIU. Finally, the results demonstrate that male gender, high FIU, low GPA, and high levels of F-income correlate significantly with PIU. Also, the social, leisure and virtual-emotional purposes of Internet use, besides demographic variables, were significantly correlated with PIU. © 2015 Wiley Publishing Asia Pty Ltd.

Incipient and overt diabetic nephropathy in African Americans with NIDDM.

PubMed

Dasmahapatra, A; Bale, A; Raghuwanshi, M P; Reddi, A; Byrne, W; Suarez, S; Nash, F; Varagiannis, E; Skurnick, J H

1994-04-01

OBJECTIVE--To determine the prevalence of incipient and overt nephropathy in African-American subjects with non-insulin-dependent diabetes mellitus (NIDDM) attending a hospital clinic. Contributory factors, such as blood pressure (BP), duration and age at onset of diabetes, hyperglycemia, hyperlipidemia, and body mass index (BMI) also were evaluated. RESEARCH DESIGN AND METHODS--We recruited 116 African-American subjects with NIDDM for this cross-sectional, descriptive, and analytical study. BP, BMI, 24-h urine albumin excretion, creatinine clearance, serum creatinine, lipids, and GHb levels were measured. Albumin excretion rate (AER) was calculated, and subjects were divided into three groups: no nephropathy (AER < 20 micrograms/min), incipient nephropathy (AER 20-200 micrograms/min), and overt nephropathy (AER > 200 micrograms/min). Frequency of hypertension and nephropathy was analyzed by chi 2 testing, group means were compared using analysis of variance, and linear correlations were performed between AER and other variables. Multiple regression analysis was used to examine the association of these variables while controlling for the effects of other variables. RESULTS--Increased AER was present in 50% of our subjects; 31% had incipient and 19% had overt nephropathy. Hypertension was present in 72.4%; nephropathy, particularly overt nephropathy, was significantly more prevalent in the hypertensive group. Mean BP and diastolic blood pressure (dBP) were higher in the groups with incipient and overt nephropathy, and systolic blood pressure (sBP) was increased in overt nephropathy. Men with either form of nephropathy had higher sBP, dBP, and mean BP, whereas only women with overt nephropathy had increased sBP and mean BP. Subjects with incipient or overt nephropathy had a longer duration of diabetes, and those with overt nephropathy had a younger age at onset of diabetes. By multiple regression analysis, AER correlated with younger age at diabetes onset, but not with diabetes duration. No correlation with age, lipid levels, or GHb was noted. BMI correlated with AER. CONCLUSIONS--Incipient and overt nephropathy were observed frequently in these African-American subjects with NIDDM. Albuminuria correlated with BP, younger age at diabetes onset, and BMI. Association of albuminuria and increased cardiovascular mortality may place 50% of inner-city African-American patients with NIDDM at risk for developing cardiovascular complications.

Dietary supplement use and smoking are important correlates of biomarkers of water-soluble vitamin status after adjusting for sociodemographic and lifestyle variables in a representative sample of US adults1,2,3

PubMed Central

Pfeiffer, Christine M.; Sternberg, Maya R.; Schleicher, Rosemary L.; Rybak, Michael E.

2016-01-01

Biochemical indicators of water-soluble vitamin (WSV) status have been measured in a nationally representative sample of the US population in NHANES 2003–2006. To examine whether demographic differentials in nutritional status were related to and confounded by certain variables, we assessed the association of sociodemographic (age, sex, race-ethnicity, education, income) and lifestyle variables (dietary supplement use, smoking, alcohol consumption, BMI, physical activity) with biomarkers of WSV status in adults (≥20 y): serum and RBC folate, serum pyridoxal-5′-phosphate (PLP), serum 4-pyridoxic acid, serum total cobalamin (B-12), plasma total homocysteine (tHcy), plasma methylmalonic acid (MMA), and serum ascorbic acid. Age (except for PLP) and smoking (except for MMA) were generally the strongest significant correlates of these biomarkers (|r| ≤0.43) and together with supplement use explained more of the variability as compared to the other covariates in bivariate analysis. In multiple regression models, sociodemographic and lifestyle variables together explained from 7% (B-12) to 29% (tHcy) of the biomarker variability. We observed significant associations for most biomarkers (≥6 out of 8) with age, sex, race-ethnicity, supplement use, smoking, and BMI; and for some biomarkers with PIR (5/8), education (1/8), alcohol consumption (4/8), and physical activity (5/8). We noted large estimated percent changes in biomarker concentrations between race-ethnic groups (from −24% to 20%), between supplement users and nonusers (from −12% to 104%), and between smokers and nonsmokers (from −28% to 8%). In summary, age, sex, and race-ethnic differentials in biomarker concentrations remained significant after adjusting for sociodemographic and lifestyle variables. Supplement use and smoking were important correlates of biomarkers of WSV status. PMID:23576641

Dietary supplement use and smoking are important correlates of biomarkers of water-soluble vitamin status after adjusting for sociodemographic and lifestyle variables in a representative sample of U.S. adults.

PubMed

Pfeiffer, Christine M; Sternberg, Maya R; Schleicher, Rosemary L; Rybak, Michael E

2013-06-01

Biochemical indicators of water-soluble vitamin (WSV) status were measured in a nationally representative sample of the U.S. population in NHANES 2003-2006. To examine whether demographic differentials in nutritional status were related to and confounded by certain variables, we assessed the association of sociodemographic (age, sex, race-ethnicity, education, income) and lifestyle (dietary supplement use, smoking, alcohol consumption, BMI, physical activity) variables with biomarkers of WSV status in adults (aged ≥ 20 y): serum and RBC folate, serum pyridoxal-5'-phosphate (PLP), serum 4-pyridoxic acid, serum total cobalamin (vitamin B-12), plasma total homocysteine (tHcy), plasma methylmalonic acid (MMA), and serum ascorbic acid. Age (except for PLP) and smoking (except for MMA) were generally the strongest significant correlates of these biomarkers (|r| ≤ 0.43) and together with supplement use explained more of the variability compared with the other covariates in bivariate analysis. In multiple regression models, sociodemographic and lifestyle variables together explained from 7 (vitamin B-12) to 29% (tHcy) of the biomarker variability. We observed significant associations for most biomarkers (≥ 6 of 8) with age, sex, race-ethnicity, supplement use, smoking, and BMI and for some biomarkers with PIR (5 of 8), education (1 of 8), alcohol consumption (4 of 8), and physical activity (5 of 8). We noted large estimated percentage changes in biomarker concentrations between race-ethnic groups (from -24 to 20%), between supplement users and nonusers (from -12 to 104%), and between smokers and nonsmokers (from -28 to 8%). In summary, age, sex, and race-ethnic differentials in biomarker concentrations remained significant after adjusting for sociodemographic and lifestyle variables. Supplement use and smoking were important correlates of biomarkers of WSV status.

Interactions between serum leptin, the insulin-like growth factor-I system, and sex, age, anthropometric and body composition variables in a healthy population randomly selected.

PubMed

Gómez, José Manuel; Maravall, Francisco Javier; Gómez, Núria; Navarro, Miguel Angel; Casamitjana, Roser; Soler, Juan

2003-02-01

Leptin secretion is influenced by many factors and the GH/IGF axis plays an important role in the regulation of body composition, but the physiological interactions between leptin and the IGF-I system remain unknown. In this study we investigated the relationship between leptin, the IGF-I system, and sex, age, anthropometric and body composition variables in a group of healthy adults randomly selected. A cross-sectional study. The study included 268 subjects, representative of the whole population of the city of L'Hospitalet de Llobregat in sex and age distribution: 134 men aged 41.4 years, range 15-70 years; and 134 women, aged 40.7 years, range 15-70 years. Body mass index (BMI) was calculated, and body composition was determined by using a bioelectrical impedance analyser. Serum leptin concentrations were determined by using a radioimmunoassay (RIA). Serum total IGF-I concentrations, after acid-ethanol extraction, were also measured by RIA. Serum free IGF-I concentrations were determined by an enzymoimmunometric assay. Serum IGFBP3 concentrations were determined by RIA. Plasma basal TSH concentrations were determined by a specific electrochemiluminescence assay. In men the BMI was similar in all decades and waist/hip ratio increased in the last three decades. Fat-free mass decreased by decade. We observed an increase in leptin in the fourth decade with a decrease in IGF-I, free IGF-I and IGFBP3 throughout the decades. Basal TSH showed an increase in the last two decades. In women, BMI, waist/hip ratio and fat mass increased significantly in the last decades. Leptin concentrations increased in the last decades and total IGF-I, free IGF-I and IGFBP3 decreased by decade without changes in basal TSH concentration. In men, there was a positive correlation between leptin and BMI, waist/hip ratio, total body water, fat-free mass and fat mass, and these anthropometric and body composition variables showed a negative correlation with free IGF-I and IGFBP3, without any correlation with total IGF-I. In women, there was a positive correlation between leptin and BMI, waist/hip ratio, total body water, fat-free mass, and fat mass, which showed a negative correlation with total IGF-I and IGFBP3, without any correlation with free IGF-I. In men, total IGF-I was negatively correlated with waist/hip ratio without any correlation with the other variables and free IGF-I was negatively correlated with BMI and waist/hip ratio, and IGFBP3 did not show any correlation. In women, total IGF-I, free IGF-I and IGFBP3 were negatively correlated with BMI, waist/hip ratio and fat mass. The multiple linear regression analysis produced a model that explained 60.5% of leptin variability in men and 40% in women. Notably, only age, BMI, fat mass and waist/hip ratio brought an independent significant contribution to leptin variability. The final model also explained 28.2% and 60.4% of total IGF-I variability and 17.2% and 27.4% of free IGF-I variability in men and women, respectively. Age and leptin contributed to free IGF-I variability in men, and age and fat mass were significantly and independently associated with total IGF-I in women. In this well-characterized population of controls randomly selected without chronic disease or drug administration and with biochemically confirmed euthyroidism, we found that both men and women had a significant correlation between leptin levels and the IGF-I system, and anthropometric and body composition variables, but that leptin did not regulate the IGF-I system, and that the IGF-I system did not regulate leptin synthesis and secretion.

Community Air Sensor Network (CAIRSENSE) project ...

EPA Pesticide Factsheets

Advances in air pollution sensor technology have enabled the development of small and low cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring networks with additional geographic and temporal measurement resolution, if the data quality were sufficient. To understand the capability of emerging air sensor technology, the Community Air Sensor Network (CAIRSENSE) project deployed low cost, continuous and commercially-available air pollution sensors at a regulatory air monitoring site and as a local sensor network over a surrounding ~2 km area in Southeastern U.S. Co-location of sensors measuring oxides of nitrogen, ozone, carbon monoxide, sulfur dioxide, and particles revealed highly variable performance, both in terms of comparison to a reference monitor as well as whether multiple identical sensors reproduced the same signal. Multiple ozone, nitrogen dioxide, and carbon monoxide sensors revealed low to very high correlation with a reference monitor, with Pearson sample correlation coefficient (r) ranging from 0.39 to 0.97, -0.25 to 0.76, -0.40 to 0.82, respectively. The only sulfur dioxide sensor tested revealed no correlation (r 0.5), step-wise multiple linear regression was performed to determine if ambient temperature, relative humidity (RH), or age of the sensor in sampling days could be used in a correction algorihm to im

100-point scale evaluating job satisfaction and the results of the 12-item General Health Questionnaire in occupational workers.

PubMed

Kawada, Tomoyuki; Yamada, Natsuki

2012-01-01

Job satisfaction is an important factor in the occupational lives of workers. In this study, the relationship between one-dimensional scale of job satisfaction and psychological wellbeing was evaluated. A total of 1,742 workers (1,191 men and 551 women) participated. 100-point scale evaluating job satisfaction (0 [extremely dissatisfied] to 100 [extremely satisfied]) and the General Health Questionnaire, 12-item version (GHQ-12) evaluating psychological wellbeing were used. A multiple regression analysis was then used, controlling for gender and age. The change in the GHQ-12 and job satisfaction scores after a two-year interval was also evaluated. The mean age for the subjects was 42.2 years for the men and 36.2 years for the women. The GHQ-12 and job satisfaction scores were significantly correlated in each generation. The partial correlation coefficients between the changes in the two variables, controlling for age, were -0.395 for men and -0.435 for women (p< 0.001). A multiple regression analysis revealed that the 100-point job satisfaction score was associated with the GHQ-12 results (p< 0.001). The adjusted multiple correlation coefficient was 0.275. The 100-point scale, which is a simple and easy tool for evaluating job satisfaction, was significantly associated with psychological wellbeing as judged using the GHQ-12.

Predictors of posttraumatic stress symptoms following childbirth

PubMed Central

2014-01-01

Background Posttraumatic stress disorder (PTSD) following childbirth has gained growing attention in the recent years. Although a number of predictors for PTSD following childbirth have been identified (e.g., history of sexual trauma, emergency caesarean section, low social support), only very few studies have tested predictors derived from current theoretical models of the disorder. This study first aimed to replicate the association of PTSD symptoms after childbirth with predictors identified in earlier research. Second, cognitive predictors derived from Ehlers and Clark’s (2000) model of PTSD were examined. Methods N = 224 women who had recently given birth completed an online survey. In addition to computing single correlations between PTSD symptom severities and variables of interest, in a hierarchical multiple regression analyses posttraumatic stress symptoms were predicted by (1) prenatal variables, (2) birth-related variables, (3) postnatal social support, and (4) cognitive variables. Results Wellbeing during pregnancy and age were the only prenatal variables contributing significantly to the explanation of PTSD symptoms in the first step of the regression analysis. In the second step, the birth-related variables peritraumatic emotions and wellbeing during childbed significantly increased the explanation of variance. Despite showing significant bivariate correlations, social support entered in the third step did not predict PTSD symptom severities over and above the variables included in the first two steps. However, with the exception of peritraumatic dissociation all cognitive variables emerged as powerful predictors and increased the amount of variance explained from 43% to a total amount of 68%. Conclusions The findings suggest that the prediction of PTSD following childbirth can be improved by focusing on variables derived from a current theoretical model of the disorder. PMID:25026966

Moral distress and burnout syndrome: are there relationships between these phenomena in nursing workers?

PubMed

Dalmolin, Graziele de Lima; Lunardi, Valéria Lerch; Lunardi, Guilherme Lerch; Barlem, Edison Luiz Devos; Silveira, Rosemary Silva da

2014-01-01

to identify relationships between moral distress and Burnout in the professional performance from the perceptions of the experiences of nursing workers. this is a survey type study with 375 nursing workers working in three different hospitals of southern Rio Grande do Sul, with the application of adaptations of the Moral Distress Scale and the Maslach Burnout Inventory, validated and standardized for use in Brazil. Data validation occurred through factor analysis and Cronbach's alpha. For the data analysis bivariate analysis using Pearson's correlation and multivariate analysis using multiple regression were performed. the existence of a weak correlation between moral distress and Burnout was verified. A possible positive correlation between Burnout and therapeutic obstinacy, and a negative correlation between professional fulfillment and moral distress were identified. the need was identified for further studies that include mediating and moderating variables that may explain more clearly the models studied.

Moral distress and Burnout syndrome: are there relationships between these phenomena in nursing workers?1

PubMed Central

Dalmolin, Graziele de Lima; Lunardi, Valéria Lerch; Lunardi, Guilherme Lerch; Barlem, Edison Luiz Devos; da Silveira, Rosemary Silva

2014-01-01

Objective to identify relationships between moral distress and Burnout in the professional performance from the perceptions of the experiences of nursing workers. Methods this is a survey type study with 375 nursing workers working in three different hospitals of southern Rio Grande do Sul, with the application of adaptations of the Moral Distress Scale and the Maslach Burnout Inventory, validated and standardized for use in Brazil. Data validation occurred through factor analysis and Cronbach's alpha. For the data analysis bivariate analysis using Pearson's correlation and multivariate analysis using multiple regression were performed. Results the existence of a weak correlation between moral distress and Burnout was verified. A possible positive correlation between Burnout and therapeutic obstinacy, and a negative correlation between professional fulfillment and moral distress were identified. Conclusion the need was identified for further studies that include mediating and moderating variables that may explain more clearly the models studied. PMID:24553701

Resting-state fMRI correlations: From link-wise unreliability to whole brain stability.

PubMed

Pannunzi, Mario; Hindriks, Rikkert; Bettinardi, Ruggero G; Wenger, Elisabeth; Lisofsky, Nina; Martensson, Johan; Butler, Oisin; Filevich, Elisa; Becker, Maxi; Lochstet, Martyna; Kühn, Simone; Deco, Gustavo

2017-08-15

The functional architecture of spontaneous BOLD fluctuations has been characterized in detail by numerous studies, demonstrating its potential relevance as a biomarker. However, the systematic investigation of its consistency is still in its infancy. Here, we analyze within- and between-subject variability and test-retest reliability of resting-state functional connectivity (FC) in a unique data set comprising multiple fMRI scans (42) from 5 subjects, and 50 single scans from 50 subjects. We adopt a statistical framework that enables us to identify different sources of variability in FC. We show that the low reliability of single links can be significantly improved by using multiple scans per subject. Moreover, in contrast to earlier studies, we show that spatial heterogeneity in FC reliability is not significant. Finally, we demonstrate that despite the low reliability of individual links, the information carried by the whole-brain FC matrix is robust and can be used as a functional fingerprint to identify individual subjects from the population. Copyright © 2017 Elsevier Inc. All rights reserved.

Modeling Pan Evaporation for Kuwait by Multiple Linear Regression

PubMed Central

Almedeij, Jaber

2012-01-01

Evaporation is an important parameter for many projects related to hydrology and water resources systems. This paper constitutes the first study conducted in Kuwait to obtain empirical relations for the estimation of daily and monthly pan evaporation as functions of available meteorological data of temperature, relative humidity, and wind speed. The data used here for the modeling are daily measurements of substantial continuity coverage, within a period of 17 years between January 1993 and December 2009, which can be considered representative of the desert climate of the urban zone of the country. Multiple linear regression technique is used with a procedure of variable selection for fitting the best model forms. The correlations of evaporation with temperature and relative humidity are also transformed in order to linearize the existing curvilinear patterns of the data by using power and exponential functions, respectively. The evaporation models suggested with the best variable combinations were shown to produce results that are in a reasonable agreement with observation values. PMID:23226984

Paleoflood Hydrology and Flood Geomorphology in the Dolores Watershed, CO and UT

NASA Astrophysics Data System (ADS)

Cline, M. L.; Baker, V.

2008-12-01

Field evidence from six slackwater deposits suggests that 4-7 extreme floods have occurred on the Dolores River since the middle-late Holocene; each of which significantly exceeds the peak historical flood. Preliminary OSL ages for the oldest deposits are corroborated by AMS 14C, dendrochronological, and archeological evidence. In addition to being the first paleoflood study of the Dolores Watershed, this study addresses a critical missing hydroclimatic region in the southwestern U.S.: those areas whose surface hydrology correlates weakly with ENSO variability. Prior paleoflood studies in the Southwest have focused on hydroclimatic regions that correlate strongly with ENSO variability, linking periods of increased flood magnitude and frequency with periods of increased El Niño activity (e.g. Ely, 1997). In this study, we are addressing this critical gap by developing a robust paleoflood chronology based on multiple geochronology techniques. We have made correlations between individual slackwater deposits based on age-control, sediment color, texture, pedogenic development, and stratigraphic position. The correlated slackwater deposits lay within both stable bedrock reaches, as well as mixed bedrock-alluvial reaches. Correlative slackwater deposits between morphologically different reaches are critical because they allow us to make discharge estimates, where the differences may inform us of the degree of channel-bed stability-a critical assumption of paleoflood hydrology. From these differences in discharge estimates, we can infer middle-late Holocene alluvial incision rates.

Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA

USGS Publications Warehouse

Ohlmacher, G.C.; Davis, J.C.

2003-01-01

Landslides in the hilly terrain along the Kansas and Missouri rivers in northeastern Kansas have caused millions of dollars in property damage during the last decade. To address this problem, a statistical method called multiple logistic regression has been used to create a landslide-hazard map for Atchison, Kansas, and surrounding areas. Data included digitized geology, slopes, and landslides, manipulated using ArcView GIS. Logistic regression relates predictor variables to the occurrence or nonoccurrence of landslides within geographic cells and uses the relationship to produce a map showing the probability of future landslides, given local slopes and geologic units. Results indicated that slope is the most important variable for estimating landslide hazard in the study area. Geologic units consisting mostly of shale, siltstone, and sandstone were most susceptible to landslides. Soil type and aspect ratio were considered but excluded from the final analysis because these variables did not significantly add to the predictive power of the logistic regression. Soil types were highly correlated with the geologic units, and no significant relationships existed between landslides and slope aspect. ?? 2003 Elsevier Science B.V. All rights reserved.

Comparing multiple imputation methods for systematically missing subject-level data.

PubMed

Kline, David; Andridge, Rebecca; Kaizar, Eloise

2017-06-01

When conducting research synthesis, the collection of studies that will be combined often do not measure the same set of variables, which creates missing data. When the studies to combine are longitudinal, missing data can occur on the observation-level (time-varying) or the subject-level (non-time-varying). Traditionally, the focus of missing data methods for longitudinal data has been on missing observation-level variables. In this paper, we focus on missing subject-level variables and compare two multiple imputation approaches: a joint modeling approach and a sequential conditional modeling approach. We find the joint modeling approach to be preferable to the sequential conditional approach, except when the covariance structure of the repeated outcome for each individual has homogenous variance and exchangeable correlation. Specifically, the regression coefficient estimates from an analysis incorporating imputed values based on the sequential conditional method are attenuated and less efficient than those from the joint method. Remarkably, the estimates from the sequential conditional method are often less efficient than a complete case analysis, which, in the context of research synthesis, implies that we lose efficiency by combining studies. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Risk factors for left ventricular hypertrophy: role of Na(+)-Li+ countertransport.

PubMed

Neves, P L; Faisca, M; Gomes, V; Cacodcar, S; Bernardo, I; Anunciada, A I; Viegas, E; Martins, H; da Silva, A M

1996-06-01

Left ventricular hypertrophy (LVH) is associated with an increase in cardiovascular death in essential hypertension (EH). The factors involved in LVH are multiple and complex. We looked for risk factors of LVH in a group of 28 nonobese patients with EH (mean age = 45.3 years). We analyzed the activity of several erythrocyte ion transports (Vmax of NaLi countertransport, NaKCl cotransport and NaK-pump, and the Na-leak Kp Na), the intracellular Na and the insulin sensitivity index. All these parameters were used as independent variables whereas the left ventricular mass index (LVMI) was used as the dependent variable. Variables showing a significant univariate correlation (age, time of EH, mean blood pressure and Vmax of NaLi countertransport) were introduced in a stepwise multiple regression model. Only age (P = 0.014), time of EH (P = 0.038) and Vmax of NaLi countertransport (P = 0.032) were independently associated with LVMI (R2 = 0.581, P = 0.0001). The NaLi CT, an operating mode of the NaH exchanger that facilitates cellular growth, may be a marker of LVH, and consequently a marker of increased cardiovascular risk.

Biopsychosocial correlates of lifetime major depression in a multiple sclerosis population.

PubMed

Patten, S B; Metz, L M; Reimer, M A

2000-04-01

The objective of this paper was to evaluate the lifetime and point prevalence of major depression in a population-based Multiple Sclerosis (MS) clinic sample, and to describe associations between selected biopsychosocial variables and the prevalence of lifetime major depression in this sample. Subjects who had participated in an earlier study were re-contacted for additional data collection. Eighty-three per cent (n=136) of those eligible consented to participate. Each subject completed the Composite International Diagnostic Interview (CIDI) and an interviewer-administered questionnaire evaluating a series of biopsychosocial variables. The lifetime prevalence of major depression in this sample was 22.8%, somewhat lower than previous estimates in MS clinic populations. Women, those under 35, and those with a family history of major depression had a higher prevalence. Also, subjects reporting high levels of stress and heavy ingestion of caffeine (>400 mg) had a higher prevalence of major depression. As this was a cross-sectional analysis, the direction of causal effect for the observed associations could not be determined. By identifying variables that are associated with lifetime major depression, these data generate hypotheses for future prospective studies. Such studies will be needed to further understand the etiology of depressive disorders in MS.

The Ensemble Kalman Filter for Groundwater Plume Characterization: A Case Study.

PubMed

Ross, James L; Andersen, Peter F

2018-04-17

The Kalman filter is an efficient data assimilation tool to refine an estimate of a state variable using measured data and the variable's correlations in space and/or time. The ensemble Kalman filter (EnKF) (Evensen 2004, 2009) is a Kalman filter variant that employs Monte Carlo analysis to define the correlations that help to refine the updated state. While use of EnKF in hydrology is somewhat limited, it has been successfully applied in other fields of engineering (e.g., oil reservoir modeling, weather forecasting). Here, EnKF is used to refine a simulated groundwater tetrachloroethylene (TCE) plume that underlies the Tooele Army Depot-North (TEAD-N) in Utah, based on observations of TCE in the aquifer. The resulting EnKF-based assimilated plume is simulated forward in time to predict future plume migration. The correlations that underpin EnKF updating implicitly contain information about how the plume developed over time under the influence of complex site hydrology and variable source history, as they are predicated on multiple realizations of a well-calibrated numerical groundwater flow and transport model. The EnKF methodology is compared to an ordinary kriging-based assimilation method with respect to the accurate representation of plume concentrations in order to determine the relative efficacy of EnKF for water quality data assimilation. © 2018, National Ground Water Association.

