Gender differences in the diagnostic accuracy of SPECT myocardial perfusion imaging: a bivariate meta-analysis.

PubMed

Iskandar, Aline; Limone, Brendan; Parker, Matthew W; Perugini, Andrew; Kim, Hyejin; Jones, Charles; Calamari, Brian; Coleman, Craig I; Heller, Gary V

2013-02-01

It remains controversial whether the diagnostic accuracy of single-photon emission computed tomography myocardial perfusion imaging (SPECT MPI) is different in men as compared to women. We performed a meta-analysis to investigate gender differences of SPECT MPI for the diagnosis of CAD (≥50% stenosis). Two investigators independently performed a systematic review of the MEDLINE and EMBASE databases from inception through January 2012 for English-language studies determining the diagnostic accuracy of SPECT MPI. We included prospective studies that compared SPECT MPI with conventional coronary angiography which provided sufficient data to calculate gender-specific true and false positives and negatives. Data from studies evaluating <20 patients of one gender were excluded. Bivariate meta-analysis was used to create summary receiver operating curves. Twenty-six studies met inclusion criteria, representing 1,148 women and 1,142 men. Bivariate meta-analysis yielded a mean sensitivity and specificity of 84.2% (95% confidence interval [CI] 78.7%-88.6%) and 78.7% (CI 70.0%-85.3%) for SPECT MPI in women and 89.1% (CI 84.0%-92.7%) and 71.2% (CI 60.8%-79.8%) for SPECT MPI in men. There was no significant difference in the sensitivity (P = .15) or specificity (P = .23) between male and female subjects. In a bivariate meta-analysis of the available literature, the diagnostic accuracy of SPECT MPI is similar for both men and women.

Bivariate analysis of floods in climate impact assessments.

PubMed

Brunner, Manuela Irene; Sikorska, Anna E; Seibert, Jan

2018-03-01

Climate impact studies regarding floods usually focus on peak discharges and a bivariate assessment of peak discharges and hydrograph volumes is not commonly included. A joint consideration of peak discharges and hydrograph volumes, however, is crucial when assessing flood risks for current and future climate conditions. Here, we present a methodology to develop synthetic design hydrographs for future climate conditions that jointly consider peak discharges and hydrograph volumes. First, change factors are derived based on a regional climate model and are applied to observed precipitation and temperature time series. Second, the modified time series are fed into a calibrated hydrological model to simulate runoff time series for future conditions. Third, these time series are used to construct synthetic design hydrographs. The bivariate flood frequency analysis used in the construction of synthetic design hydrographs takes into account the dependence between peak discharges and hydrograph volumes, and represents the shape of the hydrograph. The latter is modeled using a probability density function while the dependence between the design variables peak discharge and hydrograph volume is modeled using a copula. We applied this approach to a set of eight mountainous catchments in Switzerland to construct catchment-specific and season-specific design hydrographs for a control and three scenario climates. Our work demonstrates that projected climate changes have an impact not only on peak discharges but also on hydrograph volumes and on hydrograph shapes both at an annual and at a seasonal scale. These changes are not necessarily proportional which implies that climate impact assessments on future floods should consider more flood characteristics than just flood peaks. Copyright © 2017. Published by Elsevier B.V.

Nonparametric analysis of bivariate gap time with competing risks.

PubMed

Huang, Chiung-Yu; Wang, Chenguang; Wang, Mei-Cheng

2016-09-01

This article considers nonparametric methods for studying recurrent disease and death with competing risks. We first point out that comparisons based on the well-known cumulative incidence function can be confounded by different prevalence rates of the competing events, and that comparisons of the conditional distribution of the survival time given the failure event type are more relevant for investigating the prognosis of different patterns of recurrence disease. We then propose nonparametric estimators for the conditional cumulative incidence function as well as the conditional bivariate cumulative incidence function for the bivariate gap times, that is, the time to disease recurrence and the residual lifetime after recurrence. To quantify the association between the two gap times in the competing risks setting, a modified Kendall's tau statistic is proposed. The proposed estimators for the conditional bivariate cumulative incidence distribution and the association measure account for the induced dependent censoring for the second gap time. Uniform consistency and weak convergence of the proposed estimators are established. Hypothesis testing procedures for two-sample comparisons are discussed. Numerical simulation studies with practical sample sizes are conducted to evaluate the performance of the proposed nonparametric estimators and tests. An application to data from a pancreatic cancer study is presented to illustrate the methods developed in this article. © 2016, The International Biometric Society.

Bivariate genome-wide association meta-analysis of pediatric musculoskeletal traits reveals pleiotropic effects at the SREBF1/TOM1L2 locus.

PubMed

Medina-Gomez, Carolina; Kemp, John P; Dimou, Niki L; Kreiner, Eskil; Chesi, Alessandra; Zemel, Babette S; Bønnelykke, Klaus; Boer, Cindy G; Ahluwalia, Tarunveer S; Bisgaard, Hans; Evangelou, Evangelos; Heppe, Denise H M; Bonewald, Lynda F; Gorski, Jeffrey P; Ghanbari, Mohsen; Demissie, Serkalem; Duque, Gustavo; Maurano, Matthew T; Kiel, Douglas P; Hsu, Yi-Hsiang; C J van der Eerden, Bram; Ackert-Bicknell, Cheryl; Reppe, Sjur; Gautvik, Kaare M; Raastad, Truls; Karasik, David; van de Peppel, Jeroen; Jaddoe, Vincent W V; Uitterlinden, André G; Tobias, Jonathan H; Grant, Struan F A; Bagos, Pantelis G; Evans, David M; Rivadeneira, Fernando

2017-07-25

Bone mineral density is known to be a heritable, polygenic trait whereas genetic variants contributing to lean mass variation remain largely unknown. We estimated the shared SNP heritability and performed a bivariate GWAS meta-analysis of total-body lean mass (TB-LM) and total-body less head bone mineral density (TBLH-BMD) regions in 10,414 children. The estimated SNP heritability is 43% (95% CI: 34-52%) for TBLH-BMD, and 39% (95% CI: 30-48%) for TB-LM, with a shared genetic component of 43% (95% CI: 29-56%). We identify variants with pleiotropic effects in eight loci, including seven established bone mineral density loci: WNT4, GALNT3, MEPE, CPED1/WNT16, TNFSF11, RIN3, and PPP6R3/LRP5. Variants in the TOM1L2/SREBF1 locus exert opposing effects TB-LM and TBLH-BMD, and have a stronger association with the former trait. We show that SREBF1 is expressed in murine and human osteoblasts, as well as in human muscle tissue. This is the first bivariate GWAS meta-analysis to demonstrate genetic factors with pleiotropic effects on bone mineral density and lean mass.Bone mineral density and lean skeletal mass are heritable traits. Here, Medina-Gomez and colleagues perform bivariate GWAS analyses of total body lean mass and bone mass density in children, and show genetic loci with pleiotropic effects on both traits.

Causal networks clarify productivity-richness interrelations, bivariate plots do not

USGS Publications Warehouse

Grace, James B.; Adler, Peter B.; Harpole, W. Stanley; Borer, Elizabeth T.; Seabloom, Eric W.

2014-01-01

We urge ecologists to consider productivity–richness relationships through the lens of causal networks to advance our understanding beyond bivariate analysis. Further, we emphasize that models based on a causal network conceptualization can also provide more meaningful guidance for conservation management than can a bivariate perspective. Measuring only two variables does not permit the evaluation of complex ideas nor resolve debates about underlying mechanisms.

Univariate and bivariate likelihood-based meta-analysis methods performed comparably when marginal sensitivity and specificity were the targets of inference.

PubMed

Dahabreh, Issa J; Trikalinos, Thomas A; Lau, Joseph; Schmid, Christopher H

2017-03-01

To compare statistical methods for meta-analysis of sensitivity and specificity of medical tests (e.g., diagnostic or screening tests). We constructed a database of PubMed-indexed meta-analyses of test performance from which 2 × 2 tables for each included study could be extracted. We reanalyzed the data using univariate and bivariate random effects models fit with inverse variance and maximum likelihood methods. Analyses were performed using both normal and binomial likelihoods to describe within-study variability. The bivariate model using the binomial likelihood was also fit using a fully Bayesian approach. We use two worked examples-thoracic computerized tomography to detect aortic injury and rapid prescreening of Papanicolaou smears to detect cytological abnormalities-to highlight that different meta-analysis approaches can produce different results. We also present results from reanalysis of 308 meta-analyses of sensitivity and specificity. Models using the normal approximation produced sensitivity and specificity estimates closer to 50% and smaller standard errors compared to models using the binomial likelihood; absolute differences of 5% or greater were observed in 12% and 5% of meta-analyses for sensitivity and specificity, respectively. Results from univariate and bivariate random effects models were similar, regardless of estimation method. Maximum likelihood and Bayesian methods produced almost identical summary estimates under the bivariate model; however, Bayesian analyses indicated greater uncertainty around those estimates. Bivariate models produced imprecise estimates of the between-study correlation of sensitivity and specificity. Differences between methods were larger with increasing proportion of studies that were small or required a continuity correction. The binomial likelihood should be used to model within-study variability. Univariate and bivariate models give similar estimates of the marginal distributions for sensitivity and

Trend Detection and Bivariate Frequency Analysis for Nonstrationary Rainfall Data

NASA Astrophysics Data System (ADS)

Joo, K.; Kim, H.; Shin, J. Y.; Heo, J. H.

2017-12-01

Multivariate frequency analysis has been developing for hydro-meteorological data such as rainfall, flood, and drought. Particularly, the copula has been used as a useful tool for multivariate probability model which has no limitation on deciding marginal distributions. The time-series rainfall data can be characterized to rainfall event by inter-event time definition (IETD) and each rainfall event has a rainfall depth and rainfall duration. In addition, nonstationarity in rainfall event has been studied recently due to climate change and trend detection of rainfall event is important to determine the data has nonstationarity or not. With the rainfall depth and duration of a rainfall event, trend detection and nonstationary bivariate frequency analysis has performed in this study. 62 stations from Korea Meteorological Association (KMA) over 30 years of hourly recorded data used in this study and the suitability of nonstationary copula for rainfall event has examined by the goodness-of-fit test.

[Use of bivariate survival curves for analyzing mortality of heart failure and sudden death in dilated cardiomiopathy].

PubMed

Gregori, Dario; Rosato, Rosalba; Zecchin, Massimo; Di Lenarda, Andrea

2005-01-01

This paper discusses the use of bivariate survival curves estimators within the competing risk framework. Competing risks models are used for the analysis of medical data with more than one cause of death. The case of dilated cardiomiopathy is explored. Bivariate survival curves plot the conjoint mortality processes. The different graphic representation of bivariate survival analysis is the major contribute of this methodology to the competing risks analysis.

Bivariate discrete beta Kernel graduation of mortality data.

PubMed

Mazza, Angelo; Punzo, Antonio

2015-07-01

Various parametric/nonparametric techniques have been proposed in literature to graduate mortality data as a function of age. Nonparametric approaches, as for example kernel smoothing regression, are often preferred because they do not assume any particular mortality law. Among the existing kernel smoothing approaches, the recently proposed (univariate) discrete beta kernel smoother has been shown to provide some benefits. Bivariate graduation, over age and calendar years or durations, is common practice in demography and actuarial sciences. In this paper, we generalize the discrete beta kernel smoother to the bivariate case, and we introduce an adaptive bandwidth variant that may provide additional benefits when data on exposures to the risk of death are available; furthermore, we outline a cross-validation procedure for bandwidths selection. Using simulations studies, we compare the bivariate approach proposed here with its corresponding univariate formulation and with two popular nonparametric bivariate graduation techniques, based on Epanechnikov kernels and on P-splines. To make simulations realistic, a bivariate dataset, based on probabilities of dying recorded for the US males, is used. Simulations have confirmed the gain in performance of the new bivariate approach with respect to both the univariate and the bivariate competitors.

GIS-based bivariate statistical techniques for groundwater potential analysis (an example of Iran)

NASA Astrophysics Data System (ADS)

Haghizadeh, Ali; Moghaddam, Davoud Davoudi; Pourghasemi, Hamid Reza

2017-12-01

Groundwater potential analysis prepares better comprehension of hydrological settings of different regions. This study shows the potency of two GIS-based data driven bivariate techniques namely statistical index (SI) and Dempster-Shafer theory (DST) to analyze groundwater potential in Broujerd region of Iran. The research was done using 11 groundwater conditioning factors and 496 spring positions. Based on the ground water potential maps (GPMs) of SI and DST methods, 24.22% and 23.74% of the study area is covered by poor zone of groundwater potential, and 43.93% and 36.3% of Broujerd region is covered by good and very good potential zones, respectively. The validation of outcomes displayed that area under the curve (AUC) of SI and DST techniques are 81.23% and 79.41%, respectively, which shows SI method has slightly a better performance than the DST technique. Therefore, SI and DST methods are advantageous to analyze groundwater capacity and scrutinize the complicated relation between groundwater occurrence and groundwater conditioning factors, which permits investigation of both systemic and stochastic uncertainty. Finally, it can be realized that these techniques are very beneficial for groundwater potential analyzing and can be practical for water-resource management experts.

A tutorial on Bayesian bivariate meta-analysis of mixed binary-continuous outcomes with missing treatment effects.

PubMed

Gajic-Veljanoski, Olga; Cheung, Angela M; Bayoumi, Ahmed M; Tomlinson, George

2016-05-30

Bivariate random-effects meta-analysis (BVMA) is a method of data synthesis that accounts for treatment effects measured on two outcomes. BVMA gives more precise estimates of the population mean and predicted values than two univariate random-effects meta-analyses (UVMAs). BVMA also addresses bias from incomplete reporting of outcomes. A few tutorials have covered technical details of BVMA of categorical or continuous outcomes. Limited guidance is available on how to analyze datasets that include trials with mixed continuous-binary outcomes where treatment effects on one outcome or the other are not reported. Given the advantages of Bayesian BVMA for handling missing outcomes, we present a tutorial for Bayesian BVMA of incompletely reported treatment effects on mixed bivariate outcomes. This step-by-step approach can serve as a model for our intended audience, the methodologist familiar with Bayesian meta-analysis, looking for practical advice on fitting bivariate models. To facilitate application of the proposed methods, we include our WinBUGS code. As an example, we use aggregate-level data from published trials to demonstrate the estimation of the effects of vitamin K and bisphosphonates on two correlated bone outcomes, fracture, and bone mineral density. We present datasets where reporting of the pairs of treatment effects on both outcomes was 'partially' complete (i.e., pairs completely reported in some trials), and we outline steps for modeling the incompletely reported data. To assess what is gained from the additional work required by BVMA, we compare the resulting estimates to those from separate UVMAs. We discuss methodological findings and make four recommendations. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

A generalized right truncated bivariate Poisson regression model with applications to health data.

PubMed

Islam, M Ataharul; Chowdhury, Rafiqul I

2017-01-01

A generalized right truncated bivariate Poisson regression model is proposed in this paper. Estimation and tests for goodness of fit and over or under dispersion are illustrated for both untruncated and right truncated bivariate Poisson regression models using marginal-conditional approach. Estimation and test procedures are illustrated for bivariate Poisson regression models with applications to Health and Retirement Study data on number of health conditions and the number of health care services utilized. The proposed test statistics are easy to compute and it is evident from the results that the models fit the data very well. A comparison between the right truncated and untruncated bivariate Poisson regression models using the test for nonnested models clearly shows that the truncated model performs significantly better than the untruncated model.

Applied Statistics: From Bivariate through Multivariate Techniques [with CD-ROM

ERIC Educational Resources Information Center

Warner, Rebecca M.

2007-01-01

This book provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked…

Properties of the Bivariate Delayed Poisson Process

DTIC Science & Technology

1974-07-01

and Lewis (1972) in their Berkeley Symposium paper and here their analysis of the bivariate Poisson processes (without Poisson noise) is carried... Poisson processes . They cannot, however, be independent Poisson processes because their events are associated in pairs by the displace- ment centres...process because its marginal processes for events of each type are themselves (univariate) Poisson processes . Cox and Lewis (1972) assumed a

A generalized right truncated bivariate Poisson regression model with applications to health data

PubMed Central

Islam, M. Ataharul; Chowdhury, Rafiqul I.

2017-01-01

A generalized right truncated bivariate Poisson regression model is proposed in this paper. Estimation and tests for goodness of fit and over or under dispersion are illustrated for both untruncated and right truncated bivariate Poisson regression models using marginal-conditional approach. Estimation and test procedures are illustrated for bivariate Poisson regression models with applications to Health and Retirement Study data on number of health conditions and the number of health care services utilized. The proposed test statistics are easy to compute and it is evident from the results that the models fit the data very well. A comparison between the right truncated and untruncated bivariate Poisson regression models using the test for nonnested models clearly shows that the truncated model performs significantly better than the untruncated model. PMID:28586344

Global assessment of predictability of water availability: A bivariate probabilistic Budyko analysis

NASA Astrophysics Data System (ADS)

Wang, Weiguang; Fu, Jianyu

2018-02-01

Estimating continental water availability is of great importance for water resources management, in terms of maintaining ecosystem integrity and sustaining society development. To more accurately quantify the predictability of water availability, on the basis of univariate probabilistic Budyko framework, a bivariate probabilistic Budyko approach was developed using copula-based joint distribution model for considering the dependence between parameter ω of Wang-Tang's equation and the Normalized Difference Vegetation Index (NDVI), and was applied globally. The results indicate the predictive performance in global water availability is conditional on the climatic condition. In comparison with simple univariate distribution, the bivariate one produces the lower interquartile range under the same global dataset, especially in the regions with higher NDVI values, highlighting the importance of developing the joint distribution by taking into account the dependence structure of parameter ω and NDVI, which can provide more accurate probabilistic evaluation of water availability.

Some properties of a 5-parameter bivariate probability distribution

NASA Technical Reports Server (NTRS)

Tubbs, J. D.; Brewer, D. W.; Smith, O. E.

1983-01-01

A five-parameter bivariate gamma distribution having two shape parameters, two location parameters and a correlation parameter was developed. This more general bivariate gamma distribution reduces to the known four-parameter distribution. The five-parameter distribution gives a better fit to the gust data. The statistical properties of this general bivariate gamma distribution and a hypothesis test were investigated. Although these developments have come too late in the Shuttle program to be used directly as design criteria for ascent wind gust loads, the new wind gust model has helped to explain the wind profile conditions which cause large dynamic loads. Other potential applications of the newly developed five-parameter bivariate gamma distribution are in the areas of reliability theory, signal noise, and vibration mechanics.

A non-stationary cost-benefit based bivariate extreme flood estimation approach

NASA Astrophysics Data System (ADS)

Qi, Wei; Liu, Junguo

2018-02-01

Cost-benefit analysis and flood frequency analysis have been integrated into a comprehensive framework to estimate cost effective design values. However, previous cost-benefit based extreme flood estimation is based on stationary assumptions and analyze dependent flood variables separately. A Non-Stationary Cost-Benefit based bivariate design flood estimation (NSCOBE) approach is developed in this study to investigate influence of non-stationarities in both the dependence of flood variables and the marginal distributions on extreme flood estimation. The dependence is modeled utilizing copula functions. Previous design flood selection criteria are not suitable for NSCOBE since they ignore time changing dependence of flood variables. Therefore, a risk calculation approach is proposed based on non-stationarities in both marginal probability distributions and copula functions. A case study with 54-year observed data is utilized to illustrate the application of NSCOBE. Results show NSCOBE can effectively integrate non-stationarities in both copula functions and marginal distributions into cost-benefit based design flood estimation. It is also found that there is a trade-off between maximum probability of exceedance calculated from copula functions and marginal distributions. This study for the first time provides a new approach towards a better understanding of influence of non-stationarities in both copula functions and marginal distributions on extreme flood estimation, and could be beneficial to cost-benefit based non-stationary bivariate design flood estimation across the world.

Univariate and Bivariate Loglinear Models for Discrete Test Score Distributions.

ERIC Educational Resources Information Center

Holland, Paul W.; Thayer, Dorothy T.

2000-01-01

Applied the theory of exponential families of distributions to the problem of fitting the univariate histograms and discrete bivariate frequency distributions that often arise in the analysis of test scores. Considers efficient computation of the maximum likelihood estimates of the parameters using Newton's Method and computationally efficient…

Bivariate at-site frequency analysis of simulated flood peak-volume data using copulas

NASA Astrophysics Data System (ADS)

Gaál, Ladislav; Viglione, Alberto; Szolgay, Ján.; Blöschl, Günter; Bacigál, Tomáå.¡

2010-05-01

In frequency analysis of joint hydro-climatological extremes (flood peaks and volumes, low flows and durations, etc.), usually, bivariate distribution functions are fitted to the observed data in order to estimate the probability of their occurrence. Bivariate models, however, have a number of limitations; therefore, in the recent past, dependence models based on copulas have gained increased attention to represent the joint probabilities of hydrological characteristics. Regardless of whether standard or copula based bivariate frequency analysis is carried out, one is generally interested in the extremes corresponding to low probabilities of the fitted joint cumulative distribution functions (CDFs). However, usually there is not enough flood data in the right tail of the empirical CDFs to derive reliable statistical inferences on the behaviour of the extremes. Therefore, different techniques are used to extend the amount of information for the statistical inference, i.e., temporal extension methods that allow for making use of historical data or spatial extension methods such as regional approaches. In this study, a different approach was adopted which uses simulated flood data by rainfall-runoff modelling, to increase the amount of data in the right tail of the CDFs. In order to generate artificial runoff data (i.e. to simulate flood records of lengths of approximately 106 years), a two-step procedure was used. (i) First, the stochastic rainfall generator proposed by Sivapalan et al. (2005) was modified for our purpose. This model is based on the assumption of discrete rainfall events whose arrival times, durations, mean rainfall intensity and the within-storm intensity patterns are all random, and can be described by specified distributions. The mean storm rainfall intensity is disaggregated further to hourly intensity patterns. (ii) Secondly, the simulated rainfall data entered a semi-distributed conceptual rainfall-runoff model that consisted of a snow routine

BIVARIATE MODELLING OF CLUSTERED CONTINUOUS AND ORDERED CATEGORICAL OUTCOMES. (R824757)

EPA Science Inventory

Simultaneous observation of continuous and ordered categorical outcomes for each subject is common in biomedical research but multivariate analysis of the data is complicated by the multiple data types. Here we construct a model for the joint distribution of bivariate continuous ...

An improved method for bivariate meta-analysis when within-study correlations are unknown.

PubMed

Hong, Chuan; D Riley, Richard; Chen, Yong

2018-03-01

Multivariate meta-analysis, which jointly analyzes multiple and possibly correlated outcomes in a single analysis, is becoming increasingly popular in recent years. An attractive feature of the multivariate meta-analysis is its ability to account for the dependence between multiple estimates from the same study. However, standard inference procedures for multivariate meta-analysis require the knowledge of within-study correlations, which are usually unavailable. This limits standard inference approaches in practice. Riley et al proposed a working model and an overall synthesis correlation parameter to account for the marginal correlation between outcomes, where the only data needed are those required for a separate univariate random-effects meta-analysis. As within-study correlations are not required, the Riley method is applicable to a wide variety of evidence synthesis situations. However, the standard variance estimator of the Riley method is not entirely correct under many important settings. As a consequence, the coverage of a function of pooled estimates may not reach the nominal level even when the number of studies in the multivariate meta-analysis is large. In this paper, we improve the Riley method by proposing a robust variance estimator, which is asymptotically correct even when the model is misspecified (ie, when the likelihood function is incorrect). Simulation studies of a bivariate meta-analysis, in a variety of settings, show a function of pooled estimates has improved performance when using the proposed robust variance estimator. In terms of individual pooled estimates themselves, the standard variance estimator and robust variance estimator give similar results to the original method, with appropriate coverage. The proposed robust variance estimator performs well when the number of studies is relatively large. Therefore, we recommend the use of the robust method for meta-analyses with a relatively large number of studies (eg, m≥50). When the

Evaluating Evidence for Conceptually Related Constructs Using Bivariate Correlations

ERIC Educational Resources Information Center

Swank, Jacqueline M.; Mullen, Patrick R.