Predictors of academic performance in the discipline-specific bioscience paper: a retrospective qualitative study.

PubMed

Khareedi, R

2018-05-01

The cohort of students enrolled in the discipline-specific bioscience paper reflects a structural diversity in that it includes students of multiple ethnicities, varied age groups, differing scholastic and life experiences. These divergent identities of students are known to influence academic performance. The purpose of this retrospective quantitative study was to determine the ability of a set of variables such as age, gender, ethnicity, level of prior education, the place from which prior education was obtained, work experience and prior academic achievement to predict academic performance in the discipline-specific bioscience paper. The sample for this study was a purposive sample of all oral health students who had enrolled in the paper at the Auckland University of Technology from 2011 to 2014. The desensitised empirical data of 116 students from the University's database were subject to multivariable regression analysis. Pearson's correlation coefficients were calculated. Prior academic achievement was a statistically significant predictor variable (P < 0.001) for the academic performance in the discipline-specific bioscience paper and was also positively correlated (r = 0.641, P < 0.001) to the grades in the discipline-specific bioscience paper. Prior academic achievement was the only variable that was demonstrated to be correlated to and predictive of the academic performance in the discipline-specific bioscience paper. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Scales of snow depth variability in high elevation rangeland sagebrush

NASA Astrophysics Data System (ADS)

Tedesche, Molly E.; Fassnacht, Steven R.; Meiman, Paul J.

2017-09-01

In high elevation semi-arid rangelands, sagebrush and other shrubs can affect transport and deposition of wind-blown snow, enabling the formation of snowdrifts. Datasets from three field experiments were used to investigate the scales of spatial variability of snow depth around big mountain sagebrush ( Artemisia tridentata Nutt.) at a high elevation plateau rangeland in North Park, Colorado, during the winters of 2002, 2003, and 2008. Data were collected at multiple resolutions (0.05 to 25 m) and extents (2 to 1000 m). Finer scale data were collected specifically for this study to examine the correlation between snow depth, sagebrush microtopography, the ground surface, and the snow surface, as well as the temporal consistency of snow depth patterns. Variograms were used to identify the spatial structure and the Moran's I statistic was used to determine the spatial correlation. Results show some temporal consistency in snow depth at several scales. Plot scale snow depth variability is partly a function of the nature of individual shrubs, as there is some correlation between the spatial structure of snow depth and sagebrush, as well as between the ground and snow depth. The optimal sampling resolution appears to be 25-cm, but over a large area, this would require a multitude of samples, and thus a random stratified approach is recommended with a fine measurement resolution of 5-cm.

Preferential reduction of bone mineral density at the femur reflects impairment of physical activity in patients with low-activity rheumatoid arthritis.

PubMed

Sugiguchi, Shigeru; Goto, Hitoshi; Inaba, Masaaki; Nishizawa, Yoshiki

2010-02-01

Bone mineral density (BMD) and factors influencing BMD in rheumatoid arthritis (RA) under good or moderate control were examined to assess management of osteoporosis in RA. BMD of the lumbar spine, femur, and distal radius was measured in 105 female patients with well-controlled RA. Laboratory and clinical variables associated with disease activity were measured in the same subjects, and correlations between these variables and BMD were evaluated. The RA patients showed a greater decrease in BMD of the femoral neck than of the lumbar spine. Age, Health Assessment Questionnaire (HAQ) score, and Larsen damage score had negative correlations with BMD of the femoral neck. In multiple regression analysis of the parameters associated with BMD of the femoral neck in simple regression analysis, an increase in HAQ score showed a negative correlation with BMD of the femoral neck. After initiation of treatment with alendronate (ALN), BMD of the femoral neck increased and correlated with improvement in HAQ score. A decrease in BMD of the femoral neck is a characteristic of RA. This suggests that muscle tonus has more effect than weight-bearing activity on BMD in patients with RA. BMD of the femoral neck is a useful index for general evaluation of RA patients.

Relationship between sugarcane rust severity and soil properties in louisiana.

PubMed

Johnson, Richard M; Grisham, Michael P; Richard, Edward P

2007-06-01

ABSTRACT The extent of spatial and temporal variability of sugarcane rust (Puccinia melanocephala) infestation was related to variation in soil properties in five commercial fields of sugarcane (interspecific hybrids of Saccharum spp., cv. LCP 85-384) in southern Louisiana. Sugarcane fields were grid-soil sampled at several intensities and rust ratings were collected at each point over 6 to 7 weeks. Soil properties exhibited significant variability (coefficients of variation = 9 to 70.1%) and were spatially correlated in 39 of 40 cases with a range of spatial correlation varying from 39 to 201 m. Rust ratings were spatially correlated in 32 of 33 cases, with a range varying from 29 to 241 m. Rust ratings were correlated with several soil properties, most notably soil phosphorus (r = 0.40 to 0.81) and soil sulfur (r = 0.36 to 0.68). Multiple linear regression analysis resulted in coefficients of determination that ranged from 0.22 to 0.73, and discriminant analysis further improved the overall predictive ability of rust models. Finally, contour plots of soil properties and rust levels clearly suggested a link between these two parameters. These combined data suggest that sugarcane growers that apply fertilizer in excess of plant requirements will increase the incidence and severity of rust infestations in their fields.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Short-term electric power demand forecasting based on economic-electricity transmission model

NASA Astrophysics Data System (ADS)

Li, Wenfeng; Bai, Hongkun; Liu, Wei; Liu, Yongmin; Wang, Yubin Mao; Wang, Jiangbo; He, Dandan

2018-04-01

Short-term electricity demand forecasting is the basic work to ensure safe operation of the power system. In this paper, a practical economic electricity transmission model (EETM) is built. With the intelligent adaptive modeling capabilities of Prognoz Platform 7.2, the econometric model consists of three industrial added value and income levels is firstly built, the electricity demand transmission model is also built. By multiple regression, moving averages and seasonal decomposition, the problem of multiple correlations between variables is effectively overcome in EETM. The validity of EETM is proved by comparison with the actual value of Henan Province. Finally, EETM model is used to forecast the electricity consumption of the 1-4 quarter of 2018.

Self-regulated learning and achievement by middle-school children.

PubMed

Sink, C A; Barnett, J E; Hixon, J E

1991-12-01

The relationship of self-regulated learning to the achievement test scores of 62 Grade 6 students was studied. Generally, the metacognitive and affective variables correlated significantly with teachers' grades and standardized test scores in mathematics, reading, and science. Planning and self-assessment significantly predicted the six measures of achievement. Step-wise multiple regression analyses using the metacognitive and affective variables largely indicate that students' and teachers' perceptions of scholastic ability and planning appear to be the most salient factors in predicting academic performance. The locus of control dimension had no utility in predicting classroom grades and performance on standardized measures of achievement. The implications of the findings for teaching and learning are discussed.

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

PubMed

Toni, Tina; Tidor, Bruce

2013-01-01

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

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

PubMed Central

Toni, Tina; Tidor, Bruce

2013-01-01

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

Patterns and correlates of co-occurrence among multiple types of child maltreatment

PubMed Central

Kim, Kihyun; Mennen, Ferol E.; Trickett, Penelope K.

2017-01-01

This study examined the patterns and correlates of the types of maltreatment experienced by adolescents aged 9–12, participating in an ongoing longitudinal study on the impact of neglect on children’s development. Using case record abstraction, the study compared the child protection classification and findings from the case record abstraction with regard to the rates of four types of maltreatment (i.e. physical, sexual, emotional abuse and neglect) as well as co-occurrence across multiple types of maltreatment. Next, the study examined the frequently observed patterns of child maltreatment. Finally, the study investigated whether aspects of caretaker functioning and the detailed incident characteristics in the cases of neglect differed by the number of different types of maltreatment the children experienced. Results showed significant discrepancies between the Child Protective Service classification and case record abstraction. Child Protective Service classification considerably underestimated the rate of co-occurrence across multiple types of maltreatment. Neglect accompanied by physical and emotional abuse was the most common form. Some of the caretaker functioning variables distinguished the number of types of maltreatment. Based on the findings, future-research directions and practice implication were discussed. PMID:29225485

The clinico-radiological paradox of cognitive function and MRI burden of white matter lesions in people with multiple sclerosis: A systematic review and meta-analysis.

PubMed

Mollison, Daisy; Sellar, Robin; Bastin, Mark; Mollison, Denis; Chandran, Siddharthan; Wardlaw, Joanna; Connick, Peter

2017-01-01

Moderate correlation exists between the imaging quantification of brain white matter lesions and cognitive performance in people with multiple sclerosis (MS). This may reflect the greater importance of other features, including subvisible pathology, or methodological limitations of the primary literature. To summarise the cognitive clinico-radiological paradox and explore the potential methodological factors that could influence the assessment of this relationship. Systematic review and meta-analysis of primary research relating cognitive function to white matter lesion burden. Fifty papers met eligibility criteria for review, and meta-analysis of overall results was possible in thirty-two (2050 participants). Aggregate correlation between cognition and T2 lesion burden was r = -0.30 (95% confidence interval: -0.34, -0.26). Wide methodological variability was seen, particularly related to key factors in the cognitive data capture and image analysis techniques. Resolving the persistent clinico-radiological paradox will likely require simultaneous evaluation of multiple components of the complex pathology using optimum measurement techniques for both cognitive and MRI feature quantification. We recommend a consensus initiative to support common standards for image analysis in MS, enabling benchmarking while also supporting ongoing innovation.

[Quantitative structure-gas chromatographic retention relationship of polycyclic aromatic sulfur heterocycles using molecular electronegativity-distance vector].

PubMed

Li, Zhenghua; Cheng, Fansheng; Xia, Zhining

2011-01-01

The chemical structures of 114 polycyclic aromatic sulfur heterocycles (PASHs) have been studied by molecular electronegativity-distance vector (MEDV). The linear relationships between gas chromatographic retention index and the MEDV have been established by a multiple linear regression (MLR) model. The results of variable selection by stepwise multiple regression (SMR) and the powerful predictive abilities of the optimization model appraised by leave-one-out cross-validation showed that the optimization model with the correlation coefficient (R) of 0.994 7 and the cross-validated correlation coefficient (Rcv) of 0.994 0 possessed the best statistical quality. Furthermore, when the 114 PASHs compounds were divided into calibration and test sets in the ratio of 2:1, the statistical analysis showed our models possesses almost equal statistical quality, the very similar regression coefficients and the good robustness. The quantitative structure-retention relationship (QSRR) model established may provide a convenient and powerful method for predicting the gas chromatographic retention of PASHs.

Correlates of willingness to engage in residential gardening: implications for health optimization in ibadan, Nigeria.

PubMed

Motunrayo Ibrahim, Fausat

2013-01-01

Gardening is a worthwhile adventure which engenders health op-timization. Yet, a dearth of evidences that highlights motivations to engage in gardening exists. This study examined willingness to engage in gardening and its correlates, including some socio-psychological, health related and socio-demographic variables. In this cross-sectional survey, 508 copies of a structured questionnaire were randomly self administered among a group of civil servants of Oyo State, Nigeria. Multi-item measures were used to assess variables. Step wise multiple regression analysis was used to identify predictors of willingness to engage in gar-dening Results: Simple percentile analysis shows that 71.1% of respondents do not own a garden. Results of step wise multiple regression analysis indicate that descriptive norm of gardening is a good predictor, social support for gardening is better while gardening self efficacy is the best predictor of willingness to engage in gardening (P< 0.001). Health consciousness, gardening response efficacy, education and age are not predictors of this willingness (P> 0.05). Results of t-test and ANOVA respectively shows that gender is not associated with this willingness (P> 0.05), but marital status is (P< 0.05).  Socio-psychological characteristics and being married are very rele-vant in motivations to engage in gardening. The nexus between gardening and health optimization appears to be highly obscured in this population.

Correlates of Willingness to Engage in Residential Gardening: Implications for Health Optimization in Ibadan, Nigeria

PubMed Central

Motunrayo Ibrahim, Fausat

2013-01-01

Background: Gardening is a worthwhile adventure which engenders health op­timization. Yet, a dearth of evidences that highlights motivations to engage in gardening exists. This study examined willingness to engage in gardening and its correlates, including some socio-psychological, health related and socio-demographic variables. Methods: In this cross-sectional survey, 508 copies of a structured questionnaire were randomly self administered among a group of civil servants of Oyo State, Nigeria. Multi-item measures were used to assess variables. Step wise multiple regression analysis was used to identify predictors of willingness to engage in gar­dening Results: Simple percentile analysis shows that 71.1% of respondents do not own a garden. Results of step wise multiple regression analysis indicate that descriptive norm of gardening is a good predictor, social support for gardening is better while gardening self efficacy is the best predictor of willingness to engage in gardening (P< 0.001). Health consciousness, gardening response efficacy, education and age are not predictors of this willingness (P> 0.05). Results of t-test and ANOVA respectively shows that gender is not associated with this willingness (P> 0.05), but marital status is (P< 0.05).  Conclusion: Socio-psychological characteristics and being married are very rele­vant in motivations to engage in gardening. The nexus between gardening and health optimization appears to be highly obscured in this population. PMID:24688974

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

NASA Astrophysics Data System (ADS)

Gibbs-Harper, Nzinga A.

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

Riparian and Associated Habitat Characteristics Related to Nutrient Concentrations and Biological Responses of Small Streams in Selected Agricultural Areas, United States, 2003-04

USGS Publications Warehouse

Zelt, Ronald B.; Munn, Mark D.

2009-01-01

Physical factors, including both in-stream and riparian habitat characteristics that limit biomass or otherwise regulate aquatic biological condition, have been identified by previous studies. However, linking the ecological significance of nutrient enrichment to habitat or landscape factors that could allow for improved management of streams has proved to be a challenge in many regions, including agricultural landscapes, where many ecological stressors are strong and the variability among watersheds typically is large. Riparian and associated habitat characteristics were sampled once during 2003-04 for an intensive ecological and nutrients study of small perennial streams in five contrasting agricultural landscapes across the United States to determine how biological communities and ecosystem processes respond to varying levels of nutrient enrichment. Nutrient concentrations were determined in stream water at two different sampling times per site and biological samples were collected once per site near the time of habitat characterization. Data for 141 sampling sites were compiled, representing five study areas, located in parts of the Delmarva Peninsula (Delaware and Maryland), Georgia, Indiana, Ohio, Nebraska, and Washington. This report examines the available data for riparian and associated habitat characteristics to address questions related to study-unit contrasts, spatial scale-related differences, multivariate correlation structure, and bivariate relations between selected habitat characteristics and either stream nutrient conditions or biological responses. Riparian and associated habitat characteristics were summarized and categorized into 22 groups of habitat variables, with 11 groups representing land-use and land-cover characteristics and 11 groups representing other riparian or in-stream habitat characteristics. Principal components analysis was used to identify a reduced set of habitat variables that describe most of the variability among the sampled sites. The habitat characteristics sampled within the five study units were compared statistically. Bivariate correlations between riparian habitat variables and either nutrient-chemistry or biological-response variables were examined for all sites combined, and for sites within each study area. Nutrient concentrations were correlated with the extent of riparian cropland. For nitrogen species, these correlations were more frequently at the basin scale, whereas for phosphorus, they were about equally frequent at the segment and basin scales. Basin-level extents of riparian cropland and reach-level bank vegetative cover were correlated strongly with both total nitrogen and dissolved inorganic nitrogen (DIN) among multiple study areas, reflecting the importance of agricultural land-management and conservation practices for reducing nitrogen delivery from near-stream sources. When sites lacking segment-level wetlands were excluded, the negative correlation of riparian wetland extent with DIN among 49 sites was strong at the reach and segment levels. Riparian wetland vegetation thus may be removing dissolved nutrients from soil water and shallow groundwater passing through riparian zones. Other habitat variables that correlated strongly with nitrogen and phosphorus species included suspended sediment, light availability, and antecedent water temperature. Chlorophyll concentrations in seston were positively correlated with phosphorus concentrations for all sites combined. Benthic chlorophyll was correlated strongly with nutrient concentrations in only the Delmarva study area and only in fine-grained habitats. Current velocity or hydraulic scour could explain correlation patterns for benthic chlorophyll among Georgia sites, whereas chlorophyll in seston was correlated with antecedent water temperature among Washington and Delmarva sites. The lack of any consistent correlation pattern between habitat characteristics and organic material density (ash-free dry mass)

Investigating local controls on temporal stability of soil water content using sensor network data and an inverse modeling approach

NASA Astrophysics Data System (ADS)

Qu, W.; Bogena, H. R.; Huisman, J. A.; Martinez, G.; Pachepsky, Y. A.; Vereecken, H.

2013-12-01

Soil water content is a key variable in the soil, vegetation and atmosphere continuum with high spatial and temporal variability. Temporal stability of soil water content (SWC) has been observed in multiple monitoring studies and the quantification of controls on soil moisture variability and temporal stability presents substantial interest. The objective of this work was to assess the effect of soil hydraulic parameters on the temporal stability. The inverse modeling based on large observed time series SWC with in-situ sensor network was used to estimate the van Genuchten-Mualem (VGM) soil hydraulic parameters in a small grassland catchment located in western Germany. For the inverse modeling, the shuffled complex evaluation (SCE) optimization algorithm was coupled with the HYDRUS 1D code. We considered two cases: without and with prior information about the correlation between VGM parameters. The temporal stability of observed SWC was well pronounced at all observation depths. Both the spatial variability of SWC and the robustness of temporal stability increased with depth. Calibrated models both with and without prior information provided reasonable correspondence between simulated and measured time series of SWC. Furthermore, we found a linear relationship between the mean relative difference (MRD) of SWC and the saturated SWC (θs). Also, the logarithm of saturated hydraulic conductivity (Ks), the VGM parameter n and logarithm of α were strongly correlated with the MRD of saturation degree for the prior information case, but no correlation was found for the non-prior information case except at the 50cm depth. Based on these results we propose that establishing relationships between temporal stability and spatial variability of soil properties presents a promising research avenue for a better understanding of the controls on soil moisture variability. Correlation between Mean Relative Difference of soil water content (or saturation degree) and inversely estimated soil hydraulic parameters (log10(Ks), log10(α), n, and θs) at 5-cm, 20-cm and 50-cm depths. Solid circles represent parameters estimated by using prior information; open circles represent parameters estimated without using prior information.

The impact of social and organizational factors on workers' coping with musculoskeletal symptoms.

PubMed

Torp, S; Riise, T; Moen, B E

2001-07-01

Workers with musculoskeletal symptoms are often advised to cope with their symptoms by changing their working technique and by using lifting equipment. The main objective of this study was to test the hypothesis that negative social and organizational factors where people are employed may prevent workers from implementing these coping strategies. A total of 1,567 automobile garage workers (72%) returned a questionnaire concerning coping with musculoskeletal symptoms and social and organizational factors. When job demands, decision authority, social support, and management support related to health, environment, and safety (HES) were used as predictor variables in a multiple regression model, coping as the outcome variable was correlated with decision authority, social support, and HES-related management support (standardized beta=.079,.12, and.13, respectively). When an index for health-related support and control was added to the model, it correlated with coping (standardized beta=.36), whereas the other relationships disappeared. Decision authority and social support entail health-related support and control that, in turn, influences coping.

Variable weight spectral amplitude coding for multiservice OCDMA networks

NASA Astrophysics Data System (ADS)

Seyedzadeh, Saleh; Rahimian, Farzad Pour; Glesk, Ivan; Kakaee, Majid H.

2017-09-01

The emergence of heterogeneous data traffic such as voice over IP, video streaming and online gaming have demanded networks with capability of supporting quality of service (QoS) at the physical layer with traffic prioritisation. This paper proposes a new variable-weight code based on spectral amplitude coding for optical code-division multiple-access (OCDMA) networks to support QoS differentiation. The proposed variable-weight multi-service (VW-MS) code relies on basic matrix construction. A mathematical model is developed for performance evaluation of VW-MS OCDMA networks. It is shown that the proposed code provides an optimal code length with minimum cross-correlation value when compared to other codes. Numerical results for a VW-MS OCDMA network designed for triple-play services operating at 0.622 Gb/s, 1.25 Gb/s and 2.5 Gb/s are considered.

Optimal information networks: Application for data-driven integrated health in populations

PubMed Central

Servadio, Joseph L.; Convertino, Matteo

2018-01-01

Development of composite indicators for integrated health in populations typically relies on a priori assumptions rather than model-free, data-driven evidence. Traditional variable selection processes tend not to consider relatedness and redundancy among variables, instead considering only individual correlations. In addition, a unified method for assessing integrated health statuses of populations is lacking, making systematic comparison among populations impossible. We propose the use of maximum entropy networks (MENets) that use transfer entropy to assess interrelatedness among selected variables considered for inclusion in a composite indicator. We also define optimal information networks (OINs) that are scale-invariant MENets, which use the information in constructed networks for optimal decision-making. Health outcome data from multiple cities in the United States are applied to this method to create a systemic health indicator, representing integrated health in a city. PMID:29423440

[Academic performance in first year medical students: an explanatory multivariate model].

PubMed

Urrutia Aguilar, María Esther; Ortiz León, Silvia; Fouilloux Morales, Claudia; Ponce Rosas, Efrén Raúl; Guevara Guzmán, Rosalinda

2014-12-01

Current education is focused in intellectual, affective, and ethical aspects, thus acknowledging their significance in students´ metacognition. Nowadays, it is known that an adequate and motivating environment together with a positive attitude towards studies is fundamental to induce learning. Medical students are under multiple stressful, academic, personal, and vocational situations. To identify psychosocial, vocational, and academic variables of 2010-2011 first year medical students at UNAM that may help predict their academic performance. Academic surveys of psychological and vocational factors were applied; an academic follow-up was carried out to obtain a multivariate model. The data were analyzed considering descriptive, comparative, correlative, and predictive statistics. The main variables that affect students´ academic performance are related to previous knowledge and to psychological variables. The results show the significance of implementing institutional programs to support students throughout their college adaptation.

The Correlated Variations of {\\rm{C}}\\,{\\rm{IV}} Narrow Absorption Lines and Quasar Continuum

NASA Astrophysics Data System (ADS)

Chen, Zhi-Fu; Pang, Ting-Ting; He, Bing; Huang, Yong

2018-06-01

We assemble 207 variable quasars from the Sloan Digital Sky Survey, all with at least 3 observations, to analyze C IV narrow absorption doublets, and obtain 328 C IV narrow absorption line systems. We find that 19 out of 328 C IV narrow absorption line systems were changed by | {{Δ }}{W}rλ 1548| ≥slant 3{σ }{{Δ }{W}rλ 1548} on timescales from 15.9 to 1477 days at rest-frame. Among the 19 obviously variable C IV systems, we find that (1) 14 systems have relative velocities {\\upsilon }r> 0.01c and 4 systems have {\\upsilon }r> 0.1c, where c is the speed of light; (2) 13 systems are accompanied by other variable C IV systems; (3) 9 systems were changed continuously during multiple observations; and (4) 1 system with {\\upsilon }r = 16,862 km s‑1 was enhanced by {{Δ }}{W}rλ 1548=2.7{σ }{{Δ }{W}rλ 1548} in 0.67 day at rest-frame. The variations of absorption lines are inversely correlated with the changes in the ionizing continuum. We also find that large variations of C IV narrow absorption lines are form differently over a short timescale.

Factors influencing behavioral intention to undergo Papanicolaou testing in early adulthood: Comparison of Japanese and Korean women.

PubMed

Kang, Kyung-Ah; Kim, Shin-Jeong; Kaneko, Noriyo

2017-12-01

In this study, we identified the factors influencing behavioral intention to undergo Papanicolaou testing among Japanese and Korean women in early adulthood. Their behavioral intentions were compared in this cross-sectional descriptive study. In total, 887 women (Japanese = 498, Korean = 389) aged 20-39 years participated in this study. Using a self-report questionnaire, knowledge, attitudes, subjective norm, perceived behavioral control, and behavioral intention were surveyed. There were significant differences between Japanese and Korean women's scores on all main variables. For Japanese women, all the variables moderately correlated with behavioral intention. In comparison, for Korean women, all independent variables, except for knowledge, moderately correlated with behavioral intention. Through a multiple regression analysis, age, undergoing Papanicolaou testing, attitudes, subjective norm, and perceived behavioral control were identified as significant predictors of behavioral intention among Japanese women. Among Korean women, job status, undergoing a Papanicolaou test, attitudes, subjective norm, and perceived behavioral control were demonstrated as significant predictors of behavioral intention. Health professionals should consider these factors to encourage Papanicolaou testing in women in early adulthood. © 2017 John Wiley & Sons Australia, Ltd.

Body composition and blood pressure in children based on age, race, and sex.

PubMed

Brandon, L J; Fillingim, J

1993-01-01

We evaluated 675 nine- and twelve-year-old children for body composition and circulatory differences based on age, race, and sex. The specific variables measured included height, weight, triceps and subscapula skinfolds, body mass index, percentage fat, fat-free weight, and systolic, diastolic, and mean arterial blood pressures. A 2 x 2 x 2 factorial multiple analysis of variance (MANOVA) test of significance showed body composition and blood pressure differences (P < .01) for race, age, and sex. The univariate test of the specific variables within the factors showed that black children had higher fat-free weights and lower fat levels but higher blood pressure values (P < .05) than white children. Boys had lower fat levels than girls, and the older children had higher values on the body composition variables but not on blood pressure. Zero order correlations between body composition and blood pressure ranged from 0.14 to 0.55; systolic blood pressure and body weight shared the highest correlation. These data show that, although black children have less body fat than white children, they are heavier and have higher blood pressure. We hypothesize that some aspect of fat-free body weight may contribute to hypertension in black individuals.

A study of Solar-Enso correlation with southern Brazil tree ring index (1955- 1991)

NASA Astrophysics Data System (ADS)

Rigozo, N.; Nordemann, D.; Vieira, L.; Echer, E.

The effects of solar activity and El Niño-Southern Oscillation on tree growth in Southern Brazil were studied by correlation analysis. Trees for this study were native Araucaria (Araucaria Angustifolia)from four locations in Rio Grande do Sul State, in Southern Brazil: Canela (29o18`S, 50o51`W, 790 m asl), Nova Petropolis (29o2`S, 51o10`W, 579 m asl), Sao Francisco de Paula (29o25`S, 50o24`W, 930 m asl) and Sao Martinho da Serra (29o30`S, 53o53`W, 484 m asl). From these four sites, an average tree ring Index for this region was derived, for the period 1955-1991. Linear correlations were made on annual and 10 year running averages of this tree ring Index, of sunspot number Rz and SOI. For annual averages, the correlation coefficients were low, and the multiple regression between tree ring and SOI and Rz indicates that 20% of the variance in tree rings was explained by solar activity and ENSO variability. However, when the 10 year running averages correlations were made, the coefficient correlations were much higher. A clear anticorrelation is observed between SOI and Index (r=-0.81) whereas Rz and Index show a positive correlation (r=0.67). The multiple regression of 10 year running averages indicates that 76% of the variance in tree ring INdex was explained by solar activity and ENSO. These results indicate that the effects of solar activity and ENSO on tree rings are better seen on long timescales.

Correlation of Vitamin D status and orthodontic-induced external apical root resorption.

PubMed

Tehranchi, Azita; Sadighnia, Azin; Younessian, Farnaz; Abdi, Amir H; Shirvani, Armin

2017-01-01

Adequate Vitamin D is essential for dental and skeletal health in children and adult. The purpose of this study was to assess the correlation of serum Vitamin D level with external-induced apical root resorption (EARR) following fixed orthodontic treatment. In this cross-sectional study, the prevalence of Vitamin D deficiency (defined by25-hydroxyvitamin-D) was determined in 34 patients (23.5% male; age range 12-23 years; mean age 16.63 ± 2.84) treated with fixed orthodontic treatment. Root resorption of four maxillary incisors was measured using before and after periapical radiographs (136 measured teeth) by means of a design-to-purpose software to optimize data collection. Teeth with a maximum percentage of root resorption (%EARR) were indicated as representative root resorption for each patient. A multiple linear regression model and Pearson correlation coefficient were used to assess the association of Vitamin D status and observed EARR. P < 0.05 was considered statistically significant. The Pearson coefficient between these two variables was determined about 0.15 ( P = 0.38). Regression analysis revealed that Vitamin D status of the patients demonstrated no significant statistical correlation with EARR, after adjustment of confounding variables using linear regression model ( P > 0.05). This study suggests that Vitamin D level is not among the clinical variables that are potential contributors for EARR. The prevalence of Vitamin D deficiency does not differ in patients with higher EARR. These data suggest the possibility that Vitamin D insufficiency may not contribute to the development of more apical root resorption although this remains to be confirmed by further longitudinal cohort studies.

Drug use, mental health and problems related to crime and violence: cross-sectional study1

PubMed Central

Claro, Heloísa Garcia; de Oliveira, Márcia Aparecida Ferreira; Bourdreaux, Janet Titus; Fernandes, Ivan Filipe de Almeida Lopes; Pinho, Paula Hayasi; Tarifa, Rosana Ribeiro

2015-01-01

Objective: to investigate the correlation between disorders related to the use of alcohol and other drugs and symptoms of mental disorders, problems related to crime and violence and to age and gender. Methods: cross-sectional descriptive study carried out with 128 users of a Psychosocial Care Center for Alcohol and other Drugs, in the city of São Paulo, interviewed by means of the instrument entitled Global Appraisal of Individual Needs - Short Screener. Univariate and multiple linear regression models were used to verify the correlation between the variables. Results: using univariate regression models, internalizing and externalizing symptoms and problems related to crime/violence proved significant and were included in the multiple model, in which only the internalizing symptoms and problems related to crime and violence remained significant. Conclusions: there is a correlation between the severity of problems related to alcohol use and severity of mental health symptoms and crime and violence in the study sample. The results emphasize the need for an interdisciplinary and intersectional character of attention to users of alcohol and other drugs, since they live in a socially vulnerable environment. PMID:26626010

Space-time modeling of soil moisture

NASA Astrophysics Data System (ADS)

Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio

2017-11-01

A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.

Rethinking Dental School Admission Criteria: Correlation Between Pre-Admission Variables and First-Year Performance for Six Classes at One Dental School.

PubMed

Rowland, Kevin C; Rieken, Susan

2018-04-01

Admissions committees in dental schools are charged with the responsibility of selecting candidates who will succeed in school and become successful members of the profession. Identifying students who will have academic difficulty is challenging. The aim of this study was to determine the predictive value of pre-admission variables for the first-year performance of six classes at one U.S. dental school. The authors hypothesized that the variables undergraduate grade point average (GPA), undergraduate science GPA (biology, chemistry, and physics), and Dental Admission Test (DAT) scores would predict the level of performance achieved in the first year of dental school, measured by year-end GPA. Data were collected in 2015 from school records for all 297 students in the six cohorts who completed the first year (Classes of 2007 through 2013). In the results, statistically significant correlations existed between all pre-admission variables and first-year GPA, but the associations were only weak to moderate. Lower performing students at the end of the first year (lowest 10% of GPA) had, on average, lower pre-admission variables than the other students, but the differences were small (≤10.8% in all categories). When all the pre-admission variables were considered together in a multiple regression analysis, a significant association was found between pre-admission variables and first-year GPA, but the association was weak (adjusted R 2 =0.238). This weak association suggests that these students' first-year dental school GPAs were mostly determined by factors other than the pre-admission variables studied and has resulted in the school's placing greater emphasis on other factors for admission decisions.

Sports Participation and Positive Correlates in African American, Latino, and White Girls

PubMed Central

Duncan, Susan C.; Strycker, Lisa A.; Chaumeton, Nigel R.

2015-01-01

Purpose The purpose of the study was to examine relations among sports participation and positive correlates across African American, Latino, and white girls. Positive correlate variables were self-perceptions (self-worth, body attractiveness, athletic competence), less depression, and participation in extracurricular activities. Methods The sample comprised 372 girls (mean age = 12.03 years). Data were analyzed using multiple-sample structural equation models, controlling for age and income. Results Across all ethnic groups, greater sports participation was significantly related to higher self-worth, body attractiveness, and athletic competence, and to more extracurricular activity. Among Latino and white girls only, greater sports participation also was related to less depression. There were significant age and income influences on the positive correlates. Conclusions Findings confirm the existence of significant relationships between organized sports participation and positive correlates among early adolescent African American, Latino, and white girls. Despite a few ethnic differences in relationships, the current study revealed more similarities than differences. PMID:26692758

Capillary device refilling. [liquid rocket propellant tank tests

NASA Technical Reports Server (NTRS)

Blatt, M. H.; Merino, F.; Symons, E. P.

1980-01-01

An analytical and experimental study was conducted dealing with refilling start baskets (capillary devices) with settled fluid. A computer program was written to include dynamic pressure, screen wicking, multiple-screen barriers, standpipe screens, variable vehicle mass for computing vehicle acceleration, and calculation of tank outflow rate and vapor pullthrough height. An experimental apparatus was fabricated and tested to provide data for correlation with the analytical model; the test program was conducted in normal gravity using a scale-model capillary device and ethanol as the test fluid. The test data correlated with the analytical model; the model is a versatile and apparently accurate tool for predicting start basket refilling under actual mission conditions.

Does the perception that God controls health outcomes matter for health behaviors?

PubMed

Karvinen, Kristina H; Carr, Lucas J

2014-04-01

The purpose of this study was to examine the associations between God Locus of Health Control, health behaviors, and beliefs utilizing a cross-sectional online survey (N = 549). Results indicated that God Locus of Health Control was correlated with alcohol use, physical activity, perceived risk of chronic disease, and beliefs that poor health behaviors contribute to chronic disease (all p values < .05). Multiple regression analyses including covariates and other locus of control variables revealed that God Locus of Health Control was only an independent correlate of the belief that physical inactivity contributed to chronic disease. Insights from this study may be important for future faith-based health behavior change interventions.

Characterization of good teleoperators - What aptitudes, interests, and experience correlate with measures of teleoperator performance

NASA Technical Reports Server (NTRS)

Yorchak, J. P.; Hartley, C. S.; Hinman, E.

1985-01-01

The use of aptitude tests and questionnaries to evaluate an individuals aptitude for teleoperation is studied. The Raven Progressive Matrices Test and Differential Aptitude Tests, and a 16-item questionnaire for assessing the subject's interests, academic background, and previous experience are described. The Proto-Flight Manipulator Arm, cameras, console, hand controller, and task board utilized by the 17 engineers are examined. The correlation between aptitude scores and questionnaire responses, and operator performance is investigated. Multiple regression data reveal that the eight predictor variables are not individually significant for evaluating operator performance; however, the complete test battery is applicable for predicting 49 percent of subject variance on the criterion task.

Correlation of echo-Doppler aortic valve regurgitation index with angiographic aortic regurgitation severity.

PubMed

Chen, Ming; Luo, Huai; Miyamoto, Takashi; Atar, Shaul; Kobal, Sergio; Rahban, Masoud; Brasch, Andrea V; Makkar, Rajendra; Neuman, Yoram; Naqvi, Tasneem Z; Tolstrup, Kirsten; Siegel, Robert J

2003-09-01

We assessed aortic regurgitation (AR) severity by utilizing multiple echo-Doppler variables in comparison with AR severity by aortic root angiography. Patients were divided into 3 groups: mild, moderate, and severe. An AR index (ARI) was developed, comprising 5 echocardiographic parameters: ratio of color AR jet height to left ventricular outlet flow diameter, AR signal density from continuous-wave Doppler, pressure half-time, left ventricular end-diastolic diameter, and aortic root diameter. There was a strong correlation between AR severity by angiography and the calculated echo-Doppler ARI (r = 0.84, p = 0.0001). As validated by aortic angiography, the ARI is an accurate reflection of AR severity.

The Moderating Role of Power Distance on the Relationship between Employee Participation and Outcome Variables.

PubMed

Rafiei, Sima; Pourreza, Abolghasem

2013-06-01

Many organisations have realised the importance of human resource for their competitive advantage. Empowering employees is therefore essential for organisational effectiveness. This study aimed to investigate the relationship between employee participation with outcome variables such as organisational commitment, job satisfaction, perception of justice in an organisation and readiness to accept job responsibilities. It further examined the impact of power distance on the relationship between participation and four outcome variables. This was a cross sectional study with a descriptive research design conducted among employees and managers of hospitals affiliated with Tehran University of Medical Sciences, Tehran, Iran. A questionnaire as a main procedure to gather data was developed, distributed and collected. Descriptive statistics, Pearson correlation coefficient and moderated multiple regression were used to analyse the study data. Findings of the study showed that the level of power distance perceived by employees had a significant relationship with employee participation, organisational commitment, job satisfaction, perception of justice and readiness to accept job responsibilities. There was also a significant relationship between employee participation and four outcome variables. The moderated multiple regression results supported the hypothesis that power distance had a significant effect on the relationship between employee participation and four outcome variables. Organisations in which employee empowerment is practiced through diverse means such as participating them in decision making related to their field of work, appear to have more committed and satisfied employees with positive perception toward justice in the organisational interactions and readiness to accept job responsibilities.

Less Unique Variance Than Meets the Eye: Overlap Among Traditional Neuropsychological Dimensions in Schizophrenia

PubMed Central

Dickinson, Dwight; Gold, James M.

2008-01-01

The magnitude of the overlap among dimensions of neuropsychological test performance in schizophrenia has been the subject of perennial controversy. This issue has taken on renewed importance with the recent focus on cognition as a treatment target in schizophrenia. A substantial body of factor analytic literature indicates that dimensions are separable in schizophrenia. However, this literature is generally uninformative as to whether the separable dimensions are independent, weakly correlated, or strongly correlated. Factor analyses have often used methods (ie, principal components analysis with orthogonal rotation) that preclude this determination, and correlations among factor-based domain composites and underlying measures have been reported infrequently in these studies. Current meta-analyses of reported “between-dimension” correlations for individual neuropsychological measures and for cognitive domain composite variables indicate that cognition variables in schizophrenia are correlated, on average, at a “medium” level of r = 0.37 for individual measures from different cognitive dimensions and r = 0.45 for domain composites. Because these are mean bivariate correlations, the multiple correlation of an individual measure with all the other measures in a cognitive battery is likely to be higher. Measure reliabilities of 0.80 or less also imply greater commonality among traditional neuropsychological measures. In short, there are underappreciated constraints on the amount of reliable cognitive performance variance in traditional neuropsychological test batteries that is free to vary independently. The ability of such batteries to reveal cognitive domain–specific treatment effects in schizophrenia may be much more limited than is generally assumed. PMID:17702991

Stimulus Dependence of Correlated Variability across Cortical Areas

PubMed Central

Cohen, Marlene R.

2016-01-01

The way that correlated trial-to-trial variability between pairs of neurons in the same brain area (termed spike count or noise correlation, rSC) depends on stimulus or task conditions can constrain models of cortical circuits and of the computations performed by networks of neurons (Cohen and Kohn, 2011). In visual cortex, rSC tends not to depend on stimulus properties (Kohn and Smith, 2005; Huang and Lisberger, 2009) but does depend on cognitive factors like visual attention (Cohen and Maunsell, 2009; Mitchell et al., 2009). However, neurons across visual areas respond to any visual stimulus or contribute to any perceptual decision, and the way that information from multiple areas is combined to guide perception is unknown. To gain insight into these issues, we recorded simultaneously from neurons in two areas of visual cortex (primary visual cortex, V1, and the middle temporal area, MT) while rhesus monkeys viewed different visual stimuli in different attention conditions. We found that correlations between neurons in different areas depend on stimulus and attention conditions in very different ways than do correlations within an area. Correlations across, but not within, areas depend on stimulus direction and the presence of a second stimulus, and attention has opposite effects on correlations within and across areas. This observed pattern of cross-area correlations is predicted by a normalization model where MT units sum V1 inputs that are passed through a divisive nonlinearity. Together, our results provide insight into how neurons in different areas interact and constrain models of the neural computations performed across cortical areas. SIGNIFICANCE STATEMENT Correlations in the responses of pairs of neurons within the same cortical area have been a subject of growing interest in systems neuroscience. However, correlated variability between different cortical areas is likely just as important. We recorded simultaneously from neurons in primary visual cortex and the middle temporal area while rhesus monkeys viewed different visual stimuli in different attention conditions. We found that correlations between neurons in different areas depend on stimulus and attention conditions in very different ways than do correlations within an area. The observed pattern of cross-area correlations was predicted by a simple normalization model. Our results provide insight into how neurons in different areas interact and constrain models of the neural computations performed across cortical areas. PMID:27413163

Temperature and aridity regulate spatial variability of soil multifunctionality in drylands across the globe.

PubMed

Durán, Jorge; Delgado-Baquerizo, Manuel; Dougill, Andrew J; Guuroh, Reginald T; Linstädter, Anja; Thomas, Andrew D; Maestre, Fernando T

2018-05-01

The relationship between the spatial variability of soil multifunctionality (i.e., the capacity of soils to conduct multiple functions; SVM) and major climatic drivers, such as temperature and aridity, has never been assessed globally in terrestrial ecosystems. We surveyed 236 dryland ecosystems from six continents to evaluate the relative importance of aridity and mean annual temperature, and of other abiotic (e.g., texture) and biotic (e.g., plant cover) variables as drivers of SVM, calculated as the averaged coefficient of variation for multiple soil variables linked to nutrient stocks and cycling. We found that increases in temperature and aridity were globally correlated to increases in SVM. Some of these climatic effects on SVM were direct, but others were indirectly driven through reductions in the number of vegetation patches and increases in soil sand content. The predictive capacity of our structural equation modelling was clearly higher for the spatial variability of N- than for C- and P-related soil variables. In the case of N cycling, the effects of temperature and aridity were both direct and indirect via changes in soil properties. For C and P, the effect of climate was mainly indirect via changes in plant attributes. These results suggest that future changes in climate may decouple the spatial availability of these elements for plants and microbes in dryland soils. Our findings significantly advance our understanding of the patterns and mechanisms driving SVM in drylands across the globe, which is critical for predicting changes in ecosystem functioning in response to climate change. © 2018 by the Ecological Society of America.

Combining Fourier and lagged k-nearest neighbor imputation for biomedical time series data.

PubMed

Rahman, Shah Atiqur; Huang, Yuxiao; Claassen, Jan; Heintzman, Nathaniel; Kleinberg, Samantha

2015-12-01

Most clinical and biomedical data contain missing values. A patient's record may be split across multiple institutions, devices may fail, and sensors may not be worn at all times. While these missing values are often ignored, this can lead to bias and error when the data are mined. Further, the data are not simply missing at random. Instead the measurement of a variable such as blood glucose may depend on its prior values as well as that of other variables. These dependencies exist across time as well, but current methods have yet to incorporate these temporal relationships as well as multiple types of missingness. To address this, we propose an imputation method (FLk-NN) that incorporates time lagged correlations both within and across variables by combining two imputation methods, based on an extension to k-NN and the Fourier transform. This enables imputation of missing values even when all data at a time point is missing and when there are different types of missingness both within and across variables. In comparison to other approaches on three biological datasets (simulated and actual Type 1 diabetes datasets, and multi-modality neurological ICU monitoring) the proposed method has the highest imputation accuracy. This was true for up to half the data being missing and when consecutive missing values are a significant fraction of the overall time series length. Copyright © 2015 Elsevier Inc. All rights reserved.

Serum bilirubin levels are positively associated with glycemic variability in women with type 2 diabetes.

PubMed

Kim, Lee Kyung; Roh, Eun; Kim, Min Joo; Kim, Min Kyeong; Park, Kyeong Seon; Kwak, Soo Heon; Cho, Young Min; Park, Kyong Soo; Jang, Hak Chul; Jung, Hye Seung

2016-11-01

Glycemic variability is known to induce oxidative stress. We investigated the relationships between glycemic variability and serum bilirubin levels, an endogenous anti-oxidant, in patients with diabetes. A cross-sectional study was carried out with 77 patients with type 2 diabetes who had been recruited to two clinical studies from 2008 to 2014. There were no participants with diseases of the pancreas, liver, biliary tract and chronic renal insufficiency. Glycemic variation was calculated by a continuous glucose monitoring system, and correlation analyses were carried out to evaluate their association with bilirubin levels. Multiple linear regression was carried out to identify independent factors influencing bilirubin levels and glycemic variation. Among the participants, 42.3% were men. The mean (standard deviation) age was 61.5 years (10.4 years), body mass index was 24.2 kg/m 2 (2.8 kg/m 2 ), diabetes duration was 17.7 years (9.5 years), hemoglobin A 1c was 60.7 mmol/mol (7.1 mmol/mol; 7.7 [0.7]%) and bilirubin was 11.8 μmol/L (4.10 μmol/L). Serum bilirubin levels were not different according to age, body mass index and hemoglobin A 1c . However, the mean amplitude of glucose excursion was positively associated with bilirubin levels in women (r = 0.588, P < 0.001). After adjustment with duration of diabetes, serum albumin, liver enzymes, and mean glucose, the correlation between bilirubin and mean amplitude of glucose excursion remained significant (r = 0.566, P < 0.001). Multiple linear regression analyses showed that bilirubin was an independent determinant for the mean amplitude of glucose excursion in women. 1,5-Anhydroglucitol was also associated with bilirubin levels in women. Bilirubin level within the physiological range might be an independent predictor for glycemic variability in women with type 2 diabetes. © 2016 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.

CSI 2264: Simultaneous Optical and Infrared Light Curves of Young Disk-bearing Stars in NGC 2264 with CoRoT and Spitzer—Evidence for Multiple Origins of Variability

NASA Astrophysics Data System (ADS)

Cody, Ann Marie; Stauffer, John; Baglin, Annie; Micela, Giuseppina; Rebull, Luisa M.; Flaccomio, Ettore; Morales-Calderón, María; Aigrain, Suzanne; Bouvier, Jèrôme; Hillenbrand, Lynne A.; Gutermuth, Robert; Song, Inseok; Turner, Neal; Alencar, Silvia H. P.; Zwintz, Konstanze; Plavchan, Peter; Carpenter, John; Findeisen, Krzysztof; Carey, Sean; Terebey, Susan; Hartmann, Lee; Calvet, Nuria; Teixeira, Paula; Vrba, Frederick J.; Wolk, Scott; Covey, Kevin; Poppenhaeger, Katja; Günther, Hans Moritz; Forbrich, Jan; Whitney, Barbara; Affer, Laura; Herbst, William; Hora, Joseph; Barrado, David; Holtzman, Jon; Marchis, Franck; Wood, Kenneth; Medeiros Guimarães, Marcelo; Lillo Box, Jorge; Gillen, Ed; McQuillan, Amy; Espaillat, Catherine; Allen, Lori; D'Alessio, Paola; Favata, Fabio

2014-04-01

We present the Coordinated Synoptic Investigation of NGC 2264, a continuous 30 day multi-wavelength photometric monitoring campaign on more than 1000 young cluster members using 16 telescopes. The unprecedented combination of multi-wavelength, high-precision, high-cadence, and long-duration data opens a new window into the time domain behavior of young stellar objects. Here we provide an overview of the observations, focusing on results from Spitzer and CoRoT. The highlight of this work is detailed analysis of 162 classical T Tauri stars for which we can probe optical and mid-infrared flux variations to 1% amplitudes and sub-hour timescales. We present a morphological variability census and then use metrics of periodicity, stochasticity, and symmetry to statistically separate the light curves into seven distinct classes, which we suggest represent different physical processes and geometric effects. We provide distributions of the characteristic timescales and amplitudes and assess the fractional representation within each class. The largest category (>20%) are optical "dippers" with discrete fading events lasting ~1-5 days. The degree of correlation between the optical and infrared light curves is positive but weak; notably, the independently assigned optical and infrared morphology classes tend to be different for the same object. Assessment of flux variation behavior with respect to (circum)stellar properties reveals correlations of variability parameters with Hα emission and with effective temperature. Overall, our results point to multiple origins of young star variability, including circumstellar obscuration events, hot spots on the star and/or disk, accretion bursts, and rapid structural changes in the inner disk. Based on data from the Spitzer and CoRoT missions. The CoRoT space mission was developed and is operated by the French space agency CNES, with participation of ESA's RSSD and Science Programmes, Austria, Belgium, Brazil, Germany, and Spain.

Psychological Distress Among Caregivers of Individuals With a Diagnosis of Schizophrenia or Schizoaffective Disorder.

PubMed

Lerner, Debra; Chang, Hong; Rogers, William H; Benson, Carmela; Lyson, Mercedes C; Dixon, Lisa B

2018-02-01

The aim was to quantify caregiver distress among informal caregivers of individuals with schizophrenia or schizoaffective disorder and identify its correlates. From December 2014 through April 2015, ads posted with mental health advocates and the media recruited informal caregivers, age ≥21 years, to complete an online questionnaire. It included the ten-item Perceived Stress Scale (PSS) (0, no distress; 39, highest) and hypothesized distress correlates in four groups: caregiver and care recipient characteristics; caregiver role demands; caregiver social supports; and caregiver cognitive appraisals of caregiving. Three hypotheses were tested: first, distress is significantly related to variables from each group; second, social supports moderate the effects of role demands on distress; and third, cognitive appraisals mediate the effects of role demands on distress. Hypotheses were tested with multiple linear regression equations and structural equation models (SEMs). Of 2,338 Web site "hits," 1,708 individuals consented, 1,398 were eligible, and 1,142 had complete data. Most caregivers were women (83%), white (89%), and college educated (59%), with a mean±SD age of 55.6±13.0. Compared with U.S. norms on the PSS (13.4±6.5), mean caregiver distress was high (18.9±7.1). According to SEMs, variables from each group were associated with distress. Contributing most to greater distress were caregiver health problems, providing frequent caregiving assistance, monitoring medication, having limited social support, and appraising caregiving negatively. Cognitive appraisals mediated the effects of demands on distress. Social support had a significant direct effect only. Caregiver distress was relatively high and related to multiple variables, some of which are potentially modifiable.