2017-01-01

The article serves as a guide for researchers in developing evidence of validity using bivariate correlations, specifically construct validity. The authors outline the steps for calculating and interpreting bivariate correlations. Additionally, they provide an illustrative example and discuss the implications.

Cost-offsets of prescription drug expenditures: data analysis via a copula-based bivariate dynamic hurdle model.

PubMed

Deb, Partha; Trivedi, Pravin K; Zimmer, David M

2014-10-01

In this paper, we estimate a copula-based bivariate dynamic hurdle model of prescription drug and nondrug expenditures to test the cost-offset hypothesis, which posits that increased expenditures on prescription drugs are offset by reductions in other nondrug expenditures. We apply the proposed methodology to data from the Medical Expenditure Panel Survey, which have the following features: (i) the observed bivariate outcomes are a mixture of zeros and continuously measured positives; (ii) both the zero and positive outcomes show state dependence and inter-temporal interdependence; and (iii) the zeros and the positives display contemporaneous association. The point mass at zero is accommodated using a hurdle or a two-part approach. The copula-based approach to generating joint distributions is appealing because the contemporaneous association involves asymmetric dependence. The paper studies samples categorized by four health conditions: arthritis, diabetes, heart disease, and mental illness. There is evidence of greater than dollar-for-dollar cost-offsets of expenditures on prescribed drugs for relatively low levels of spending on drugs and less than dollar-for-dollar cost-offsets at higher levels of drug expenditures. Copyright © 2013 John Wiley & Sons, Ltd.

Bivariate Heritability of Total and Regional Brain Volumes: the Framingham Study

PubMed Central

DeStefano, Anita L.; Seshadri, Sudha; Beiser, Alexa; Atwood, Larry D.; Massaro, Joe M.; Au, Rhoda; Wolf, Philip A.; DeCarli, Charles

2009-01-01

Heritability and genetic and environmental correlations of total and regional brain volumes were estimated from a large, generally healthy, community-based sample, to determine if there are common elements to the genetic influence of brain volumes and white matter hyperintensity volume. There were 1538 Framingham Heart Study participants with brain volume measures from quantitative magnetic resonance imaging (MRI) who were free of stroke and other neurological disorders that might influence brain volumes and who were members of families with at least two Framingham Heart Study participants. Heritability was estimated using variance component methodology and adjusting for the components of the Framingham stroke risk profile. Genetic and environmental correlations between traits were obtained from bivariate analysis. Heritability estimates ranging from 0.46 to 0.60, were observed for total brain, white matter hyperintensity, hippocampal, temporal lobe, and lateral ventricular volumes. Moderate, yet significant, heritability was observed for the other measures. Bivariate analyses demonstrated that relationships between brain volume measures, except for white matter hyperintensity, reflected both moderate to strong shared genetic and shared environmental influences. This study confirms strong genetic effects on brain and white matter hyperintensity volumes. These data extend current knowledge by showing that these two different types of MRI measures do not share underlying genetic or environmental influences. PMID:19812462

CI2 for creating and comparing confidence-intervals for time-series bivariate plots.

PubMed

Mullineaux, David R

2017-02-01

Currently no method exists for calculating and comparing the confidence-intervals (CI) for the time-series of a bivariate plot. The study's aim was to develop 'CI2' as a method to calculate the CI on time-series bivariate plots, and to identify if the CI between two bivariate time-series overlap. The test data were the knee and ankle angles from 10 healthy participants running on a motorised standard-treadmill and non-motorised curved-treadmill. For a recommended 10+ trials, CI2 involved calculating 95% confidence-ellipses at each time-point, then taking as the CI the points on the ellipses that were perpendicular to the direction vector between the means of two adjacent time-points. Consecutive pairs of CI created convex quadrilaterals, and any overlap of these quadrilaterals at the same time or ±1 frame as a time-lag calculated using cross-correlations, indicated where the two time-series differed. CI2 showed no group differences between left and right legs on both treadmills, but the same legs between treadmills for all participants showed differences of less knee extension on the curved-treadmill before heel-strike. To improve and standardise the use of CI2 it is recommended to remove outlier time-series, use 95% confidence-ellipses, and scale the ellipse by the fixed Chi-square value as opposed to the sample-size dependent F-value. For practical use, and to aid in standardisation or future development of CI2, Matlab code is provided. CI2 provides an effective method to quantify the CI of bivariate plots, and to explore the differences in CI between two bivariate time-series. Copyright © 2016 Elsevier B.V. All rights reserved.

Bivariate frequency analysis of rainfall intensity and duration for urban stormwater infrastructure design

NASA Astrophysics Data System (ADS)

Jun, Changhyun; Qin, Xiaosheng; Gan, Thian Yew; Tung, Yeou-Koung; De Michele, Carlo

2017-10-01

This study presents a storm-event based bivariate frequency analysis approach to determine design rainfalls in which, the number, intensity and duration of actual rainstorm events were considered. To derive more realistic design storms, the occurrence probability of an individual rainstorm event was determined from the joint distribution of storm intensity and duration through a copula model. Hourly rainfall data were used at three climate stations respectively located in Singapore, South Korea and Canada. It was found that the proposed approach could give a more realistic description of rainfall characteristics of rainstorm events and design rainfalls. As results, the design rainfall quantities from actual rainstorm events at the three studied sites are consistently lower than those obtained from the conventional rainfall depth-duration-frequency (DDF) method, especially for short-duration storms (such as 1-h). It results from occurrence probabilities of each rainstorm event and a different angle for rainfall frequency analysis, and could offer an alternative way of describing extreme rainfall properties and potentially help improve the hydrologic design of stormwater management facilities in urban areas.

Bivariate normal, conditional and rectangular probabilities: A computer program with applications

NASA Technical Reports Server (NTRS)

Swaroop, R.; Brownlow, J. D.; Ashwworth, G. R.; Winter, W. R.

1980-01-01

Some results for the bivariate normal distribution analysis are presented. Computer programs for conditional normal probabilities, marginal probabilities, as well as joint probabilities for rectangular regions are given: routines for computing fractile points and distribution functions are also presented. Some examples from a closed circuit television experiment are included.

Simultaneous determination of Nifuroxazide and Drotaverine hydrochloride in pharmaceutical preparations by bivariate and multivariate spectral analysis

NASA Astrophysics Data System (ADS)

Metwally, Fadia H.

2008-02-01

The quantitative predictive abilities of the new and simple bivariate spectrophotometric method are compared with the results obtained by the use of multivariate calibration methods [the classical least squares (CLS), principle component regression (PCR) and partial least squares (PLS)], using the information contained in the absorption spectra of the appropriate solutions. Mixtures of the two drugs Nifuroxazide (NIF) and Drotaverine hydrochloride (DRO) were resolved by application of the bivariate method. The different chemometric approaches were applied also with previous optimization of the calibration matrix, as they are useful in simultaneous inclusion of many spectral wavelengths. The results found by application of the bivariate, CLS, PCR and PLS methods for the simultaneous determinations of mixtures of both components containing 2-12 μg ml -1 of NIF and 2-8 μg ml -1 of DRO are reported. Both approaches were satisfactorily applied to the simultaneous determination of NIF and DRO in pure form and in pharmaceutical formulation. The results were in accordance with those given by the EVA Pharma reference spectrophotometric method.

Bivariate copula in fitting rainfall data

NASA Astrophysics Data System (ADS)

Yee, Kong Ching; Suhaila, Jamaludin; Yusof, Fadhilah; Mean, Foo Hui

2014-07-01

The usage of copula to determine the joint distribution between two variables is widely used in various areas. The joint distribution of rainfall characteristic obtained using the copula model is more ideal than the standard bivariate modelling where copula is belief to have overcome some limitation. Six copula models will be applied to obtain the most suitable bivariate distribution between two rain gauge stations. The copula models are Ali-Mikhail-Haq (AMH), Clayton, Frank, Galambos, Gumbel-Hoogaurd (GH) and Plackett. The rainfall data used in the study is selected from rain gauge stations which are located in the southern part of Peninsular Malaysia, during the period from 1980 to 2011. The goodness-of-fit test in this study is based on the Akaike information criterion (AIC).

Fisher information for two gamma frailty bivariate Weibull models.

PubMed

Bjarnason, H; Hougaard, P

2000-03-01

The asymptotic properties of frailty models for multivariate survival data are not well understood. To study this aspect, the Fisher information is derived in the standard bivariate gamma frailty model, where the survival distribution is of Weibull form conditional on the frailty. For comparison, the Fisher information is also derived in the bivariate gamma frailty model, where the marginal distribution is of Weibull form.

Evidence for bivariate linkage of obesity and HDL-C levels in the Framingham Heart Study.

PubMed

Arya, Rector; Lehman, Donna; Hunt, Kelly J; Schneider, Jennifer; Almasy, Laura; Blangero, John; Stern, Michael P; Duggirala, Ravindranath

2003-12-31

Epidemiological studies have indicated that obesity and low high-density lipoprotein (HDL) levels are strong cardiovascular risk factors, and that these traits are inversely correlated. Despite the belief that these traits are correlated in part due to pleiotropy, knowledge on specific genes commonly affecting obesity and dyslipidemia is very limited. To address this issue, we first conducted univariate multipoint linkage analysis for body mass index (BMI) and HDL-C to identify loci influencing variation in these phenotypes using Framingham Heart Study data relating to 1702 subjects distributed across 330 pedigrees. Subsequently, we performed bivariate multipoint linkage analysis to detect common loci influencing covariation between these two traits. We scanned the genome and identified a major locus near marker D6S1009 influencing variation in BMI (LOD = 3.9) using the program SOLAR. We also identified a major locus for HDL-C near marker D2S1334 on chromosome 2 (LOD = 3.5) and another region near marker D6S1009 on chromosome 6 with suggestive evidence for linkage (LOD = 2.7). Since these two phenotypes have been independently mapped to the same region on chromosome 6q, we used the bivariate multipoint linkage approach using SOLAR. The bivariate linkage analysis of BMI and HDL-C implicated the genetic region near marker D6S1009 as harboring a major gene commonly influencing these phenotypes (bivariate LOD = 6.2; LODeq = 5.5) and appears to improve power to map the correlated traits to a region, precisely. We found substantial evidence for a quantitative trait locus with pleiotropic effects, which appears to influence both BMI and HDL-C phenotypes in the Framingham data.

Numerical analysis of the accuracy of bivariate quantile distributions utilizing copulas compared to the GUM supplement 2 for oil pressure balance uncertainties

NASA Astrophysics Data System (ADS)

Ramnath, Vishal

2017-11-01

In the field of pressure metrology the effective area is Ae = A0 (1 + λP) where A0 is the zero-pressure area and λ is the distortion coefficient and the conventional practise is to construct univariate probability density functions (PDFs) for A0 and λ. As a result analytical generalized non-Gaussian bivariate joint PDFs has not featured prominently in pressure metrology. Recently extended lambda distribution based quantile functions have been successfully utilized for summarizing univariate arbitrary PDF distributions of gas pressure balances. Motivated by this development we investigate the feasibility and utility of extending and applying quantile functions to systems which naturally exhibit bivariate PDFs. Our approach is to utilize the GUM Supplement 1 methodology to solve and generate Monte Carlo based multivariate uncertainty data for an oil based pressure balance laboratory standard that is used to generate known high pressures, and which are in turn cross-floated against another pressure balance transfer standard in order to deduce the transfer standard's respective area. We then numerically analyse the uncertainty data by formulating and constructing an approximate bivariate quantile distribution that directly couples A0 and λ in order to compare and contrast its accuracy to an exact GUM Supplement 2 based uncertainty quantification analysis.

Some bivariate distributions for modeling the strength properties of lumber

Treesearch

Richard A. Johnson; James W. Evans; David W. Green

Accurate modeling of the joint stochastic nature of the strength properties of dimension lumber is essential to the determination of reliability-based design safety factors. This report reviews the major techniques for obtaining bivariate distributions and then discusses bivariate distributions whose marginal distributions suggest they might be useful for modeling the...

Contributions to the Underlying Bivariate Normal Method for Factor Analyzing Ordinal Data

ERIC Educational Resources Information Center

Xi, Nuo; Browne, Michael W.

2014-01-01

A promising "underlying bivariate normal" approach was proposed by Jöreskog and Moustaki for use in the factor analysis of ordinal data. This was a limited information approach that involved the maximization of a composite likelihood function. Its advantage over full-information maximum likelihood was that very much less computation was…

A comparison of bivariate, multivariate random-effects, and Poisson correlated gamma-frailty models to meta-analyze individual patient data of ordinal scale diagnostic tests.

PubMed

Simoneau, Gabrielle; Levis, Brooke; Cuijpers, Pim; Ioannidis, John P A; Patten, Scott B; Shrier, Ian; Bombardier, Charles H; de Lima Osório, Flavia; Fann, Jesse R; Gjerdingen, Dwenda; Lamers, Femke; Lotrakul, Manote; Löwe, Bernd; Shaaban, Juwita; Stafford, Lesley; van Weert, Henk C P M; Whooley, Mary A; Wittkampf, Karin A; Yeung, Albert S; Thombs, Brett D; Benedetti, Andrea

2017-11-01

Individual patient data (IPD) meta-analyses are increasingly common in the literature. In the context of estimating the diagnostic accuracy of ordinal or semi-continuous scale tests, sensitivity and specificity are often reported for a given threshold or a small set of thresholds, and a meta-analysis is conducted via a bivariate approach to account for their correlation. When IPD are available, sensitivity and specificity can be pooled for every possible threshold. Our objective was to compare the bivariate approach, which can be applied separately at every threshold, to two multivariate methods: the ordinal multivariate random-effects model and the Poisson correlated gamma-frailty model. Our comparison was empirical, using IPD from 13 studies that evaluated the diagnostic accuracy of the 9-item Patient Health Questionnaire depression screening tool, and included simulations. The empirical comparison showed that the implementation of the two multivariate methods is more laborious in terms of computational time and sensitivity to user-supplied values compared to the bivariate approach. Simulations showed that ignoring the within-study correlation of sensitivity and specificity across thresholds did not worsen inferences with the bivariate approach compared to the Poisson model. The ordinal approach was not suitable for simulations because the model was highly sensitive to user-supplied starting values. We tentatively recommend the bivariate approach rather than more complex multivariate methods for IPD diagnostic accuracy meta-analyses of ordinal scale tests, although the limited type of diagnostic data considered in the simulation study restricts the generalization of our findings. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Bivariate sub-Gaussian model for stock index returns

NASA Astrophysics Data System (ADS)

Jabłońska-Sabuka, Matylda; Teuerle, Marek; Wyłomańska, Agnieszka

2017-11-01

Financial time series are commonly modeled with methods assuming data normality. However, the real distribution can be nontrivial, also not having an explicitly formulated probability density function. In this work we introduce novel parameter estimation and high-powered distribution testing methods which do not rely on closed form densities, but use the characteristic functions for comparison. The approach applied to a pair of stock index returns demonstrates that such a bivariate vector can be a sample coming from a bivariate sub-Gaussian distribution. The methods presented here can be applied to any nontrivially distributed financial data, among others.

Multiple imputation methods for bivariate outcomes in cluster randomised trials.

PubMed

DiazOrdaz, K; Kenward, M G; Gomes, M; Grieve, R

2016-09-10

Missing observations are common in cluster randomised trials. The problem is exacerbated when modelling bivariate outcomes jointly, as the proportion of complete cases is often considerably smaller than the proportion having either of the outcomes fully observed. Approaches taken to handling such missing data include the following: complete case analysis, single-level multiple imputation that ignores the clustering, multiple imputation with a fixed effect for each cluster and multilevel multiple imputation. We contrasted the alternative approaches to handling missing data in a cost-effectiveness analysis that uses data from a cluster randomised trial to evaluate an exercise intervention for care home residents. We then conducted a simulation study to assess the performance of these approaches on bivariate continuous outcomes, in terms of confidence interval coverage and empirical bias in the estimated treatment effects. Missing-at-random clustered data scenarios were simulated following a full-factorial design. Across all the missing data mechanisms considered, the multiple imputation methods provided estimators with negligible bias, while complete case analysis resulted in biased treatment effect estimates in scenarios where the randomised treatment arm was associated with missingness. Confidence interval coverage was generally in excess of nominal levels (up to 99.8%) following fixed-effects multiple imputation and too low following single-level multiple imputation. Multilevel multiple imputation led to coverage levels of approximately 95% throughout. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

A Bivariate return period for levee failure monitoring

NASA Astrophysics Data System (ADS)

Isola, M.; Caporali, E.

2017-12-01

Levee breaches are strongly linked with the interaction processes among water, soil and structure, thus many are the factors that affect the breach development. One of the main is the hydraulic load, characterized by intensity and duration, i.e. by the flood event hydrograph. On the magnitude of the hydraulic load is based the levee design, generally without considering the fatigue failure due to the load duration. Moreover, many are the cases in which the levee breach are characterized by flood of magnitude lower than the design one. In order to implement the strategies of flood risk management, we built here a procedure based on a multivariate statistical analysis of flood peak and volume together with the analysis of the past levee failure events. Particularly, in order to define the probability of occurrence of the hydraulic load on a levee, a bivariate copula model is used to obtain the bivariate joint distribution of flood peak and volume. Flood peak is the expression of the load magnitude, while the volume is the expression of the stress over time. We consider the annual flood peak and the relative volume. The volume is given by the hydrograph area between the beginning and the end of event. The beginning of the event is identified as an abrupt rise of the discharge by more than 20%. The end is identified as the point from which the receding limb is characterized by the baseflow, using a nonlinear reservoir algorithm as baseflow separation technique. By this, with the aim to define warning thresholds we consider the past levee failure events and the relative bivariate return period (BTr) compared with the estimation of a traditional univariate model. The discharge data of 30 hydrometric stations of Arno River in Tuscany, Italy, in the period 1995-2016 are analysed. The database of levee failure events, considering for each event the location as well as the failure mode, is also created. The events were registered in the period 2000-2014 by EEA

A User’s Guide to BISAM (BIvariate SAMple): The Bivariate Data Modeling Program.

DTIC Science & Technology

1983-08-01

method for the null case specified and is then used to form the bivariate density-quantile function as described in section 4. If D(U) in stage...employed assigns average ranks for tied observations. Other methods for assigning ranks to tied observations are often employed but are not attempted...34 €.. . . . .. . .. . . . ,.. . ,•. . . ... *.., .. , - . . . . - - . . .. - -. .. observations will weaken the results obtained since underlying continuous distributions are assumed. One should avoid such situations if possible. Two methods

The bivariate regression model and its application

NASA Astrophysics Data System (ADS)

Pratikno, B.; Sulistia, L.; Saniyah

2018-03-01

The paper studied a bivariate regression model (BRM) and its application. The maximum power and minimum size are used to choose the eligible tests using non-sample prior information (NSPI). In the simulation study on real data, we used Wilk’s lamda to determine the best model of the BRM. The result showed that the power of the pre-test-test (PTT) on the NSPI is a significant choice of the tests among unrestricted test (UT) and restricted test (RT), and the best model of the BRM is Y (1) = ‑894 + 46X and Y (2) = 78 + 0.2X with significant Wilk’s lamda 0.88 < 0.90 (Wilk’s table).

Application of continuous normal-lognormal bivariate density functions in a sensitivity analysis of municipal solid waste landfill.

PubMed

Petrovic, Igor; Hip, Ivan; Fredlund, Murray D

2016-09-01

The variability of untreated municipal solid waste (MSW) shear strength parameters, namely cohesion and shear friction angle, with respect to waste stability problems, is of primary concern due to the strong heterogeneity of MSW. A large number of municipal solid waste (MSW) shear strength parameters (friction angle and cohesion) were collected from published literature and analyzed. The basic statistical analysis has shown that the central tendency of both shear strength parameters fits reasonably well within the ranges of recommended values proposed by different authors. In addition, it was established that the correlation between shear friction angle and cohesion is not strong but it still remained significant. Through use of a distribution fitting method it was found that the shear friction angle could be adjusted to a normal probability density function while cohesion follows the log-normal density function. The continuous normal-lognormal bivariate density function was therefore selected as an adequate model to ascertain rational boundary values ("confidence interval") for MSW shear strength parameters. It was concluded that a curve with a 70% confidence level generates a "confidence interval" within the reasonable limits. With respect to the decomposition stage of the waste material, three different ranges of appropriate shear strength parameters were indicated. Defined parameters were then used as input parameters for an Alternative Point Estimated Method (APEM) stability analysis on a real case scenario of the Jakusevec landfill. The Jakusevec landfill is the disposal site of the capital of Croatia - Zagreb. The analysis shows that in the case of a dry landfill the most significant factor influencing the safety factor was the shear friction angle of old, decomposed waste material, while in the case of a landfill with significant leachate level the most significant factor influencing the safety factor was the cohesion of old, decomposed waste material. The

Spectrum-based estimators of the bivariate Hurst exponent

NASA Astrophysics Data System (ADS)

Kristoufek, Ladislav

2014-12-01

We discuss two alternate spectrum-based estimators of the bivariate Hurst exponent in the power-law cross-correlations setting, the cross-periodogram and local X -Whittle estimators, as generalizations of their univariate counterparts. As the spectrum-based estimators are dependent on a part of the spectrum taken into consideration during estimation, a simulation study showing performance of the estimators under varying bandwidth parameter as well as correlation between processes and their specification is provided as well. These estimators are less biased than the already existent averaged periodogram estimator, which, however, has slightly lower variance. The spectrum-based estimators can serve as a good complement to the popular time domain estimators.

Modeling continuous covariates with a "spike" at zero: Bivariate approaches.

PubMed

Jenkner, Carolin; Lorenz, Eva; Becher, Heiko; Sauerbrei, Willi

2016-07-01

In epidemiology and clinical research, predictors often take value zero for a large amount of observations while the distribution of the remaining observations is continuous. These predictors are called variables with a spike at zero. Examples include smoking or alcohol consumption. Recently, an extension of the fractional polynomial (FP) procedure, a technique for modeling nonlinear relationships, was proposed to deal with such situations. To indicate whether or not a value is zero, a binary variable is added to the model. In a two stage procedure, called FP-spike, the necessity of the binary variable and/or the continuous FP function for the positive part are assessed for a suitable fit. In univariate analyses, the FP-spike procedure usually leads to functional relationships that are easy to interpret. This paper introduces four approaches for dealing with two variables with a spike at zero (SAZ). The methods depend on the bivariate distribution of zero and nonzero values. Bi-Sep is the simplest of the four bivariate approaches. It uses the univariate FP-spike procedure separately for the two SAZ variables. In Bi-D3, Bi-D1, and Bi-Sub, proportions of zeros in both variables are considered simultaneously in the binary indicators. Therefore, these strategies can account for correlated variables. The methods can be used for arbitrary distributions of the covariates. For illustration and comparison of results, data from a case-control study on laryngeal cancer, with smoking and alcohol intake as two SAZ variables, is considered. In addition, a possible extension to three or more SAZ variables is outlined. A combination of log-linear models for the analysis of the correlation in combination with the bivariate approaches is proposed. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Unadjusted Bivariate Two-Group Comparisons: When Simpler is Better.