Caries risk assessment in schoolchildren - a form based on Cariogram® software

PubMed Central

CABRAL, Renata Nunes; HILGERT, Leandro Augusto; FABER, Jorge; LEAL, Soraya Coelho

2014-01-01

Identifying caries risk factors is an important measure which contributes to best understanding of the cariogenic profile of the patient. The Cariogram® software provides this analysis, and protocols simplifying the method were suggested. Objectives The aim of this study was to determine whether a newly developed Caries Risk Assessment (CRA) form based on the Cariogram® software could classify schoolchildren according to their caries risk and to evaluate relationships between caries risk and the variables in the form. Material and Methods 150 schoolchildren aged 5 to 7 years old were included in this survey. Caries prevalence was obtained according to International Caries Detection and Assessment System (ICDAS) II. Information for filling in the form based on Cariogram® was collected clinically and from questionnaires sent to parents. Linear regression and a forward stepwise multiple regression model were applied to correlate the variables included in the form with the caries risk. Results Caries prevalence, in primary dentition, including enamel and dentine carious lesions was 98.6%, and 77.3% when only dentine lesions were considered. Eighty-six percent of the children were classified as at moderate caries risk. The forward stepwise multiple regression model result was significant (R2=0.904; p<0.00001), showing that the most significant factors influencing caries risk were caries experience, oral hygiene, frequency of food consumption, sugar consumption and fluoride sources. Conclusion The use of the form based on the Cariogram® software enabled classification of the schoolchildren at low, moderate and high caries risk. Caries experience, oral hygiene, frequency of food consumption, sugar consumption and fluoride sources are the variables that were shown to be highly correlated with caries risk. PMID:25466473

Quality of life profile and correlated factors in chronic leg ulcer patients in the mid-west of São Paulo State, Brazil*

PubMed Central

Wachholz, Patrick Alexander; Masuda, Paula Yoshiko; Nascimento, Dejair Caitano; Taira, Cecilia Midori Higashi; Cleto, Norma Gondim

2014-01-01

BACKGROUND Chronic leg ulcer may have an impact on patients' quality of life. OBJECTIVES This study aimed to identify the impact of leg ulcers on patient's quality of life using the Dermatology Life Quality Index and to define the main factors correlated with this perception. METHOD Cross-sectional, non-probabilistic sampling study. We included patients with chronic leg ulcers being treated for at least 3 months. A sociodemographic and clinical survey was conducted to assess the profile of the ulcers. We administered a screening for depressive symptoms and the Dermatology Life Quality Index. We performed a descriptive statistical analysis, chi-square test and Mann-Whitney test for categorical data, Pearson for numeric variables, and multiple regression for categorical data. RESULTS Forty-one patients were assessed. Their mean age was 61.78 years. Venous ulcers (48.8%) were the most prevalent. Seventy-three percent of the sample perceived no impact/low impact on quality of life in the past week, and 26.8% perceived moderate/high impact. A multiple regression analysis identified the causes of lesion, pain related to the ulcers, time of onset, and severity of the depressive symptoms as the variables that had an influence on quality of life. CONCLUSIONS The majority of the sample perceived low or no impact of the condition on the quality of the life. The variables etiology of the lesion (p<0.001), pain related to the ulcers (p=0.001), time of onset (p=0.006), and severity of the depressive symptoms (p<0.001) had an influence on the quality of life, suggesting the need for further studies with more robust designs to confirm the causal relationship between these characteristics and quality of life. PMID:24626651

CSI 2264: simultaneous optical and infrared light curves of young disk-bearing stars in NGC 2264 with CoRoT and Spitzer—evidence for multiple origins of variability

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

Cody, Ann Marie; Stauffer, John; Rebull, Luisa M.

2014-04-01

We present the Coordinated Synoptic Investigation of NGC 2264, a continuous 30 day multi-wavelength photometric monitoring campaign on more than 1000 young cluster members using 16 telescopes. The unprecedented combination of multi-wavelength, high-precision, high-cadence, and long-duration data opens a new window into the time domain behavior of young stellar objects. Here we provide an overview of the observations, focusing on results from Spitzer and CoRoT. The highlight of this work is detailed analysis of 162 classical T Tauri stars for which we can probe optical and mid-infrared flux variations to 1% amplitudes and sub-hour timescales. We present a morphological variabilitymore » census and then use metrics of periodicity, stochasticity, and symmetry to statistically separate the light curves into seven distinct classes, which we suggest represent different physical processes and geometric effects. We provide distributions of the characteristic timescales and amplitudes and assess the fractional representation within each class. The largest category (>20%) are optical 'dippers' with discrete fading events lasting ∼1-5 days. The degree of correlation between the optical and infrared light curves is positive but weak; notably, the independently assigned optical and infrared morphology classes tend to be different for the same object. Assessment of flux variation behavior with respect to (circum)stellar properties reveals correlations of variability parameters with Hα emission and with effective temperature. Overall, our results point to multiple origins of young star variability, including circumstellar obscuration events, hot spots on the star and/or disk, accretion bursts, and rapid structural changes in the inner disk.« less

Factors associated with endodontic flare-ups: a prospective study.

PubMed

Imura, N; Zuolo, M L

1995-09-01

The purpose of this prospective study was to assess the incidence of flare-ups (a severe problem requiring an unscheduled visit and treatment) among patients who received endodontic treatment by the two authors in their respective practices during a period of one year, and also to examine the correlation with pre-operative and operative variables. The results showed an incidence of 1.58% for flare-ups from 1012 endodontically treated teeth. Statistical analysis using the chi-square test (P<0.05) indicated that flare-ups were found to be positively correlated with multiple appointments, retreatment cases, periradicular pain prior to treatment, presence of radiolucent lesions, and patients taking analgesic or anti-inflammatory drugs. In contrast, there was no correlation between flare-up, and age, sex, different arch/tooth groups and the status of the pulp.

Stratification of a cityscape using census and land use variables for inventory of building materials

USGS Publications Warehouse

Rosenfield, G.H.; Fitzpatrick-Lins, K.; Johnson, T.L.

1987-01-01

A cityscape (or any landscape) can be stratified into environmental units using multiple variables of information. For the purposes of sampling building materials, census and land use variables were used to identify similar strata. In the Metropolitan Statistical Area of a cityscape, the census tract is the smallest unit for which census data are summarized and digitized boundaries are available. For purposes of this analysis, census data on total population, total number of housing units, and number of singleunit dwellings were aggregated into variables of persons per square kilometer and proportion of housing units in single-unit dwellings. The level 2 categories of the U.S. Geological Survey's land use and land cover data base were aggregated into variables of proportion of residential land with buildings, proportion of nonresidential land with buildings, and proportion of open land. The cityscape was stratified, from these variables, into environmental strata of Urban Central Business District, Urban Livelihood Industrial Commercial, Urban Multi-Family Residential, Urban Single Family Residential, Non-Urban Suburbanizing, and Non-Urban Rural. The New England region was chosen as a region with commonality of building materials, and a procedure developed for trial classification of census tracts into one of the strata. Final stratification was performed by discriminant analysis using the trial classification and prior probabilities as weights. The procedure was applied to several cities, and the results analyzed by correlation analysis from a field sample of building materials. The methodology developed for stratification of a cityscape using multiple variables has application to many other types of environmental studies, including forest inventory, hydrologic unit management, waste disposal, transportation studies, and other urban studies. Multivariate analysis techniques have recently been used for urban stratification in England. ?? 1987 Annals of Regional Science.

Bon-EV: an improved multiple testing procedure for controlling false discovery rates.

PubMed

Li, Dongmei; Xie, Zidian; Zand, Martin; Fogg, Thomas; Dye, Timothy

2017-01-03

Stability of multiple testing procedures, defined as the standard deviation of total number of discoveries, can be used as an indicator of variability of multiple testing procedures. Improving stability of multiple testing procedures can help to increase the consistency of findings from replicated experiments. Benjamini-Hochberg's and Storey's q-value procedures are two commonly used multiple testing procedures for controlling false discoveries in genomic studies. Storey's q-value procedure has higher power and lower stability than Benjamini-Hochberg's procedure. To improve upon the stability of Storey's q-value procedure and maintain its high power in genomic data analysis, we propose a new multiple testing procedure, named Bon-EV, to control false discovery rate (FDR) based on Bonferroni's approach. Simulation studies show that our proposed Bon-EV procedure can maintain the high power of the Storey's q-value procedure and also result in better FDR control and higher stability than Storey's q-value procedure for samples of large size(30 in each group) and medium size (15 in each group) for either independent, somewhat correlated, or highly correlated test statistics. When sample size is small (5 in each group), our proposed Bon-EV procedure has performance between the Benjamini-Hochberg procedure and the Storey's q-value procedure. Examples using RNA-Seq data show that the Bon-EV procedure has higher stability than the Storey's q-value procedure while maintaining equivalent power, and higher power than the Benjamini-Hochberg's procedure. For medium or large sample sizes, the Bon-EV procedure has improved FDR control and stability compared with the Storey's q-value procedure and improved power compared with the Benjamini-Hochberg procedure. The Bon-EV multiple testing procedure is available as the BonEV package in R for download at https://CRAN.R-project.org/package=BonEV .

Ghrelin, leptin and insulin in cirrhotic children and adolescents: relationship with cirrhosis severity and nutritional status.

PubMed

Dornelles, Cristina T L; Goldani, Helena A S; Wilasco, Maria Inês A; Maurer, Rafael L; Kieling, Carlos O; Porowski, Marilene; Ferreira, Cristina T; Santos, Jorge L; Vieira, Sandra M G; Silveira, Themis R

2013-01-10

Ghrelin, leptin, and insulin concentrations are involved in the control of food intake and they seem to be associated with anorexia-cachexia in cirrhotic patients. The present study aimed to investigate the relationship between the nutritional status and fasting ghrelin, leptin and insulin concentrations in pediatric cirrhotic patients. Thirty-nine patients with cirrhosis and 39 healthy controls aged 0-15 years matched by sex and age were enrolled. Severity of liver disease was assessed by Child-Pugh classification, and Pediatric for End Stage Liver Disease (PELD) or Model for End-stage Liver Disease (MELD) scores. Blood samples were collected from patients and controls to assay total ghrelin, acyl ghrelin, leptin and insulin by using a commercial ELISA kit. Anthropometry parameters used were standard deviation score of height-for-age and triceps skinfold thickness-for-age ratio. A multiple linear regression analysis was used to determine the correlation between dependent and independent variables. Acyl ghrelin was significantly lower in cirrhotic patients than in controls [142 (93-278) pg/mL vs 275 (208-481) pg/mL, P=0.001]. After multiple linear regression analysis, total ghrelin and acyl ghrelin showed an inverse correlation with age; acyl ghrelin was associated with the severity of cirrhosis and des-acyl ghrelin with PELD or MELD scores ≥15. Leptin was positively correlated with gender and anthropometric parameters. Insulin was not associated with any variable. Low acyl ghrelin and high des-acyl ghrelin concentrations were associated with cirrhosis severity, whereas low leptin concentration was associated with undernourishment in children and adolescents with cirrhosis. Copyright © 2012 Elsevier B.V. All rights reserved.

Signal transduction molecules in gliomas of all grades.

PubMed

Ermoian, Ralph P; Kaprealian, Tania; Lamborn, Kathleen R; Yang, Xiaodong; Jelluma, Nannette; Arvold, Nils D; Zeidman, Ruth; Berger, Mitchel S; Stokoe, David; Haas-Kogan, Daphne A

2009-01-01

To interrogate grade II, III, and IV gliomas and characterize the critical effectors within the PI3-kinase pathway upstream and downstream of mTOR. Experimental design Tissues from 87 patients who were treated at UCSF between 1990 and 2004 were analyzed. Twenty-eight grade II, 17 grade III glioma, 26 grade IV gliomas, and 16 non-tumor brain specimens were analyzed. Protein levels were assessed by immunoblots; RNA levels were determined by polymerase chain reaction amplification. To address the multiple comparisons, first an overall analysis was done comparing the four groups using Spearman's Correlation Coefficient. Only if this analysis was statistically significant were individual pairwise comparisons done. Multiple comparison analyses revealed a significant correlation with grade for all variables examined, except phosphorylated-S6. Expression of phosphorylated-4E-BP1, phosphorylated-PKB/Akt, PTEN, TSC1, and TSC2 correlated with grade (P < 0.01 for all). We extended our analyses to ask whether decreases in TSC proteins levels were due to changes in mRNA levels, or due to changes in post-transcriptional alterations. We found significantly lower levels of TSC1 and TSC2 mRNA in GBMs than in grade II gliomas or non-tumor brain (P < 0.01). Expression levels of critical signaling molecules upstream and downstream of mTOR differ between non-tumor brain and gliomas of any grade. The single variable whose expression did not differ between non-tumor brain and gliomas was phosphorylated-S6, suggesting that other protein kinases, in addition to mTOR, contribute significantly to S6 phosphorylation. mTOR provides a rational therapeutic target in gliomas of all grades, and clinical benefit may emerge as mTOR inhibitors are combined with additional agents.

Comparing daily temperature averaging methods: the role of surface and atmosphere variables in determining spatial and seasonal variability

NASA Astrophysics Data System (ADS)

Bernhardt, Jase; Carleton, Andrew M.

2018-05-01

The two main methods for determining the average daily near-surface air temperature, twice-daily averaging (i.e., [Tmax+Tmin]/2) and hourly averaging (i.e., the average of 24 hourly temperature measurements), typically show differences associated with the asymmetry of the daily temperature curve. To quantify the relative influence of several land surface and atmosphere variables on the two temperature averaging methods, we correlate data for 215 weather stations across the Contiguous United States (CONUS) for the period 1981-2010 with the differences between the two temperature-averaging methods. The variables are land use-land cover (LULC) type, soil moisture, snow cover, cloud cover, atmospheric moisture (i.e., specific humidity, dew point temperature), and precipitation. Multiple linear regression models explain the spatial and monthly variations in the difference between the two temperature-averaging methods. We find statistically significant correlations between both the land surface and atmosphere variables studied with the difference between temperature-averaging methods, especially for the extreme (i.e., summer, winter) seasons (adjusted R2 > 0.50). Models considering stations with certain LULC types, particularly forest and developed land, have adjusted R2 values > 0.70, indicating that both surface and atmosphere variables control the daily temperature curve and its asymmetry. This study improves our understanding of the role of surface and near-surface conditions in modifying thermal climates of the CONUS for a wide range of environments, and their likely importance as anthropogenic forcings—notably LULC changes and greenhouse gas emissions—continues.

Functional Multiple-Set Canonical Correlation Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Jung, Kwanghee; Takane, Yoshio; Woodward, Todd S.

2012-01-01

We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the…

[Culture and quality of life assessment in Chinese populations].

PubMed

Xia, Ping; Li, Ning-Xiu; Liu, Chao-Jie; Lü, Yu-Bo; Zhang, Qiang; Ou, Ai-Hua

2010-07-01

To investigate the impact of cultural factors on quality of life (QOL) and to identify appropriate ways of dividing sub-populations for population norm-based quality of life assessment. The WHOQOL-BREF was used as a QOL instrument. Another questionnaire was developed to assess cultural values. A cross-sectional survey was undertaken in 1090 Guangzhou residents, which included 635 respondents from communities and 455 patients who visited outpatient departments of hospitals. Cronbach's a coefficients and item-domain correlation coefficients were calculated to test the reliability and validity of the WHOQOL-BREF, respectively. Student t test, ANOVA and stepwise multiple linear regression analysis were performed to identify the variables that might have an impact on the QOL. Two regression models with and without including cultural variables were constructed, and the extent of impact exerted by the cultural factors was assessed through a comparison of the change of adjusted R square values. A total of 1052 (96%) valid questionnaire were returned. The Cronbach's alpha coefficients of the WHOQOL-BREF ranged from 0.67 to 0.78. Age, education, occupation and family income were correlated with all of the domains of the WHOQOL-BREF. Chronic condition was correlated with physical, psychological, and social relationship domains of the WHOQOL-BREF. Gender was correlated with physical and psychological domains of the WHOQOL-BREF. The multiple regression analysis showed that social and demographic factors contributed to 6.3%, 13.6%, 10.4% and 8.7% of the predicted variances for the physical, psychological, social relationship, and environment domains, respectively. Social support, horizontal collectivism, vertical individualism, escape acceptance, fear of death, health value, supernatural belief had a significant impact on QOL. However, social support was the only one factor that had an impact on all of the four QOL domains. It is necessary to divide sub-cultural populations for population norm-based QOL assessment. Further research is needed to develop a practical approach to the sub-cultural population division.

The use of a combination of instrumental methods to assess change in sensory crispness during storage of a "Honeycrisp" apple breeding family.

PubMed

Chang, Hsueh-Yuan; Vickers, Zata M; Tong, Cindy B S

2018-04-01

Loss of crispness in apple fruit during storage reduces the fruit's fresh sensation and consumer acceptance. Apple varieties that maintain crispness thus have higher potential for longer-term consumer appeal. To efficiently phenotype crispness, several instrumental methods have been tested, but variable results were obtained when different apple varieties were assayed. To extend these studies, we assessed the extent to which instrumental measurements correlate to and predict sensory crispness, with a focus on crispness maintenance. We used an apple breeding family derived from a cross between "Honeycrisp" and "MN1764," which segregates for crispness maintenance. Three types of instrumental measurements (puncture, snapping, and mechanical-acoustic tests) and sensory evaluation were performed on fruit at harvest and after 8 weeks of cold storage. Overall, 20 genotypes from the family and the 2 parents were characterized by 19 force and acoustic measures. In general, crispness was more related to force than to acoustic measures. Force linear distance and maximum force as measured by the mechanical-acoustic test were best correlated with sensory crispness and change in crispness, respectively. The correlations varied by apple genotype. The best multiple linear regression model to predict change in sensory crispness between harvest and storage of fruit of this breeding family incorporated both force and acoustic measures. This work compared the abilities of instrumental tests to predict sensory crispness maintenance of apple fruit. The use of an instrumental method that is highly correlated to sensory crispness evaluation can enhance the efficiency and reduce the cost of measuring crispness for breeding purposes. This study showed that sensory crispness and change in crispness after storage of an apple breeding family were reliably predicted with a combination of instrumental measurements and multiple variable analyses. The strategy potentially can be applied to other apple varieties for more accurate interpretation of crispness maintenance measured instrumentally. © 2018 Wiley Periodicals, Inc.

Quantifying drivers of wild pig movement across multiple spatial and temporal scales.

PubMed

Kay, Shannon L; Fischer, Justin W; Monaghan, Andrew J; Beasley, James C; Boughton, Raoul; Campbell, Tyler A; Cooper, Susan M; Ditchkoff, Stephen S; Hartley, Steve B; Kilgo, John C; Wisely, Samantha M; Wyckoff, A Christy; VerCauteren, Kurt C; Pepin, Kim M

2017-01-01

The movement behavior of an animal is determined by extrinsic and intrinsic factors that operate at multiple spatio-temporal scales, yet much of our knowledge of animal movement comes from studies that examine only one or two scales concurrently. Understanding the drivers of animal movement across multiple scales is crucial for understanding the fundamentals of movement ecology, predicting changes in distribution, describing disease dynamics, and identifying efficient methods of wildlife conservation and management. We obtained over 400,000 GPS locations of wild pigs from 13 different studies spanning six states in southern U.S.A., and quantified movement rates and home range size within a single analytical framework. We used a generalized additive mixed model framework to quantify the effects of five broad predictor categories on movement: individual-level attributes, geographic factors, landscape attributes, meteorological conditions, and temporal variables. We examined effects of predictors across three temporal scales: daily, monthly, and using all data during the study period. We considered both local environmental factors such as daily weather data and distance to various resources on the landscape, as well as factors acting at a broader spatial scale such as ecoregion and season. We found meteorological variables (temperature and pressure), landscape features (distance to water sources), a broad-scale geographic factor (ecoregion), and individual-level characteristics (sex-age class), drove wild pig movement across all scales, but both the magnitude and shape of covariate relationships to movement differed across temporal scales. The analytical framework we present can be used to assess movement patterns arising from multiple data sources for a range of species while accounting for spatio-temporal correlations. Our analyses show the magnitude by which reaction norms can change based on the temporal scale of response data, illustrating the importance of appropriately defining temporal scales of both the movement response and covariates depending on the intended implications of research (e.g., predicting effects of movement due to climate change versus planning local-scale management). We argue that consideration of multiple spatial scales within the same framework (rather than comparing across separate studies post-hoc ) gives a more accurate quantification of cross-scale spatial effects by appropriately accounting for error correlation.

Evidence of forward-backward multiplicity correlation at SPS energy

NASA Astrophysics Data System (ADS)

Bhoumik, Gopa; Bhattacharyya, Swarnapratim; Deb, Argha; Ghosh, Dipak

In this paper, a detailed study of two-particle rapidity correlation has been presented by measuring the dynamical fluctuation variable σc2 in forward and backward pseudo-rapidity window of shower particles produced in the relativistic heavy ion collision, 16O-AgBr interactions at 60AGeV and 32S-AgBr interactions at 200AGeV. Variations of σc2 with rapidity gap between forward and backward zones and with the width of each zone have been studied. For both cases, σc2 increase with increasing either width of the zone or gap between the zones. Our findings show the presence of strong long-range correlation. Comparison of experimental results with MC-RAND events confirms the present correlation to be dynamical in nature. We have also compared our results with FRITIOF and UrQMD events. Such events also show the presence of correlation, but found to fail to reproduce the experimental results both quantitatively and qualitatively. Strength of correlation is dependent on the centrality of collision for experimental events, it decreases with centrality.

Using ground penetrating radar to assess the variability of snow water equivalent and melt in a mixed canopy forest, Northern Colorado

NASA Astrophysics Data System (ADS)

Webb, Ryan W.

2017-09-01

Snow is an important environmental variable in headwater systems that controls hydrological processes such as streamflow, groundwater recharge, and evapotranspiration. These processes will be affected by both the amount of snow available for melt and the rate at which it melts. Snow water equivalent (SWE) and snowmelt are known to vary within complex subalpine terrain due to terrain and canopy influences. This study assesses this variability during the melt season using ground penetrating radar to survey multiple plots in northwestern Colorado near a snow telemetry (SNOTEL) station. The plots include south aspect and flat aspect slopes with open, coniferous (subalpine fir, Abies lasiocarpa and engelman spruce, Picea engelmanii), and deciduous (aspen, populous tremuooides) canopy cover. Results show the high variability for both SWE and loss of SWE during spring snowmelt in 2014. The coefficient of variation for SWE tended to increase with time during snowmelt whereas loss of SWE remained similar. Correlation lengths for SWE were between two and five meters with melt having correlation lengths between two and four meters. The SNOTEL station regularly measured higher SWE values relative to the survey plots but was able to reasonably capture the overall mean loss of SWE during melt. Ground Penetrating Radar methods can improve future investigations with the advantage of non-destructive sampling and the ability to estimate depth, density, and SWE.

Cardiovascular Disease Death Before Age 65 in 168 Countries Correlated Statistically with Biometrics, Socioeconomic Status, Tobacco, Gender, Exercise, Macronutrients, and Vitamin K

PubMed Central

Agutter, Paul S

2016-01-01

Background Nutrition researchers recently recognized that deficiency of vitamin K2 (menaquinone: MK-4–MK-13) is widespread and contributes to cardiovascular disease (CVD). The deficiency of vitamin K2 or vitamin K inhibition with warfarin leads to calcium deposition in the arterial blood vessels. Methods Using publicly available sources, we collected food commodity availability data and derived nutrient profiles including vitamin K2 for people from 168 countries. We also collected female and male cohort data on early death from CVD (ages 15–64 years), insufficient physical activity, tobacco, biometric CVD risk markers, socioeconomic risk factors for CVD, and gender. The outcome measures included (1) univariate correlations of early death from CVD with each risk factor, (2) a multiple regression-derived formula relating early death from CVD (dependent variable) to macronutrient profile, vitamin K1 and K2 and other risk factors (independent variables), (3) for each risk factor appearing in the multiple regression formula, the portion of CVD risk attributable to that factor, and (4) similar univariate and multivariate analyses of body mass index (BMI), fasting blood sugar (FBS) (simulated from diabetes prevalence), systolic blood pressure (SBP), and cholesterol/ HDL-C ratio (simulated from serum cholesterol) (dependent variables) and dietary and other risk factors (independent variables). Results Female and male cohorts in countries that have vitamin K2 < 5µg per 2000 kcal/day per capita (n = 70) had about 2.2 times the rate of early CVD deaths as people in countries with > 24 µg/day of vitamin K2 per 2000 kcal/day (n = 72). A multiple regression-derived formula relating early death from CVD to dietary nutrients and other risk factors accounted for about 50% of the variance between cohorts in early CVD death. The attributable risks of the variables in the CVD early death formula were: too much alcohol (0.38%), too little vitamin K2 (6.95%), tobacco (6.87%), high blood pressure (9.01%), air pollution (9.15%), early childhood death (3.64%), poverty (7.66%), and male gender (6.13%). Conclusions Worldwide dietary vitamin K2 data derived from food commodities add much understanding to the analysis of CVD risk factors and the etiology of CVD. Vitamin K2 in food products should be systematically quantified. Public health programs should be considered to increase the intake of vitamin K2-containing fermented plant foods such as sauerkraut, miso, and natto. PMID:27688985

Cardiovascular Disease Death Before Age 65 in 168 Countries Correlated Statistically with Biometrics, Socioeconomic Status, Tobacco, Gender, Exercise, Macronutrients, and Vitamin K.

PubMed

Cundiff, David K; Agutter, Paul S

2016-08-24

Nutrition researchers recently recognized that deficiency of vitamin K2 (menaquinone: MK-4-MK-13) is widespread and contributes to cardiovascular disease (CVD). The deficiency of vitamin K2 or vitamin K inhibition with warfarin leads to calcium deposition in the arterial blood vessels. Using publicly available sources, we collected food commodity availability data and derived nutrient profiles including vitamin K2 for people from 168 countries. We also collected female and male cohort data on early death from CVD (ages 15-64 years), insufficient physical activity, tobacco, biometric CVD risk markers, socioeconomic risk factors for CVD, and gender. The outcome measures included (1) univariate correlations of early death from CVD with each risk factor, (2) a multiple regression-derived formula relating early death from CVD (dependent variable) to macronutrient profile, vitamin K1 and K2 and other risk factors (independent variables), (3) for each risk factor appearing in the multiple regression formula, the portion of CVD risk attributable to that factor, and (4) similar univariate and multivariate analyses of body mass index (BMI), fasting blood sugar (FBS) (simulated from diabetes prevalence), systolic blood pressure (SBP), and cholesterol/ HDL-C ratio (simulated from serum cholesterol) (dependent variables) and dietary and other risk factors (independent variables). Female and male cohorts in countries that have vitamin K2 < 5µg per 2000 kcal/day per capita (n = 70) had about 2.2 times the rate of early CVD deaths as people in countries with > 24 µg/day of vitamin K2 per 2000 kcal/day (n = 72). A multiple regression-derived formula relating early death from CVD to dietary nutrients and other risk factors accounted for about 50% of the variance between cohorts in early CVD death. The attributable risks of the variables in the CVD early death formula were: too much alcohol (0.38%), too little vitamin K2 (6.95%), tobacco (6.87%), high blood pressure (9.01%), air pollution (9.15%), early childhood death (3.64%), poverty (7.66%), and male gender (6.13%). Worldwide dietary vitamin K2 data derived from food commodities add much understanding to the analysis of CVD risk factors and the etiology of CVD. Vitamin K2 in food products should be systematically quantified. Public health programs should be considered to increase the intake of vitamin K2-containing fermented plant foods such as sauerkraut, miso, and natto.

Social embeddedness and economic opportunism: a game situation.

PubMed

Sakalaki, Maria; Fousiani, Kyriaki

2012-06-01

According to Evolutionary Game Theory, multiple exchanges with partners are necessary to foster cooperation. Multiple exchanges with partners tend to enhance the good experience of the partners and the predictability of their behaviour and should therefore increase cooperativeness. This study explored whether social embeddedness, or the preference for close and stable social relationships, a variable which tends to increase multiple exchanges, is associated with more cooperative attitudes; and whether social embeddedness increases cooperative behavior towards unknown partners in a game situation. The first study, with 169 undergraduates, indicated that social embeddedness (preference for close and durable social relations) was negatively associated with opportunistic attitudes. The second study had a sample of 60 undergraduates playing a Trust Game with unknown partners and showed that self-reported social embeddedness was positively correlated with scores for cooperative economic behavior towards the partners. These results highlight the relationships of social embeddedness with cooperative attitudes and behaviour.

Multiple Sclerosis and Catastrophic Health Expenditure in Iran.

PubMed

Juyani, Yaser; Hamedi, Dorsa; Hosseini Jebeli, Seyede Sedighe; Qasham, Maryam

2016-09-01

There are many disabling medical conditions which can result in catastrophic health expenditure. Multiple Sclerosis is one of the most costly medical conditions through the world which encounter families to the catastrophic health expenditures. This study aims to investigate on what extent Multiple sclerosis patients face catastrophic costs. This study was carried out in Ahvaz, Iran (2014). The study population included households that at least one of their members suffers from MS. To analyze data, Logit regression model was employed by using the default software STATA12. 3.37% of families were encountered with catastrophic costs. Important variables including brand of drug, housing, income and health insurance were significantly correlated with catastrophic expenditure. This study suggests that although a small proportion of MS patients met the catastrophic health expenditure, mechanisms that pool risk and cost (e.g. health insurance) are required to protect them and improve financial and access equity in health care.

Cognitive status in patients with multiple sclerosis in Lanzarote.

PubMed

Pérez-Martín, María Yaiza; Eguia-Del Río, Pablo; González-Platas, Montserrat; Jiménez-Sosa, Alejandro

2016-01-01

Cognitive impairment is a common feature in multiple sclerosis affecting ~43%-72% of patients, which involves cognitive functions such as memory, processing speed, attention, and executive function. The aim of this study was to describe the extent and pattern of the involvement of cognitive impairment and psychological status in all patients with multiple sclerosis on a small Spanish island. In all, 70 patients and 56 healthy controls were included in the study between February 2013 and May 2013. All participants were assessed using the Brief Repeatable Battery of Neuropsychological Test. The patients also completed instruments to evaluate the presence of fatigue, perceived cognitive dysfunction, and symptoms of anxiety and depression. All procedures were performed in a single session. Cognitive impairment, defined as a score <1.5 standard deviation on two subtests of the battery, was present in 35% of the participants. The most frequently affected domain was working memory, followed by verbal memory and processing speed. Disease duration showed a moderate correlation with visuospatial memory and processing speed. The Expanded Disability Status Scale score correlated with verbal and processing speed. Verbal memory was correlated with depression symptoms and fatigue. Cognitive impairment was present in 35% of the study population. The most affected domains were working memory and verbal memory. Working memory and verbal fluency deficit are independent factors of disease evolution. Cognitive decline is related to clinical variables and psychological measures such as fatigue or depression but not to anxiety.

Cognitive status in patients with multiple sclerosis in Lanzarote

PubMed Central

Pérez-Martín, María Yaiza; Eguia-del Río, Pablo; González-Platas, Montserrat; Jiménez-Sosa, Alejandro

2016-01-01

Objectives Cognitive impairment is a common feature in multiple sclerosis affecting ~43%–72% of patients, which involves cognitive functions such as memory, processing speed, attention, and executive function. The aim of this study was to describe the extent and pattern of the involvement of cognitive impairment and psychological status in all patients with multiple sclerosis on a small Spanish island. Patients and methods In all, 70 patients and 56 healthy controls were included in the study between February 2013 and May 2013. All participants were assessed using the Brief Repeatable Battery of Neuropsychological Test. The patients also completed instruments to evaluate the presence of fatigue, perceived cognitive dysfunction, and symptoms of anxiety and depression. All procedures were performed in a single session. Results Cognitive impairment, defined as a score <1.5 standard deviation on two subtests of the battery, was present in 35% of the participants. The most frequently affected domain was working memory, followed by verbal memory and processing speed. Disease duration showed a moderate correlation with visuospatial memory and processing speed. The Expanded Disability Status Scale score correlated with verbal and processing speed. Verbal memory was correlated with depression symptoms and fatigue. Conclusion Cognitive impairment was present in 35% of the study population. The most affected domains were working memory and verbal memory. Working memory and verbal fluency deficit are independent factors of disease evolution. Cognitive decline is related to clinical variables and psychological measures such as fatigue or depression but not to anxiety. PMID:27418825

Valid statistical approaches for analyzing sholl data: Mixed effects versus simple linear models.

PubMed

Wilson, Machelle D; Sethi, Sunjay; Lein, Pamela J; Keil, Kimberly P

2017-03-01

The Sholl technique is widely used to quantify dendritic morphology. Data from such studies, which typically sample multiple neurons per animal, are often analyzed using simple linear models. However, simple linear models fail to account for intra-class correlation that occurs with clustered data, which can lead to faulty inferences. Mixed effects models account for intra-class correlation that occurs with clustered data; thus, these models more accurately estimate the standard deviation of the parameter estimate, which produces more accurate p-values. While mixed models are not new, their use in neuroscience has lagged behind their use in other disciplines. A review of the published literature illustrates common mistakes in analyses of Sholl data. Analysis of Sholl data collected from Golgi-stained pyramidal neurons in the hippocampus of male and female mice using both simple linear and mixed effects models demonstrates that the p-values and standard deviations obtained using the simple linear models are biased downwards and lead to erroneous rejection of the null hypothesis in some analyses. The mixed effects approach more accurately models the true variability in the data set, which leads to correct inference. Mixed effects models avoid faulty inference in Sholl analysis of data sampled from multiple neurons per animal by accounting for intra-class correlation. Given the widespread practice in neuroscience of obtaining multiple measurements per subject, there is a critical need to apply mixed effects models more widely. Copyright © 2017 Elsevier B.V. All rights reserved.

Neural variability, or lack thereof

PubMed Central

Masquelier, Timothée

2013-01-01

We do not claim that the brain is completely deterministic, and we agree that noise may be beneficial in some cases. But we suggest that neuronal variability may be often overestimated, due to uncontrolled internal variables, and/or the use of inappropriate reference times. These ideas are not new, but should be re-examined in the light of recent experimental findings: trial-to-trial variability is often correlated across neurons, across trials, greater for higher-order neurons, and reduced by attention, suggesting that “intrinsic” sources of noise can only account for a minimal part of it. While it is obviously difficult to control for all internal variables, the problem of reference time can be largely avoided by recording multiple neurons at the same time, and looking at statistical structures in relative latencies. These relative latencies have another major advantage: they are insensitive to the variability that is shared across neurons, which is often a significant part of the total variability. Thus, we suggest that signal-to-noise ratios in the brain may be much higher than usually thought, leading to reactive systems, economic in terms of number of neurons, and energy efficient. PMID:23444270

Hydraulic Tomography and the Curse of Storativity

NASA Astrophysics Data System (ADS)

Cirpka, O. A.; Li, W.; Englert, A.

2006-12-01

Pumping tests are among the most common techniques for hydrogeological site investigation. Their traditional analysis is based on fitting analytical expressions to measured time series of drawdown. These expressions were derived for homogeneous conditions, whereas all natural aquifers are heterogeneous. The mentioned conceptual inconsistency complicates the hydrogeological interpretation of the obtained coefficients. In particularly, it has been shown that the heterogeneity of transmissivity is aliased to variability in the estimated storativity. In hydraulic tomography, multiple pumping tests are jointly analyzed. The hydraulic parameters to be estimated are allowed to fluctuate in space. For regularization, a geostatistical smoothness criterion may be introduced. Thus, the inversion results in the most likely spatial distribution of parameters that is consistent with the drawdown measurements and follows a predefined geostatistical model. Applying the restricted maximum likelihood approach, the parameters of the prior covariance function (i.e., the prior variance and correlation length) can be inferred from the data as well. We have applied the quasi-linear geostatistical approach of inverse modeling to drawdown measurements of multiple, overlapping pumping tests performed at the test site Krauthausen near Jülich, Germany. To reduce the computational costs, we have characterized the drawdown curves by their temporal moments. In the estimation of the geostatistical parameters, the measurement error of heads turned out to be of vital importance. The less we trust the data, the larger is the estimated correlation length, resulting in a more uniform distribution of transmissivity. Similar to conventional pumping test analysis, the data analysis point to a high variability of storativity although the properties making up storativity are known to be only mildly heterogeneous. We conjecture that the unresolved small-scale spatial variability of conductivity is mapped to variability of storativity. This is rather unfortunate since reliable field data on the variability of storativity are missing. The study underscores that structural information is difficult to extract from hydraulic data alone. Information on length scales and major deterministic features may be gained by geophysical surveying, even if rock-laws directly relating geophysical to hydraulic properties are considered unreliable.

Entropy-Based Analysis and Bioinformatics-Inspired Integration of Global Economic Information Transfer

PubMed Central

An, Sungbae; Kwon, Young-Kyun; Yoon, Sungroh

2013-01-01

The assessment of information transfer in the global economic network helps to understand the current environment and the outlook of an economy. Most approaches on global networks extract information transfer based mainly on a single variable. This paper establishes an entirely new bioinformatics-inspired approach to integrating information transfer derived from multiple variables and develops an international economic network accordingly. In the proposed methodology, we first construct the transfer entropies (TEs) between various intra- and inter-country pairs of economic time series variables, test their significances, and then use a weighted sum approach to aggregate information captured in each TE. Through a simulation study, the new method is shown to deliver better information integration compared to existing integration methods in that it can be applied even when intra-country variables are correlated. Empirical investigation with the real world data reveals that Western countries are more influential in the global economic network and that Japan has become less influential following the Asian currency crisis. PMID:23300959

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.

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.

Entropy-based analysis and bioinformatics-inspired integration of global economic information transfer.

PubMed

Kim, Jinkyu; Kim, Gunn; An, Sungbae; Kwon, Young-Kyun; Yoon, Sungroh

2013-01-01

The assessment of information transfer in the global economic network helps to understand the current environment and the outlook of an economy. Most approaches on global networks extract information transfer based mainly on a single variable. This paper establishes an entirely new bioinformatics-inspired approach to integrating information transfer derived from multiple variables and develops an international economic network accordingly. In the proposed methodology, we first construct the transfer entropies (TEs) between various intra- and inter-country pairs of economic time series variables, test their significances, and then use a weighted sum approach to aggregate information captured in each TE. Through a simulation study, the new method is shown to deliver better information integration compared to existing integration methods in that it can be applied even when intra-country variables are correlated. Empirical investigation with the real world data reveals that Western countries are more influential in the global economic network and that Japan has become less influential following the Asian currency crisis.

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).

Periodic optical variability of radio-detected ultracool dwarfs

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

Harding, L. K.; Golden, A.; Singh, Navtej

2013-12-20

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

Relation of Environmental characteristics to the composition of aquatic assemblages along a gradient of urban land use in New Jersey, 1996-98

USGS Publications Warehouse

Kennen, Jonathan G.; Ayers, Mark A.

2002-01-01

Community data from 36 watersheds were used to evaluate the response of fish, invertebrate, and algal assemblages in New Jersey streams to environmental characteristics along a gradient of urban land use that ranged from 3 to 96 percent. Aquatic assemblages were sampled at 36 sites during 1996-98, and more than 400 environmental attributes at multiple spatial scales were summarized. Data matrices were reduced to 43, 170, and 103 species of fish, invertebrates, and algae, respectively, by means of a predetermined joint frequency and relative abundance approach. White sucker (Catostomus commersoni) and Tessellated darter (Etheostoma olmstedi) were the most abundant fishes, accounting for more than 20 and 17 percent, respectively, of the mean abundance. Net-spinning caddisflies (Hydropsychidae) were the most commonly occurring benthic invertebrates and were found at all but one of the 36 sampling sites. Blue-green (for example, Calothrix sp. and Oscillatoria sp.) and green (for example, Protoderma viride) algae were the most widely distrib-uted algae; however, more than 81 percent of the algal taxa collected were diatoms. Principal-component and correlation analyses were used to reduce the dimensionality of the environmental data. Multiple linear regression analysis of extracted ordination axes then was used to develop models that expressed effects of increasing urban land use on the structure of aquatic assemblages. Significant environmental variables identified by using multiple linear regression analysis then were included in a direct gradient analysis. Partial canonical correspondence analysis of relativized abundance data was used to restrict further the effects of residual natural variability, and to identify relations among the environmental variables and the structure of fish, invertebrate, and algal assemblages along an urban land-use gradient. Results of this approach, combined with the results of the multiple linear regression analyses, were used to identify human population density (311-37,594 persons/km2), amount and type of impervious surface cover (0.12-1,350 km2), nutrient concentrations (for example, 0.01-0.29 mg/L of phosphorus), hydrologic instability (for example, 100-8,955 ft3/s for 2-year peak flow), the amount of forest and wetlands in a basin (0.01-6.25 km2), and substrate quality (0-87 percent cobble substrate) as variables that are highly correlated with aquatic-assemblage structure. Species distributions in ordination space clearly indicate that tolerant species are more abundant in the streams impaired by urbanization and sensitive taxa are more closely associated with the least impaired basins. The distinct differences in aquatic assemblages along the urban land-use gradient demonstrate the deleterious effects of urbanization on assemblage structure and indicate that conserving landscape attributes that mitigate anthropogenic influences (for example, stormwater-management practices emphasizing infiltration and preservation of existing forests, wetlands, and riparian corridors) will help to maintain the relative abundance of sensitive taxa. Complementary multiple linear regression models indicate that aquatic community indices were correlated with many of the anthropogenic factors that were found to be significant along the urban land-use gradient. These indices appear to be effective in differentiating the moderately and severely impaired streams from the minimally impaired streams. Evaluation of disturbance thresholds for aquatic assemblages indicates that moderate to severe impairment is detectable in New Jersey streams when impervious surface cover in the drainage basin reaches approximately 18 percent.

Multi-mesh gear dynamics program evaluation and enhancements

NASA Technical Reports Server (NTRS)

Boyd, L. S.; Pike, J.

1985-01-01

A multiple mesh gear dynamics computer program was continually developed and modified during the last four years. The program can handle epicyclic gear systems as well as single mesh systems with internal, buttress, or helical tooth forms. The following modifications were added under the current funding: variable contact friction, planet cage and ring gear rim flexibility options, user friendly options, dynamic side bands, a speed survey option and the combining of the single and multiple mesh options into one general program. The modified program was evaluated by comparing calculated values to published test data and to test data taken on a Hamilton Standard turboprop reduction gear-box. In general, the correlation between the test data and the analytical data is good.

Periodontal inflamed surface area as a novel numerical variable describing periodontal conditions

PubMed Central

2017-01-01

Purpose A novel index, the periodontal inflamed surface area (PISA), represents the sum of the periodontal pocket depth of bleeding on probing (BOP)-positive sites. In the present study, we evaluated correlations between PISA and periodontal classifications, and examined PISA as an index integrating the discrete conventional periodontal indexes. Methods This study was a cross-sectional subgroup analysis of data from a prospective cohort study investigating the association between chronic periodontitis and the clinical features of ankylosing spondylitis. Data from 84 patients without systemic diseases (the control group in the previous study) were analyzed in the present study. Results PISA values were positively correlated with conventional periodontal classifications (Spearman correlation coefficient=0.52; P<0.01) and with periodontal indexes, such as BOP and the plaque index (PI) (r=0.94; P<0.01 and r=0.60; P<0.01, respectively; Pearson correlation test). Porphyromonas gingivalis (P. gingivalis) expression and the presence of serum P. gingivalis antibodies were significant factors affecting PISA values in a simple linear regression analysis, together with periodontal classification, PI, bleeding index, and smoking, but not in the multivariate analysis. In the multivariate linear regression analysis, PISA values were positively correlated with the quantity of current smoking, PI, and severity of periodontal disease. Conclusions PISA integrates multiple periodontal indexes, such as probing pocket depth, BOP, and PI into a numerical variable. PISA is advantageous for quantifying periodontal inflammation and plaque accumulation. PMID:29093989

A Robust and Multi-Weighted Approach to Estimating Topographically Correlated Tropospheric Delays in Radar Interferograms

PubMed Central

Zhu, Bangyan; Li, Jiancheng; Chu, Zhengwei; Tang, Wei; Wang, Bin; Li, Dawei

2016-01-01

Spatial and temporal variations in the vertical stratification of the troposphere introduce significant propagation delays in interferometric synthetic aperture radar (InSAR) observations. Observations of small amplitude surface deformations and regional subsidence rates are plagued by tropospheric delays, and strongly correlated with topographic height variations. Phase-based tropospheric correction techniques assuming a linear relationship between interferometric phase and topography have been exploited and developed, with mixed success. Producing robust estimates of tropospheric phase delay however plays a critical role in increasing the accuracy of InSAR measurements. Meanwhile, few phase-based correction methods account for the spatially variable tropospheric delay over lager study regions. Here, we present a robust and multi-weighted approach to estimate the correlation between phase and topography that is relatively insensitive to confounding processes such as regional subsidence over larger regions as well as under varying tropospheric conditions. An expanded form of robust least squares is introduced to estimate the spatially variable correlation between phase and topography by splitting the interferograms into multiple blocks. Within each block, correlation is robustly estimated from the band-filtered phase and topography. Phase-elevation ratios are multiply- weighted and extrapolated to each persistent scatter (PS) pixel. We applied the proposed method to Envisat ASAR images over the Southern California area, USA, and found that our method mitigated the atmospheric noise better than the conventional phase-based method. The corrected ground surface deformation agreed better with those measured from GPS. PMID:27420066

A Robust and Multi-Weighted Approach to Estimating Topographically Correlated Tropospheric Delays in Radar Interferograms.

PubMed

Zhu, Bangyan; Li, Jiancheng; Chu, Zhengwei; Tang, Wei; Wang, Bin; Li, Dawei

2016-07-12

Spatial and temporal variations in the vertical stratification of the troposphere introduce significant propagation delays in interferometric synthetic aperture radar (InSAR) observations. Observations of small amplitude surface deformations and regional subsidence rates are plagued by tropospheric delays, and strongly correlated with topographic height variations. Phase-based tropospheric correction techniques assuming a linear relationship between interferometric phase and topography have been exploited and developed, with mixed success. Producing robust estimates of tropospheric phase delay however plays a critical role in increasing the accuracy of InSAR measurements. Meanwhile, few phase-based correction methods account for the spatially variable tropospheric delay over lager study regions. Here, we present a robust and multi-weighted approach to estimate the correlation between phase and topography that is relatively insensitive to confounding processes such as regional subsidence over larger regions as well as under varying tropospheric conditions. An expanded form of robust least squares is introduced to estimate the spatially variable correlation between phase and topography by splitting the interferograms into multiple blocks. Within each block, correlation is robustly estimated from the band-filtered phase and topography. Phase-elevation ratios are multiply- weighted and extrapolated to each persistent scatter (PS) pixel. We applied the proposed method to Envisat ASAR images over the Southern California area, USA, and found that our method mitigated the atmospheric noise better than the conventional phase-based method. The corrected ground surface deformation agreed better with those measured from GPS.

Makeup of the genetic correlation between milk production traits using genome-wide single nucleotide polymorphism information.

PubMed

van Binsbergen, R; Veerkamp, R F; Calus, M P L

2012-04-01

The correlated responses between traits may differ depending on the makeup of genetic covariances, and may differ from the predictions of polygenic covariances. Therefore, the objective of the present study was to investigate the makeup of the genetic covariances between the well-studied traits: milk yield, fat yield, protein yield, and their percentages in more detail. Phenotypic records of 1,737 heifers of research farms in 4 different countries were used after homogenizing and adjusting for management effects. All cows had a genotype for 37,590 single nucleotide polymorphisms (SNP). A bayesian stochastic search variable selection model was used to estimate the SNP effects for each trait. About 0.5 to 1.0% of the SNP had a significant effect on 1 or more traits; however, the SNP without a significant effect explained most of the genetic variances and covariances of the traits. Single nucleotide polymorphism correlations differed from the polygenic correlations, but only 10 regions were found with an effect on multiple traits; in 1 of these regions the DGAT1 gene was previously reported with an effect on multiple traits. This region explained up to 41% of the variances of 4 traits and explained a major part of the correlation between fat yield and fat percentage and contributes to asymmetry in correlated response between fat yield and fat percentage. Overall, for the traits in this study, the infinitesimal model is expected to be sufficient for the estimation of the variances and covariances. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Relationship between parent–infant attachment and parental satisfaction with supportive nursing care

PubMed Central

Ghadery-Sefat, Akram; Abdeyazdan, Zahra; Badiee, Zohreh; Zargham-Boroujeni, Ali

2016-01-01

Background: Parent–infant attachment is an important factor in accepting parenting role, accelerating infant survival, and adjusting to the environment outside the uterus. Since family supportive interventions can strengthen the parent–infant caring relationship, this study sought to investigate the relationship between mother–infant attachment and satisfaction of the mothers with the supportive nursing care received in the neonatal intensive care unit (NICU). Materials and Methods: In this descriptive–correlational study, 210 mothers with premature infants who were hospitalized in the NICUs affiliated to Isfahan Medical University hospitals took part. The data were collected via Maternal Postnatal Attachment Scale and researcher's self-tailored questionnaire based on Nurse Parent Support Tool. Pearson correlation coefficient and multiple linear regressions were used to analyze the collected data. Results: The results showed that the overall score of mother–infant attachment and the overall score of maternal satisfaction correlated with a correlation coefficient of r = 0.195. Also, the overall score of mother–infant attachment and mothers’ satisfaction scores in the emotional, communicative-informative, and self-confidence domains correlated with correlation coefficients of r = 0.182, r = 0.0.189, and r = 0.0.304, respectively. The results of multiple regression analysis revealed that about 15% of changes in the dependent variable (mother–infant attachment) could be explained by different dimensions of mothers’ satisfaction. Conclusions: The results of the study showed that mother–infant attachment improved by increasing mothers’ satisfaction of supportive nursing care. Therefore, it seems necessary to increase maternal satisfaction through given nursing care support, in order to promote mother–infant attachment. PMID:26985225

Relationship between parent-infant attachment and parental satisfaction with supportive nursing care.