PubMed

Vetter, Thomas R; Mascha, Edward J

2018-01-01

Hypothesis testing involves posing both a null hypothesis and an alternative hypothesis. This basic statistical tutorial discusses the appropriate use, including their so-called assumptions, of the common unadjusted bivariate tests for hypothesis testing and thus comparing study sample data for a difference or association. The appropriate choice of a statistical test is predicated on the type of data being analyzed and compared. The unpaired or independent samples t test is used to test the null hypothesis that the 2 population means are equal, thereby accepting the alternative hypothesis that the 2 population means are not equal. The unpaired t test is intended for comparing dependent continuous (interval or ratio) data from 2 study groups. A common mistake is to apply several unpaired t tests when comparing data from 3 or more study groups. In this situation, an analysis of variance with post hoc (posttest) intragroup comparisons should instead be applied. Another common mistake is to apply a series of unpaired t tests when comparing sequentially collected data from 2 study groups. In this situation, a repeated-measures analysis of variance, with tests for group-by-time interaction, and post hoc comparisons, as appropriate, should instead be applied in analyzing data from sequential collection points. The paired t test is used to assess the difference in the means of 2 study groups when the sample observations have been obtained in pairs, often before and after an intervention in each study subject. The Pearson chi-square test is widely used to test the null hypothesis that 2 unpaired categorical variables, each with 2 or more nominal levels (values), are independent of each other. When the null hypothesis is rejected, 1 concludes that there is a probable association between the 2 unpaired categorical variables. When comparing 2 groups on an ordinal or nonnormally distributed continuous outcome variable, the 2-sample t test is usually not appropriate. The

Developing a bivariate spatial association measure: An integration of Pearson's r and Moran's I

NASA Astrophysics Data System (ADS)

Lee, Sang-Il

This research is concerned with developing a bivariate spatial association measure or spatial correlation coefficient, which is intended to capture spatial association among observations in terms of their point-to-point relationships across two spatial patterns. The need for parameterization of the bivariate spatial dependence is precipitated by the realization that aspatial bivariate association measures, such as Pearson's correlation coefficient, do not recognize spatial distributional aspects of data sets. This study devises an L statistic by integrating Pearson's r as an aspatial bivariate association measure and Moran's I as a univariate spatial association measure. The concept of a spatial smoothing scalar (SSS) plays a pivotal role in this task.

Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogates.

PubMed

Andrzejak, R G; Chicharro, D; Lehnertz, K; Mormann, F

2011-04-01

The disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free interval. In multichannel recordings from brain areas involved in the epileptic process, this interdependence can be reflected in an increased linear cross correlation but also in signal properties of higher order. Bivariate time series analysis comprises a variety of approaches, each with different degrees of sensitivity and specificity for interdependencies reflected in lower- or higher-order properties of pairs of simultaneously recorded signals. Here we investigate which approach is best suited to detect putatively elevated interdependence levels in signals recorded from brain areas involved in the epileptic process. For this purpose, we use the linear cross correlation that is sensitive to lower-order signatures of interdependence, a nonlinear interdependence measure that integrates both lower- and higher-order properties, and a surrogate-corrected nonlinear interdependence measure that aims to specifically characterize higher-order properties. We analyze intracranial electroencephalographic recordings of the seizure-free interval from 29 patients with an epileptic focus located in the medial temporal lobe. Our results show that all three approaches detect higher levels of interdependence for signals recorded from the brain hemisphere containing the epileptic focus as compared to signals recorded from the opposite hemisphere. For the linear cross correlation, however, these differences are not significant. For the nonlinear interdependence measure, results are significant but only of moderate accuracy with regard to the discriminative power for the focal and nonfocal hemispheres. The highest significance and accuracy is obtained for the surrogate-corrected nonlinear

Using bivariate signal analysis to characterize the epileptic focus: The benefit of surrogates

NASA Astrophysics Data System (ADS)

Andrzejak, R. G.; Chicharro, D.; Lehnertz, K.; Mormann, F.

2011-04-01

The disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free interval. In multichannel recordings from brain areas involved in the epileptic process, this interdependence can be reflected in an increased linear cross correlation but also in signal properties of higher order. Bivariate time series analysis comprises a variety of approaches, each with different degrees of sensitivity and specificity for interdependencies reflected in lower- or higher-order properties of pairs of simultaneously recorded signals. Here we investigate which approach is best suited to detect putatively elevated interdependence levels in signals recorded from brain areas involved in the epileptic process. For this purpose, we use the linear cross correlation that is sensitive to lower-order signatures of interdependence, a nonlinear interdependence measure that integrates both lower- and higher-order properties, and a surrogate-corrected nonlinear interdependence measure that aims to specifically characterize higher-order properties. We analyze intracranial electroencephalographic recordings of the seizure-free interval from 29 patients with an epileptic focus located in the medial temporal lobe. Our results show that all three approaches detect higher levels of interdependence for signals recorded from the brain hemisphere containing the epileptic focus as compared to signals recorded from the opposite hemisphere. For the linear cross correlation, however, these differences are not significant. For the nonlinear interdependence measure, results are significant but only of moderate accuracy with regard to the discriminative power for the focal and nonfocal hemispheres. The highest significance and accuracy is obtained for the surrogate-corrected nonlinear

A bivariate model for analyzing recurrent multi-type automobile failures

NASA Astrophysics Data System (ADS)

Sunethra, A. A.; Sooriyarachchi, M. R.

2017-09-01

The failure mechanism in an automobile can be defined as a system of multi-type recurrent failures where failures can occur due to various multi-type failure modes and these failures are repetitive such that more than one failure can occur from each failure mode. In analysing such automobile failures, both the time and type of the failure serve as response variables. However, these two response variables are highly correlated with each other since the timing of failures has an association with the mode of the failure. When there are more than one correlated response variables, the fitting of a multivariate model is more preferable than separate univariate models. Therefore, a bivariate model of time and type of failure becomes appealing for such automobile failure data. When there are multiple failure observations pertaining to a single automobile, such data cannot be treated as independent data because failure instances of a single automobile are correlated with each other while failures among different automobiles can be treated as independent. Therefore, this study proposes a bivariate model consisting time and type of failure as responses adjusted for correlated data. The proposed model was formulated following the approaches of shared parameter models and random effects models for joining the responses and for representing the correlated data respectively. The proposed model is applied to a sample of automobile failures with three types of failure modes and up to five failure recurrences. The parametric distributions that were suitable for the two responses of time to failure and type of failure were Weibull distribution and multinomial distribution respectively. The proposed bivariate model was programmed in SAS Procedure Proc NLMIXED by user programming appropriate likelihood functions. The performance of the bivariate model was compared with separate univariate models fitted for the two responses and it was identified that better performance is secured by

The return period analysis of natural disasters with statistical modeling of bivariate joint probability distribution.

PubMed

Li, Ning; Liu, Xueqin; Xie, Wei; Wu, Jidong; Zhang, Peng

2013-01-01

New features of natural disasters have been observed over the last several years. The factors that influence the disasters' formation mechanisms, regularity of occurrence and main characteristics have been revealed to be more complicated and diverse in nature than previously thought. As the uncertainty involved increases, the variables need to be examined further. This article discusses the importance and the shortage of multivariate analysis of natural disasters and presents a method to estimate the joint probability of the return periods and perform a risk analysis. Severe dust storms from 1990 to 2008 in Inner Mongolia were used as a case study to test this new methodology, as they are normal and recurring climatic phenomena on Earth. Based on the 79 investigated events and according to the dust storm definition with bivariate, the joint probability distribution of severe dust storms was established using the observed data of maximum wind speed and duration. The joint return periods of severe dust storms were calculated, and the relevant risk was analyzed according to the joint probability. The copula function is able to simulate severe dust storm disasters accurately. The joint return periods generated are closer to those observed in reality than the univariate return periods and thus have more value in severe dust storm disaster mitigation, strategy making, program design, and improvement of risk management. This research may prove useful in risk-based decision making. The exploration of multivariate analysis methods can also lay the foundation for further applications in natural disaster risk analysis. © 2012 Society for Risk Analysis.

Effect of catchment properties and flood generation regime on copula selection for bivariate flood frequency analysis

NASA Astrophysics Data System (ADS)

Filipova, Valeriya; Lawrence, Deborah; Klempe, Harald

2018-02-01

Applying copula-based bivariate flood frequency analysis is advantageous because the results provide information on both the flood peak and volume. More data are, however, required for such an analysis, and it is often the case that only data series with a limited record length are available. To overcome this issue of limited record length, data regarding climatic and geomorphological properties can be used to complement statistical methods. In this paper, we present a study of 27 catchments located throughout Norway, in which we assess whether catchment properties, flood generation processes and flood regime have an effect on the correlation between flood peak and volume and, in turn, on the selection of copulas. To achieve this, the annual maximum flood events were first classified into events generated primarily by rainfall, snowmelt or a combination of these. The catchments were then classified into flood regime, depending on the predominant flood generation process producing the annual maximum flood events. A contingency table and Fisher's exact test were used to determine the factors that affect the selection of copulas in the study area. The results show that the two-parameter copulas BB1 and BB7 are more commonly selected in catchments with high steepness, high mean annual runoff and rainfall flood regime. These findings suggest that in these types of catchments, the dependence structure between flood peak and volume is more complex and cannot be modeled effectively using a one-parameter copula. The results illustrate that by relating copula types to flood regime and catchment properties, additional information can be supplied for selecting copulas in catchments with limited data.

A Method for Approximating the Bivariate Normal Correlation Coefficient.

ERIC Educational Resources Information Center

Kirk, David B.

Improvements of the Gaussian quadrature in conjunction with the Newton-Raphson iteration technique (TM 000 789) are discussed as effective methods of calculating the bivariate normal correlation coefficient. (CK)

Computational approach to Thornley's problem by bivariate operational calculus

NASA Astrophysics Data System (ADS)

Bazhlekova, E.; Dimovski, I.

2012-10-01

Thornley's problem is an initial-boundary value problem with a nonlocal boundary condition for linear onedimensional reaction-diffusion equation, used as a mathematical model of spiral phyllotaxis in botany. Applying a bivariate operational calculus we find explicit representation of the solution, containing two convolution products of special solutions and the arbitrary initial and boundary functions. We use a non-classical convolution with respect to the space variable, extending in this way the classical Duhamel principle. The special solutions involved are represented in the form of fast convergent series. Numerical examples are considered to show the application of the present technique and to analyze the character of the solution.

Cost-effectiveness analysis using data from multinational trials: The use of bivariate hierarchical modelling

PubMed Central

Manca, Andrea; Lambert, Paul C; Sculpher, Mark; Rice, Nigel

2008-01-01

Healthcare cost-effectiveness analysis (CEA) often uses individual patient data (IPD) from multinational randomised controlled trials. Although designed to account for between-patient sampling variability in the clinical and economic data, standard analytical approaches to CEA ignore the presence of between-location variability in the study results. This is a restrictive limitation given that countries often differ in factors that could affect the results of CEAs, such as the availability of healthcare resources, their unit costs, clinical practice, and patient case-mix. We advocate the use of Bayesian bivariate hierarchical modelling to analyse multinational cost-effectiveness data. This analytical framework explicitly recognises that patient-level costs and outcomes are nested within countries. Using real life data, we illustrate how the proposed methods can be applied to obtain (a) more appropriate estimates of overall cost-effectiveness and associated measure of sampling uncertainty compared to standard CEA; and (b) country-specific cost-effectiveness estimates which can be used to assess the between-location variability of the study results, while controlling for differences in country-specific and patient-specific characteristics. It is demonstrated that results from standard CEA using IPD from multinational trials display a large degree of variability across the 17 countries included in the analysis, producing potentially misleading results. In contrast, ‘shrinkage estimates’ obtained from the modelling approach proposed here facilitate the appropriate quantification of country-specific cost-effectiveness estimates, while weighting the results based on the level of information available within each country. We suggest that the methods presented here represent a general framework for the analysis of economic data collected from different locations. PMID:17641141

A Bivariate Generalized Linear Item Response Theory Modeling Framework to the Analysis of Responses and Response Times.

PubMed

Molenaar, Dylan; Tuerlinckx, Francis; van der Maas, Han L J

2015-01-01

A generalized linear modeling framework to the analysis of responses and response times is outlined. In this framework, referred to as bivariate generalized linear item response theory (B-GLIRT), separate generalized linear measurement models are specified for the responses and the response times that are subsequently linked by cross-relations. The cross-relations can take various forms. Here, we focus on cross-relations with a linear or interaction term for ability tests, and cross-relations with a curvilinear term for personality tests. In addition, we discuss how popular existing models from the psychometric literature are special cases in the B-GLIRT framework depending on restrictions in the cross-relation. This allows us to compare existing models conceptually and empirically. We discuss various extensions of the traditional models motivated by practical problems. We also illustrate the applicability of our approach using various real data examples, including data on personality and cognitive ability.

New approach in bivariate drought duration and severity analysis

NASA Astrophysics Data System (ADS)

Montaseri, Majid; Amirataee, Babak; Rezaie, Hossein

2018-04-01

The copula functions have been widely applied as an advance technique to create joint probability distribution of drought duration and severity. The approach of data collection as well as the amount of data and dispersion of data series can last a significant impact on creating such joint probability distribution using copulas. Usually, such traditional analyses have shed an Unconnected Drought Runs (UDR) approach towards droughts. In other word, droughts with different durations would be independent of each other. Emphasis on such data collection method causes the omission of actual potentials of short-term extreme droughts located within a long-term UDR. Meanwhile, traditional method is often faced with significant gap in drought data series. However, a long-term UDR can be approached as a combination of short-term Connected Drought Runs (CDR). Therefore this study aims to evaluate systematically two UDR and CDR procedures in joint probability of drought duration and severity investigations. For this purpose, rainfall data (1971-2013) from 24 rain gauges in Lake Urmia basin, Iran were applied. Also, seven common univariate marginal distributions and seven types of bivariate copulas were examined. Compared to traditional approach, the results demonstrated a significant comparative advantage of the new approach. Such comparative advantages led to determine the correct copula function, more accurate estimation of copula parameter, more realistic estimation of joint/conditional probabilities of drought duration and severity and significant reduction in uncertainty for modeling.

Combine bivariate statistics analysis and multivariate statistics analysis to assess landslide susceptibility in Chen-Yu-Lan watershed, Nantou, Taiwan.

NASA Astrophysics Data System (ADS)

Ngan Nguyen, Thi To; Liu, Cheng-Chien

2013-04-01

How landslides occurred and which factors triggered and sped up landslide occurrences were usually asked by researchers in the past decades. Many investigations carried out in many places in the world to finding out methods that predict and prevent damages from landslides phenomena. Chen-Yu-Lan River watershed is reputed as a 'hot pot' of landslide researches in Taiwan by its complicated geological structures with the significant tectonic fault systems and steeply mountainous terrain. Beside annual high precipitation concentration and the abrupt slopes, some natural disaster, as typhoons (Sinlaku-2008, Kalmaegi-2008, and Marakot-2009) and earthquake (Chi-Chi earthquake-1999) are also the triggered factors cause landslides with serious damages in this place. This research expresses the quantitative approaches to generate landslide susceptible map for Chen-Yu-Lan watershed, a mountainous area in the central Taiwan. Landslide inventories data, which were detected from the Formosat-2 imageries for eight years from 2004 to 2011, were applied to carry out landslide susceptibility mapping. Bivariate statistics analysis and multivariate statistics analysis would be applied to calculate susceptible index of landslides. The weights of parameters were computed based on landslide data for eight years from 2004 to 2011. To validate effective levels of factors to landslide occurrences, this method built some multivariate algorithms and compared these results with real landslide occurrences. Besides this method, the historical data of landslides were also used to assess and classify landslide susceptibility levels. From long-term landslide data, relation between landslide susceptibility levels and landslide repetition was assigned. The results demonstrated differently effective levels of potential factors, such as, slope gradient, drainage density, lithology and land use to landslide phenomena. The results also showed logical relationship between weights and characteristics of

Bivariate versus multivariate smart spectrophotometric calibration methods for the simultaneous determination of a quaternary mixture of mosapride, pantoprazole and their degradation products.

PubMed

Hegazy, M A; Yehia, A M; Moustafa, A A

2013-05-01

The ability of bivariate and multivariate spectrophotometric methods was demonstrated in the resolution of a quaternary mixture of mosapride, pantoprazole and their degradation products. The bivariate calibrations include bivariate spectrophotometric method (BSM) and H-point standard addition method (HPSAM), which were able to determine the two drugs, simultaneously, but not in the presence of their degradation products, the results showed that simultaneous determinations could be performed in the concentration ranges of 5.0-50.0 microg/ml for mosapride and 10.0-40.0 microg/ml for pantoprazole by bivariate spectrophotometric method and in the concentration ranges of 5.0-45.0 microg/ml for both drugs by H-point standard addition method. Moreover, the applied multivariate calibration methods were able for the determination of mosapride, pantoprazole and their degradation products using concentration residuals augmented classical least squares (CRACLS) and partial least squares (PLS). The proposed multivariate methods were applied to 17 synthetic samples in the concentration ranges of 3.0-12.0 microg/ml mosapride, 8.0-32.0 microg/ml pantoprazole, 1.5-6.0 microg/ml mosapride degradation products and 2.0-8.0 microg/ml pantoprazole degradation products. The proposed bivariate and multivariate calibration methods were successfully applied to the determination of mosapride and pantoprazole in their pharmaceutical preparations.

Analysis of competition performance in dressage and show jumping of Dutch Warmblood horses.

PubMed

Rovere, G; Ducro, B J; van Arendonk, J A M; Norberg, E; Madsen, P

2016-12-01

Most Warmblood horse studbooks aim to improve the performance in dressage and show jumping. The Dutch Royal Warmblood Studbook (KWPN) includes the highest score achieved in competition by a horse to evaluate its genetic ability of performance. However, the records collected during competition are associated with some aspects that might affect the quality of the genetic evaluation based on these records. These aspects include the influence of rider, censoring and preselection of the data. The aim of this study was to quantify the impact of rider effect, censoring and preselection on the genetic analysis of competition data of dressage and show jumping of KWPN. Different models including rider effect were evaluated. To assess the impact of censoring, genetic parameters were estimated in data sets that differed in the degree of censoring. The effect of preselection on variance components was analysed by defining a binary trait (sport-status) depending on whether the horse has a competition record or not. This trait was included in a bivariate model with the competition trait and used all horses registered by KWPN since 1984. Results showed that performance in competition for dressage and show jumping is a heritable trait (h 2 ~ 0.11-0.13) and that it is important to account for the effect of rider in the genetic analysis. Censoring had a small effect on the genetic parameter for highest performance achieved by the horse. A moderate heritability obtained for sport-status indicates that preselection has a genetic basis, but the effect on genetic parameters was relatively small. © 2016 Blackwell Verlag GmbH.

Bivariate- distribution for transition matrix elements in Breit-Wigner to Gaussian domains of interacting particle systems.

PubMed

Kota, V K B; Chavda, N D; Sahu, R

2006-04-01

Interacting many-particle systems with a mean-field one-body part plus a chaos generating random two-body interaction having strength lambda exhibit Poisson to Gaussian orthogonal ensemble and Breit-Wigner (BW) to Gaussian transitions in level fluctuations and strength functions with transition points marked by lambda = lambda c and lambda = lambda F, respectively; lambda F > lambda c. For these systems a theory for the matrix elements of one-body transition operators is available, as valid in the Gaussian domain, with lambda > lambda F, in terms of orbital occupation numbers, level densities, and an integral involving a bivariate Gaussian in the initial and final energies. Here we show that, using a bivariate-t distribution, the theory extends below from the Gaussian regime to the BW regime up to lambda = lambda c. This is well tested in numerical calculations for 6 spinless fermions in 12 single-particle states.

Sequential deconvolution from wave-front sensing using bivariate simplex splines

NASA Astrophysics Data System (ADS)

Guo, Shiping; Zhang, Rongzhi; Li, Jisheng; Zou, Jianhua; Xu, Rong; Liu, Changhai

2015-05-01

Deconvolution from wave-front sensing (DWFS) is an imaging compensation technique for turbulence degraded images based on simultaneous recording of short exposure images and wave-front sensor data. This paper employs the multivariate splines method for the sequential DWFS: a bivariate simplex splines based average slopes measurement model is built firstly for Shack-Hartmann wave-front sensor; next, a well-conditioned least squares estimator for the spline coefficients is constructed using multiple Shack-Hartmann measurements; then, the distorted wave-front is uniquely determined by the estimated spline coefficients; the object image is finally obtained by non-blind deconvolution processing. Simulated experiments in different turbulence strength show that our method performs superior image restoration results and noise rejection capability especially when extracting the multidirectional phase derivatives.

Recurrent major depression and right hippocampal volume: A bivariate linkage and association study.

PubMed

Mathias, Samuel R; Knowles, Emma E M; Kent, Jack W; McKay, D Reese; Curran, Joanne E; de Almeida, Marcio A A; Dyer, Thomas D; Göring, Harald H H; Olvera, Rene L; Duggirala, Ravi; Fox, Peter T; Almasy, Laura; Blangero, John; Glahn, David C

2016-01-01

Previous work has shown that the hippocampus is smaller in the brains of individuals suffering from major depressive disorder (MDD) than those of healthy controls. Moreover, right hippocampal volume specifically has been found to predict the probability of subsequent depressive episodes. This study explored the utility of right hippocampal volume as an endophenotype of recurrent MDD (rMDD). We observed a significant genetic correlation between the two traits in a large sample of Mexican American individuals from extended pedigrees (ρg = -0.34, p = 0.013). A bivariate linkage scan revealed a significant pleiotropic quantitative trait locus on chromosome 18p11.31-32 (LOD = 3.61). Bivariate association analysis conducted under the linkage peak revealed a variant (rs574972) within an intron of the gene SMCHD1 meeting the corrected significance level (χ(2) = 19.0, p = 7.4 × 10(-5)). Univariate association analyses of each phenotype separately revealed that the same variant was significant for right hippocampal volume alone, and also revealed a suggestively significant variant (rs12455524) within the gene DLGAP1 for rMDD alone. The results implicate right-hemisphere hippocampal volume as a possible endophenotype of rMDD, and in so doing highlight a potential gene of interest for rMDD risk. © 2015 Wiley Periodicals, Inc.

Diagnostic value of sTREM-1 in bronchoalveolar lavage fluid in ICU patients with bacterial lung infections: a bivariate meta-analysis.

PubMed

Shi, Jia-Xin; Li, Jia-Shu; Hu, Rong; Li, Chun-Hua; Wen, Yan; Zheng, Hong; Zhang, Feng; Li, Qin

2013-01-01

The serum soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) is a useful biomarker in differentiating bacterial infections from others. However, the diagnostic value of sTREM-1 in bronchoalveolar lavage fluid (BALF) in lung infections has not been well established. We performed a meta-analysis to assess the accuracy of sTREM-1 in BALF for diagnosis of bacterial lung infections in intensive care unit (ICU) patients. We searched PUBMED, EMBASE and Web of Knowledge (from January 1966 to October 2012) databases for relevant studies that reported diagnostic accuracy data of BALF sTREM-1 in the diagnosis of bacterial lung infections in ICU patients. Pooled sensitivity, specificity, and positive and negative likelihood ratios were calculated by a bivariate regression analysis. Measures of accuracy and Q point value (Q*) were calculated using summary receiver operating characteristic (SROC) curve. The potential between-studies heterogeneity was explored by subgroup analysis. Nine studies were included in the present meta-analysis. Overall, the prevalence was 50.6%; the sensitivity was 0.87 (95% confidence interval (CI), 0.72-0.95); the specificity was 0.79 (95% CI, 0.56-0.92); the positive likelihood ratio (PLR) was 4.18 (95% CI, 1.78-9.86); the negative likelihood ratio (NLR) was 0.16 (95% CI, 0.07-0.36), and the diagnostic odds ratio (DOR) was 25.60 (95% CI, 7.28-89.93). The area under the SROC curve was 0.91 (95% CI, 0.88-0.93), with a Q* of 0.83. Subgroup analysis showed that the assay method and cutoff value influenced the diagnostic accuracy of sTREM-1. BALF sTREM-1 is a useful biomarker of bacterial lung infections in ICU patients. Further studies are needed to confirm the optimized cutoff value.

The Evaluation of Bivariate Mixed Models in Meta-analyses of Diagnostic Accuracy Studies with SAS, Stata and R.

PubMed

Vogelgesang, Felicitas; Schlattmann, Peter; Dewey, Marc

2018-05-01

Meta-analyses require a thoroughly planned procedure to obtain unbiased overall estimates. From a statistical point of view not only model selection but also model implementation in the software affects the results. The present simulation study investigates the accuracy of different implementations of general and generalized bivariate mixed models in SAS (using proc mixed, proc glimmix and proc nlmixed), Stata (using gllamm, xtmelogit and midas) and R (using reitsma from package mada and glmer from package lme4). Both models incorporate the relationship between sensitivity and specificity - the two outcomes of interest in meta-analyses of diagnostic accuracy studies - utilizing random effects. Model performance is compared in nine meta-analytic scenarios reflecting the combination of three sizes for meta-analyses (89, 30 and 10 studies) with three pairs of sensitivity/specificity values (97%/87%; 85%/75%; 90%/93%). The evaluation of accuracy in terms of bias, standard error and mean squared error reveals that all implementations of the generalized bivariate model calculate sensitivity and specificity estimates with deviations less than two percentage points. proc mixed which together with reitsma implements the general bivariate mixed model proposed by Reitsma rather shows convergence problems. The random effect parameters are in general underestimated. This study shows that flexibility and simplicity of model specification together with convergence robustness should influence implementation recommendations, as the accuracy in terms of bias was acceptable in all implementations using the generalized approach. Schattauer GmbH.