PubMed

Ghadery-Sefat, Akram; Abdeyazdan, Zahra; Badiee, Zohreh; Zargham-Boroujeni, Ali

2016-01-01

Parent-infant attachment is an important factor in accepting parenting role, accelerating infant survival, and adjusting to the environment outside the uterus. Since family supportive interventions can strengthen the parent-infant caring relationship, this study sought to investigate the relationship between mother-infant attachment and satisfaction of the mothers with the supportive nursing care received in the neonatal intensive care unit (NICU). In this descriptive-correlational study, 210 mothers with premature infants who were hospitalized in the NICUs affiliated to Isfahan Medical University hospitals took part. The data were collected via Maternal Postnatal Attachment Scale and researcher's self-tailored questionnaire based on Nurse Parent Support Tool. Pearson correlation coefficient and multiple linear regressions were used to analyze the collected data. The results showed that the overall score of mother-infant attachment and the overall score of maternal satisfaction correlated with a correlation coefficient of r = 0.195. Also, the overall score of mother-infant attachment and mothers' satisfaction scores in the emotional, communicative-informative, and self-confidence domains correlated with correlation coefficients of r = 0.182, r = 0.0.189, and r = 0.0.304, respectively. The results of multiple regression analysis revealed that about 15% of changes in the dependent variable (mother-infant attachment) could be explained by different dimensions of mothers' satisfaction. The results of the study showed that mother-infant attachment improved by increasing mothers' satisfaction of supportive nursing care. Therefore, it seems necessary to increase maternal satisfaction through given nursing care support, in order to promote mother-infant attachment.

Improved workflow for quantification of left ventricular volumes and mass using free-breathing motion corrected cine imaging.

PubMed

Cross, Russell; Olivieri, Laura; O'Brien, Kendall; Kellman, Peter; Xue, Hui; Hansen, Michael

2016-02-25

Traditional cine imaging for cardiac functional assessment requires breath-holding, which can be problematic in some situations. Free-breathing techniques have relied on multiple averages or real-time imaging, producing images that can be spatially and/or temporally blurred. To overcome this, methods have been developed to acquire real-time images over multiple cardiac cycles, which are subsequently motion corrected and reformatted to yield a single image series displaying one cardiac cycle with high temporal and spatial resolution. Application of these algorithms has required significant additional reconstruction time. The use of distributed computing was recently proposed as a way to improve clinical workflow with such algorithms. In this study, we have deployed a distributed computing version of motion corrected re-binning reconstruction for free-breathing evaluation of cardiac function. Twenty five patients and 25 volunteers underwent cardiovascular magnetic resonance (CMR) for evaluation of left ventricular end-systolic volume (ESV), end-diastolic volume (EDV), and end-diastolic mass. Measurements using motion corrected re-binning were compared to those using breath-held SSFP and to free-breathing SSFP with multiple averages, and were performed by two independent observers. Pearson correlation coefficients and Bland-Altman plots tested agreement across techniques. Concordance correlation coefficient and Bland-Altman analysis tested inter-observer variability. Total scan plus reconstruction times were tested for significant differences using paired t-test. Measured volumes and mass obtained by motion corrected re-binning and by averaged free-breathing SSFP compared favorably to those obtained by breath-held SSFP (r = 0.9863/0.9813 for EDV, 0.9550/0.9685 for ESV, 0.9952/0.9771 for mass). Inter-observer variability was good with concordance correlation coefficients between observers across all acquisition types suggesting substantial agreement. Both motion corrected re-binning and averaged free-breathing SSFP acquisition and reconstruction times were shorter than breath-held SSFP techniques (p < 0.0001). On average, motion corrected re-binning required 3 min less than breath-held SSFP imaging, a 37% reduction in acquisition and reconstruction time. The motion corrected re-binning image reconstruction technique provides robust cardiac imaging that can be used for quantification that compares favorably to breath-held SSFP as well as multiple average free-breathing SSFP, but can be obtained in a fraction of the time when using cloud-based distributed computing reconstruction.

Cognitive Agility Measurement in a Complex Environment

DTIC Science & Technology

2017-04-01

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

The relationship between foot pain, anthropometric variables and footwear among older people.

PubMed

Paiva de Castro, Alessandra; Rebelatto, José Rubens; Aurichio, Thaís Rabiatti

2010-01-01

To verify the prevalence of pain among older people when wearing shoes, and the relationships between foot pain, high-heeled shoes and anthropometric variables. Both feet of 227 older women and 172 older men were evaluated with respect to anthropometric variables, arch index and foot posture index. The participants were also asked about the presence of foot pain while wearing high-heeled shoes. The data were analyzed using the Chi-square test, Pearson's correlation, MANOVA, multiple regression analysis, t test, and analysis of probability. The prevalence of foot pain when wearing shoes was high and was associated with the female gender, however wearing high-heeled shoes was not associated with pain. The women with foot pain presented larger values for the circumferences of the metatarsal heads and the instep (after normalization with the foot length) than those without pain. The men with pain did not present different measurements from those without pain.

A Methodological Review of Meditation Research

PubMed Central

Thomas, John W.; Cohen, Marc

2014-01-01

Despite over 50 years of research into the states of consciousness induced by various meditation practices, no clear neurophysiological signatures of these states have been found. Much of this failure can be attributed to the narrow range of variables examined in most meditation studies, with the focus being restricted to a search for correlations between neurophysiological measures and particular practices, without documenting the content and context of these practices. We contend that more meaningful results can be obtained by expanding the methodological paradigm to include multiple domains including: the cultural setting (“the place”), the life situation of the meditator (“the person”), details of the particular meditation practice (‘the practice’), and the state of consciousness of the meditator (“the phenomenology”). Inclusion of variables from all these domains will improve the ability to predict the psychophysiological variables (“the psychophysiology”) associated with specific meditation states and thus explore the mysteries of human consciousness. PMID:25071607

Lifestyle factors and dietary intake of Iranian postgraduate students in Universiti Putra Malaysia (UPM)

PubMed Central

Zarei, Maryam; Taib, Mohd Nasir Mohd; Zarei, Fatemeh

2013-01-01

Background: A student’s lifestyle can change notably in a foreign country. The objective of this study was to determine factors associated with the body weight status of Iranian postgraduate students in Universiti Putra Malaysia (UPM) 2009. Methods: A self-administered questionnaire was administered to 210 Iranian postgraduate students at UPM. Anthropometric factors also were measured using standard procedures. Body mass index (BMI) and waist-to-hip ratio (WHR) also were calculated. The chi-squared test, Spearman’s rho, and the Pearson product-moment correlation coefficient were used to determine the associations between the variables that were studied. Multiple linear regression analysis was used to measure the amount of influence a predictor variable had on a outcome variable. Results: There was no significant correlation between nutritional knowledge (P > 0.05), weight-management knowledge (P > 0.05), and smoking (P > 0.05) and BMI. There were statistically significant correlations between gender (P < 0.01), physical activity (P < 0.05), protein (P < 0.01), carbohydrate (P < 0.01), fat (P < 0.01), fiber (P < 0.01), vitamin C (P < 0.05), calcium (P < 0.01), and iron (P < 0.01) and BMI. There were also relationships between body fat (P < 0.01), waist circumference (P < 0.01), hip circumference (P < 0.01) and WHR (P < 0.01) and BMI. Conclusion: Our findings showed the need for a nutrition promotion program for the Iranian students to help them change their negative food habits and improve their lifestyles. PMID:26120404

Personality Domains, Duration of Untreated Psychosis, Functioning, and Symptom Severity in First-Episode Psychosis

PubMed Central

Compton, Michael T.; Bakeman, Roger; Alolayan, Yazeed; Balducci, Pierfrancesco Maria; Bernardini, Francesco; Broussard, Beth; Crisafio, Anthony; Cristofaro, Sarah; Amar, Patrick; Johnson, Stephanie; Wan, Claire Ramsay

2015-01-01

Objectives Early-course psychotic disorders have been extensively studied in terms of phenomenology, but little is known about the influence of personality traits on clinical features of first-episode psychosis. The aim of this study was to explore how the “big five” personality domains (neuroticism, extraversion, openness, agreeableness, and conscientiousness) are associated with treatment delay (duration of untreated psychosis, DUP), functioning, and positive and negative symptom severity. Methods Data for these analyses were obtained from 104 participants enrolled from psychiatric inpatient units in Atlanta, Georgia, between August 2008 and March 2011. The NEO Five-Factor Inventory (NEO-FFI) was used to assess personality domains, and all other variables were measured in a standardized and rigorous manner using psychometrically sound instruments. Correlational analyses and multiple linear regressions were carried out to examine the strength of associations between variables of interest. Results Findings indicated that except for openness, all the other personality variables contributed to some extent to the variance in DUP. Conscientiousness was positively correlated with functioning. Agreeableness was independently negatively associated with positive symptom severity and extraversion was independently negatively correlated with negative symptom severity. Conclusions We report the first evidence suggesting that DUP is in part driven by personality domains. Functioning and symptom severity are also associated with those domains. Personality should be taken into account in order to better understand the phenomenology of early-course psychotic disorders as well as treatment-seeking behaviors. PMID:26209478

Correlations Between Clinical Judgement and Learning Style Preferences of Nursing Students in the Simulation Room.

PubMed

Hallin, Karin; Haggstrom, Marie; Backstrom, Britt; Kristiansen, Lisbeth Porskrog

2015-09-28

Health care educators account for variables affecting patient safety and are responsible for developing the highly complex process of education planning. Clinical judgement is a multidimensional process, which may be affected by learning styles. The aim was to explore three specific hypotheses to test correlations between nursing students' team achievements in clinical judgement and emotional, sociological and physiological learning style preferences. A descriptive cross-sectional study was conducted with Swedish university nursing students in 2012-2013. Convenience sampling was used with 60 teams with 173 nursing students in the final semester of a three-year Bachelor of Science in nursing programme. Data collection included questionnaires of personal characteristics, learning style preferences, determined by the Dunn and Dunn Productivity Environmental Preference Survey, and videotaped complex nursing simulation scenarios. Comparison with Lasater Clinical Judgement Rubric and Non-parametric analyses were performed. Three significant correlations were found between the team achievements and the students' learning style preferences: significant negative correlation with 'Structure' and 'Kinesthetic' at the individual level, and positive correlation with the 'Tactile' variable. No significant correlations with students' 'Motivation', 'Persistence', 'Wish to learn alone' and 'Wish for an authoritative person present' were seen. There were multiple complex interactions between the tested learning style preferences and the team achievements of clinical judgement in the simulation room, which provides important information for the becoming nurses. Several factors may have influenced the results that should be acknowledged when designing further research. We suggest conducting mixed methods to determine further relationships between team achievements, learning style preferences, cognitive learning outcomes and group processes.

The Association Between Sexual Satisfaction and Body Image in Women

PubMed Central

Pujols, Yasisca; Meston, Cindy M.; Seal, Brooke N.

2010-01-01

Introduction Although sexual functioning has been linked to sexual satisfaction, it only partially explains the degree to which women report being sexually satisfied. Other factors include quality of life, relational variables, and individual factors such as body image. Of the few studies that have investigated the link between body image and sexual satisfaction, most have considered body image to be a single construct and have shown mixed results. Aim The present study assessed multiple body image variables in order to better understand which aspects of body image influence multiple domains of sexual satisfaction, including sexual communication, compatibility, contentment, personal concern, and relational concern in a community sample of women. Methods Women between the ages of 18 and 49 years in sexual relationships (N = 154) participated in an Internet survey that assessed sexual functioning, five domains of sexual satisfaction, and several body image variables. Main Outcome Measures Body image variables included the sexual attractiveness, weight concern, and physical condition subscales of the Body Esteem Scale, the appearance-based subscale of the Cognitive Distractions During Sexual Activity Scale, and body mass index. Total score of the Sexual Satisfaction Scale for Women was the main outcome measure. Sexual functioning was measured by a modified Female Sexual Function Index. Results Consistent with expectations, correlations indicated significant positive relationships between sexual functioning, sexual satisfaction, and all body image variables. A multiple regression analysis revealed that sexual satisfaction was predicted by high body esteem and low frequency of appearance-based distracting thoughts during sexual activity, even after controlling for sexual functioning status. Conclusion Several aspects of body image, including weight concern, physical condition, sexual attractiveness, and thoughts about the body during sexual activity predict sexual satisfaction in women. The findings suggest that women who experience low sexual satisfaction may benefit from treatments that target these specific aspects of body image. PMID:19968771

Frontiers of Two-Dimensional Correlation Spectroscopy. Part 1. New concepts and noteworthy developments

NASA Astrophysics Data System (ADS)

Noda, Isao

2014-07-01

A comprehensive survey review of new and noteworthy developments, which are advancing forward the frontiers in the field of 2D correlation spectroscopy during the last four years, is compiled. This review covers books, proceedings, and review articles published on 2D correlation spectroscopy, a number of significant conceptual developments in the field, data pretreatment methods and other pertinent topics, as well as patent and publication trends and citation activities. Developments discussed include projection 2D correlation analysis, concatenated 2D correlation, and correlation under multiple perturbation effects, as well as orthogonal sample design, predicting 2D correlation spectra, manipulating and comparing 2D spectra, correlation strategy based on segmented data blocks, such as moving-window analysis, features like determination of sequential order and enhanced spectral resolution, statistical 2D spectroscopy using covariance and other statistical metrics, hetero-correlation analysis, and sample-sample correlation technique. Data pretreatment operations prior to 2D correlation analysis are discussed, including the correction for physical effects, background and baseline subtraction, selection of reference spectrum, normalization and scaling of data, derivatives spectra and deconvolution technique, and smoothing and noise reduction. Other pertinent topics include chemometrics and statistical considerations, peak position shift phenomena, variable sampling increments, computation and software, display schemes, such as color coded format, slice and power spectra, tabulation, and other schemes.

A study of certain correlates of job satisfaction among judicial personnel, in a district of Western Maharashtra

PubMed Central

Patel, Kriti A.; Rajderkar, Shekhar S.; Naik, Jayashree D.; Behere, Vivek S.

2014-01-01

Background: In present scenario, the legal profession has gained utmost importance, which makes the job of a lawyer the most challenging, with lots of mental and physical strain. The rewards can be great, but so are the pressures. High job demands lead to imbalance between what is expected and what is received (job dissatisfaction) which, in turn, leads to job strains. So, the present study focused on the impact of certain variables on job satisfaction of the judiciaries. Objectives: To study the level of job satisfaction among judicial personnel; to identify the impact of job level (hierarchy) in the experience of job satisfaction; to find the gender difference (if any) for the level of job satisfaction; and to examine the pattern of relationship of certain variables with job satisfaction. Materials and Methods: A cross-sectional study was conducted in 1 year duration, in total 965 judicial personnel of different courts in the district of Sangli, which involved data collection using predesigned proforma. A scale, having 15 different independent predictors was used as a validated screening tool, to calculate their job satisfaction score. The most contributing variable and its correlation with job satisfaction was found by stepwise multiple regression and correlation analysis using SPSS Version-16. Results and Conclusion: Out of the total, Class I judiciaries were 692 (71.7%). A majority (71.4%) of the study subjects were male. Overall mean job satisfaction score was 5.38 ± 2.7. Twenty-three percent females, compared with only 9% males, had low job satisfaction (P < 0.5). The best predictor of job satisfaction in males and females was emotional exhaustion (β = 0.191) and conflicts between values and practice (β = 0.252), respectively. Higher is the job satisfaction score, lesser the level of job satisfaction. The findings of the study revealed that job satisfaction was found to be significantly (P < 0.0005) and positively correlated with all the variables in the study. PMID:25568601

A Bayesian joint probability modeling approach for seasonal forecasting of streamflows at multiple sites

NASA Astrophysics Data System (ADS)

Wang, Q. J.; Robertson, D. E.; Chiew, F. H. S.

2009-05-01

Seasonal forecasting of streamflows can be highly valuable for water resources management. In this paper, a Bayesian joint probability (BJP) modeling approach for seasonal forecasting of streamflows at multiple sites is presented. A Box-Cox transformed multivariate normal distribution is proposed to model the joint distribution of future streamflows and their predictors such as antecedent streamflows and El Niño-Southern Oscillation indices and other climate indicators. Bayesian inference of model parameters and uncertainties is implemented using Markov chain Monte Carlo sampling, leading to joint probabilistic forecasts of streamflows at multiple sites. The model provides a parametric structure for quantifying relationships between variables, including intersite correlations. The Box-Cox transformed multivariate normal distribution has considerable flexibility for modeling a wide range of predictors and predictands. The Bayesian inference formulated allows the use of data that contain nonconcurrent and missing records. The model flexibility and data-handling ability means that the BJP modeling approach is potentially of wide practical application. The paper also presents a number of statistical measures and graphical methods for verification of probabilistic forecasts of continuous variables. Results for streamflows at three river gauges in the Murrumbidgee River catchment in southeast Australia show that the BJP modeling approach has good forecast quality and that the fitted model is consistent with observed data.

Multiple sclerosis and employment: Associations of psychological factors and work instability.

PubMed

Wicks, Charlotte Rose; Ward, Karl; Stroud, Amanda; Tennant, Alan; Ford, Helen L

2016-10-12

People with multiple sclerosis often stop working earlier than expected. Psychological factors may have an impact on job retention. Investigation may inform interventions to help people stay in work. To investigate the associations between psychological factors and work instability in people with multiple sclerosis. A multi-method, 2-phased study. Focus groups were held to identify key themes. Questionnaire packs using validated scales of the key themes were completed at baseline and at 8-month follow-up. Four key psychological themes emerged. Out of 208 study subjects 57.2% reported medium/high risk of job loss, with marginal changes at 8 months. Some psychological variables fluctuated significantly, e.g. depression fell from 24.6% to 14.5%. Work instability and anxiety and depression were strongly correlated (χ2 p < 0.001). Those with probable depression at baseline had 7.1 times increased odds of medium/high work instability, and baseline depression levels also predicted later work instability (Hosmer-Lemeshow test 0.899; Nagelkerke R Square 0.579). Psychological factors fluctuated over the 8-month follow-up period. Some psychological variables, including anxiety and depression, were significantly associated with, and predictive of, work instability. Longitudinal analysis should further identify how these psychological attributes impact on work instability and potential job loss in the longer term.

Internal predictors of burnout in psychiatric nurses: An Indian study

PubMed Central

Chakraborty, Rudraprosad; Chatterjee, Arunima; Chaudhury, Suprakash

2012-01-01

Background: Research has not adequately focused on the issue of burnout in Psychiatric nurses, despite the fact that they suffer considerable stress in their work. Till date no study has been conducted on burnout among psychiatric nurses in India. Further, there is a particular lack of research in internal variables predicting burnout in them. Aims: To determine whether there are any internal psychological factors relevant to burnout in psychiatric nurses in India. Materials and Methods: We recruited 101 psychiatric nurses scoring less than two in General Health Questionnaire, version 12 (GHQ-12) from two psychiatric hospitals after obtaining informed consent. All subjects filled up a sociodemographic data sheet along with global adjustment scale, emotional maturity scale, PGI general well-being scale, locus of control scale, and Copenhagen burnout inventory (CBI). Correlations between burnout and sociodemographic/clinical variables were done by Pearson's r or Spearman's rho. Signi ficant variables were entered in a stepwise multiple linear regression analysis with total burnout score as dependent variable. Results: Age, duration of total period of nursing, prior military training, locus of control, sense of general well-being, adjustment capabilities, and emotional maturity had significant relation with burnout. Of them, emotional maturity was the most significant protective factors against burnout along with adjustment capabilities, sense of physical well-being, and military training in decreasing significance. Together they explained 41% variation in total burnout score which is significant at <0.001 level. An internal locus of control was inversely correlated with burnout, but failed to predict it in regression analysis. Conclusion: Emotional maturity, adjustability, sense of general physical well-being as well as prior military training significantly predicted lower burnout. Of them, emotional maturity was the most important predictor. Internal locus of control was also correlated with lower burnout. PMID:24250044

Intra-event variability of Escherichia coli and total suspended solids in urban stormwater runoff.

PubMed

McCarthy, D T; Hathaway, J M; Hunt, W F; Deletic, A

2012-12-15

Sediment levels are important for environmental health risk assessments of surface water bodies, while faecal pollution can introduce significant public health risks for users of these systems. Urban stormwater is one of the largest sources of contaminants to surface waters, yet the fate and transport of these contaminants (especially those microbiological) have received little attention in the literature. Stormwater runoff from five urbanized catchments were monitored for pathogen indicator bacteria and total suspended solids in two developed countries. Multiple discrete samples were collected during each storm event, allowing an analysis of intra-event characteristics such as initial concentration, peak concentration, maximum rate of change, and relative confidence interval. The data suggest that a catchment's area influences pollutant characteristics, as larger catchments have more complex stormwater infrastructure and more variable pollutant sources. The variability of total suspended solids for many characteristics was similar to Escherichia coli, indicating that the variability of E. coli may not be substantially higher than that of other pollutants as initially speculated. Further, variations in E. coli appeared to be more commonly correlated to antecedent climate, while total suspended solids were more highly correlated to rainfall/runoff characteristics. This emphasizes the importance of climate on microbial persistence and die off in urban systems. Discrete intra-event concentrations of total suspended solids and, to a lesser extent E. coli, were correlated to flow, velocity, and rainfall intensity (adjusted by time of concentrations). Concentration changes were found to be best described by adjusted rainfall intensity, as shown by other researchers. This study has resulted in an increased understanding of the magnitude of intra-event variations of total suspended solids and E. coli and what physical and climatic parameters influence these variations. Copyright © 2012 Elsevier Ltd. All rights reserved.

The relationship of lithology and watershed characteristics to fine sediment deposition in streams of the Oregon coast range.

PubMed

Sable, K A; Wohl, E

2006-05-01

Lithology is one of many factors influencing the amount, grain size distribution, and location of fine sediment deposition on the bed of mountain stream channels. In the Oregon Coast Range, 18 pool-riffle stream reaches with similar slope and intact riparian area and relatively unaffected by logjams were surveyed for assessment of fine sediment deposition. Half of the streams were in watersheds underlain by relatively erodible sandstone. The other half were underlain by a more resistant basalt. Channel morphology, hydraulic variables, particle size, relative pool volume of fine sediment (V*), and wood characteristics were measured in the streams. A significantly higher amount of fine sediment was deposited in the sandstone channels than in the basalt channels, as indicated by V*. Grab samples of sediment from pools also were significantly finer grained in the sandstone channels. Geographic information systems (GIS) software was used to derive several variables that might correlate with fine sediment deposition. These variables were combined with those derived from field data to create multiple linear regression models to be used for further exploration of the type and relative influence of factors affecting fine sediment deposition. Lithology appeared to be significant in some of these models, but usually was not the primary driver. The results from these models indicate that V* at the reach scale is best explained by stream power per unit area and by the volume of wood perpendicular to the flow per channel area (R(2) = 0.46). Findings show that V* is best explained using only watershed scale variables, including negative correlations with relief ratio and basin precipitation index, and positive correlations with maximum slope and circularity.

[Development of weight-estimation formulae for the bedridden elderly requiring care].

PubMed

Oonishi, Reiko; Fujii, Kouji; Tsuda, Hiroko; Imai, Katsumi

2012-01-01

Bedridden elderly persons requiring care need special body-weight measurement implements, and body-weighting assumes more difficult if they live at their own homes. Therefore, we tried to design a new weight-estimation formulae using various anthropometric variables. The subjects were 33 male and 132 female elderly inpatients certified to be at care level 4 or 5. The body composition included height, body weight, arm circumference, triceps skinfold thickness, subscapular skinfold thickness, calf circumference, and waist circumference. We studied the correlation between the body weight and each anthropometric variable and age. In men, the highest correlation with body weight was shown by waist circumference (r=0.891, p<0.0001), followed by age (r=0.779, p<0.0001) and calf circumference (r=0.614, p<0.0001). The variables that showed the highest correlation with body weight in women were waist circumference (r=0.806, p<0.0001), followed by triceps skinfold thickness (r=0.723, p<0.0001) and arm circumference (r=0.662, p<0.0001). The weight estimation formulae were obtained by multiple regression analysis. Formulae for men: body weight=0.660×waist circumference (cm)+0.702×calf circumference (cm)+0.096×age (years)-26.917 (R(2)=0.862, p<0.001); formulae for women: body weight=0.315×waist circumference (cm)+0.684×arm circumference (cm)+0.183×height (cm)-28.788 (R(2)=0.836, p<0.001). We successfully developed gender-specific weight-estimation formulae with high coefficients of determination. The results suggest that waist circumference, which is an index of visceral fat, is an effective anthropometric variable to estimate the body weight of bedridden elderly patients requiring care.