Association of Supply Type with Fecal Contamination of Source Water and Household Stored Drinking Water in Developing Countries: A Bivariate Meta-analysis

PubMed Central

Bain, Robert E.S.; Cronk, Ryan; Wright, Jim A.; Bartram, Jamie

2015-01-01

Background Access to safe drinking water is essential for health. Monitoring access to drinking water focuses on water supply type at the source, but there is limited evidence on whether quality differences at the source persist in water stored in the household. Objectives We assessed the extent of fecal contamination at the source and in household stored water (HSW) and explored the relationship between contamination at each sampling point and water supply type. Methods We performed a bivariate random-effects meta-analysis of 45 studies, identified through a systematic review, that reported either the proportion of samples free of fecal indicator bacteria and/or individual sample bacteria counts for source and HSW, disaggregated by supply type. Results Water quality deteriorated substantially between source and stored water. The mean percentage of contaminated samples (noncompliance) at the source was 46% (95% CI: 33, 60%), whereas mean noncompliance in HSW was 75% (95% CI: 64, 84%). Water supply type was significantly associated with noncompliance at the source (p < 0.001) and in HSW (p = 0.03). Source water (OR = 0.2; 95% CI: 0.1, 0.5) and HSW (OR = 0.3; 95% CI: 0.2, 0.8) from piped supplies had significantly lower odds of contamination compared with non-piped water, potentially due to residual chlorine. Conclusions Piped water is less likely to be contaminated compared with other water supply types at both the source and in HSW. A focus on upgrading water services to piped supplies may help improve safety, including for those drinking stored water. Citation Shields KF, Bain RE, Cronk R, Wright JA, Bartram J. 2015. Association of supply type with fecal contamination of source water and household stored drinking water in developing countries: a bivariate meta-analysis. Environ Health Perspect 123:1222–1231; http://dx.doi.org/10.1289/ehp.1409002 PMID:25956006

INLAND DISSOLVED SALT CHEMISTRY: STATISTICAL EVALUATION OF BIVARIATE AND TERNARY DIAGRAM MODELS FOR SURFACE AND SUBSURFACE WATERS

EPA Science Inventory

We compared the use of ternary and bivariate diagrams to distinguish the effects of atmospheric precipitation, rock weathering, and evaporation on inland surface and subsurface water chemistry. The three processes could not be statistically differentiated using bivariate models e...

Parameters Selection for Bivariate Multiscale Entropy Analysis of Postural Fluctuations in Fallers and Non-Fallers Older Adults.

PubMed

Ramdani, Sofiane; Bonnet, Vincent; Tallon, Guillaume; Lagarde, Julien; Bernard, Pierre Louis; Blain, Hubert

2016-08-01

Entropy measures are often used to quantify the regularity of postural sway time series. Recent methodological developments provided both multivariate and multiscale approaches allowing the extraction of complexity features from physiological signals; see "Dynamical complexity of human responses: A multivariate data-adaptive framework," in Bulletin of Polish Academy of Science and Technology, vol. 60, p. 433, 2012. The resulting entropy measures are good candidates for the analysis of bivariate postural sway signals exhibiting nonstationarity and multiscale properties. These methods are dependant on several input parameters such as embedding parameters. Using two data sets collected from institutionalized frail older adults, we numerically investigate the behavior of a recent multivariate and multiscale entropy estimator; see "Multivariate multiscale entropy: A tool for complexity analysis of multichannel data," Physics Review E, vol. 84, p. 061918, 2011. We propose criteria for the selection of the input parameters. Using these optimal parameters, we statistically compare the multivariate and multiscale entropy values of postural sway data of non-faller subjects to those of fallers. These two groups are discriminated by the resulting measures over multiple time scales. We also demonstrate that the typical parameter settings proposed in the literature lead to entropy measures that do not distinguish the two groups. This last result confirms the importance of the selection of appropriate input parameters.

Bivariate tensor product [Formula: see text]-analogue of Kantorovich-type Bernstein-Stancu-Schurer operators.

PubMed

Cai, Qing-Bo; Xu, Xiao-Wei; Zhou, Guorong

2017-01-01

In this paper, we construct a bivariate tensor product generalization of Kantorovich-type Bernstein-Stancu-Schurer operators based on the concept of [Formula: see text]-integers. We obtain moments and central moments of these operators, give the rate of convergence by using the complete modulus of continuity for the bivariate case and estimate a convergence theorem for the Lipschitz continuous functions. We also give some graphs and numerical examples to illustrate the convergence properties of these operators to certain functions.

Galaxy And Mass Assembly (GAMA): bivariate functions of Hα star-forming galaxies

NASA Astrophysics Data System (ADS)

Gunawardhana, M. L. P.; Hopkins, A. M.; Taylor, E. N.; Bland-Hawthorn, J.; Norberg, P.; Baldry, I. K.; Loveday, J.; Owers, M. S.; Wilkins, S. M.; Colless, M.; Brown, M. J. I.; Driver, S. P.; Alpaslan, M.; Brough, S.; Cluver, M.; Croom, S.; Kelvin, L.; Lara-López, M. A.; Liske, J.; López-Sánchez, A. R.; Robotham, A. S. G.

2015-02-01

We present bivariate luminosity and stellar mass functions of Hα star-forming galaxies drawn from the Galaxy And Mass Assembly (GAMA) survey. While optically deep spectroscopic observations of GAMA over a wide sky area enable the detection of a large number of 0.001 < SFRHα (M⊙ yr-1) < 100 galaxies, the requirement for an Hα detection in targets selected from an r-band magnitude-limited survey leads to an incompleteness due to missing optically faint star-forming galaxies. Using z < 0.1 bivariate distributions as a reference we model the higher-z distributions, thereby approximating a correction for the missing optically faint star-forming galaxies to the local star formation rate (SFR) and M densities. Furthermore, we obtain the r-band luminosity functions (LFs) and stellar mass functions of Hα star-forming galaxies from the bivariate LFs. As our sample is selected on the basis of detected Hα emission, a direct tracer of ongoing star formation, this sample represents a true star-forming galaxy sample, and is drawn from both photometrically classified blue and red subpopulations, though mostly from the blue population. On average 20-30 per cent of red galaxies at all stellar masses are star forming, implying that these galaxies may be dusty star-forming systems.

Modeling Bivariate Longitudinal Hormone Profiles by Hierarchical State Space Models.

PubMed

Liu, Ziyue; Cappola, Anne R; Crofford, Leslie J; Guo, Wensheng

2014-01-01

The hypothalamic-pituitary-adrenal (HPA) axis is crucial in coping with stress and maintaining homeostasis. Hormones produced by the HPA axis exhibit both complex univariate longitudinal profiles and complex relationships among different hormones. Consequently, modeling these multivariate longitudinal hormone profiles is a challenging task. In this paper, we propose a bivariate hierarchical state space model, in which each hormone profile is modeled by a hierarchical state space model, with both population-average and subject-specific components. The bivariate model is constructed by concatenating the univariate models based on the hypothesized relationship. Because of the flexible framework of state space form, the resultant models not only can handle complex individual profiles, but also can incorporate complex relationships between two hormones, including both concurrent and feedback relationship. Estimation and inference are based on marginal likelihood and posterior means and variances. Computationally efficient Kalman filtering and smoothing algorithms are used for implementation. Application of the proposed method to a study of chronic fatigue syndrome and fibromyalgia reveals that the relationships between adrenocorticotropic hormone and cortisol in the patient group are weaker than in healthy controls.

An integrated user-friendly ArcMAP tool for bivariate statistical modeling in geoscience applications

NASA Astrophysics Data System (ADS)

Jebur, M. N.; Pradhan, B.; Shafri, H. Z. M.; Yusof, Z.; Tehrany, M. S.

2014-10-01

Modeling and classification difficulties are fundamental issues in natural hazard assessment. A geographic information system (GIS) is a domain that requires users to use various tools to perform different types of spatial modeling. Bivariate statistical analysis (BSA) assists in hazard modeling. To perform this analysis, several calculations are required and the user has to transfer data from one format to another. Most researchers perform these calculations manually by using Microsoft Excel or other programs. This process is time consuming and carries a degree of uncertainty. The lack of proper tools to implement BSA in a GIS environment prompted this study. In this paper, a user-friendly tool, BSM (bivariate statistical modeler), for BSA technique is proposed. Three popular BSA techniques such as frequency ratio, weights-of-evidence, and evidential belief function models are applied in the newly proposed ArcMAP tool. This tool is programmed in Python and is created by a simple graphical user interface, which facilitates the improvement of model performance. The proposed tool implements BSA automatically, thus allowing numerous variables to be examined. To validate the capability and accuracy of this program, a pilot test area in Malaysia is selected and all three models are tested by using the proposed program. Area under curve is used to measure the success rate and prediction rate. Results demonstrate that the proposed program executes BSA with reasonable accuracy. The proposed BSA tool can be used in numerous applications, such as natural hazard, mineral potential, hydrological, and other engineering and environmental applications.

An integrated user-friendly ArcMAP tool for bivariate statistical modelling in geoscience applications

NASA Astrophysics Data System (ADS)

Jebur, M. N.; Pradhan, B.; Shafri, H. Z. M.; Yusoff, Z. M.; Tehrany, M. S.

2015-03-01

Modelling and classification difficulties are fundamental issues in natural hazard assessment. A geographic information system (GIS) is a domain that requires users to use various tools to perform different types of spatial modelling. Bivariate statistical analysis (BSA) assists in hazard modelling. To perform this analysis, several calculations are required and the user has to transfer data from one format to another. Most researchers perform these calculations manually by using Microsoft Excel or other programs. This process is time-consuming and carries a degree of uncertainty. The lack of proper tools to implement BSA in a GIS environment prompted this study. In this paper, a user-friendly tool, bivariate statistical modeler (BSM), for BSA technique is proposed. Three popular BSA techniques, such as frequency ratio, weight-of-evidence (WoE), and evidential belief function (EBF) models, are applied in the newly proposed ArcMAP tool. This tool is programmed in Python and created by a simple graphical user interface (GUI), which facilitates the improvement of model performance. The proposed tool implements BSA automatically, thus allowing numerous variables to be examined. To validate the capability and accuracy of this program, a pilot test area in Malaysia is selected and all three models are tested by using the proposed program. Area under curve (AUC) is used to measure the success rate and prediction rate. Results demonstrate that the proposed program executes BSA with reasonable accuracy. The proposed BSA tool can be used in numerous applications, such as natural hazard, mineral potential, hydrological, and other engineering and environmental applications.

Testing independence of bivariate interval-censored data using modified Kendall's tau statistic.

PubMed

Kim, Yuneung; Lim, Johan; Park, DoHwan

2015-11-01

In this paper, we study a nonparametric procedure to test independence of bivariate interval censored data; for both current status data (case 1 interval-censored data) and case 2 interval-censored data. To do it, we propose a score-based modification of the Kendall's tau statistic for bivariate interval-censored data. Our modification defines the Kendall's tau statistic with expected numbers of concordant and disconcordant pairs of data. The performance of the modified approach is illustrated by simulation studies and application to the AIDS study. We compare our method to alternative approaches such as the two-stage estimation method by Sun et al. (Scandinavian Journal of Statistics, 2006) and the multiple imputation method by Betensky and Finkelstein (Statistics in Medicine, 1999b). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Comparison of simple pooling and bivariate model used in meta-analyses of diagnostic test accuracy published in Chinese journals].

PubMed

Huang, Yuan-sheng; Yang, Zhi-rong; Zhan, Si-yan

2015-06-18

To investigate the use of simple pooling and bivariate model in meta-analyses of diagnostic test accuracy (DTA) published in Chinese journals (January to November, 2014), compare the differences of results from these two models, and explore the impact of between-study variability of sensitivity and specificity on the differences. DTA meta-analyses were searched through Chinese Biomedical Literature Database (January to November, 2014). Details in models and data for fourfold table were extracted. Descriptive analysis was conducted to investigate the prevalence of the use of simple pooling method and bivariate model in the included literature. Data were re-analyzed with the two models respectively. Differences in the results were examined by Wilcoxon signed rank test. How the results differences were affected by between-study variability of sensitivity and specificity, expressed by I2, was explored. The 55 systematic reviews, containing 58 DTA meta-analyses, were included and 25 DTA meta-analyses were eligible for re-analysis. Simple pooling was used in 50 (90.9%) systematic reviews and bivariate model in 1 (1.8%). The remaining 4 (7.3%) articles used other models pooling sensitivity and specificity or pooled neither of them. Of the reviews simply pooling sensitivity and specificity, 41(82.0%) were at the risk of wrongly using Meta-disc software. The differences in medians of sensitivity and specificity between two models were both 0.011 (P<0.001, P=0.031 respectively). Greater differences could be found as I2 of sensitivity or specificity became larger, especially when I2>75%. Most DTA meta-analyses published in Chinese journals(January to November, 2014) combine the sensitivity and specificity by simple pooling. Meta-disc software can pool the sensitivity and specificity only through fixed-effect model, but a high proportion of authors think it can implement random-effect model. Simple pooling tends to underestimate the results compared with bivariate model. The

On non-parametric maximum likelihood estimation of the bivariate survivor function.

PubMed

Prentice, R L

The likelihood function for the bivariate survivor function F, under independent censorship, is maximized to obtain a non-parametric maximum likelihood estimator &Fcirc;. &Fcirc; may or may not be unique depending on the configuration of singly- and doubly-censored pairs. The likelihood function can be maximized by placing all mass on the grid formed by the uncensored failure times, or half lines beyond the failure time grid, or in the upper right quadrant beyond the grid. By accumulating the mass along lines (or regions) where the likelihood is flat, one obtains a partially maximized likelihood as a function of parameters that can be uniquely estimated. The score equations corresponding to these point mass parameters are derived, using a Lagrange multiplier technique to ensure unit total mass, and a modified Newton procedure is used to calculate the parameter estimates in some limited simulation studies. Some considerations for the further development of non-parametric bivariate survivor function estimators are briefly described.

Modeling Bivariate Longitudinal Hormone Profiles by Hierarchical State Space Models

PubMed Central

Liu, Ziyue; Cappola, Anne R.; Crofford, Leslie J.; Guo, Wensheng

2013-01-01

The hypothalamic-pituitary-adrenal (HPA) axis is crucial in coping with stress and maintaining homeostasis. Hormones produced by the HPA axis exhibit both complex univariate longitudinal profiles and complex relationships among different hormones. Consequently, modeling these multivariate longitudinal hormone profiles is a challenging task. In this paper, we propose a bivariate hierarchical state space model, in which each hormone profile is modeled by a hierarchical state space model, with both population-average and subject-specific components. The bivariate model is constructed by concatenating the univariate models based on the hypothesized relationship. Because of the flexible framework of state space form, the resultant models not only can handle complex individual profiles, but also can incorporate complex relationships between two hormones, including both concurrent and feedback relationship. Estimation and inference are based on marginal likelihood and posterior means and variances. Computationally efficient Kalman filtering and smoothing algorithms are used for implementation. Application of the proposed method to a study of chronic fatigue syndrome and fibromyalgia reveals that the relationships between adrenocorticotropic hormone and cortisol in the patient group are weaker than in healthy controls. PMID:24729646

Bivariate spline solution of time dependent nonlinear PDE for a population density over irregular domains.

PubMed

Gutierrez, Juan B; Lai, Ming-Jun; Slavov, George

2015-12-01

We study a time dependent partial differential equation (PDE) which arises from classic models in ecology involving logistic growth with Allee effect by introducing a discrete weak solution. Existence, uniqueness and stability of the discrete weak solutions are discussed. We use bivariate splines to approximate the discrete weak solution of the nonlinear PDE. A computational algorithm is designed to solve this PDE. A convergence analysis of the algorithm is presented. We present some simulations of population development over some irregular domains. Finally, we discuss applications in epidemiology and other ecological problems. Copyright © 2015 Elsevier Inc. All rights reserved.

Bivariate and multivariate analyses of the correlations between stability of the erythrocyte membrane, serum lipids and hematological variables.

PubMed

Bernardino Neto, M; de Avelar, E B; Arantes, T S; Jordão, I A; da Costa Huss, J C; de Souza, T M T; de Souza Penha, V A; da Silva, S C; de Souza, P C A; Tavares, M; Penha-Silva, N

2013-01-01

The observation that the fluidity must remain within a critical interval, outside which the stability and functionality of the cell tends to decrease, shows that stability, fluidity and function are related and that the measure of erythrocyte stability allows inferences about the fluidity or functionality of these cells. This study determined the biochemical and hematological variables that are directly or indirectly related to erythrocyte stability in a population of 71 volunteers. Data were evaluated by bivariate and multivariate analysis. The erythrocyte stability showed a greater association with hematological variables than the biochemical variables. The RDW stands out for its strong correlation with the stability of erythrocyte membrane, without being heavily influenced by other factors. Regarding the biochemical variables, the erythrocyte stability was more sensitive to LDL-C. Erythrocyte stability was significantly associated with RDW and LDL-C. Thus, the level of LDL-C is a consistent link between stability and functionality, suggesting that a measure of stability could be more one indirect parameter for assessing the risk of degenerative processes associated with high levels of LDL-C.

An assessment on the use of bivariate, multivariate and soft computing techniques for collapse susceptibility in GIS environ

NASA Astrophysics Data System (ADS)

Yilmaz, Işik; Marschalko, Marian; Bednarik, Martin

2013-04-01

The paper presented herein compares and discusses the use of bivariate, multivariate and soft computing techniques for collapse susceptibility modelling. Conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) models representing the bivariate, multivariate and soft computing techniques were used in GIS based collapse susceptibility mapping in an area from Sivas basin (Turkey). Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index (TWI), stream power index (SPI), Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from the models, and they were then compared by means of their validations. However, Area Under Curve (AUC) values obtained from all three models showed that the map obtained from soft computing (ANN) model looks like more accurate than the other models, accuracies of all three models can be evaluated relatively similar. The results also showed that the conditional probability is an essential method in preparation of collapse susceptibility map and highly compatible with GIS operating features.

Bivariate genome-wide association analyses identified genetic pleiotropic effects for bone mineral density and alcohol drinking in Caucasians

PubMed Central

Lu, Shan; Zhao, Lan-Juan; Chen, Xiang-Ding; Papasian, Christopher J.; Wu, Ke-Hao; Tan, Li-Jun; Wang, Zhuo-Er; Pei, Yu-Fang; Tian, Qing

2018-01-01

Several studies indicated bone mineral density (BMD) and alcohol intake might share common genetic factors. The study aimed to explore potential SNPs/genes related to both phenotypes in US Caucasians at the genome-wide level. A bivariate genome-wide association study (GWAS) was performed in 2069 unrelated participants. Regular drinking was graded as 1, 2, 3, 4, 5, or 6, representing drinking alcohol never, less than once, once or twice, three to six times, seven to ten times, or more than ten times per week respectively. Hip, spine, and whole body BMDs were measured. The bivariate GWAS was conducted on the basis of a bivariate linear regression model. Sex-stratified association analyses were performed in the male and female subgroups. In males, the most significant association signal was detected in SNP rs685395 in DYNC2H1 with bivariate spine BMD and alcohol drinking (P = 1.94 × 10−8). SNP rs685395 and five other SNPs, rs657752, rs614902, rs682851, rs626330, and rs689295, located in the same haplotype block in DYNC2H1 were the top ten most significant SNPs in the bivariate GWAS in males. Additionally, two SNPs in GRIK4 in males and three SNPs in OPRM1 in females were suggestively associated with BMDs (of the hip, spine, and whole body) and alcohol drinking. Nine SNPs in IL1RN were only suggestively associated with female whole body BMD and alcohol drinking. Our study indicated that DYNC2H1 may contribute to the genetic mechanisms of both spine BMD and alcohol drinking in male Caucasians. Moreover, our study suggested potential pleiotropic roles of OPRM1 and IL1RN in females and GRIK4 in males underlying variation of both BMD and alcohol drinking. PMID:28012008

Bivariate functional data clustering: grouping streams based on a varying coefficient model of the stream water and air temperature relationship

Treesearch

H. Li; X. Deng; Andy Dolloff; E. P. Smith

2015-01-01

A novel clustering method for bivariate functional data is proposed to group streams based on their water–air temperature relationship. A distance measure is developed for bivariate curves by using a time-varying coefficient model and a weighting scheme. This distance is also adjusted by spatial correlation of streams via the variogram. Therefore, the proposed...

Multivariate Longitudinal Analysis with Bivariate Correlation Test

PubMed Central

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model’s parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated. PMID:27537692

Multivariate Longitudinal Analysis with Bivariate Correlation Test.

PubMed

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated.

Aquaculture in artificially developed wetlands in urban areas: an application of the bivariate relationship between soil and surface water in landscape ecology.

PubMed

Paul, Abhijit

2011-01-01

Wetlands show a strong bivariate relationship between soil and surface water. Artificially developed wetlands help to build landscape ecology and make built environments sustainable. The bheries, wetlands of eastern Calcutta (India), utilize the city sewage to develop urban aquaculture that supports the local fish industries and opens a new frontier in sustainable environmental planning research.

Copula-based regression modeling of bivariate severity of temporary disability and permanent motor injuries.

PubMed

Ayuso, Mercedes; Bermúdez, Lluís; Santolino, Miguel

2016-04-01

The analysis of factors influencing the severity of the personal injuries suffered by victims of motor accidents is an issue of major interest. Yet, most of the extant literature has tended to address this question by focusing on either the severity of temporary disability or the severity of permanent injury. In this paper, a bivariate copula-based regression model for temporary disability and permanent injury severities is introduced for the joint analysis of the relationship with the set of factors that might influence both categories of injury. Using a motor insurance database with 21,361 observations, the copula-based regression model is shown to give a better performance than that of a model based on the assumption of independence. The inclusion of the dependence structure in the analysis has a higher impact on the variance estimates of the injury severities than it does on the point estimates. By taking into account the dependence between temporary and permanent severities a more extensive factor analysis can be conducted. We illustrate that the conditional distribution functions of injury severities may be estimated, thus, providing decision makers with valuable information. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

He, Ling-Yun; Chen, Shu-Peng

2011-01-01

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

IDF relationships using bivariate copula for storm events in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Ariff, N. M.; Jemain, A. A.; Ibrahim, K.; Wan Zin, W. Z.

2012-11-01

SummaryIntensity-duration-frequency (IDF) curves are used in many hydrologic designs for the purpose of water managements and flood preventions. The IDF curves available in Malaysia are those obtained from univariate analysis approach which only considers the intensity of rainfalls at fixed time intervals. As several rainfall variables are correlated with each other such as intensity and duration, this paper aims to derive IDF points for storm events in Peninsular Malaysia by means of bivariate frequency analysis. This is achieved through utilizing the relationship between storm intensities and durations using the copula method. Four types of copulas; namely the Ali-Mikhail-Haq (AMH), Frank, Gaussian and Farlie-Gumbel-Morgenstern (FGM) copulas are considered because the correlation between storm intensity, I, and duration, D, are negative and these copulas are appropriate when the relationship between the variables are negative. The correlations are attained by means of Kendall's τ estimation. The analysis was performed on twenty rainfall stations with hourly data across Peninsular Malaysia. Using Akaike's Information Criteria (AIC) for testing goodness-of-fit, both Frank and Gaussian copulas are found to be suitable to represent the relationship between I and D. The IDF points found by the copula method are compared to the IDF curves yielded based on the typical IDF empirical formula of the univariate approach. This study indicates that storm intensities obtained from both methods are in agreement with each other for any given storm duration and for various return periods.

A Bivariate Chebyshev Spectral Collocation Quasilinearization Method for Nonlinear Evolution Parabolic Equations

PubMed Central

Motsa, S. S.; Magagula, V. M.; Sibanda, P.

2014-01-01

This paper presents a new method for solving higher order nonlinear evolution partial differential equations (NPDEs). The method combines quasilinearisation, the Chebyshev spectral collocation method, and bivariate Lagrange interpolation. In this paper, we use the method to solve several nonlinear evolution equations, such as the modified KdV-Burgers equation, highly nonlinear modified KdV equation, Fisher's equation, Burgers-Fisher equation, Burgers-Huxley equation, and the Fitzhugh-Nagumo equation. The results are compared with known exact analytical solutions from literature to confirm accuracy, convergence, and effectiveness of the method. There is congruence between the numerical results and the exact solutions to a high order of accuracy. Tables were generated to present the order of accuracy of the method; convergence graphs to verify convergence of the method and error graphs are presented to show the excellent agreement between the results from this study and the known results from literature. PMID:25254252

A bivariate Chebyshev spectral collocation quasilinearization method for nonlinear evolution parabolic equations.

PubMed

Motsa, S S; Magagula, V M; Sibanda, P

2014-01-01

This paper presents a new method for solving higher order nonlinear evolution partial differential equations (NPDEs). The method combines quasilinearisation, the Chebyshev spectral collocation method, and bivariate Lagrange interpolation. In this paper, we use the method to solve several nonlinear evolution equations, such as the modified KdV-Burgers equation, highly nonlinear modified KdV equation, Fisher's equation, Burgers-Fisher equation, Burgers-Huxley equation, and the Fitzhugh-Nagumo equation. The results are compared with known exact analytical solutions from literature to confirm accuracy, convergence, and effectiveness of the method. There is congruence between the numerical results and the exact solutions to a high order of accuracy. Tables were generated to present the order of accuracy of the method; convergence graphs to verify convergence of the method and error graphs are presented to show the excellent agreement between the results from this study and the known results from literature.

A Semiparametric Approach to Simultaneous Covariance Estimation for Bivariate Sparse Longitudinal Data

PubMed Central

Das, Kiranmoy; Daniels, Michael J.

2014-01-01

Summary Estimation of the covariance structure for irregular sparse longitudinal data has been studied by many authors in recent years but typically using fully parametric specifications. In addition, when data are collected from several groups over time, it is known that assuming the same or completely different covariance matrices over groups can lead to loss of efficiency and/or bias. Nonparametric approaches have been proposed for estimating the covariance matrix for regular univariate longitudinal data by sharing information across the groups under study. For the irregular case, with longitudinal measurements that are bivariate or multivariate, modeling becomes more difficult. In this article, to model bivariate sparse longitudinal data from several groups, we propose a flexible covariance structure via a novel matrix stick-breaking process for the residual covariance structure and a Dirichlet process mixture of normals for the random effects. Simulation studies are performed to investigate the effectiveness of the proposed approach over more traditional approaches. We also analyze a subset of Framingham Heart Study data to examine how the blood pressure trajectories and covariance structures differ for the patients from different BMI groups (high, medium and low) at baseline. PMID:24400941

The Effects of Selection Strategies for Bivariate Loglinear Smoothing Models on NEAT Equating Functions

ERIC Educational Resources Information Center

Moses, Tim; Holland, Paul W.

2010-01-01

In this study, eight statistical strategies were evaluated for selecting the parameterizations of loglinear models for smoothing the bivariate test score distributions used in nonequivalent groups with anchor test (NEAT) equating. Four of the strategies were based on significance tests of chi-square statistics (Likelihood Ratio, Pearson,…

Identifying hidden common causes from bivariate time series: a method using recurrence plots.

PubMed

Hirata, Yoshito; Aihara, Kazuyuki

2010-01-01

We propose a method for inferring the existence of hidden common causes from observations of bivariate time series. We detect related time series by excessive simultaneous recurrences in the corresponding recurrence plots. We also use a noncoverage property of a recurrence plot by the other to deny the existence of a directional coupling. We apply the proposed method to real wind data.

Optical Coherence Tomography Noise Reduction Using Anisotropic Local Bivariate Gaussian Mixture Prior in 3D Complex Wavelet Domain

PubMed Central

Sonka, Milan; Abramoff, Michael D.

2013-01-01

In this paper, MMSE estimator is employed for noise-free 3D OCT data recovery in 3D complex wavelet domain. Since the proposed distribution for noise-free data plays a key role in the performance of MMSE estimator, a priori distribution for the pdf of noise-free 3D complex wavelet coefficients is proposed which is able to model the main statistical properties of wavelets. We model the coefficients with a mixture of two bivariate Gaussian pdfs with local parameters which are able to capture the heavy-tailed property and inter- and intrascale dependencies of coefficients. In addition, based on the special structure of OCT images, we use an anisotropic windowing procedure for local parameters estimation that results in visual quality improvement. On this base, several OCT despeckling algorithms are obtained based on using Gaussian/two-sided Rayleigh noise distribution and homomorphic/nonhomomorphic model. In order to evaluate the performance of the proposed algorithm, we use 156 selected ROIs from 650 × 512 × 128 OCT dataset in the presence of wet AMD pathology. Our simulations show that the best MMSE estimator using local bivariate mixture prior is for the nonhomomorphic model in the presence of Gaussian noise which results in an improvement of 7.8 ± 1.7 in CNR. PMID:24222760

Optical Coherence Tomography Noise Reduction Using Anisotropic Local Bivariate Gaussian Mixture Prior in 3D Complex Wavelet Domain.

PubMed

Rabbani, Hossein; Sonka, Milan; Abramoff, Michael D

2013-01-01

In this paper, MMSE estimator is employed for noise-free 3D OCT data recovery in 3D complex wavelet domain. Since the proposed distribution for noise-free data plays a key role in the performance of MMSE estimator, a priori distribution for the pdf of noise-free 3D complex wavelet coefficients is proposed which is able to model the main statistical properties of wavelets. We model the coefficients with a mixture of two bivariate Gaussian pdfs with local parameters which are able to capture the heavy-tailed property and inter- and intrascale dependencies of coefficients. In addition, based on the special structure of OCT images, we use an anisotropic windowing procedure for local parameters estimation that results in visual quality improvement. On this base, several OCT despeckling algorithms are obtained based on using Gaussian/two-sided Rayleigh noise distribution and homomorphic/nonhomomorphic model. In order to evaluate the performance of the proposed algorithm, we use 156 selected ROIs from 650 × 512 × 128 OCT dataset in the presence of wet AMD pathology. Our simulations show that the best MMSE estimator using local bivariate mixture prior is for the nonhomomorphic model in the presence of Gaussian noise which results in an improvement of 7.8 ± 1.7 in CNR.

Genetic correlations between body condition scores and fertility in dairy cattle using bivariate random regression models.

PubMed

De Haas, Y; Janss, L L G; Kadarmideen, H N

2007-10-01

Genetic correlations between body condition score (BCS) and fertility traits in dairy cattle were estimated using bivariate random regression models. BCS was recorded by the Swiss Holstein Association on 22,075 lactating heifers (primiparous cows) from 856 sires. Fertility data during first lactation were extracted for 40,736 cows. The fertility traits were days to first service (DFS), days between first and last insemination (DFLI), calving interval (CI), number of services per conception (NSPC) and conception rate to first insemination (CRFI). A bivariate model was used to estimate genetic correlations between BCS as a longitudinal trait by random regression components, and daughter's fertility at the sire level as a single lactation measurement. Heritability of BCS was 0.17, and heritabilities for fertility traits were low (0.01-0.08). Genetic correlations between BCS and fertility over the lactation varied from: -0.45 to -0.14 for DFS; -0.75 to 0.03 for DFLI; from -0.59 to -0.02 for CI; from -0.47 to 0.33 for NSPC and from 0.08 to 0.82 for CRFI. These results show (genetic) interactions between fat reserves and reproduction along the lactation trajectory of modern dairy cows, which can be useful in genetic selection as well as in management. Maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in mid lactation when the genetic variance for BCS is largest, and the genetic correlations between BCS and fertility is strongest.

Bivariate empirical mode decomposition for ECG-based biometric identification with emotional data.

PubMed

Ferdinando, Hany; Seppanen, Tapio; Alasaarela, Esko

2017-07-01

Emotions modulate ECG signals such that they might affect ECG-based biometric identification in real life application. It motivated in finding good feature extraction methods where the emotional state of the subjects has minimum impacts. This paper evaluates feature extraction based on bivariate empirical mode decomposition (BEMD) for biometric identification when emotion is considered. Using the ECG signal from the Mahnob-HCI database for affect recognition, the features were statistical distributions of dominant frequency after applying BEMD analysis to ECG signals. The achieved accuracy was 99.5% with high consistency using kNN classifier in 10-fold cross validation to identify 26 subjects when the emotional states of the subjects were ignored. When the emotional states of the subject were considered, the proposed method also delivered high accuracy, around 99.4%. We concluded that the proposed method offers emotion-independent features for ECG-based biometric identification. The proposed method needs more evaluation related to testing with other classifier and variation in ECG signals, e.g. normal ECG vs. ECG with arrhythmias, ECG from various ages, and ECG from other affective databases.

New Colors for Histology: Optimized Bivariate Color Maps Increase Perceptual Contrast in Histological Images.

PubMed

Kather, Jakob Nikolas; Weis, Cleo-Aron; Marx, Alexander; Schuster, Alexander K; Schad, Lothar R; Zöllner, Frank Gerrit

2015-01-01

Accurate evaluation of immunostained histological images is required for reproducible research in many different areas and forms the basis of many clinical decisions. The quality and efficiency of histopathological evaluation is limited by the information content of a histological image, which is primarily encoded as perceivable contrast differences between objects in the image. However, the colors of chromogen and counterstain used for histological samples are not always optimally distinguishable, even under optimal conditions. In this study, we present a method to extract the bivariate color map inherent in a given histological image and to retrospectively optimize this color map. We use a novel, unsupervised approach based on color deconvolution and principal component analysis to show that the commonly used blue and brown color hues in Hematoxylin-3,3'-Diaminobenzidine (DAB) images are poorly suited for human observers. We then demonstrate that it is possible to construct improved color maps according to objective criteria and that these color maps can be used to digitally re-stain histological images. To validate whether this procedure improves distinguishability of objects and background in histological images, we re-stain phantom images and N = 596 large histological images of immunostained samples of human solid tumors. We show that perceptual contrast is improved by a factor of 2.56 in phantom images and up to a factor of 2.17 in sets of histological tumor images. Thus, we provide an objective and reliable approach to measure object distinguishability in a given histological image and to maximize visual information available to a human observer. This method could easily be incorporated in digital pathology image viewing systems to improve accuracy and efficiency in research and diagnostics.

A Basic Bivariate Structure of Personality Attributes Evident Across Nine Languages.

PubMed

Saucier, Gerard; Thalmayer, Amber Gayle; Payne, Doris L; Carlson, Robert; Sanogo, Lamine; Ole-Kotikash, Leonard; Church, A Timothy; Katigbak, Marcia S; Somer, Oya; Szarota, Piotr; Szirmák, Zsofia; Zhou, Xinyue

2014-02-01

Here, two studies seek to characterize a parsimonious common-denominator personality structure with optimal cross-cultural replicability. Personality differences are observed in all human populations and cultures, but lexicons for personality attributes contain so many distinctions that parsimony is lacking. Models stipulating the most important attributes have been formulated by experts or by empirical studies drawing on experience in a very limited range of cultures. Factor analyses of personality lexicons of nine languages of diverse provenance (Chinese, Korean, Filipino, Turkish, Greek, Polish, Hungarian, Maasai, and Senoufo) were examined, and their common structure was compared to that of several prominent models in psychology. A parsimonious bivariate model showed evidence of substantial convergence and ubiquity across cultures. Analyses involving key markers of these dimensions in English indicate that they are broad dimensions involving the overlapping content of the interpersonal circumplex, models of communion and agency, and morality/warmth and competence. These "Big Two" dimensions-Social Self-Regulation and Dynamism-provide a common-denominator model involving the two most crucial axes of personality variation, ubiquitous across cultures. The Big Two might serve as an umbrella model serving to link diverse theoretical models and associated research literatures. © 2013 Wiley Periodicals, Inc.

Neural Systems with Numerically Matched Input-Output Statistic: Isotonic Bivariate Statistical Modeling

PubMed Central

Fiori, Simone

2007-01-01

Bivariate statistical modeling from incomplete data is a useful statistical tool that allows to discover the model underlying two data sets when the data in the two sets do not correspond in size nor in ordering. Such situation may occur when the sizes of the two data sets do not match (i.e., there are “holes” in the data) or when the data sets have been acquired independently. Also, statistical modeling is useful when the amount of available data is enough to show relevant statistical features of the phenomenon underlying the data. We propose to tackle the problem of statistical modeling via a neural (nonlinear) system that is able to match its input-output statistic to the statistic of the available data sets. A key point of the new implementation proposed here is that it is based on look-up-table (LUT) neural systems, which guarantee a computationally advantageous way of implementing neural systems. A number of numerical experiments, performed on both synthetic and real-world data sets, illustrate the features of the proposed modeling procedure. PMID:18566641

Structural Zeros and Their Implications with Log-Linear Bivariate Presmoothing under the Internal-Anchor Design

ERIC Educational Resources Information Center

Kim, Hyung Jin; Brennan, Robert L.; Lee, Won-Chan

2017-01-01

In equating, when common items are internal and scoring is conducted in terms of the number of correct items, some pairs of total scores ("X") and common-item scores ("V") can never be observed in a bivariate distribution of "X" and "V"; these pairs are called "structural zeros." This simulation…

Bayesian bivariate meta-analysis of correlated effects: Impact of the prior distributions on the between-study correlation, borrowing of strength, and joint inferences

PubMed Central

Bujkiewicz, Sylwia; Riley, Richard D

2016-01-01

Multivariate random-effects meta-analysis allows the joint synthesis of correlated results from multiple studies, for example, for multiple outcomes or multiple treatment groups. In a Bayesian univariate meta-analysis of one endpoint, the importance of specifying a sensible prior distribution for the between-study variance is well understood. However, in multivariate meta-analysis, there is little guidance about the choice of prior distributions for the variances or, crucially, the between-study correlation, ρB; for the latter, researchers often use a Uniform(−1,1) distribution assuming it is vague. In this paper, an extensive simulation study and a real illustrative example is used to examine the impact of various (realistically) vague prior distributions for ρB and the between-study variances within a Bayesian bivariate random-effects meta-analysis of two correlated treatment effects. A range of diverse scenarios are considered, including complete and missing data, to examine the impact of the prior distributions on posterior results (for treatment effect and between-study correlation), amount of borrowing of strength, and joint predictive distributions of treatment effectiveness in new studies. Two key recommendations are identified to improve the robustness of multivariate meta-analysis results. First, the routine use of a Uniform(−1,1) prior distribution for ρB should be avoided, if possible, as it is not necessarily vague. Instead, researchers should identify a sensible prior distribution, for example, by restricting values to be positive or negative as indicated by prior knowledge. Second, it remains critical to use sensible (e.g. empirically based) prior distributions for the between-study variances, as an inappropriate choice can adversely impact the posterior distribution for ρB, which may then adversely affect inferences such as joint predictive probabilities. These recommendations are especially important with a small number of studies and

Dynamics of intracranial electroencephalographic recordings from epilepsy patients using univariate and bivariate recurrence networks.

PubMed

Subramaniyam, Narayan Puthanmadam; Hyttinen, Jari

2015-02-01

Recently Andrezejak et al. combined the randomness and nonlinear independence test with iterative amplitude adjusted Fourier transform (iAAFT) surrogates to distinguish between the dynamics of seizure-free intracranial electroencephalographic (EEG) signals recorded from epileptogenic (focal) and nonepileptogenic (nonfocal) brain areas of epileptic patients. However, stationarity is a part of the null hypothesis for iAAFT surrogates and thus nonstationarity can violate the null hypothesis. In this work we first propose the application of the randomness and nonlinear independence test based on recurrence network measures to distinguish between the dynamics of focal and nonfocal EEG signals. Furthermore, we combine these tests with both iAAFT and truncated Fourier transform (TFT) surrogate methods, which also preserves the nonstationarity of the original data in the surrogates along with its linear structure. Our results indicate that focal EEG signals exhibit an increased degree of structural complexity and interdependency compared to nonfocal EEG signals. In general, we find higher rejections for randomness and nonlinear independence tests for focal EEG signals compared to nonfocal EEG signals. In particular, the univariate recurrence network measures, the average clustering coefficient C and assortativity R, and the bivariate recurrence network measure, the average cross-clustering coefficient C(cross), can successfully distinguish between the focal and nonfocal EEG signals, even when the analysis is restricted to nonstationary signals, irrespective of the type of surrogates used. On the other hand, we find that the univariate recurrence network measures, the average path length L, and the average betweenness centrality BC fail to distinguish between the focal and nonfocal EEG signals when iAAFT surrogates are used. However, these two measures can distinguish between focal and nonfocal EEG signals when TFT surrogates are used for nonstationary signals. We also

Dynamics of intracranial electroencephalographic recordings from epilepsy patients using univariate and bivariate recurrence networks

NASA Astrophysics Data System (ADS)

Subramaniyam, Narayan Puthanmadam; Hyttinen, Jari

2015-02-01

Recently Andrezejak et al. combined the randomness and nonlinear independence test with iterative amplitude adjusted Fourier transform (iAAFT) surrogates to distinguish between the dynamics of seizure-free intracranial electroencephalographic (EEG) signals recorded from epileptogenic (focal) and nonepileptogenic (nonfocal) brain areas of epileptic patients. However, stationarity is a part of the null hypothesis for iAAFT surrogates and thus nonstationarity can violate the null hypothesis. In this work we first propose the application of the randomness and nonlinear independence test based on recurrence network measures to distinguish between the dynamics of focal and nonfocal EEG signals. Furthermore, we combine these tests with both iAAFT and truncated Fourier transform (TFT) surrogate methods, which also preserves the nonstationarity of the original data in the surrogates along with its linear structure. Our results indicate that focal EEG signals exhibit an increased degree of structural complexity and interdependency compared to nonfocal EEG signals. In general, we find higher rejections for randomness and nonlinear independence tests for focal EEG signals compared to nonfocal EEG signals. In particular, the univariate recurrence network measures, the average clustering coefficient C and assortativity R , and the bivariate recurrence network measure, the average cross-clustering coefficient Ccross, can successfully distinguish between the focal and nonfocal EEG signals, even when the analysis is restricted to nonstationary signals, irrespective of the type of surrogates used. On the other hand, we find that the univariate recurrence network measures, the average path length L , and the average betweenness centrality BC fail to distinguish between the focal and nonfocal EEG signals when iAAFT surrogates are used. However, these two measures can distinguish between focal and nonfocal EEG signals when TFT surrogates are used for nonstationary signals. We also

New Colors for Histology: Optimized Bivariate Color Maps Increase Perceptual Contrast in Histological Images

PubMed Central

Kather, Jakob Nikolas; Weis, Cleo-Aron; Marx, Alexander; Schuster, Alexander K.; Schad, Lothar R.; Zöllner, Frank Gerrit

2015-01-01

Background Accurate evaluation of immunostained histological images is required for reproducible research in many different areas and forms the basis of many clinical decisions. The quality and efficiency of histopathological evaluation is limited by the information content of a histological image, which is primarily encoded as perceivable contrast differences between objects in the image. However, the colors of chromogen and counterstain used for histological samples are not always optimally distinguishable, even under optimal conditions. Methods and Results In this study, we present a method to extract the bivariate color map inherent in a given histological image and to retrospectively optimize this color map. We use a novel, unsupervised approach based on color deconvolution and principal component analysis to show that the commonly used blue and brown color hues in Hematoxylin—3,3’-Diaminobenzidine (DAB) images are poorly suited for human observers. We then demonstrate that it is possible to construct improved color maps according to objective criteria and that these color maps can be used to digitally re-stain histological images. Validation To validate whether this procedure improves distinguishability of objects and background in histological images, we re-stain phantom images and N = 596 large histological images of immunostained samples of human solid tumors. We show that perceptual contrast is improved by a factor of 2.56 in phantom images and up to a factor of 2.17 in sets of histological tumor images. Context Thus, we provide an objective and reliable approach to measure object distinguishability in a given histological image and to maximize visual information available to a human observer. This method could easily be incorporated in digital pathology image viewing systems to improve accuracy and efficiency in research and diagnostics. PMID:26717571

Constructing a bivariate distribution function with given marginals and correlation: application to the galaxy luminosity function

NASA Astrophysics Data System (ADS)

Takeuchi, Tsutomu T.

2010-08-01

We provide an analytic method to construct a bivariate distribution function (DF) with given marginal distributions and correlation coefficient. We introduce a convenient mathematical tool, called a copula, to connect two DFs with any prescribed dependence structure. If the correlation of two variables is weak (Pearson's correlation coefficient |ρ| < 1/3), the Farlie-Gumbel-Morgenstern (FGM) copula provides an intuitive and natural way to construct such a bivariate DF. When the linear correlation is stronger, the FGM copula cannot work anymore. In this case, we propose using a Gaussian copula, which connects two given marginals and is directly related to the linear correlation coefficient between two variables. Using the copulas, we construct the bivariate luminosity function (BLF) and discuss its statistical properties. We focus especially on the far-infrared-far-ulatraviolet (FUV-FIR) BLF, since these two wavelength regions are related to star-formation (SF) activity. Though both the FUV and FIR are related to SF activity, the univariate LFs have a very different functional form: the former is well described by the Schechter function whilst the latter has a much more extended power-law-like luminous end. We construct the FUV-FIR BLFs using the FGM and Gaussian copulas with different strengths of correlation, and examine their statistical properties. We then discuss some further possible applications of the BLF: the problem of a multiband flux-limited sample selection, the construction of the star-formation rate (SFR) function, and the construction of the stellar mass of galaxies (M*)-specific SFR (SFR/M*) relation. The copulas turn out to be a very useful tool to investigate all these issues, especially for including complicated selection effects.

Ultrasonographic fetal head position to predict mode of delivery: a systematic review and bivariate meta-analysis.

PubMed

Verhoeven, C J M; Rückert, M E P F; Opmeer, B C; Pajkrt, E; Mol, B W J

2012-07-01

We performed a systematic review to determine whether sonographic assessment of occipital position of the fetal head can contribute to the prediction of the mode of delivery. We performed a systematic literature search of electronic databases from inception to May 2011. Two reviewers independently extracted data from the included studies. We used a bivariate model to estimate point estimates for sensitivity and specificity curves for the outcome Cesarean delivery. Eligible studies were cohort studies or cross-sectional studies that reported on both the position of the fetal head, as assessed by ultrasound, before or at the beginning of active labor as well as the outcome of labor in women at term. We included 11 primary articles reporting on 5053 women, of whom 898 had a Cesarean section. All studies indicated disappointing values for sensitivity and specificity in the prediction of Cesarean section. Summary point estimates of sensitivity and specificity were 0.39 (95% CI, 0.32-0.48) and 0.71 (95% CI, 0.67-0.74), respectively. Sonographic assessment of occipital position of the fetal head before delivery should not be used in the prediction of mode of delivery. Copyright © 2012 ISUOG. Published by John Wiley & Sons, Ltd.

Multifractal detrended cross-correlation analysis on air pollutants of University of Hyderabad Campus, India

NASA Astrophysics Data System (ADS)

Manimaran, P.; Narayana, A. C.

2018-07-01

In this paper, we study the multifractal characteristics and cross-correlation behaviour of Air Pollution Index (API) time series data through multifractal detrended cross-correlation analysis method. We analyse the daily API records of nine air pollutants of the university of Hyderabad campus for a period of three years (2013-2016). The cross-correlation behaviour has been measured from the Hurst scaling exponents and the singularity spectrum quantitatively. From the results, it is found that the cross-correlation analysis shows anti-correlation behaviour for all possible 36 bivariate time series. We also observe the existence of multifractal nature in all the bivariate time series in which many of them show strong multifractal behaviour. In particular, the hazardous particulate matter PM2.5 and inhalable particulate matter PM10 shows anti-correlated behaviour with all air pollutants.