Describing rainfall in northern Australia using multiple climate indices

NASA Astrophysics Data System (ADS)

Wilks Rogers, Cassandra Denise; Beringer, Jason

2017-02-01

Savanna landscapes are globally extensive and highly sensitive to climate change, yet the physical processes and climate phenomena which affect them remain poorly understood and therefore poorly represented in climate models. Both human populations and natural ecosystems are highly susceptible to precipitation variation in these regions due to the effects on water and food availability and atmosphere-biosphere energy fluxes. Here we quantify the relationship between climate phenomena and historical rainfall variability in Australian savannas and, in particular, how these relationships changed across a strong rainfall gradient, namely the North Australian Tropical Transect (NATT). Climate phenomena were described by 16 relevant climate indices and correlated against precipitation from 1900 to 2010 to determine the relative importance of each climate index on seasonal, annual and decadal timescales. Precipitation trends, climate index trends and wet season characteristics have also been investigated using linear statistical methods. In general, climate index-rainfall correlations were stronger in the north of the NATT where annual rainfall variability was lower and a high proportion of rainfall fell during the wet season. This is consistent with a decreased influence of the Indian-Australian monsoon from the north to the south. Seasonal variation was most strongly correlated with the Australian Monsoon Index, whereas yearly variability was related to a greater number of climate indices, predominately the Tasman Sea and Indonesian sea surface temperature indices (both of which experienced a linear increase over the duration of the study) and the El Niño-Southern Oscillation indices. These findings highlight the importance of understanding the climatic processes driving variability and, subsequently, the importance of understanding the relationships between rainfall and climatic phenomena in the Northern Territory in order to project future rainfall patterns in the region.

Chronic low back pain in patients with systemic lupus erythematosus: prevalence and predictors of back muscle strength and its correlation with disability.

PubMed

Cezarino, Raíssa Sudré; Cardoso, Jefferson Rosa; Rodrigues, Kedma Neves; Magalhães, Yasmin Santana; Souza, Talita Yokoy de; Mota, Lícia Maria Henrique da; Bonini-Rocha, Ana Clara; McVeigh, Joseph; Martins, Wagner Rodrigues

To determine the prevalence of Chronic Low Back Pain and predictors of Back Muscle Strength in patients with Systemic Lupus Erythematosus. Cross-sectional study. Ninety-six ambulatory patients with lupus were selected by non-probability sampling and interviewed and tested during medical consultation. The outcomes measurements were: Point prevalence of chronic low back pain, Oswestry Disability Index, Tampa Scale of Kinesiophobia, Fatigue Severity Scale and maximal voluntary isometric contractions of handgrip and of the back muscles. Correlation coefficient and multiple linear regression were used in statistical analysis. Of the 96 individuals interviewed, 25 had chronic low back pain, indicating a point prevalence of 26% (92% women). The correlation between the Oswestry Index and maximal voluntary isometric contraction of the back muscles was r=-0.4, 95% CI [-0.68; -0.01] and between the maximal voluntary isometric contraction of handgrip and of the back muscles was r=0.72, 95% CI [0.51; 0.88]. The regression model presented the highest value of R 2 being observed when maximal voluntary isometric contraction of the back muscles was tested with five independent variables (63%). In this model handgrip strength was the only predictive variable (β=0.61, p=0.001). The prevalence of chronic low back pain in individuals with systemic lupus erythematosus was 26%. The maximal voluntary isometric contraction of the back muscles was 63% predicted by five variables of interest, however, only the handgrip strength was a statistically significant predictive variable. The maximal voluntary isometric contraction of the back muscles presented a linear relation directly proportional to handgrip and inversely proportional to Oswestry Index i.e. stronger back muscles are associated with lower disability scores. Copyright © 2017. Published by Elsevier Editora Ltda.

Internal predictors of burnout in psychiatric nurses: An Indian study.

PubMed

Chakraborty, Rudraprosad; Chatterjee, Arunima; Chaudhury, Suprakash

2012-07-01

Research has not adequately focused on the issue of burnout in Psychiatric nurses, despite the fact that they suffer considerable stress in their work. Till date no study has been conducted on burnout among psychiatric nurses in India. Further, there is a particular lack of research in internal variables predicting burnout in them. To determine whether there are any internal psychological factors relevant to burnout in psychiatric nurses in India. We recruited 101 psychiatric nurses scoring less than two in General Health Questionnaire, version 12 (GHQ-12) from two psychiatric hospitals after obtaining informed consent. All subjects filled up a sociodemographic data sheet along with global adjustment scale, emotional maturity scale, PGI general well-being scale, locus of control scale, and Copenhagen burnout inventory (CBI). Correlations between burnout and sociodemographic/clinical variables were done by Pearson's r or Spearman's rho. Signi ficant variables were entered in a stepwise multiple linear regression analysis with total burnout score as dependent variable. Age, duration of total period of nursing, prior military training, locus of control, sense of general well-being, adjustment capabilities, and emotional maturity had significant relation with burnout. Of them, emotional maturity was the most significant protective factors against burnout along with adjustment capabilities, sense of physical well-being, and military training in decreasing significance. Together they explained 41% variation in total burnout score which is significant at <0.001 level. An internal locus of control was inversely correlated with burnout, but failed to predict it in regression analysis. Emotional maturity, adjustability, sense of general physical well-being as well as prior military training significantly predicted lower burnout. Of them, emotional maturity was the most important predictor. Internal locus of control was also correlated with lower burnout.

Relationship between dietary protein intake and the changes in creatinine clearance and glomerular cross-sectional area in patients with IgA nephropathy.

PubMed

Wada, Toshikazu; Nakao, Toshiyuki; Matsumoto, Hiroshi; Okada, Tomonari; Nagaoka, Yume; Iwasawa, Hideaki; Gondo, Asako; Niwata, Ami; Kanno, Yoshihiko

2015-08-01

Dietary protein intake (PI) induces glomerular hyperfiltration and reduced dietary PI can be effective in preserving kidney function. However, there is limited information regarding the relationship between dietary PI and glomerular histological changes in chronic kidney disease. We investigated the relationship between changes in dietary PI and both the changes in creatinine clearance and glomerular histomorphometry in adult patients with IgA nephropathy (IgAN). A total of 24 consecutive adult patients with biopsy-confirmed IgAN were enrolled and glomerular histomorphometric variables and clinical variables were investigated. The main clinical variables were differences in creatinine clearance (Ccr) (dCcr) and in PI (dPI) which were calculated by subtracting PI and Ccr values in patients on a controlled diet during hospitalization for kidney biopsy from the respective values in patients on daily diets as outpatients. These values of PI were estimated from urinary urea excretion measured by 24-h urine collection. The main renal histomorphometric variable was glomerular tuft area (GTA) (μm(2)). dCcr positively correlated with dPI (r = 0.726, P < 0.001). GTA correlated positively with dPI (r = 0.556, P = 0.013). Multiple regression analysis showed that dPI was independently associated with both dCcr and GTA. Additionally, GTA positively correlated with dietary PI as outpatients (r = 0.457, P = 0.043). Changes in dietary PI were associated with the changes in glomerular filtration rate. Furthermore, histomorphometric findings suggested that a greater dietary PI can affect the glomerular size at the time of the initial diagnostic biopsy for IgAN.

Self-monitoring urinary salt excretion in adults: A novel education program for restricting dietary salt intake

PubMed Central

YASUTAKE, KENICHIRO; SAWANO, KAYOKO; YAMAGUCHI, SHOKO; SAKAI, HIROKO; AMADERA, HATSUMI; TSUCHIHASHI, TAKUYA

2011-01-01

This study aimed to examine the usefulness of the self-monitoring of urinary salt excretion for educating individuals about the risk of excessive dietary salt intake. The subjects were 30 volunteers (15 men and 15 women) not consuming anti-hypertensive medication. The subjects measured urinary salt excretion at home for 4 weeks using a self-monitoring device. Blood pressure (BP), anthropometric variables and nutritional variables (by a dietary-habits questionnaire) were measured before and after the measurement of urinary salt excretion. Statistical analyses were performed, including paired t-tests, Chi-square test, Pearson’s product moment correlation coefficient and multiple linear regression analysis. In all subjects, the average urinary salt excretion over 4 weeks was 8.05±1.61 g/day and the range (maximum-minimum value) was 5.58±2.15 g/day. Salt excretion decreased significantly in weeks 3 and 4 (P<0.05 and P<0.01, respectively). Diastolic BP decreased from 77.7±14.3 (at baseline) to 74.3±13.3 after 4 weeks (P<0.05), while systolic BP and anthropometric variables remained unchanged. Nutrition surveys indicated that energy intake was correlated with salt intake both before and after the measurements; changes in both variables during the observation period were correlated (r=0.40, P<0.05). The percentage of subjects who were aware of the restriction in dietary salt intake increased from 47 to 90%. In conclusion, daily monitoring of the amount of urinary salt excretion using a self-monitoring device appears to be an effective educational tool for improving the quality of life of healthy adults. PMID:22977549

Self-monitoring urinary salt excretion in adults: A novel education program for restricting dietary salt intake.

PubMed

Yasutake, Kenichiro; Sawano, Kayoko; Yamaguchi, Shoko; Sakai, Hiroko; Amadera, Hatsumi; Tsuchihashi, Takuya

2011-07-01

This study aimed to examine the usefulness of the self-monitoring of urinary salt excretion for educating individuals about the risk of excessive dietary salt intake. The subjects were 30 volunteers (15 men and 15 women) not consuming anti-hypertensive medication. The subjects measured urinary salt excretion at home for 4 weeks using a self-monitoring device. Blood pressure (BP), anthropometric variables and nutritional variables (by a dietary-habits questionnaire) were measured before and after the measurement of urinary salt excretion. Statistical analyses were performed, including paired t-tests, Chi-square test, Pearson's product moment correlation coefficient and multiple linear regression analysis. In all subjects, the average urinary salt excretion over 4 weeks was 8.05±1.61 g/day and the range (maximum-minimum value) was 5.58±2.15 g/day. Salt excretion decreased significantly in weeks 3 and 4 (P<0.05 and P<0.01, respectively). Diastolic BP decreased from 77.7±14.3 (at baseline) to 74.3±13.3 after 4 weeks (P<0.05), while systolic BP and anthropometric variables remained unchanged. Nutrition surveys indicated that energy intake was correlated with salt intake both before and after the measurements; changes in both variables during the observation period were correlated (r=0.40, P<0.05). The percentage of subjects who were aware of the restriction in dietary salt intake increased from 47 to 90%. In conclusion, daily monitoring of the amount of urinary salt excretion using a self-monitoring device appears to be an effective educational tool for improving the quality of life of healthy adults.

Multichannel microformulators for massively parallel machine learning and automated design of biological experiments

NASA Astrophysics Data System (ADS)

Wikswo, John; Kolli, Aditya; Shankaran, Harish; Wagoner, Matthew; Mettetal, Jerome; Reiserer, Ronald; Gerken, Gregory; Britt, Clayton; Schaffer, David

Genetic, proteomic, and metabolic networks describing biological signaling can have 102 to 103 nodes. Transcriptomics and mass spectrometry can quantify 104 different dynamical experimental variables recorded from in vitro experiments with a time resolution approaching 1 s. It is difficult to infer metabolic and signaling models from such massive data sets, and it is unlikely that causality can be determined simply from observed temporal correlations. There is a need to design and apply specific system perturbations, which will be difficult to perform manually with 10 to 102 externally controlled variables. Machine learning and optimal experimental design can select an experiment that best discriminates between multiple conflicting models, but a remaining problem is to control in real time multiple variables in the form of concentrations of growth factors, toxins, nutrients and other signaling molecules. With time-division multiplexing, a microfluidic MicroFormulator (μF) can create in real time complex mixtures of reagents in volumes suitable for biological experiments. Initial 96-channel μF implementations control the exposure profile of cells in a 96-well plate to different temporal profiles of drugs; future experiments will include challenge compounds. Funded in part by AstraZeneca, NIH/NCATS HHSN271201600009C and UH3TR000491, and VIIBRE.

The Heterogeneity in Retrieved Relations between the Personality Trait ‘Harm Avoidance’ and Gray Matter Volumes Due to Variations in the VBM and ROI Labeling Processing Settings

PubMed Central

Van Schuerbeek, Peter; Baeken, Chris; De Mey, Johan

2016-01-01

Concerns are raising about the large variability in reported correlations between gray matter morphology and affective personality traits as ‘Harm Avoidance’ (HA). A recent review study (Mincic 2015) stipulated that this variability could come from methodological differences between studies. In order to achieve more robust results by standardizing the data processing procedure, as a first step, we repeatedly analyzed data from healthy females while changing the processing settings (voxel-based morphology (VBM) or region-of-interest (ROI) labeling, smoothing filter width, nuisance parameters included in the regression model, brain atlas and multiple comparisons correction method). The heterogeneity in the obtained results clearly illustrate the dependency of the study outcome to the opted analysis settings. Based on our results and the existing literature, we recommended the use of VBM over ROI labeling for whole brain analyses with a small or intermediate smoothing filter (5-8mm) and a model variable selection step included in the processing procedure. Additionally, it is recommended that ROI labeling should only be used in combination with a clear hypothesis and that authors are encouraged to report their results uncorrected for multiple comparisons as supplementary material to aid review studies. PMID:27096608

A rotor optimization using regression analysis

NASA Technical Reports Server (NTRS)

Giansante, N.

1984-01-01

The design and development of helicopter rotors is subject to the many design variables and their interactions that effect rotor operation. Until recently, selection of rotor design variables to achieve specified rotor operational qualities has been a costly, time consuming, repetitive task. For the past several years, Kaman Aerospace Corporation has successfully applied multiple linear regression analysis, coupled with optimization and sensitivity procedures, in the analytical design of rotor systems. It is concluded that approximating equations can be developed rapidly for a multiplicity of objective and constraint functions and optimizations can be performed in a rapid and cost effective manner; the number and/or range of design variables can be increased by expanding the data base and developing approximating functions to reflect the expanded design space; the order of the approximating equations can be expanded easily to improve correlation between analyzer results and the approximating equations; gradients of the approximating equations can be calculated easily and these gradients are smooth functions reducing the risk of numerical problems in the optimization; the use of approximating functions allows the problem to be started easily and rapidly from various initial designs to enhance the probability of finding a global optimum; and the approximating equations are independent of the analysis or optimization codes used.

A New Metric for Land-Atmosphere Coupling Strength: Applications on Observations and Modeling

NASA Astrophysics Data System (ADS)

Tang, Q.; Xie, S.; Zhang, Y.; Phillips, T. J.; Santanello, J. A., Jr.; Cook, D. R.; Riihimaki, L.; Gaustad, K.

2017-12-01

A new metric is proposed to quantify the land-atmosphere (LA) coupling strength and is elaborated by correlating the surface evaporative fraction and impacting land and atmosphere variables (e.g., soil moisture, vegetation, and radiation). Based upon multiple linear regression, this approach simultaneously considers multiple factors and thus represents complex LA coupling mechanisms better than existing single variable metrics. The standardized regression coefficients quantify the relative contributions from individual drivers in a consistent manner, avoiding the potential inconsistency in relative influence of conventional metrics. Moreover, the unique expendable feature of the new method allows us to verify and explore potentially important coupling mechanisms. Our observation-based application of the new metric shows moderate coupling with large spatial variations at the U.S. Southern Great Plains. The relative importance of soil moisture vs. vegetation varies by location. We also show that LA coupling strength is generally underestimated by single variable methods due to their incompleteness. We also apply this new metric to evaluate the representation of LA coupling in the Accelerated Climate Modeling for Energy (ACME) V1 Contiguous United States (CONUS) regionally refined model (RRM). This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-734201

What Influences How Patients Rate Their Hospital After Total Knee Arthroplasty?

PubMed

Chughtai, Morad; Jauregui, Julio J; Mistry, Jaydev B; Elmallah, Randa K; Diedrich, Aloise M; Bonutti, Peter M; Delanois, Ronald; Mont, Michael A

2016-04-01

There is increasing pressure from Centers for Medicare and Medicaid Services (CMS) to report quality measures for all hospitalizations. These quality measures are determined based on results from satisfaction surveys, such as Press Ganey® (PG) (Press Ganey® Performance Solutions, Wakefield, Massachusetts). Included in this particular survey element are questions regarding staff, including nurses and doctors, as well as items such as pain control. The results of these surveys will dictate the amount doctors are compensated for their services. Therefore, this study was undertaken to evaluate the effect of treating orthopaedists and nurses, as well as pain control, on PG surveys in patients who underwent total knee arthroplasty (TKA). Specifically, we aimed to ascertain the effect of these factors on how post-TKA patients perceive: 1) their orthopaedist, and 2) their overall surgical experience. We queried the Press Ganey® Database for all patients who underwent a TKA at our institution between November 2009 and January 2015. A weighted mean of question domains was utilized since each had multiple questions. In order to assess if pain management influences orthopaedist perception, a correlation analysis was performed between pain control and perception. In order to assess the influence of pain management on surgical experience, we performed a correlation analysis between pain control and overall hospital rating. A multiple regression analysis was performed using the hospital rating as the dependent variable to determine the most influential factors on surgical experience. Our analysis demonstrated a significantly positive correlation between patient perception of their pain control and their orthopaedist. There was a significant positive correlation between patient's perception of their pain control and their overall surgical experience. Multiple regression analysis using overall surgical experience as the dependent variable demonstrated a significant positive influence of perception of nurses and orthopaedists. Pain management positively influenced surgical experience; however, this was not significant. We found that perception of pain control in post-TKA patients affects perception of the treating orthopaedists, as well as their overall surgical experience. In addition, perception of orthopaedists and nurses both outweigh perception of pain control on overall surgical experience, with nurses being the most important. Orthopaedists should focus on staff education-particularly nurses-and educate them in order to optimize results on PG surveys and, ultimately, improve patient satisfaction. Further studies should correlate current standardized scoring systems and questionnaires for TKA with PG surveys in order to recognize gaps that need to be bridged to improve post-TKA patient satisfaction.

Effects of Cerebral Blood Flow and Vessel Conditions on Speech Recognition in Patients With Postlingual Adult Cochlear Implant: Predictable Factors for the Efficacy of Cochlear Implant.

PubMed

Ishino, Takashi; Ragaee, Mahmoud Ali; Maruhashi, Tatsuya; Kajikawa, Masato; Higashi, Yukihito; Sonoyama, Toru; Takeno, Sachio; Hirakawa, Katsuhiro

Cochlear implantation (CI) has been the most successful procedure for restoring hearing in a patient with severe and profound hearing loss. However, possibly owing to the variable brain functions of each patient, its performance and the associated patient satisfaction are widely variable. The authors hypothesize that peripheral and cerebral circulation can be assessed by noninvasive and globally available methods, yielding superior presurgical predictive factors of the performance of CI in adult patients with postlingual hearing loss who are scheduled to undergo CI. Twenty-two adult patients with cochlear implants for postlingual hearing loss were evaluated using Doppler sonography measurement of the cervical arteries (reflecting cerebral blood flow), flow-mediated dilation (FMD; reflecting the condition of cerebral arteries), and their pre-/post-CI best score on a monosyllabic discrimination test (pre-/post-CI best monosyllabic discrimination [BMD] score). Correlations between post-CI BMD score and the other factors were examined using univariate analysis and stepwise multiple linear regression analysis. The prediction factors were calculated by examining the receiver-operating characteristic curve between post-CI BMD score and the significantly positively correlated factors. Age and duration of deafness had a moderately negative correlation. The mean velocity of the internal carotid arteries and FMD had a moderate-to-strong positive correlation with the post-CI BMD score in univariate analysis. Stepwise multiple linear regression analysis revealed that only FMD was significantly positively correlated with post-CI BMD score. Analysis of the receiver-operating characteristic curve showed that a FMD cutoff score of 1.8 significantly predicted post-CI BMD score. These data suggest that FMD is a convenient, noninvasive, and widely available tool for predicting the efficacy of cochlear implants. An FMD cutoff score of 1.8 could be a good index for determining whether patients will hear well with cochlear implants. It could also be used to predict whether cochlear implants will provide good speech recognition benefits to candidates, even if their speech discrimination is poor. This FMD index could become a useful predictive tool for candidates with poor speech discrimination to determine the efficacy of CI before surgery.

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.

Liquid Jets in Crossflow at Elevated Temperatures and Pressures

NASA Astrophysics Data System (ADS)

Amighi, Amirreza

An experimental study on the characterization of liquid jets injected into subsonic air crossflows is conducted. The aim of the study is to relate the droplet size and other attributes of the spray, such as breakup length, position, plume width, and time to flow parameters, including jet and air velocities, pressure and temperature as well as non-dimensional variables. Furthermore, multiple expressions are defined that would summarize the general behavior of the spray. For this purpose, an experimental setup is developed, which could withstand high temperatures and pressures to simulate conditions close to those experienced inside gas turbine engines. Images are captured using a laser based shadowgraphy system similar to a 2D PIV system. Image processing is extensively used to measure droplet size and boundaries of the spray. In total 209 different conditions are tested and over 72,000 images are captured and processed. The crossflow air temperatures are 25°C, 200°C, and 300°C; absolute crossflow air pressures are 2.1, 3.8, and 5.2 bars. Various liquid and gas velocities are tested for each given temperature and pressure in order to study the breakup mechanisms and regimes. Effects of dimensional and non-dimensional variables on droplet size are presented in detail. Several correlations for the mean droplet size, which are generated in this process, are presented. In addition, the influence of non-dimensional variables on the breakup length, time, plume area, angle, width and mean jet surface thickness are discussed and individual correlations are provided for each parameter. The influence of each individual parameter on the droplet sizes is discussed for a better understanding of the fragmentation process. Finally, new correlations for the centerline, windward and leeward trajectories are presented and compared to the previously reported correlations.

Correlation of Vitamin D status and orthodontic-induced external apical root resorption

PubMed Central

Tehranchi, Azita; Sadighnia, Azin; Younessian, Farnaz; Abdi, Amir H.; Shirvani, Armin

2017-01-01

Background: Adequate Vitamin D is essential for dental and skeletal health in children and adult. The purpose of this study was to assess the correlation of serum Vitamin D level with external-induced apical root resorption (EARR) following fixed orthodontic treatment. Materials and Methods: In this cross-sectional study, the prevalence of Vitamin D deficiency (defined by25-hydroxyvitamin-D) was determined in 34 patients (23.5% male; age range 12–23 years; mean age 16.63 ± 2.84) treated with fixed orthodontic treatment. Root resorption of four maxillary incisors was measured using before and after periapical radiographs (136 measured teeth) by means of a design-to-purpose software to optimize data collection. Teeth with a maximum percentage of root resorption (%EARR) were indicated as representative root resorption for each patient. A multiple linear regression model and Pearson correlation coefficient were used to assess the association of Vitamin D status and observed EARR. P < 0.05 was considered statistically significant. Results: The Pearson coefficient between these two variables was determined about 0.15 (P = 0.38). Regression analysis revealed that Vitamin D status of the patients demonstrated no significant statistical correlation with EARR, after adjustment of confounding variables using linear regression model (P > 0.05). Conclusion: This study suggests that Vitamin D level is not among the clinical variables that are potential contributors for EARR. The prevalence of Vitamin D deficiency does not differ in patients with higher EARR. These data suggest the possibility that Vitamin D insufficiency may not contribute to the development of more apical root resorption although this remains to be confirmed by further longitudinal cohort studies. PMID:29238379

Perceptual structure of adductor spasmodic dysphonia and its acoustic correlates.

PubMed

Cannito, Michael P; Doiuchi, Maki; Murry, Thomas; Woodson, Gayle E

2012-11-01

To examine the perceptual structure of voice attributes in adductor spasmodic dysphonia (ADSD) before and after botulinum toxin treatment and identify acoustic correlates of underlying perceptual factors. Reliability of perceptual judgments is considered in detail. Pre- and posttreatment trial with comparison to healthy controls, using single-blind randomized listener judgments of voice qualities, as well as retrospective comparison with acoustic measurements. Oral readings were recorded from 42 ADSD speakers before and after treatment as well as from their age- and sex-matched controls. Experienced judges listened to speech samples and rated attributes of overall voice quality, breathiness, roughness, and brokenness, using computer-implemented visual analog scaling. Data were adjusted for regression to the mean and submitted to principal components factor analysis. Acoustic waveforms, extracted from the reading samples, were analyzed and measurements correlated with perceptual factor scores. Four reliable perceptual variables of ADSD voice were effectively reduced to two underlying factors that corresponded to hyperadduction, most strongly associated with roughness, and hypoadduction, most strongly associated with breathiness. After treatment, the hyperadduction factor improved, whereas the hypoadduction factor worsened. Statistically significant (P<0.01) correlations were observed between perceived roughness and four acoustic measures, whereas breathiness correlated with aperiodicity and cepstral peak prominence (CPPs). This study supported a two-factor model of ADSD, suggesting perceptual characterization by both hyperadduction and hypoadduction before and after treatment. Responses of the factors to treatment were consistent with previous research. Correlations among perceptual and acoustic variables suggested that multiple acoustic features contributed to the overall impression of roughness. Although CPPs appears to be a partial correlate of perceived breathiness, a physical basis of this percept remained less clear. Copyright © 2012 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

Biostatistics Series Module 6: Correlation and Linear Regression.

PubMed

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.