Powerful Bivariate Genome-Wide Association Analyses Suggest the SOX6 Gene Influencing Both Obesity and Osteoporosis Phenotypes in Males

PubMed Central

Liu, Yao-Zhong; Pei, Yu-Fang; Liu, Jian-Feng; Yang, Fang; Guo, Yan; Zhang, Lei; Liu, Xiao-Gang; Yan, Han; Wang, Liang; Zhang, Yin-Ping; Levy, Shawn; Recker, Robert R.; Deng, Hong-Wen

2009-01-01

Background Current genome-wide association studies (GWAS) are normally implemented in a univariate framework and analyze different phenotypes in isolation. This univariate approach ignores the potential genetic correlation between important disease traits. Hence this approach is difficult to detect pleiotropic genes, which may exist for obesity and osteoporosis, two common diseases of major public health importance that are closely correlated genetically. Principal Findings To identify such pleiotropic genes and the key mechanistic links between the two diseases, we here performed the first bivariate GWAS of obesity and osteoporosis. We searched for genes underlying co-variation of the obesity phenotype, body mass index (BMI), with the osteoporosis risk phenotype, hip bone mineral density (BMD), scanning ∼380,000 SNPs in 1,000 unrelated homogeneous Caucasians, including 499 males and 501 females. We identified in the male subjects two SNPs in intron 1 of the SOX6 (SRY-box 6) gene, rs297325 and rs4756846, which were bivariately associated with both BMI and hip BMD, achieving p values of 6.82×10−7 and 1.47×10−6, respectively. The two SNPs ranked at the top in significance for bivariate association with BMI and hip BMD in the male subjects among all the ∼380,000 SNPs examined genome-wide. The two SNPs were replicated in a Framingham Heart Study (FHS) cohort containing 3,355 Caucasians (1,370 males and 1,985 females) from 975 families. In the FHS male subjects, the two SNPs achieved p values of 0.03 and 0.02, respectively, for bivariate association with BMI and femoral neck BMD. Interestingly, SOX6 was previously found to be essential to both cartilage formation/chondrogenesis and obesity-related insulin resistance, suggesting the gene's dual role in both bone and fat. Conclusions Our findings, together with the prior biological evidence, suggest the SOX6 gene's importance in co-regulation of obesity and osteoporosis. PMID:19714249

Predicting the Size of Sunspot Cycle 24 on the Basis of Single- and Bi-Variate Geomagnetic Precursor Methods

NASA Technical Reports Server (NTRS)

Wilson, Robert M.; Hathaway, David H.

2009-01-01

Examined are single- and bi-variate geomagnetic precursors for predicting the maximum amplitude (RM) of a sunspot cycle several years in advance. The best single-variate fit is one based on the average of the ap index 36 mo prior to cycle minimum occurrence (E(Rm)), having a coefficient of correlation (r) equal to 0.97 and a standard error of estimate (se) equal to 9.3. Presuming cycle 24 not to be a statistical outlier and its minimum in March 2008, the fit suggests cycle 24 s RM to be about 69 +/- 20 (the 90% prediction interval). The weighted mean prediction of 11 statistically important single-variate fits is 116 +/- 34. The best bi-variate fit is one based on the maximum and minimum values of the 12-mma of the ap index; i.e., APM# and APm*, where # means the value post-E(RM) for the preceding cycle and * means the value in the vicinity of cycle minimum, having r = 0.98 and se = 8.2. It predicts cycle 24 s RM to be about 92 +/- 27. The weighted mean prediction of 22 statistically important bi-variate fits is 112 32. Thus, cycle 24's RM is expected to lie somewhere within the range of about 82 to 144. Also examined are the late-cycle 23 behaviors of geomagnetic indices and solar wind velocity in comparison to the mean behaviors of cycles 2023 and the geomagnetic indices of cycle 14 (RM = 64.2), the weakest sunspot cycle of the modern era.

Geovisualization of land use and land cover using bivariate maps and Sankey flow diagrams

NASA Astrophysics Data System (ADS)

Strode, Georgianna; Mesev, Victor; Thornton, Benjamin; Jerez, Marjorie; Tricarico, Thomas; McAlear, Tyler

2018-05-01

The terms `land use' and `land cover' typically describe categories that convey information about the landscape. Despite the major difference of land use implying some degree of anthropogenic disturbance, the two terms are commonly used interchangeably, especially when anthropogenic disturbance is ambiguous, say managed forestland or abandoned agricultural fields. Cartographically, land use and land cover are also sometimes represented interchangeably within common legends, giving with the impression that the landscape is a seamless continuum of land use parcels spatially adjacent to land cover tracts. We believe this is misleading, and feel we need to reiterate the well-established symbiosis of land uses as amalgams of land covers; in other words land covers are subsets of land use. Our paper addresses this spatially complex, and frequently ambiguous relationship, and posits that bivariate cartographic techniques are an ideal vehicle for representing both land use and land cover simultaneously. In more specific terms, we explore the use of nested symbology as ways to represent graphically land use and land cover, where land cover are circles nested with land use squares. We also investigate bivariate legends for representing statistical covariance as a means for visualizing the combinations of land use and cover. Lastly, we apply Sankey flow diagrams to further illustrate the complex, multifaceted relationships between land use and land cover. Our work is demonstrated on data representing land use and cover data for the US state of Florida.

A Bivariate Genetic Analysis of Drug Abuse ascertained through medical and criminal registries in Swedish Twins, Siblings and Half-Siblings

PubMed Central

Maes, Hermine H.; Neale, Michael C.; Ohlsson, Henrik; Zahery, Mahsa; Lichtenstein, Paul; Sundquist, Kristina; Sundquist, Jan; Kendler, Kenneth S.

2016-01-01

Objective Using Swedish nationwide registry data, the authors investigated the correlation of genetic and environmental risk factors in the etiology of drug abuse as ascertained from medical and criminal registries by modeling twin and sibling data. Methods Medical drug abuse was defined using public inpatient and outpatient records, while criminal drug abuse was ascertained through legal records. Twin, full and half sibling pairs were obtained from the national twin and genealogical registers. Information about sibling pair residence within the same household was obtained from Statistics Sweden. Standard bivariate genetic structural equation modeling was applied to the population-based data on drug abuse ascertained through medical and crime registries, using OpenMx. Results Analyses of all possible pairs of twins (MZ: N=4,482; DZ: N=9,838 pairs), full- (N=1,278,086) and half-siblings (paternal: N=7,767; maternal N=70,553) who grew up together suggested that factors explaining familial resemblance for drug abuse as defined through medical or criminal registries were mostly the same. Results showed substantial heritability and moderate contributions of shared environmental factors to drug abuse; both were higher in males versus females, and higher for drug abuse ascertained through criminal than medical records. Because of the low prevalence of both assessments of drug abuse, having access to population data was crucial to obtain stable estimates. Conclusions Using objective registry data, the authors found that drug abuse - whether ascertained through medical versus criminal records - was highly heritable. Furthermore, shared environmental factors contributed significantly to the liability of drug abuse. Genetic and shared environmental risk factors for these two forms of drug abuse were highly correlated. PMID:27480873

A Bivariate Genetic Analysis of Drug Abuse Ascertained Through Medical and Criminal Registries in Swedish Twins, Siblings and Half-Siblings.

PubMed

Maes, Hermine H; Neale, Michael C; Ohlsson, Henrik; Zahery, Mahsa; Lichtenstein, Paul; Sundquist, Kristina; Sundquist, Jan; Kendler, Kenneth S

2016-11-01

Using Swedish nationwide registry data, the authors investigated the correlation of genetic and environmental risk factors in the etiology of drug abuse as ascertained from medical and criminal registries by modeling twin and sibling data. Medical drug abuse was defined using public inpatient and outpatient records, while criminal drug abuse was ascertained through legal records. Twin, full and half sibling pairs were obtained from the national twin and genealogical registers. Information about sibling pair residence within the same household was obtained from Statistics Sweden. Standard bivariate genetic structural equation modeling was applied to the population-based data on drug abuse ascertained through medical and crime registries, using OpenMx. Analyses of all possible pairs of twins (MZ: N = 4482; DZ: N = 9838 pairs), full- (N = 1,278,086) and half-siblings (paternal: N = 7767; maternal N = 70,553) who grew up together suggested that factors explaining familial resemblance for drug abuse as defined through medical or criminal registries were mostly the same. Results showed substantial heritability and moderate contributions of shared environmental factors to drug abuse; both were higher in males versus females, and higher for drug abuse ascertained through criminal than medical records. Because of the low prevalence of both assessments of drug abuse, having access to population data was crucial to obtain stable estimates. Using objective registry data, the authors found that drug abuse-whether ascertained through medical versus criminal records-was highly heritable. Furthermore, shared environmental factors contributed significantly to the liability of drug abuse. Genetic and shared environmental risk factors for these two forms of drug abuse were highly correlated.

Association of Supply Type with Fecal Contamination of Source Water and Household Stored Drinking Water in Developing Countries: A Bivariate Meta-analysis.

PubMed

Shields, Katherine F; Bain, Robert E S; Cronk, Ryan; Wright, Jim A; Bartram, Jamie

2015-12-01

Access to safe drinking water is essential for health. Monitoring access to drinking water focuses on water supply type at the source, but there is limited evidence on whether quality differences at the source persist in water stored in the household. We assessed the extent of fecal contamination at the source and in household stored water (HSW) and explored the relationship between contamination at each sampling point and water supply type. We performed a bivariate random-effects meta-analysis of 45 studies, identified through a systematic review, that reported either the proportion of samples free of fecal indicator bacteria and/or individual sample bacteria counts for source and HSW, disaggregated by supply type. Water quality deteriorated substantially between source and stored water. The mean percentage of contaminated samples (noncompliance) at the source was 46% (95% CI: 33, 60%), whereas mean noncompliance in HSW was 75% (95% CI: 64, 84%). Water supply type was significantly associated with noncompliance at the source (p < 0.001) and in HSW (p = 0.03). Source water (OR = 0.2; 95% CI: 0.1, 0.5) and HSW (OR = 0.3; 95% CI: 0.2, 0.8) from piped supplies had significantly lower odds of contamination compared with non-piped water, potentially due to residual chlorine. Piped water is less likely to be contaminated compared with other water supply types at both the source and in HSW. A focus on upgrading water services to piped supplies may help improve safety, including for those drinking stored water.

Exploratory Causal Analysis in Bivariate Time Series Data

NASA Astrophysics Data System (ADS)

McCracken, James M.

Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments and data analysis techniques are required for identifying causal information and relationships directly from observational data. This need has lead to the development of many different time series causality approaches and tools including transfer entropy, convergent cross-mapping (CCM), and Granger causality statistics. In this thesis, the existing time series causality method of CCM is extended by introducing a new method called pairwise asymmetric inference (PAI). It is found that CCM may provide counter-intuitive causal inferences for simple dynamics with strong intuitive notions of causality, and the CCM causal inference can be a function of physical parameters that are seemingly unrelated to the existence of a driving relationship in the system. For example, a CCM causal inference might alternate between ''voltage drives current'' and ''current drives voltage'' as the frequency of the voltage signal is changed in a series circuit with a single resistor and inductor. PAI is introduced to address both of these limitations. Many of the current approaches in the times series causality literature are not computationally straightforward to apply, do not follow directly from assumptions of probabilistic causality, depend on assumed models for the time series generating process, or rely on embedding procedures. A new approach, called causal leaning, is introduced in this work to avoid these issues. The leaning is found to provide causal inferences that agree with intuition for both simple systems and more complicated empirical examples, including space weather data sets. The leaning may provide a clearer interpretation of the results than those from existing time series causality tools. A practicing analyst can explore the literature to find many proposals for identifying drivers and causal connections in times series data

On the level of skill in predicting maximum sunspot number - A comparative study of single variate and bivariate precursor techniques

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

1990-01-01

The level of skill in predicting the size of the sunspot cycle is investigated for the two types of precursor techniques, single variate and bivariate fits, both applied to cycle 22. The present level of growth in solar activity is compared to the mean level of growth (cycles 10-21) and to the predictions based on the precursor techniques. It is shown that, for cycle 22, both single variate methods (based on geomagnetic data) and bivariate methods suggest a maximum amplitude smaller than that observed for cycle 19, and possibly for cycle 21. Compared to the mean cycle, cycle 22 is presently behaving as if it were a +2.6 sigma cycle (maximum amplitude of about 225), which means that either it will be the first cycle not to be reliably predicted by the combined precursor techniques or its deviation relative to the mean cycle will substantially decrease over the next 18 months.

Local linear estimation of concordance probability with application to covariate effects models on association for bivariate failure-time data.

PubMed

Ding, Aidong Adam; Hsieh, Jin-Jian; Wang, Weijing

2015-01-01

Bivariate survival analysis has wide applications. In the presence of covariates, most literature focuses on studying their effects on the marginal distributions. However covariates can also affect the association between the two variables. In this article we consider the latter issue by proposing a nonstandard local linear estimator for the concordance probability as a function of covariates. Under the Clayton copula, the conditional concordance probability has a simple one-to-one correspondence with the copula parameter for different data structures including those subject to independent or dependent censoring and dependent truncation. The proposed method can be used to study how covariates affect the Clayton association parameter without specifying marginal regression models. Asymptotic properties of the proposed estimators are derived and their finite-sample performances are examined via simulations. Finally, for illustration, we apply the proposed method to analyze a bone marrow transplant data set.

An efficient algorithm for generating random number pairs drawn from a bivariate normal distribution

NASA Technical Reports Server (NTRS)

Campbell, C. W.

1983-01-01

An efficient algorithm for generating random number pairs from a bivariate normal distribution was developed. Any desired value of the two means, two standard deviations, and correlation coefficient can be selected. Theoretically the technique is exact and in practice its accuracy is limited only by the quality of the uniform distribution random number generator, inaccuracies in computer function evaluation, and arithmetic. A FORTRAN routine was written to check the algorithm and good accuracy was obtained. Some small errors in the correlation coefficient were observed to vary in a surprisingly regular manner. A simple model was developed which explained the qualities aspects of the errors.

Improving runoff risk estimates: Formulating runoff as a bivariate process using the SCS curve number method

NASA Astrophysics Data System (ADS)

Shaw, Stephen B.; Walter, M. Todd

2009-03-01

The Soil Conservation Service curve number (SCS-CN) method is widely used to predict storm runoff for hydraulic design purposes, such as sizing culverts and detention basins. As traditionally used, the probability of calculated runoff is equated to the probability of the causative rainfall event, an assumption that fails to account for the influence of variations in soil moisture on runoff generation. We propose a modification to the SCS-CN method that explicitly incorporates rainfall return periods and the frequency of different soil moisture states to quantify storm runoff risks. Soil moisture status is assumed to be correlated to stream base flow. Fundamentally, this approach treats runoff as the outcome of a bivariate process instead of dictating a 1:1 relationship between causative rainfall and resulting runoff volumes. Using data from the Fall Creek watershed in western New York and the headwaters of the French Broad River in the mountains of North Carolina, we show that our modified SCS-CN method improves frequency discharge predictions in medium-sized watersheds in the eastern United States in comparison to the traditional application of the method.

Investigating the relationship between costs and outcomes for English mental health providers: a bi-variate multi-level regression analysis.

PubMed

Moran, Valerie; Jacobs, Rowena

2018-06-01

Provider payment systems for mental health care that incentivize cost control and quality improvement have been a policy focus in a number of countries. In England, a new prospective provider payment system is being introduced to mental health that should encourage providers to control costs and improve outcomes. The aim of this research is to investigate the relationship between costs and outcomes to ascertain whether there is a trade-off between controlling costs and improving outcomes. The main data source is the Mental Health Minimum Data Set (MHMDS) for the years 2011/12 and 2012/13. Costs are calculated using NHS reference cost data while outcomes are measured using the Health of the Nation Outcome Scales (HoNOS). We estimate a bivariate multi-level model with costs and outcomes simultaneously. We calculate the correlation and plot the pairwise relationship between residual costs and outcomes at the provider level. After controlling for a range of demographic, need, social, and treatment variables, residual variation in costs and outcomes remains at the provider level. The correlation between residual costs and outcomes is negative, but very small, suggesting that cost-containment efforts by providers should not undermine outcome-improving efforts under the new payment system.

Interpreting Bivariate Regression Coefficients: Going beyond the Average

ERIC Educational Resources Information Center

Halcoussis, Dennis; Phillips, G. Michael

2010-01-01

Statistics, econometrics, investment analysis, and data analysis classes often review the calculation of several types of averages, including the arithmetic mean, geometric mean, harmonic mean, and various weighted averages. This note shows how each of these can be computed using a basic regression framework. By recognizing when a regression model…

A bivariate contaminated binormal model for robust fitting of proper ROC curves to a pair of correlated, possibly degenerate, ROC datasets.

PubMed

Zhai, Xuetong; Chakraborty, Dev P

2017-06-01

The objective was to design and implement a bivariate extension to the contaminated binormal model (CBM) to fit paired receiver operating characteristic (ROC) datasets-possibly degenerate-with proper ROC curves. Paired datasets yield two correlated ratings per case. Degenerate datasets have no interior operating points and proper ROC curves do not inappropriately cross the chance diagonal. The existing method, developed more than three decades ago utilizes a bivariate extension to the binormal model, implemented in CORROC2 software, which yields improper ROC curves and cannot fit degenerate datasets. CBM can fit proper ROC curves to unpaired (i.e., yielding one rating per case) and degenerate datasets, and there is a clear scientific need to extend it to handle paired datasets. In CBM, nondiseased cases are modeled by a probability density function (pdf) consisting of a unit variance peak centered at zero. Diseased cases are modeled with a mixture distribution whose pdf consists of two unit variance peaks, one centered at positive μ with integrated probability α, the mixing fraction parameter, corresponding to the fraction of diseased cases where the disease was visible to the radiologist, and one centered at zero, with integrated probability (1-α), corresponding to disease that was not visible. It is shown that: (a) for nondiseased cases the bivariate extension is a unit variances bivariate normal distribution centered at (0,0) with a specified correlation ρ 1 ; (b) for diseased cases the bivariate extension is a mixture distribution with four peaks, corresponding to disease not visible in either condition, disease visible in only one condition, contributing two peaks, and disease visible in both conditions. An expression for the likelihood function is derived. A maximum likelihood estimation (MLE) algorithm, CORCBM, was implemented in the R programming language that yields parameter estimates and the covariance matrix of the parameters, and other statistics

Bivariate mass-size relation as a function of morphology as determined by Galaxy Zoo 2 crowdsourced visual classifications

NASA Astrophysics Data System (ADS)

Beck, Melanie; Scarlata, Claudia; Fortson, Lucy; Willett, Kyle; Galloway, Melanie

2016-01-01

It is well known that the mass-size distribution evolves as a function of cosmic time and that this evolution is different between passive and star-forming galaxy populations. However, the devil is in the details and the precise evolution is still a matter of debate since this requires careful comparison between similar galaxy populations over cosmic time while simultaneously taking into account changes in image resolution, rest-frame wavelength, and surface brightness dimming in addition to properly selecting representative morphological samples.Here we present the first step in an ambitious undertaking to calculate the bivariate mass-size distribution as a function of time and morphology. We begin with a large sample (~3 x 105) of SDSS galaxies at z ~ 0.1. Morphologies for this sample have been determined by Galaxy Zoo crowdsourced visual classifications and we split the sample not only by disk- and bulge-dominated galaxies but also in finer morphology bins such as bulge strength. Bivariate distribution functions are the only way to properly account for biases and selection effects. In particular, we quantify the mass-size distribution with a version of the parametric Maximum Likelihood estimator which has been modified to account for measurement errors as well as upper limits on galaxy sizes.

Operator identities involving the bivariate Rogers-Szegö polynomials and their applications to the multiple q-series identities

NASA Astrophysics Data System (ADS)

Zhang, Zhizheng; Wang, Tianze

2008-07-01

In this paper, we first give several operator identities involving the bivariate Rogers-Szegö polynomials. By applying the technique of parameter augmentation to the multiple q-binomial theorems given by Milne [S.C. Milne, Balanced summation theorems for U(n) basic hypergeometric series, AdvE Math. 131 (1997) 93-187], we obtain several new multiple q-series identities involving the bivariate Rogers-Szegö polynomials. These include multiple extensions of Mehler's formula and Rogers's formula. Our U(n+1) generalizations are quite natural as they are also a direct and immediate consequence of their (often classical) known one-variable cases and Milne's fundamental theorem for An or U(n+1) basic hypergeometric series in Theorem 1E49 of [S.C. Milne, An elementary proof of the Macdonald identities for , Adv. Math. 57 (1985) 34-70], as rewritten in Lemma 7.3 on p. 163 of [S.C. Milne, Balanced summation theorems for U(n) basic hypergeometric series, Adv. Math. 131 (1997) 93-187] or Corollary 4.4 on pp. 768-769 of [S.C. Milne, M. Schlosser, A new An extension of Ramanujan's summation with applications to multilateral An series, Rocky Mountain J. Math. 32 (2002) 759-792].

Applying Emax model and bivariate thin plate splines to assess drug interactions

PubMed Central

Kong, Maiying; Lee, J. Jack

2014-01-01

We review the semiparametric approach previously proposed by Kong and Lee and extend it to a case in which the dose-effect curves follow the Emax model instead of the median effect equation. When the maximum effects for the investigated drugs are different, we provide a procedure to obtain the additive effect based on the Loewe additivity model. Then, we apply a bivariate thin plate spline approach to estimate the effect beyond additivity along with its 95% point-wise confidence interval as well as its 95% simultaneous confidence interval for any combination dose. Thus, synergy, additivity, and antagonism can be identified. The advantages of the method are that it provides an overall assessment of the combination effect on the entire two-dimensional dose space spanned by the experimental doses, and it enables us to identify complex patterns of drug interaction in combination studies. In addition, this approach is robust to outliers. To illustrate this procedure, we analyzed data from two case studies. PMID:20036878

Applying Emax model and bivariate thin plate splines to assess drug interactions.

PubMed

Kong, Maiying; Lee, J Jack

2010-01-01

We review the semiparametric approach previously proposed by Kong and Lee and extend it to a case in which the dose-effect curves follow the Emax model instead of the median effect equation. When the maximum effects for the investigated drugs are different, we provide a procedure to obtain the additive effect based on the Loewe additivity model. Then, we apply a bivariate thin plate spline approach to estimate the effect beyond additivity along with its 95 per cent point-wise confidence interval as well as its 95 per cent simultaneous confidence interval for any combination dose. Thus, synergy, additivity, and antagonism can be identified. The advantages of the method are that it provides an overall assessment of the combination effect on the entire two-dimensional dose space spanned by the experimental doses, and it enables us to identify complex patterns of drug interaction in combination studies. In addition, this approach is robust to outliers. To illustrate this procedure, we analyzed data from two case studies.

Asymptotics of bivariate generating functions with algebraic singularities

NASA Astrophysics Data System (ADS)

Greenwood, Torin

Flajolet and Odlyzko (1990) derived asymptotic formulae the coefficients of a class of uni- variate generating functions with algebraic singularities. Gao and Richmond (1992) and Hwang (1996, 1998) extended these results to classes of multivariate generating functions, in both cases by reducing to the univariate case. Pemantle and Wilson (2013) outlined new multivariate ana- lytic techniques and used them to analyze the coefficients of rational generating functions. After overviewing these methods, we use them to find asymptotic formulae for the coefficients of a broad class of bivariate generating functions with algebraic singularities. Beginning with the Cauchy integral formula, we explicity deform the contour of integration so that it hugs a set of critical points. The asymptotic contribution to the integral comes from analyzing the integrand near these points, leading to explicit asymptotic formulae. Next, we use this formula to analyze an example from current research. In the following chapter, we apply multivariate analytic techniques to quan- tum walks. Bressler and Pemantle (2007) found a (d + 1)-dimensional rational generating function whose coefficients described the amplitude of a particle at a position in the integer lattice after n steps. Here, the minimal critical points form a curve on the (d + 1)-dimensional unit torus. We find asymptotic formulae for the amplitude of a particle in a given position, normalized by the number of steps n, as n approaches infinity. Each critical point contributes to the asymptotics for a specific normalized position. Using Groebner bases in Maple again, we compute the explicit locations of peak amplitudes. In a scaling window of size the square root of n near the peaks, each amplitude is asymptotic to an Airy function.

A Bivariate Mixed Distribution with a Heavy-tailed Component and its Application to Single-site Daily Rainfall Simulation

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

Li, Chao ..; Singh, Vijay P.; Mishra, Ashok K.

2013-02-06

This paper presents an improved brivariate mixed distribution, which is capable of modeling the dependence of daily rainfall from two distinct sources (e.g., rainfall from two stations, two consecutive days, or two instruments such as satellite and rain gauge). The distribution couples an existing framework for building a bivariate mixed distribution, the theory of copulae and a hybrid marginal distribution. Contributions of the improved distribution are twofold. One is the appropriate selection of the bivariate dependence structure from a wider admissible choice (10 candidate copula families). The other is the introduction of a marginal distribution capable of better representing lowmore » to moderate values as well as extremes of daily rainfall. Among several applications of the improved distribution, particularly presented here is its utility for single-site daily rainfall simulation. Rather than simulating rainfall occurrences and amounts separately, the developed generator unifies the two processes by generalizing daily rainfall as a Markov process with autocorrelation described by the improved bivariate mixed distribution. The generator is first tested on a sample station in Texas. Results reveal that the simulated and observed sequences are in good agreement with respect to essential characteristics. Then, extensive simulation experiments are carried out to compare the developed generator with three other alternative models: the conventional two-state Markov chain generator, the transition probability matrix model and the semi-parametric Markov chain model with kernel density estimation for rainfall amounts. Analyses establish that overall the developed generator is capable of reproducing characteristics of historical extreme rainfall events and is apt at extrapolating rare values beyond the upper range of available observed data. Moreover, it automatically captures the persistence of rainfall amounts on consecutive wet days in a relatively natural and

Improving the chi-squared approximation for bivariate normal tolerance regions

NASA Technical Reports Server (NTRS)

Feiveson, Alan H.

1993-01-01

Let X be a two-dimensional random variable distributed according to N2(mu,Sigma) and let bar-X and S be the respective sample mean and covariance matrix calculated from N observations of X. Given a containment probability beta and a level of confidence gamma, we seek a number c, depending only on N, beta, and gamma such that the ellipsoid R = (x: (x - bar-X)'S(exp -1) (x - bar-X) less than or = c) is a tolerance region of content beta and level gamma; i.e., R has probability gamma of containing at least 100 beta percent of the distribution of X. Various approximations for c exist in the literature, but one of the simplest to compute -- a multiple of the ratio of certain chi-squared percentage points -- is badly biased for small N. For the bivariate normal case, most of the bias can be removed by simple adjustment using a factor A which depends on beta and gamma. This paper provides values of A for various beta and gamma so that the simple approximation for c can be made viable for any reasonable sample size. The methodology provides an illustrative example of how a combination of Monte-Carlo simulation and simple regression modelling can be used to improve an existing approximation.

Chromosome heteromorphism quantified by high-resolution bivariate flow karyotyping.

PubMed Central

Trask, B; van den Engh, G; Mayall, B; Gray, J W

1989-01-01

Maternal and paternal homologues of many chromosome types can be differentiated on the basis of their peak position in Hoechst 33258 versus chromomycin A3 bivariate flow karyotypes. We demonstrate here the magnitude of DNA content differences among normal chromosomes of the same type. Significant peak-position differences between homologues were observed for an average of four chromosome types in each of the karyotypes of 98 different individuals. The frequency of individuals with differences in homologue peak positions varied among chromosome types: e.g., chromosome 15, 61%; chromosome 3, 4%. Flow karyotypes of 33 unrelated individuals were compared to determine the range of peak position among normal chromosomes. Chromosomes Y, 21, 22, 15, 16, 13, 14, and 19 were most heteromorphic, and chromosomes 2-8 and X were least heteromorphic. The largest chromosome 21 was 45% larger than the smallest 21 chromosome observed. The base composition of the variable regions differed among chromosome types. DNA contents of chromosome variants determined from flow karyotypes were closely correlated to measurements of DNA content made of gallocyanin chrome alum-stained metaphase chromosomes on slides. Fluorescence in situ hybridization with chromosome-specific repetitive sequences indicated that variability in their copy number is partly responsible for peak-position variability in some chromosomes. Heteromorphic chromosomes are identified for which parental flow karyotype information will be essential if de novo rearrangements resulting in small DNA content changes are to be detected with flow karyotyping. Images Figure 5 PMID:2479266

Assessing characteristics related to the use of seatbelts and cell phones by drivers: application of a bivariate probit model.

PubMed

Russo, Brendan J; Kay, Jonathan J; Savolainen, Peter T; Gates, Timothy J

2014-06-01

The effects of cell phone use and safety belt use have been an important focus of research related to driver safety. Cell phone use has been shown to be a significant source of driver distraction contributing to substantial degradations in driver performance, while safety belts have been demonstrated to play a vital role in mitigating injuries to crash-involved occupants. This study examines the prevalence of cell phone use and safety belt non-use among the driving population through direct observation surveys. A bivariate probit model is developed to simultaneously examine the factors that affect cell phone and safety belt use among motor vehicle drivers. The results show that several factors may influence drivers' decision to use cell phones and safety belts, and that these decisions are correlated. Understanding the factors that affect both cell phone use and safety belt non-use is essential to targeting policy and programs that reduce such behavior. Copyright © 2014 Elsevier Ltd. All rights reserved.

A view on coupled cluster perturbation theory using a bivariational Lagrangian formulation.

PubMed

Kristensen, Kasper; Eriksen, Janus J; Matthews, Devin A; Olsen, Jeppe; Jørgensen, Poul

2016-02-14

We consider two distinct coupled cluster (CC) perturbation series that both expand the difference between the energies of the CCSD (CC with single and double excitations) and CCSDT (CC with single, double, and triple excitations) models in orders of the Møller-Plesset fluctuation potential. We initially introduce the E-CCSD(T-n) series, in which the CCSD amplitude equations are satisfied at the expansion point, and compare it to the recently developed CCSD(T-n) series [J. J. Eriksen et al., J. Chem. Phys. 140, 064108 (2014)], in which not only the CCSD amplitude, but also the CCSD multiplier equations are satisfied at the expansion point. The computational scaling is similar for the two series, and both are term-wise size extensive with a formal convergence towards the CCSDT target energy. However, the two series are different, and the CCSD(T-n) series is found to exhibit a more rapid convergence up through the series, which we trace back to the fact that more information at the expansion point is utilized than for the E-CCSD(T-n) series. The present analysis can be generalized to any perturbation expansion representing the difference between a parent CC model and a higher-level target CC model. In general, we demonstrate that, whenever the parent parameters depend upon the perturbation operator, a perturbation expansion of the CC energy (where only parent amplitudes are used) differs from a perturbation expansion of the CC Lagrangian (where both parent amplitudes and parent multipliers are used). For the latter case, the bivariational Lagrangian formulation becomes more than a convenient mathematical tool, since it facilitates a different and faster convergent perturbation series than the simpler energy-based expansion.

Migraineurs without aura show microstructural abnormalities in the cerebellum and frontal lobe.

PubMed

Granziera, C; Romascano, D; Daducci, A; Roche, A; Vincent, M; Krueger, G; Hadjikhani, N

2013-12-01

The involvement of the cerebellum in migraine pathophysiology is not well understood. We used a biparametric approach at high-field MRI (3 T) to assess the structural integrity of the cerebellum in 15 migraineurs with aura (MWA), 23 migraineurs without aura (MWoA), and 20 healthy controls (HC). High-resolution T1 relaxation maps were acquired together with magnetization transfer images in order to probe microstructural and myelin integrity. Clusterwise analysis was performed on T1 and magnetization transfer ratio (MTR) maps of the cerebellum of MWA, MWoA, and HC using an ANOVA and a non-parametric clusterwise permutation F test, with age and gender as covariates and correction for familywise error rate. In addition, mean MTR and T1 in frontal regions known to be highly connected to the cerebellum were computed. Clusterwise comparison among groups showed a cluster of lower MTR in the right Crus I of MWoA patients vs. HC and MWA subjects (p = 0.04). Univariate and bivariate analysis on T1 and MTR contrasts showed that MWoA patients had longer T1 and lower MTR in the right and left pars orbitalis compared to MWA (p < 0.01 and 0.05, respectively), but no differences were found with HC. Lower MTR and longer T1 point at a loss of macromolecules and/or micro-edema in Crus I and pars orbitalis in MWoA patients vs. HC and vs. MWA. The pathophysiological implications of these findings are discussed in light of recent literature.

A Vehicle for Bivariate Data Analysis

ERIC Educational Resources Information Center

Roscoe, Matt B.

2016-01-01

Instead of reserving the study of probability and statistics for special fourth-year high school courses, the Common Core State Standards for Mathematics (CCSSM) takes a "statistics for all" approach. The standards recommend that students in grades 6-8 learn to summarize and describe data distributions, understand probability, draw…

Multidimensional stock network analysis: An Escoufier's RV coefficient approach

NASA Astrophysics Data System (ADS)

Lee, Gan Siew; Djauhari, Maman A.

2013-09-01

The current practice of stocks network analysis is based on the assumption that the time series of closed stock price could represent the behaviour of the each stock. This assumption leads to consider minimal spanning tree (MST) and sub-dominant ultrametric (SDU) as an indispensible tool to filter the economic information contained in the network. Recently, there is an attempt where researchers represent stock not only as a univariate time series of closed price but as a bivariate time series of closed price and volume. In this case, they developed the so-called multidimensional MST to filter the important economic information. However, in this paper, we show that their approach is only applicable for that bivariate time series only. This leads us to introduce a new methodology to construct MST where each stock is represented by a multivariate time series. An example of Malaysian stock exchange will be presented and discussed to illustrate the advantages of the method.

Gene selection and cancer type classification of diffuse large-B-cell lymphoma using a bivariate mixture model for two-species data.

PubMed

Su, Yuhua; Nielsen, Dahlia; Zhu, Lei; Richards, Kristy; Suter, Steven; Breen, Matthew; Motsinger-Reif, Alison; Osborne, Jason

2013-01-05

: A bivariate mixture model utilizing information across two species was proposed to solve the fundamental problem of identifying differentially expressed genes in microarray experiments. The model utility was illustrated using a dog and human lymphoma data set prepared by a group of scientists in the College of Veterinary Medicine at North Carolina State University. A small number of genes were identified as being differentially expressed in both species and the human genes in this cluster serve as a good predictor for classifying diffuse large-B-cell lymphoma (DLBCL) patients into two subgroups, the germinal center B-cell-like diffuse large B-cell lymphoma and the activated B-cell-like diffuse large B-cell lymphoma. The number of human genes that were observed to be significantly differentially expressed (21) from the two-species analysis was very small compared to the number of human genes (190) identified with only one-species analysis (human data). The genes may be clinically relevant/important, as this small set achieved low misclassification rates of DLBCL subtypes. Additionally, the two subgroups defined by this cluster of human genes had significantly different survival functions, indicating that the stratification based on gene-expression profiling using the proposed mixture model provided improved insight into the clinical differences between the two cancer subtypes.

The association between body mass index and severe biliary infections: a multivariate analysis.

PubMed

Stewart, Lygia; Griffiss, J McLeod; Jarvis, Gary A; Way, Lawrence W

2012-11-01

Obesity has been associated with worse infectious disease outcomes. It is a risk factor for cholesterol gallstones, but little is known about associations between body mass index (BMI) and biliary infections. We studied this using factors associated with biliary infections. A total of 427 patients with gallstones were studied. Gallstones, bile, and blood (as applicable) were cultured. Illness severity was classified as follows: none (no infection or inflammation), systemic inflammatory response syndrome (fever, leukocytosis), severe (abscess, cholangitis, empyema), or multi-organ dysfunction syndrome (bacteremia, hypotension, organ failure). Associations between BMI and biliary bacteria, bacteremia, gallstone type, and illness severity were examined using bivariate and multivariate analysis. BMI inversely correlated with pigment stones, biliary bacteria, bacteremia, and increased illness severity on bivariate and multivariate analysis. Obesity correlated with less severe biliary infections. BMI inversely correlated with pigment stones and biliary bacteria; multivariate analysis showed an independent correlation between lower BMI and illness severity. Most patients with severe biliary infections had a normal BMI, suggesting that obesity may be protective in biliary infections. This study examined the correlation between BMI and biliary infection severity. Published by Elsevier Inc.

Laser capillary spectrophotometric acquisition of bivariate drop size and concentration data for liquid-liquid dispersion

DOEpatents

Tavlarides, Lawrence L.; Bae, Jae-Heum

1991-01-01

A laser capillary spectrophotometric technique measures real time or near real time bivariate drop size and concentration distribution for a reactive liquid-liquid dispersion system. The dispersion is drawn into a precision-bore glass capillary and an appropriate light source is used to distinguish the aqueous phase from slugs of the organic phase at two points along the capillary whose separation is precisely known. The suction velocity is measured, as is the length of each slug from which the drop free diameter is calculated. For each drop, the absorptivity at a given wavelength is related to the molar concentration of a solute of interest, and the concentration of given drops of the organic phase is derived from pulse heights of the detected light. This technique permits on-line monitoring and control of liquid-liquid dispersion processes.

Laser capillary spectrophotometric acquisition of bivariate drop size and concentration data for liquid-liquid dispersion

DOEpatents

Tavlarides, L.L.; Bae, J.H.

1991-12-24

A laser capillary spectrophotometric technique measures real time or near real time bivariate drop size and concentration distribution for a reactive liquid-liquid dispersion system. The dispersion is drawn into a precision-bore glass capillary and an appropriate light source is used to distinguish the aqueous phase from slugs of the organic phase at two points along the capillary whose separation is precisely known. The suction velocity is measured, as is the length of each slug from which the drop free diameter is calculated. For each drop, the absorptivity at a given wavelength is related to the molar concentration of a solute of interest, and the concentration of given drops of the organic phase is derived from pulse heights of the detected light. This technique permits on-line monitoring and control of liquid-liquid dispersion processes. 17 figures.

Bivariate Gaussian bridges: directional factorization of diffusion in Brownian bridge models.

PubMed

Kranstauber, Bart; Safi, Kamran; Bartumeus, Frederic

2014-01-01

In recent years high resolution animal tracking data has become the standard in movement ecology. The Brownian Bridge Movement Model (BBMM) is a widely adopted approach to describe animal space use from such high resolution tracks. One of the underlying assumptions of the BBMM is isotropic diffusive motion between consecutive locations, i.e. invariant with respect to the direction. Here we propose to relax this often unrealistic assumption by separating the Brownian motion variance into two directional components, one parallel and one orthogonal to the direction of the motion. Our new model, the Bivariate Gaussian bridge (BGB), tracks movement heterogeneity across time. Using the BGB and identifying directed and non-directed movement within a trajectory resulted in more accurate utilisation distributions compared to dynamic Brownian bridges, especially for trajectories with a non-isotropic diffusion, such as directed movement or Lévy like movements. We evaluated our model with simulated trajectories and observed tracks, demonstrating that the improvement of our model scales with the directional correlation of a correlated random walk. We find that many of the animal trajectories do not adhere to the assumptions of the BBMM. The proposed model improves accuracy when describing the space use both in simulated correlated random walks as well as observed animal tracks. Our novel approach is implemented and available within the "move" package for R.

On the joint spectral density of bivariate random sequences. Thesis Technical Report No. 21

NASA Technical Reports Server (NTRS)

Aalfs, David D.

1995-01-01

For univariate random sequences, the power spectral density acts like a probability density function of the frequencies present in the sequence. This dissertation extends that concept to bivariate random sequences. For this purpose, a function called the joint spectral density is defined that represents a joint probability weighing of the frequency content of pairs of random sequences. Given a pair of random sequences, the joint spectral density is not uniquely determined in the absence of any constraints. Two approaches to constraining the sequences are suggested: (1) assume the sequences are the margins of some stationary random field, (2) assume the sequences conform to a particular model that is linked to the joint spectral density. For both approaches, the properties of the resulting sequences are investigated in some detail, and simulation is used to corroborate theoretical results. It is concluded that under either of these two constraints, the joint spectral density can be computed from the non-stationary cross-correlation.

Technology-enhanced Interactive Teaching of Marginal, Joint and Conditional Probabilities: The Special Case of Bivariate Normal Distribution

PubMed Central

Dinov, Ivo D.; Kamino, Scott; Bhakhrani, Bilal; Christou, Nicolas

2014-01-01

Summary Data analysis requires subtle probability reasoning to answer questions like What is the chance of event A occurring, given that event B was observed? This generic question arises in discussions of many intriguing scientific questions such as What is the probability that an adolescent weighs between 120 and 140 pounds given that they are of average height? and What is the probability of (monetary) inflation exceeding 4% and housing price index below 110? To address such problems, learning some applied, theoretical or cross-disciplinary probability concepts is necessary. Teaching such courses can be improved by utilizing modern information technology resources. Students’ understanding of multivariate distributions, conditional probabilities, correlation and causation can be significantly strengthened by employing interactive web-based science educational resources. Independent of the type of a probability course (e.g. majors, minors or service probability course, rigorous measure-theoretic, applied or statistics course) student motivation, learning experiences and knowledge retention may be enhanced by blending modern technological tools within the classical conceptual pedagogical models. We have designed, implemented and disseminated a portable open-source web-application for teaching multivariate distributions, marginal, joint and conditional probabilities using the special case of bivariate Normal distribution. A real adolescent height and weight dataset is used to demonstrate the classroom utilization of the new web-application to address problems of parameter estimation, univariate and multivariate inference. PMID:25419016

Technology-enhanced Interactive Teaching of Marginal, Joint and Conditional Probabilities: The Special Case of Bivariate Normal Distribution.

PubMed

Dinov, Ivo D; Kamino, Scott; Bhakhrani, Bilal; Christou, Nicolas

2013-01-01

Data analysis requires subtle probability reasoning to answer questions like What is the chance of event A occurring, given that event B was observed? This generic question arises in discussions of many intriguing scientific questions such as What is the probability that an adolescent weighs between 120 and 140 pounds given that they are of average height? and What is the probability of (monetary) inflation exceeding 4% and housing price index below 110? To address such problems, learning some applied, theoretical or cross-disciplinary probability concepts is necessary. Teaching such courses can be improved by utilizing modern information technology resources. Students' understanding of multivariate distributions, conditional probabilities, correlation and causation can be significantly strengthened by employing interactive web-based science educational resources. Independent of the type of a probability course (e.g. majors, minors or service probability course, rigorous measure-theoretic, applied or statistics course) student motivation, learning experiences and knowledge retention may be enhanced by blending modern technological tools within the classical conceptual pedagogical models. We have designed, implemented and disseminated a portable open-source web-application for teaching multivariate distributions, marginal, joint and conditional probabilities using the special case of bivariate Normal distribution. A real adolescent height and weight dataset is used to demonstrate the classroom utilization of the new web-application to address problems of parameter estimation, univariate and multivariate inference.

Contributory fault and level of personal injury to drivers involved in head-on collisions: Application of copula-based bivariate ordinal models.

PubMed

Wali, Behram; Khattak, Asad J; Xu, Jingjing

2018-01-01

The main objective of this study is to simultaneously investigate the degree of injury severity sustained by drivers involved in head-on collisions with respect to fault status designation. This is complicated to answer due to many issues, one of which is the potential presence of correlation between injury outcomes of drivers involved in the same head-on collision. To address this concern, we present seemingly unrelated bivariate ordered response models by analyzing the joint injury severity probability distribution of at-fault and not-at-fault drivers. Moreover, the assumption of bivariate normality of residuals and the linear form of stochastic dependence implied by such models may be unduly restrictive. To test this, Archimedean copula structures and normal mixture marginals are integrated into the joint estimation framework, which can characterize complex forms of stochastic dependencies and non-normality in residual terms. The models are estimated using 2013 Virginia police reported two-vehicle head-on collision data, where exactly one driver is at-fault. The results suggest that both at-fault and not-at-fault drivers sustained serious/fatal injuries in 8% of crashes, whereas, in 4% of the cases, the not-at-fault driver sustained a serious/fatal injury with no injury to the at-fault driver at all. Furthermore, if the at-fault driver is fatigued, apparently asleep, or has been drinking the not-at-fault driver is more likely to sustain a severe/fatal injury, controlling for other factors and potential correlations between the injury outcomes. While not-at-fault vehicle speed affects injury severity of at-fault driver, the effect is smaller than the effect of at-fault vehicle speed on at-fault injury outcome. Contrarily, and importantly, the effect of at-fault vehicle speed on injury severity of not-at-fault driver is almost equal to the effect of not-at-fault vehicle speed on injury outcome of not-at-fault driver. Compared to traditional ordered probability

Genome-wide meta-analysis identifies novel gender specific loci associated with thyroid antibodies level in Croatians.

PubMed

Matana, Antonela; Popović, Marijana; Boutin, Thibaud; Torlak, Vesela; Brdar, Dubravka; Gunjača, Ivana; Kolčić, Ivana; Boraska Perica, Vesna; Punda, Ante; Polašek, Ozren; Hayward, Caroline; Barbalić, Maja; Zemunik, Tatijana

2018-04-18

Autoimmune thyroid diseases (AITD) are multifactorial endocrine diseases most frequently accompanied by Tg and TPO autoantibodies. Both antibodies have a higher prevalence in females and act under a strong genetic influence. To identify novel variants underlying thyroid antibody levels, we performed GWAS meta-analysis on the plasma levels of TgAb and TPOAb in three Croatian cohorts, as well as gender specific GWAS and a bivariate analysis. No significant association was detected with the level of TgAb and TPOAb in the meta-analysis of GWAS or bivariate results for all individuals. The bivariate analysis in females only revealed a genome-wide significant association for the locus near GRIN3A (rs4457391, P = 7.76 × 10 -9 ). The same locus had borderline association with TPOAb levels in females (rs1935377, P = 8.58 × 10 -8 ). In conclusion, we identified a novel gender specific locus associated with TgAb and TPOAb levels. Our findings provide a novel insight into genetic and gender differences associated with thyroid antibodies. Copyright © 2018 Elsevier Inc. All rights reserved.

Predictors of postoperative outcomes of cubital tunnel syndrome treatments using multiple logistic regression analysis.

PubMed

Suzuki, Taku; Iwamoto, Takuji; Shizu, Kanae; Suzuki, Katsuji; Yamada, Harumoto; Sato, Kazuki

2017-05-01

This retrospective study was designed to investigate prognostic factors for postoperative outcomes for cubital tunnel syndrome (CubTS) using multiple logistic regression analysis with a large number of patients. Eighty-three patients with CubTS who underwent surgeries were enrolled. The following potential prognostic factors for disease severity were selected according to previous reports: sex, age, type of surgery, disease duration, body mass index, cervical lesion, presence of diabetes mellitus, Workers' Compensation status, preoperative severity, and preoperative electrodiagnostic testing. Postoperative severity of disease was assessed 2 years after surgery by Messina's criteria which is an outcome measure specifically for CubTS. Bivariate analysis was performed to select candidate prognostic factors for multiple linear regression analyses. Multiple logistic regression analysis was conducted to identify the association between postoperative severity and selected prognostic factors. Both bivariate and multiple linear regression analysis revealed only preoperative severity as an independent risk factor for poor prognosis, while other factors did not show any significant association. Although conflicting results exist regarding prognosis of CubTS, this study supports evidence from previous studies and concludes early surgical intervention portends the most favorable prognosis. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Attention deficit hyperactivity disorder in cocaine-dependent adults: a psychiatric comorbidity analysis.