Biostatistics Series Module 6: Correlation and Linear Regression

PubMed Central

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient (r). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation (y = a + bx), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous. PMID:27904175

Clinical dysphagia risk predictors after prolonged orotracheal intubation

PubMed Central

de Medeiros, Gisele Chagas; Sassi, Fernanda Chiarion; Mangilli, Laura Davison; Zilberstein, Bruno; de Andrade, Claudia Regina Furquim

2014-01-01

OBJECTIVES: To elucidate independent risk factors for dysphagia after prolonged orotracheal intubation. METHODS: The participants were 148 consecutive patients who underwent clinical bedside swallowing assessments from September 2009 to September 2011. All patients had received prolonged orotracheal intubations and were admitted to one of several intensive care units of a large Brazilian school hospital. The correlations between the conducted water swallow test results and dysphagia risk levels were analyzed for statistical significance. RESULTS: Of the 148 patients included in the study, 91 were male and 57 were female (mean age, 53.64 years). The univariate analysis results indicated that specific variables, including extraoral loss, multiple swallows, cervical auscultation, vocal quality, cough, choking, and other signs, were possible significant high-risk indicators of dysphagia onset. The multivariate analysis results indicated that cervical auscultation and coughing were independent predictive variables for high dysphagia risk. CONCLUSIONS: Patients displaying extraoral loss, multiple swallows, cervical auscultation, vocal quality, cough, choking and other signs should benefit from early swallowing evaluations. Additionally, early post-extubation dysfunction recognition is paramount in reducing the morbidity rate in this high-risk population. PMID:24473554

On Latent Growth Models for Composites and Their Constituents.

PubMed

Hancock, Gregory R; Mao, Xiulin; Kher, Hemant

2013-09-01

Over the last decade and a half, latent growth modeling has become an extremely popular and versatile technique for evaluating longitudinal change and its determinants. Most common among the models applied are those for a single measured variable over time. This model has been extended in a variety of ways, most relevant for the current work being the multidomain and the second-order latent growth models. Whereas the former allows for growth function characteristics to be modeled for multiple outcomes simultaneously, with the degree of growth characteristics' relations assessed within the model (e.g., cross-domain slope factor correlations), the latter models growth in latent outcomes, each of which has effect indicators repeated over time. But what if one has an outcome that is believed to be formative relative to its indicator variables rather than latent? In this case, where the outcome is a composite of multiple constituents, modeling change over time is less straightforward. This article provides analytical and applied details for simultaneously modeling growth in composites and their constituent elements, including a real data example using a general computer self-efficacy questionnaire.

Clinical dysphagia risk predictors after prolonged orotracheal intubation.

PubMed

Medeiros, Gisele Chagas de; Sassi, Fernanda Chiarion; Mangilli, Laura Davison; Zilberstein, Bruno; Andrade, Claudia Regina Furquim de

2014-01-01

To elucidate independent risk factors for dysphagia after prolonged orotracheal intubation. The participants were 148 consecutive patients who underwent clinical bedside swallowing assessments from September 2009 to September 2011. All patients had received prolonged orotracheal intubations and were admitted to one of several intensive care units of a large Brazilian school hospital. The correlations between the conducted water swallow test results and dysphagia risk levels were analyzed for statistical significance. Of the 148 patients included in the study, 91 were male and 57 were female (mean age, 53.64 years). The univariate analysis results indicated that specific variables, including extraoral loss, multiple swallows, cervical auscultation, vocal quality, cough, choking, and other signs, were possible significant high-risk indicators of dysphagia onset. The multivariate analysis results indicated that cervical auscultation and coughing were independent predictive variables for high dysphagia risk. Patients displaying extraoral loss, multiple swallows, cervical auscultation, vocal quality, cough, choking and other signs should benefit from early swallowing evaluations. Additionally, early post-extubation dysfunction recognition is paramount in reducing the morbidity rate in this high-risk population.

Modeling the energy content of combustible ship-scrapping waste at Alang-Sosiya, India, using multiple regression analysis.

PubMed

Reddy, M Srinivasa; Basha, Shaik; Joshi, H V; Sravan Kumar, V G; Jha, B; Ghosh, P K

2005-01-01

Alang-Sosiya is the largest ship-scrapping yard in the world, established in 1982. Every year an average of 171 ships having a mean weight of 2.10 x 10(6)(+/-7.82 x 10(5)) of light dead weight tonnage (LDT) being scrapped. Apart from scrapped metals, this yard generates a massive amount of combustible solid waste in the form of waste wood, plastic, insulation material, paper, glass wool, thermocol pieces (polyurethane foam material), sponge, oiled rope, cotton waste, rubber, etc. In this study multiple regression analysis was used to develop predictive models for energy content of combustible ship-scrapping solid wastes. The scope of work comprised qualitative and quantitative estimation of solid waste samples and performing a sequential selection procedure for isolating variables. Three regression models were developed to correlate the energy content (net calorific values (LHV)) with variables derived from material composition, proximate and ultimate analyses. The performance of these models for this particular waste complies well with the equations developed by other researchers (Dulong, Steuer, Scheurer-Kestner and Bento's) for estimating energy content of municipal solid waste.

Use of electronic cigarettes and alternative tobacco products among Romanian adolescents.

PubMed

Nădăşan, Valentin; Foley, Kristie L; Pénzes, Melinda; Paulik, Edit; Mihăicuţă, Ştefan; Ábrám, Zoltán; Bálint, Jozsef; Urbán, Robert

2016-03-01

To assess socio-demographic and smoking-related correlates of e-cigarette and alternative tobacco products (ATPs) use in a multi-ethnic group of adolescents in Tîrgu Mures, Romania. The cross-sectional study included 1835 high school students from Tirgu Mures, Romania. Socio-demographic variables and data about smoking and e-cigarettes and ATP use were collected using an online questionnaire. Chi-square tests or one-way ANOVA were applied to compare never smokers, non-current smokers, and current smokers. Multiple logistic regression was conducted to determine the correlates of e-cigarettes and ATP use. The most frequently tried non-cigarette nicotine and tobacco products were e-cigarette (38.5 %), cigar (31.4 %) and waterpipe (21.1 %). Ever trying and current use of cigarettes were the most important correlates of e-cigarette and ATPs use. Sex, ethnicity, sensation seeking and perceived peer smoking were correlates of several ATPs use. The results of this study may inform the development of tailored tobacco control programs.

Plants remember past weather: a study for atmospheric pollen concentrations of Ambrosia, Poaceae and Populus

NASA Astrophysics Data System (ADS)

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

2015-10-01

After extreme dry (wet) summers or years, pollen production of different taxa may decrease (increase) substantially. Accordingly, studying effects of current and past meteorological conditions on current pollen concentrations for different taxa have of major importance. The purpose of this study is separating the weight of current and past weather conditions influencing current pollen productions of three taxa. Two procedures, namely multiple correlations and factor analysis with special transformation are used. The 11-year (1997-2007) data sets include daily pollen counts of Ambrosia (ragweed), Poaceae (grasses) and Populus (poplar), as well as daily values of four climate variables (temperature, relative humidity, global solar flux and precipitation). Multiple correlations of daily pollen counts with simultaneous values of daily meteorological variables do not show annual course for Ambrosia, but do show definite trends for Populus and Poaceae. Results received using the two methods revealed characteristic similarities. For all the three taxa, the continental rainfall peak and additional local showers in the growing season can strengthen the weight of the current meteorological elements. However, due to the precipitation, big amount of water can be stored in the soil contributing to the effect of the past climate elements during dry periods. Higher climate sensitivity (especially water sensitivity) of the herbaceous taxa ( Ambrosia and Poaceae) can be definitely established compared to the arboreal Populus. Separation of the weight of the current and past weather conditions for different taxa involves practical importance both for health care and agricultural production.

Dehydroepiandrosterone and multiple measures of functional immunity in young adults.

PubMed

Prall, Sean P; Muehlenbein, Michael P

2015-01-01

Human immune function is strongly influenced by variation in hormone concentrations. The adrenal androgens dehydroepiandrosterone (DHEA) and dehydroepiandrosterone-sulfate (DHEA-S) are thought to be beneficial to immune function and disease resistance, but physiologically interact with testosterone and cortisol. We predict that DHEA and DHEA-S will interact with these other hormones in determining immunological outcomes. Understanding the interactive effects of these hormones will aid in understanding variability in immunocompetence and clarify discrepancies in human studies of androgen-immune interactions. Thirty-eight participants collected morning saliva over three days, from which concentrations of DHEA, DHEA-S, testosterone, and cortisol were measured, as well as salivary bacteria killing ability to measure innate immune function. From blood collection, serum was collected to measure innate immune function via a hemolytic complement assay, and whole blood collected and processed to measure proliferative responses of lymphocytes in the presence of mitogens. DHEA was negatively correlated with T cell proliferation, and positively correlated with salivary bacteria killing in male participants. Additionally, using regression models, DHEA-S was negatively associated with hemolytic complement activity, but interaction variables did not yield statistically significant relationships for any other outcome measure. While interactions with other hormones did not significantly relate with immune function measures in this sample, DHEA and DHEA-S did differentially impact multiple branches of the immune system. Generally characterized as immunosupportive in action, DHEA is shown to inhibit certain facets of innate and cell-mediated immunity, suggesting a more complex role in regulating immunocompetence. © 2015 Wiley Periodicals, Inc.

The Moderating Role of Power Distance on the Relationship between Employee Participation and Outcome Variables

PubMed Central

Rafiei, Sima; Pourreza, Abolghasem

2013-01-01

Background: Many organisations have realised the importance of human resource for their competitive advantage. Empowering employees is therefore essential for organisational effectiveness. This study aimed to investigate the relationship between employee participation with outcome variables such as organisational commitment, job satisfaction, perception of justice in an organisation and readiness to accept job responsibilities. It further examined the impact of power distance on the relationship between participation and four outcome variables. Methods: This was a cross sectional study with a descriptive research design conducted among employees and managers of hospitals affiliated with Tehran University of Medical Sciences, Tehran, Iran. A questionnaire as a main procedure to gather data was developed, distributed and collected. Descriptive statistics, Pearson correlation coefficient and moderated multiple regression were used to analyse the study data. Results: Findings of the study showed that the level of power distance perceived by employees had a significant relationship with employee participation, organisational commitment, job satisfaction, perception of justice and readiness to accept job responsibilities. There was also a significant relationship between employee participation and four outcome variables. The moderated multiple regression results supported the hypothesis that power distance had a significant effect on the relationship between employee participation and four outcome variables. Conclusion: Organisations in which employee empowerment is practiced through diverse means such as participating them in decision making related to their field of work, appear to have more committed and satisfied employees with positive perception toward justice in the organisational interactions and readiness to accept job responsibilities. PMID:24596840

Multivariate Bayesian variable selection exploiting dependence structure among outcomes: Application to air pollution effects on DNA methylation.

PubMed

Lee, Kyu Ha; Tadesse, Mahlet G; Baccarelli, Andrea A; Schwartz, Joel; Coull, Brent A

2017-03-01

The analysis of multiple outcomes is becoming increasingly common in modern biomedical studies. It is well-known that joint statistical models for multiple outcomes are more flexible and more powerful than fitting a separate model for each outcome; they yield more powerful tests of exposure or treatment effects by taking into account the dependence among outcomes and pooling evidence across outcomes. It is, however, unlikely that all outcomes are related to the same subset of covariates. Therefore, there is interest in identifying exposures or treatments associated with particular outcomes, which we term outcome-specific variable selection. In this work, we propose a variable selection approach for multivariate normal responses that incorporates not only information on the mean model, but also information on the variance-covariance structure of the outcomes. The approach effectively leverages evidence from all correlated outcomes to estimate the effect of a particular covariate on a given outcome. To implement this strategy, we develop a Bayesian method that builds a multivariate prior for the variable selection indicators based on the variance-covariance of the outcomes. We show via simulation that the proposed variable selection strategy can boost power to detect subtle effects without increasing the probability of false discoveries. We apply the approach to the Normative Aging Study (NAS) epigenetic data and identify a subset of five genes in the asthma pathway for which gene-specific DNA methylations are associated with exposures to either black carbon, a marker of traffic pollution, or sulfate, a marker of particles generated by power plants. © 2016, The International Biometric Society.

Handgrip fatiguing exercise can provide objective assessment of cancer-related fatigue: a pilot study.

PubMed

Veni, T; Boyas, S; Beaune, B; Bourgeois, H; Rahmani, A; Landry, S; Bochereau, A; Durand, S; Morel, B

2018-06-24

As a subjective symptom, cancer-related fatigue is assessed via patient-reported outcomes. Due to the inherent bias of such evaluation, screening and treatment for cancer-related fatigue remains suboptimal. The purpose is to evaluate whether objective cancer patients' hand muscle mechanical parameters (maximal force, critical force, force variability) extracted from a fatiguing handgrip exercise may be correlated to the different dimensions (physical, emotional, and cognitive) of cancer-related fatigue. Fourteen women with advanced breast cancer, still under or having previously received chemotherapy within the preceding 3 months, and 11 healthy women participated to the present study. Cancer-related fatigue was first assessed through the EORTC QLQ-30 and its fatigue module. Fatigability was then measured during 60 maximal repeated handgrip contractions. The maximum force, critical force (asymptote of the force-time evolution), and force variability (root mean square of the successive differences) were extracted. Multiple regression models were performed to investigate the influence of the force parameters on cancer-related fatigue's dimensions. The multiple linear regression analysis evidenced that physical fatigue was best explained by maximum force and critical force (r = 0.81; p = 0.029). The emotional fatigue was best explained by maximum force, critical force, and force variability (r = 0.83; p = 0.008). The cognitive fatigue was best explained by critical force and force variability (r = 0.62; p = 0.035). The handgrip maximal force, critical force, and force variability may offer objective measures of the different dimensions of cancer-related fatigue and could provide a complementary approach to the patient reported outcomes.

Using Simpson's diversity index to examine multidimensional models of diversity in health professions education.

PubMed

McLaughlin, Jacqueline E; McLaughlin, Gerald W; McLaughlin, Josetta S; White, Carla Y

2016-01-03

This study explored new models of diversity for health professions education that incorporate multiple attributes and examined differences in diversity based on urbanicity, geographic region, and institutional structure. Simpson's Diversity Index was used to develop race, gender, and interprofessional diversity indices for health professions schools in the United States (N = 318). Sullivan's extension was used to develop a composite diversity index that incorporated multiple individual attributes for each school. Pearson's r was used to investigate correlations between continuous variables. ANOVA and independent t-tests were used to compare groups based on urbanicity, geographic region, and Basic Carnegie Classification. Mean (SD) for race, gender, and interprofessional diversity indices were 0.36(0.17), 0.45(0.07), and 0.22(0.27) respectively. All correlations between the three indices were weak. The composite diversity index for this sample was 0.34(0.13). Significant differences in diversity were found between institutions based on urbanicity, Basic Carnegie Classification, and geographic region. Multidimensional models provide support for expanding measures of diversity to include multiple characteristics and attributes. The approach demonstrated in this study enables institutions to complement and extend traditional measures of diversity as a means of providing evidence for decision-making and progress towards institutional initiatives.

Using Simpson’s diversity index to examine multidimensional models of diversity in health professions education

PubMed Central

McLaughlin, Gerald W.; McLaughlin, Josetta S.; White, Carla Y.

2016-01-01

Objectives This study explored new models of diversity for health professions education that incorporate multiple attributes and examined differences in diversity based on urbanicity, geographic region, and institutional structure. Methods Simpson’s Diversity Index was used to develop race, gender, and interprofessional diversity indices for health professions schools in the United States (N = 318). Sullivan’s extension was used to develop a composite diversity index that incorporated multiple individual attributes for each school. Pearson’s r was used to investigate correlations between continuous variables. ANOVA and independent t-tests were used to compare groups based on urbanicity, geographic region, and Basic Carnegie Classification. Results Mean (SD) for race, gender, and interprofessional  diversity indices were 0.36(0.17), 0.45(0.07), and 0.22(0.27) respectively. All correlations between the three indices were weak. The composite diversity index for this sample was 0.34(0.13). Significant differences in diversity were found between institutions based on urbanicity, Basic Carnegie Classification, and geographic region. Conclusions Multidimensional models provide support for expanding measures of diversity to include multiple characteristics and attributes. The approach demonstrated in this study enables institutions to complement and extend traditional measures of diversity as a means of providing evidence for decision-making and progress towards institutional initiatives. PMID:26724917

Automated statistical matching of multiple tephra records exemplified using five long maar sequences younger than 75 ka, Auckland, New Zealand

NASA Astrophysics Data System (ADS)

Green, Rebecca M.; Bebbington, Mark S.; Cronin, Shane J.; Jones, Geoff

2014-09-01

Detailed tephrochronologies are built to underpin probabilistic volcanic hazard forecasting, and to understand the dynamics and history of diverse geomorphic, climatic, soil-forming and environmental processes. Complicating factors include highly variable tephra distribution over time; difficulty in correlating tephras from site to site based on physical and chemical properties; and uncertain age determinations. Multiple sites permit construction of more accurate composite tephra records, but correctly merging individual site records by recognizing common events and site-specific gaps is complex. We present an automated procedure for matching tephra sequences between multiple deposition sites using stochastic local optimization techniques. If individual tephra age determinations are not significantly different between sites, they are matched and a more precise age is assigned. Known stratigraphy and mineralogical or geochemical compositions are used to constrain tephra matches. We apply this method to match tephra records from five long sediment cores (≤ 75 cal ka BP) in Auckland, New Zealand. Sediments at these sites preserve basaltic tephras from local eruptions of the Auckland Volcanic Field as well as distal rhyolitic and andesitic tephras from Okataina, Taupo, Egmont, Tongariro, and Tuhua (Mayor Island) volcanic centers. The new correlated record compiled is statistically more likely than previously published arrangements from this area.

Self-transcendence and well-being in homeless adults.

PubMed

Runquist, Jennifer J; Reed, Pamela G

2007-03-01

This study examines the relationships of spiritually and physically related variables to well-being among homeless adults. A convenience sample of 61 sheltered homeless persons completed the Spiritual Perspective Scale, the Self-Transcendence Scale, the Index of Well-Being, and items measuring fatigue and health status. The data were subjected to correlational and multiple regression analysis. Positive, significant correlations were found among spiritual perspective, self-transcendence, health status, and well-being. Fatigue was inversely correlated with health status and well-being. Self-transcendence and health status together explained 59% of the variance in well-being. The findings support Reed's theory of self-transcendence, in which there is the basic assumption that human beings have the potential to integrate difficult life situations. This study contributes to the growing body of evidence that conceptualizes homeless persons as having spiritual, emotional, and physical capacities that can be used by health care professionals to promote well-being in this vulnerable population.

The Moral Frameworks and Foundations of Contesting Orientations.

PubMed

Shields, David Light; Funk, Christopher D; Bredemeier, Brenda Light

2016-04-01

According to contesting theory (Shields & Bredemeier, 2011), people conceptualize competition either through a metaphor of partnership or war. These two alternate metaphors suggest differing sociomoral relationships among the participants. In the current study of intercollegiate athletes (n = 610), we investigated the two approaches to contesting in relation to formalist and consequentialist moral frameworks (Brady & Wheeler, 1996) and individualizing and binding moral foundations (Haidt, 2001). Correlational analysis indicated that the partnership approach correlated significantly with all four moral dimensions, while the war approach correlated with formalist and consequentialist frameworks and binding foundations (i.e., appeals to in-group loyalty, authority, and purity). Multiple regressions demonstrated that the best predictors of a partnership approach were formalist thinking and endorsement of individualizing moral foundations (i.e., appeal to fairness and welfare). Among our primary variables, the best predictors of a war orientation were consequentialist thinking and endorsement of binding foundations.

[Correlation between feeding index and growth development of 6-36 month-old infants in two counties of western China by applying multiple correspondence analysis].

PubMed

Chen, Hong-da; Hao, Bo; Kang, Xiao-ping; Zhao, Geng-li; Zhou, Min

2012-06-18

To explore the correlation between feeding index and growth development status of infants from two counties of western China by applying the method of multiple correspondence analysis. Two sample counties were randomly selected from the ones that satisfied the research conditions in Shaanxi province and Chongqing in western China. In the study, 472 premature/low birth weight infants (PLBW) and 461 normal term infants (NT) of 6-36 months from the two counties were investigated from September 2010 to November 2010. The SPSS 19.0 software was applied to analyze the data using general statistical analysis and multiple correspondence analysis. In the two counties of western China, the proportion of infants with feeding index at the medium level was the highest, which was between 50% and 60%. In the PLBW group and the NT group, the proportion of low level of feeding index among 6-9 month-old infants was the highest, and the proportion was 33.3% for the PLBW group and 29.4% for the NT group. For both the PLBW group and the NT group, the distribution of feeding index among the different age groups showed significant difference (P<0.05).Among the infants with low level of feeding index, the growth development of the PLBW lay behind that of the NT. We could see a catching-up trend of the PLBW with medium or good level of feeding index, but their growth development index was still at a lower level than that of the NT with the same level of feeding condition. Through multiple correspondence analyses, the outcomes of PLBW corresponded and strongly correlated with low level of feeding index, low level of growth development index, mother's low education degree and low annual family income. And the outcomes of NT corresponded and strongly correlated with medium/good level of feeding index, medium level of growth development status, mother's medium/high education degree and medium/high level of annual family income. There are good correspondence correlations at different hierarchical levels of the infants' group, feeding index, growth development index and family factors in the two counties of western China. Multiple correspondence analysis could directly reveal the correlation among several variables, which is a suitable method for categorical data. The result can be illustrated directly through a two-dimensional graph and could provide the suggestion of feeding practice for different infants in western rural China.

[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.

Associations between Caries among Children and Household Sugar Procurement, Exposure to Fluoridated Water and Socioeconomic Indicators in the Brazilian Capital Cities

PubMed Central

Gonçalves, Michele Martins; Leles, Cláudio Rodrigues; Freire, Maria do Carmo Matias

2013-01-01

The objective of this ecological study was to investigate the association between caries experience in 5- and 12-year-old Brazilian children in 2010 and household sugar procurement in 2003 and the effects of exposure to water fluoridation and socioeconomic indicators. Sample units were all 27 Brazilian capital cities. Data were obtained from the National Surveys of Oral Health; the National Household Food Budget Survey; and the United Nations Program for Development. Data analysis included correlation coefficients, exploratory factor analysis, and linear regression. There were significant negative associations between caries experience and procurement of confectionery, fluoridated water, HDI, and per capita income. Procurement of confectionery and soft drinks was positively associated with HDI and per capita income. Exploratory factor analysis grouped the independent variables by reducing highly correlated variables into two uncorrelated component variables that explained 86.1% of total variance. The first component included income, HDI, water fluoridation, and procurement of confectionery, while the second included free sugar and procurement of soft drinks. Multiple regression analysis showed that caries is associated with the first component. Caries experience was associated with better socioeconomic indicators of a city and exposure to fluoridated water, which may affect the impact of sugars on the disease. PMID:24307900

Lack of association between systolic blood pressure and blood viscosity in normotensive healthy subjects.

PubMed

Irace, Concetta; Carallo, Claudio; Scavelli, Faustina; Loprete, Antonio; Merante, Valentina; Gnasso, Agostino

2012-01-01

A direct relationship between blood pressure and viscosity has frequently been reported, although clear data are not available. To better understand the relationship between these two variables, we evaluated blood viscosity and blood pressure in a group of healthy subjects without cardiovascular risk factors. Healthy subjects were selected from participants in a campaign of prevention of cardiovascular disease (n = 103). They underwent blood sampling for measurement of plasma and blood viscosity, haematocrit, blood lipids and glucose. The quantity and distribution of body fat was assessed by body mass index and waist/hip ratio, respectively. Systolic blood pressure (SBP) correlated significantly with age (r = 0.222) and waist/hip ratio (r = 0.374). Diastolic blood pressure (DBP) correlated significantly with waist/hip ratio (r = 0.216), haematocrit (r = 0.333) and blood viscosity (r = 0.258). Multiple linear regression analyses demonstrated that the only variable significantly associated with SBP was age, while haematocrit was the only variable significantly associated with DBP. Blood viscosity was closely related to waist/hip ratio. These findings show that SBP, in healthy subjects, is not influenced by haematocrit and blood viscosity. In contrast, DBP is related to the values of haematocrit. Among classical cardiovascular risk factors, waist/hip ratio is closely related to blood viscosity.

A FIVE-YEAR SPECTROSCOPIC AND PHOTOMETRIC CAMPAIGN ON THE PROTOTYPICAL {alpha} CYGNI VARIABLE AND A-TYPE SUPERGIANT STAR DENEB

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

Richardson, N. D.; Morrison, N. D.; Kryukova, E. E.

2011-01-15

Deneb is often considered the prototypical A-type supergiant and is one of the visually most luminous stars in the Galaxy. A-type supergiants are potential extragalactic distance indicators, but the variability of these stars needs to be better characterized before this technique can be considered reliable. We analyzed 339 high-resolution echelle spectra of Deneb obtained over the five-year span of 1997 through 2001 as well as 370 Stroemgren photometric measurements obtained during the same time frame. Our spectroscopic analysis included dynamical spectra of the H{alpha} profile, H{alpha} equivalent widths, and radial velocities measured from Si II {lambda}{lambda} 6347, 6371. Time-series analysismore » reveals no obvious cyclic behavior that proceeds through multiple observing seasons, although we found a suspected 40 day period in two, non-consecutive observing seasons. Some correlations are found between photometric and radial velocity data sets and suggest radial pulsations at two epochs. No correlation is found between the variability of the H{alpha} profiles and that of the radial velocities or the photometry. Lucy found evidence that Deneb was a long-period single-lined spectroscopic binary star, but our data set shows no evidence for radial velocity variations caused by a binary companion.« less