PubMed

Daigre, Constanza; Roncero, Carlos; Grau-López, Lara; Martínez-Luna, Nieves; Prat, Gemma; Valero, Sergi; Tejedor, Rosa; Ramos-Quiroga, Josep A; Casas, Miguel

2013-01-01

Attention deficit hyperactivity disorder (ADHD) is highly prevalent among drug abusers. We studied the psychiatric comorbidity and characteristics of cocaine use in relation to the presence of ADHD among patients with cocaine dependence. A total of 200 cocaine-dependent patients attending an Outpatient Drug Clinic participated in the study. A systematic evaluation of ADHD (CAADID-II), the severity of addiction (EuropASI) and other axes I and II psychiatric disorders was made (SCID-I and SCID-II). A descriptive, bivariate, and multivariate analysis of the data was performed. In the multivariate analysis, the identified risk factors for the development of ADHD were a history of behavioral disorder in childhood (OR: 3.04), a lifetime history of cannabis dependence in the course of life (OR: 2.68), and age at the start of treatment (OR: 1.08). The bivariate analysis showed ADHD to be associated with other factors such as male gender, age at start of cocaine use and dependence, the amount of cocaine consumed weekly, increased occupational alteration, alcohol consumption, general psychological discomfort, depressive disorder, and antisocial personality disorder. We conclude that ADHD is associated with increased psychiatric comorbidity and greater severity of addiction. Copyright © American Academy of Addiction Psychiatry.

Hydrologic risk analysis in the Yangtze River basin through coupling Gaussian mixtures into copulas

NASA Astrophysics Data System (ADS)

Fan, Y. R.; Huang, W. W.; Huang, G. H.; Li, Y. P.; Huang, K.; Li, Z.

2016-02-01

In this study, a bivariate hydrologic risk framework is proposed through coupling Gaussian mixtures into copulas, leading to a coupled GMM-copula method. In the coupled GMM-Copula method, the marginal distributions of flood peak, volume and duration are quantified through Gaussian mixture models and the joint probability distributions of flood peak-volume, peak-duration and volume-duration are established through copulas. The bivariate hydrologic risk is then derived based on the joint return period of flood variable pairs. The proposed method is applied to the risk analysis for the Yichang station on the main stream of the Yangtze River, China. The results indicate that (i) the bivariate risk for flood peak-volume would keep constant for the flood volume less than 1.0 × 105 m3/s day, but present a significant decreasing trend for the flood volume larger than 1.7 × 105 m3/s day; and (ii) the bivariate risk for flood peak-duration would not change significantly for the flood duration less than 8 days, and then decrease significantly as duration value become larger. The probability density functions (pdfs) of the flood volume and duration conditional on flood peak can also be generated through the fitted copulas. The results indicate that the conditional pdfs of flood volume and duration follow bimodal distributions, with the occurrence frequency of the first vertex decreasing and the latter one increasing as the increase of flood peak. The obtained conclusions from the bivariate hydrologic analysis can provide decision support for flood control and mitigation.

[Bioimpedance vector analysis for body composition in Mexican population].

PubMed

Espinosa-Cuevas, Maria de los Angeles; Rivas-Rodríguez, Lucía; González-Medina, Enna Cristal; Atilano-Carsi, Ximena; Miranda-Alatriste, Paola; Correa-Rotter, Ricardo

2007-01-01

To construct bivariate tolerance ellipses from impedance values normalized for height, which can be used in Mexican population for the assessment of body composition and compare them with others made in different populations. Body composition was assessed by bioelectrical impedance analysis (BIA) in 439 subjects (204 men and 235 women), 18 to 82 years old, with a BMI between 18-31, using an impedanciometer Quadscan 4000. Resistance, reactance and phase angle were used to calculate bioelectrical impedance vectors and construct bivariate tolerance ellipses. Mean age in men was 47.1 +/- 16 years and 42.4 +/- 13 for women, mean weight (73.4 + 9 vs. 60.1 + 8 kg) and height (1.68 vs. 1.55 m) were significant greater in men than in women (p < 0.002). Women in comparison with men, had greater values of impedance (622.96 +/- 66.16 S2 vs. 523.59 +/- 56.56 D) and resistance (618.96 +/- 66.10 Q 61.97 vs. 521.73 +/- 61.97 2), as well as of resistance and reactance standardized by height (398.24 +/-46.30 S2/m vs. 308.66 +/- 38.44) (44.32 +/- 7.14 i/m vs. 39.75 +/-6.29) respectively, with a significant difference in all of them (p < 0.0001). Similarly, the reactance was greater in females, nevertheless this difference did not reach statistical significance (68.96 +/- 11.17 vs. 67.18 +/- 10.3; p = 0.0861). The phase angle was greater in men than in women, with a statistically significant difference (7.330 +/- 0.88 vs. 6.360 +/- 0.97; p < 0.0001). Bivariate tolerance ellipses (50%, 75% and 95%) derived from Mexican subjects showed a significant upward deviation (p < 0.05) from previously published references from Mexican American and Italian populations. New ellipses of tolerance were therefore constructed for the Mexican population. Bioimpedance vectors in Mexican subjects are significantly different from the existing ones, supporting the need of population specific bivariate tolerance ellipses for the evaluation of body composition.

The Bivariate Luminosity--HI Mass Distribution Function of Galaxies based on the NIBLES Survey

NASA Astrophysics Data System (ADS)

Butcher, Zhon; Schneider, Stephen E.; van Driel, Wim; Lehnert, Matt

2016-01-01

We use 21cm HI line observations for 2610 galaxies from the Nançay Interstellar Baryons Legacy Extragalactic Survey (NIBLES) to derive a bivariate luminosity--HI mass distribution function. Our HI survey was selected to randomly probe the local (900 < cz < 12,000 km/s) galaxy population in each 0.5 mag wide bin for the absolute z-band magnitude range of -13.5 < Mz < -24 without regard to morphology or color. This targeted survey allowed more on-source integration time for weak and non-detected sources, enabling us to probe lower HI mass fractions and apply lower upper limits for non-detections than would be possible with the larger blind HI surveys. Additionally, we obtained a factor of four higher sensitivity follow-up observations at Arecibo of 90 galaxies from our non-detected and marginally detected categories to quantify the underlying HI distribution of sources not detected at Nançay. Using the optical luminosity function and our higher sensitivity follow up observations as priors, we use a 2D stepwise maximum likelihood technique to derive the two dimensional volume density distribution of luminosity and HI mass in each SDSS band.

Time-dependent summary receiver operating characteristics for meta-analysis of prognostic studies.

PubMed

Hattori, Satoshi; Zhou, Xiao-Hua

2016-11-20

Prognostic studies are widely conducted to examine whether biomarkers are associated with patient's prognoses and play important roles in medical decisions. Because findings from one prognostic study may be very limited, meta-analyses may be useful to obtain sound evidence. However, prognostic studies are often analyzed by relying on a study-specific cut-off value, which can lead to difficulty in applying the standard meta-analysis techniques. In this paper, we propose two methods to estimate a time-dependent version of the summary receiver operating characteristics curve for meta-analyses of prognostic studies with a right-censored time-to-event outcome. We introduce a bivariate normal model for the pair of time-dependent sensitivity and specificity and propose a method to form inferences based on summary statistics reported in published papers. This method provides a valid inference asymptotically. In addition, we consider a bivariate binomial model. To draw inferences from this bivariate binomial model, we introduce a multiple imputation method. The multiple imputation is found to be approximately proper multiple imputation, and thus the standard Rubin's variance formula is justified from a Bayesian view point. Our simulation study and application to a real dataset revealed that both methods work well with a moderate or large number of studies and the bivariate binomial model coupled with the multiple imputation outperforms the bivariate normal model with a small number of studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

REGRES: A FORTRAN-77 program to calculate nonparametric and ``structural'' parametric solutions to bivariate regression equations

NASA Astrophysics Data System (ADS)

Rock, N. M. S.; Duffy, T. R.

REGRES allows a range of regression equations to be calculated for paired sets of data values in which both variables are subject to error (i.e. neither is the "independent" variable). Nonparametric regressions, based on medians of all possible pairwise slopes and intercepts, are treated in detail. Estimated slopes and intercepts are output, along with confidence limits, Spearman and Kendall rank correlation coefficients. Outliers can be rejected with user-determined stringency. Parametric regressions can be calculated for any value of λ (the ratio of the variances of the random errors for y and x)—including: (1) major axis ( λ = 1); (2) reduced major axis ( λ = variance of y/variance of x); (3) Y on Xλ = infinity; or (4) X on Y ( λ = 0) solutions. Pearson linear correlation coefficients also are output. REGRES provides an alternative to conventional isochron assessment techniques where bivariate normal errors cannot be assumed, or weighting methods are inappropriate.

Inference for the Bivariate and Multivariate Hidden Truncated Pareto(type II) and Pareto(type IV) Distribution and Some Measures of Divergence Related to Incompatibility of Probability Distribution

ERIC Educational Resources Information Center

Ghosh, Indranil

2011-01-01

Consider a discrete bivariate random variable (X, Y) with possible values x[subscript 1], x[subscript 2],..., x[subscript I] for X and y[subscript 1], y[subscript 2],..., y[subscript J] for Y. Further suppose that the corresponding families of conditional distributions, for X given values of Y and of Y for given values of X are available. We…

Flood risk analysis for flood control and sediment transportation: a case study in the catchments of the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Wang, Y.; Chang, J.; Guo, A.

2017-12-01

Traditional flood risk analysis focuses on the probability of flood events exceeding the design flood of downstream hydraulic structures while neglecting the influence of sedimentation in river channels on flood control systems. Given this focus, a univariate and copula-based bivariate hydrological risk framework focusing on flood control and sediment transport is proposed in the current work. Additionally, the conditional probabilities of occurrence of different flood events under various extreme precipitation scenarios are estimated by exploiting the copula model. Moreover, a Monte Carlo-based algorithm is used to evaluate the uncertainties of univariate and bivariate hydrological risk. Two catchments located on the Loess plateau are selected as study regions: the upper catchments of the Xianyang and Huaxian stations (denoted as UCX and UCH, respectively). The results indicate that (1) 2-day and 3-day consecutive rainfall are highly correlated with the annual maximum flood discharge (AMF) in UCX and UCH, respectively; and (2) univariate and bivariate return periods, risk and reliability for the purposes of flood control and sediment transport are successfully estimated. Sedimentation triggers higher risks of damaging the safety of local flood control systems compared with the AMF, exceeding the design flood of downstream hydraulic structures in the UCX and UCH. Most importantly, there was considerable sampling uncertainty in the univariate and bivariate hydrologic risk analysis, which would greatly challenge measures of future flood mitigation. The proposed hydrological risk framework offers a promising technical reference for flood risk analysis in sandy regions worldwide.

Semiparametric bivariate zero-inflated Poisson models with application to studies of abundance for multiple species

USGS Publications Warehouse

Arab, Ali; Holan, Scott H.; Wikle, Christopher K.; Wildhaber, Mark L.

2012-01-01

Ecological studies involving counts of abundance, presence–absence or occupancy rates often produce data having a substantial proportion of zeros. Furthermore, these types of processes are typically multivariate and only adequately described by complex nonlinear relationships involving externally measured covariates. Ignoring these aspects of the data and implementing standard approaches can lead to models that fail to provide adequate scientific understanding of the underlying ecological processes, possibly resulting in a loss of inferential power. One method of dealing with data having excess zeros is to consider the class of univariate zero-inflated generalized linear models. However, this class of models fails to address the multivariate and nonlinear aspects associated with the data usually encountered in practice. Therefore, we propose a semiparametric bivariate zero-inflated Poisson model that takes into account both of these data attributes. The general modeling framework is hierarchical Bayes and is suitable for a broad range of applications. We demonstrate the effectiveness of our model through a motivating example on modeling catch per unit area for multiple species using data from the Missouri River Benthic Fishes Study, implemented by the United States Geological Survey.

Bivariate spatiotemporal disease mapping of cancer of the breast and cervix uteri among Iranian women.

PubMed

Raei, Mehdi; Schmid, Volker Johann; Mahaki, Behzad

2018-05-08

Cervical cancer in women is one of the most common cancers and breast cancer has grown dramatically in recent years. The purpose of this study was to map the incidence of breast and cervix uteri cancer among Iranian women over a 6-year period (2004-2009) searching for trend changes and risk factors. Cancer incidence data were extracted from the annual reports of the National Cancer Registry in Iran. Hierarchical Bayesian models, including random spatial and temporal effects was utilized together with bivariate, spatio-temporal shared component modelling. The provinces Tehran, Isfahan, Mazandaran and Gilan were found to have the highest relative risk (RR) of breast cancer, while the highest RR of cervix uteri cancer was observed in Tehran, Golestan, Khuzestan and Khorasan Razavi. Shared risk factors (smoking component) between the two cancers were seen to have the highest influence in Tehran, Khorasan Razavi, Yazd, Isfahan, Golestan, Khuzestan, Fars and Mazandaran, while the least were observed in Kohgiluyeh Boyerahmad. Apparent differences and distinctions between high-risk and low-risk provinces reveal a pattern of obvious dispersion for these cancers in Iran that should be considered when allocating healthcare resources and services in different areas.

Modeling both of the number of pausibacillary and multibacillary leprosy patients by using bivariate poisson regression

NASA Astrophysics Data System (ADS)

Winahju, W. S.; Mukarromah, A.; Putri, S.

2015-03-01

Leprosy is a chronic infectious disease caused by bacteria of leprosy (Mycobacterium leprae). Leprosy has become an important thing in Indonesia because its morbidity is quite high. Based on WHO data in 2014, in 2012 Indonesia has the highest number of new leprosy patients after India and Brazil with a contribution of 18.994 people (8.7% of the world). This number makes Indonesia automatically placed as the country with the highest number of leprosy morbidity of ASEAN countries. The province that most contributes to the number of leprosy patients in Indonesia is East Java. There are two kind of leprosy. They consist of pausibacillary and multibacillary. The morbidity of multibacillary leprosy is higher than pausibacillary leprosy. This paper will discuss modeling both of the number of multibacillary and pausibacillary leprosy patients as responses variables. These responses are count variables, so modeling will be conducted by using bivariate poisson regression method. Unit experiment used is in East Java, and predictors involved are: environment, demography, and poverty. The model uses data in 2012, and the result indicates that all predictors influence significantly.

Meta-Analyses of Diagnostic Accuracy in Imaging Journals: Analysis of Pooling Techniques and Their Effect on Summary Estimates of Diagnostic Accuracy.

PubMed

McGrath, Trevor A; McInnes, Matthew D F; Korevaar, Daniël A; Bossuyt, Patrick M M

2016-10-01

Purpose To determine whether authors of systematic reviews of diagnostic accuracy studies published in imaging journals used recommended methods for meta-analysis, and to evaluate the effect of traditional methods on summary estimates of sensitivity and specificity. Materials and Methods Medline was searched for published systematic reviews that included meta-analysis of test accuracy data limited to imaging journals published from January 2005 to May 2015. Two reviewers independently extracted study data and classified methods for meta-analysis as traditional (univariate fixed- or random-effects pooling or summary receiver operating characteristic curve) or recommended (bivariate model or hierarchic summary receiver operating characteristic curve). Use of methods was analyzed for variation with time, geographical location, subspecialty, and journal. Results from reviews in which study authors used traditional univariate pooling methods were recalculated with a bivariate model. Results Three hundred reviews met the inclusion criteria, and in 118 (39%) of those, authors used recommended meta-analysis methods. No change in the method used was observed with time (r = 0.54, P = .09); however, there was geographic (χ(2) = 15.7, P = .001), subspecialty (χ(2) = 46.7, P < .001), and journal (χ(2) = 27.6, P < .001) heterogeneity. Fifty-one univariate random-effects meta-analyses were reanalyzed with the bivariate model; the average change in the summary estimate was -1.4% (P < .001) for sensitivity and -2.5% (P < .001) for specificity. The average change in width of the confidence interval was 7.7% (P < .001) for sensitivity and 9.9% (P ≤ .001) for specificity. Conclusion Recommended methods for meta-analysis of diagnostic accuracy in imaging journals are used in a minority of reviews; this has not changed significantly with time. Traditional (univariate) methods allow overestimation of diagnostic accuracy and provide narrower confidence intervals than do recommended

Meta-analysis of diagnostic tests accounting for disease prevalence: a new model using trivariate copulas.

PubMed

Hoyer, A; Kuss, O

2015-05-20

In real life and somewhat contrary to biostatistical textbook knowledge, sensitivity and specificity (and not only predictive values) of diagnostic tests can vary with the underlying prevalence of disease. In meta-analysis of diagnostic studies, accounting for this fact naturally leads to a trivariate expansion of the traditional bivariate logistic regression model with random study effects. In this paper, a new model is proposed using trivariate copulas and beta-binomial marginal distributions for sensitivity, specificity, and prevalence as an expansion of the bivariate model. Two different copulas are used, the trivariate Gaussian copula and a trivariate vine copula based on the bivariate Plackett copula. This model has a closed-form likelihood, so standard software (e.g., SAS PROC NLMIXED) can be used. The results of a simulation study have shown that the copula models perform at least as good but frequently better than the standard model. The methods are illustrated by two examples. Copyright © 2015 John Wiley & Sons, Ltd.

Multifractal detrended cross-correlation analysis on gold, crude oil and foreign exchange rate time series

NASA Astrophysics Data System (ADS)

Pal, Mayukha; Madhusudana Rao, P.; Manimaran, P.

2014-12-01

We apply the recently developed multifractal detrended cross-correlation analysis method to investigate the cross-correlation behavior and fractal nature between two non-stationary time series. We analyze the daily return price of gold, West Texas Intermediate and Brent crude oil, foreign exchange rate data, over a period of 18 years. The cross correlation has been measured from the Hurst scaling exponents and the singularity spectrum quantitatively. From the results, the existence of multifractal cross-correlation between all of these time series is found. We also found that the cross correlation between gold and oil prices possess uncorrelated behavior and the remaining bivariate time series possess persistent behavior. It was observed for five bivariate series that the cross-correlation exponents are less than the calculated average generalized Hurst exponents (GHE) for q<0 and greater than GHE when q>0 and for one bivariate series the cross-correlation exponent is greater than GHE for all q values.

Fat stigmatization in television shows and movies: a content analysis.

PubMed

Himes, Susan M; Thompson, J Kevin

2007-03-01

To examine the phenomenon of fat stigmatization messages presented in television shows and movies, a content analysis was used to quantify and categorize fat-specific commentary and humor. Fat stigmatization vignettes were identified using a targeted sampling procedure, and 135 scenes were excised from movies and television shows. The material was coded by trained raters. Reliability indices were uniformly high for the seven categories (percentage agreement ranged from 0.90 to 0.98; kappas ranged from 0.66 to 0.94). Results indicated that fat stigmatization commentary and fat humor were often verbal, directed toward another person, and often presented directly in the presence of the overweight target. Results also indicated that male characters were three times more likely to engage in fat stigmatization commentary or fat humor than female characters. To our knowledge, these findings provide the first information regarding the specific gender, age, and types of fat stigmatization that occur frequently in movies and television shows. The stimuli should prove useful in future research examining the role of individual difference factors (e.g., BMI) in the reaction to viewing such vignettes.

Improving risk estimates of runoff producing areas: formulating variable source areas as a bivariate process.

PubMed

Cheng, Xiaoya; Shaw, Stephen B; Marjerison, Rebecca D; Yearick, Christopher D; DeGloria, Stephen D; Walter, M Todd

2014-05-01

Predicting runoff producing areas and their corresponding risks of generating storm runoff is important for developing watershed management strategies to mitigate non-point source pollution. However, few methods for making these predictions have been proposed, especially operational approaches that would be useful in areas where variable source area (VSA) hydrology dominates storm runoff. The objective of this study is to develop a simple approach to estimate spatially-distributed risks of runoff production. By considering the development of overland flow as a bivariate process, we incorporated both rainfall and antecedent soil moisture conditions into a method for predicting VSAs based on the Natural Resource Conservation Service-Curve Number equation. We used base-flow immediately preceding storm events as an index of antecedent soil wetness status. Using nine sub-basins of the Upper Susquehanna River Basin, we demonstrated that our estimated runoff volumes and extent of VSAs agreed with observations. We further demonstrated a method for mapping these areas in a Geographic Information System using a Soil Topographic Index. The proposed methodology provides a new tool for watershed planners for quantifying runoff risks across watersheds, which can be used to target water quality protection strategies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Principal component regression analysis with SPSS.

PubMed

Liu, R X; Kuang, J; Gong, Q; Hou, X L

2003-06-01

The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.

Assessing protein conformational sampling methods based on bivariate lag-distributions of backbone angles

PubMed Central

Maadooliat, Mehdi; Huang, Jianhua Z.

2013-01-01

Despite considerable progress in the past decades, protein structure prediction remains one of the major unsolved problems in computational biology. Angular-sampling-based methods have been extensively studied recently due to their ability to capture the continuous conformational space of protein structures. The literature has focused on using a variety of parametric models of the sequential dependencies between angle pairs along the protein chains. In this article, we present a thorough review of angular-sampling-based methods by assessing three main questions: What is the best distribution type to model the protein angles? What is a reasonable number of components in a mixture model that should be considered to accurately parameterize the joint distribution of the angles? and What is the order of the local sequence–structure dependency that should be considered by a prediction method? We assess the model fits for different methods using bivariate lag-distributions of the dihedral/planar angles. Moreover, the main information across the lags can be extracted using a technique called Lag singular value decomposition (LagSVD), which considers the joint distribution of the dihedral/planar angles over different lags using a nonparametric approach and monitors the behavior of the lag-distribution of the angles using singular value decomposition. As a result, we developed graphical tools and numerical measurements to compare and evaluate the performance of different model fits. Furthermore, we developed a web-tool (http://www.stat.tamu.edu/∼madoliat/LagSVD) that can be used to produce informative animations. PMID:22926831

Using the Bivariate Dale Model to jointly estimate predictors of frequency and quantity of alcohol use.

PubMed

McMillan, Garnett P; Hanson, Tim; Bedrick, Edward J; Lapham, Sandra C

2005-09-01

This study demonstrates the usefulness of the Bivariate Dale Model (BDM) as a method for estimating the relationship between risk factors and the quantity and frequency of alcohol use, as well as the degree of association between these highly correlated drinking measures. The BDM is used to evaluate childhood sexual abuse, along with age and gender, as risk factors for the quantity and frequency of beer consumption in a sample of driving-while-intoxicated (DWI) offenders (N = 1,964; 1,612 men). The BDM allows one to estimate the relative odds of drinking up to each level of ordinal-scaled quantity and frequency of alcohol use, as well as model the degree of association between quantity and frequency of alcohol consumption as a function of covariates. Individuals who experienced childhood sexual abuse have increased risks of higher quantity and frequency of beer consumption. History of childhood sexual abuse has a greater effect on women, causing them to drink higher quantities of beer per drinking occasion. The BDM is a useful method for evaluating predictors of the quantity-frequency of alcohol consumption. SAS macrocode for fitting the BDM model is provided.

Direct, indirect, and intangible costs after severe trauma up to occupational reintegration - an empirical analysis of 113 seriously injured patients.

PubMed

Anders, Benjamin; Ommen, Oliver; Pfaff, Holger; Lüngen, Markus; Lefering, Rolf; Thüm, Sonja; Janssen, Christian

2013-01-01

Although seriously injured patients account for a high medical as well as socioeconomic burden of disease in the German health care system, there are only very few data describing the costs that arise between the days of accident and occupational reintegration. With this study, a comprehensive cost model is developed that describes the direct, indirect and intangible costs of an accident and their relationship with socioeconomic background of the patients. This study included 113 patients who each had at least two injuries and a total Abbreviated Injury Scale (AIS) greater than or equal to five. We calculated the direct, indirect and intangible costs that arose between the day of the accident and occupational reintegration. Direct costs were the treatment costs at hospitals and rehabilitation centers. Indirect costs were calculated using the human capital approach on the basis of the work days lost due to injury, including sickness allowance benefits. Intangible costs were assessed using the Short Form Survey (SF-36) and represented in non-monetary form. Following univariate analysis, a bivariate analysis of the above costs and the patients' sociodemographic and socioeconomic characteristics was performed. At an average Injury Severity Score (ISS) of 19.2, the average direct cost per patient were €35,661. An average of 185.2 work days were lost, resulting in indirect costs of €17,205. The resulting total costs per patient were €50,431. A bivariate analysis showed that the costs for hospital treatment were 58% higher in patients who graduated from lower secondary school [Hauptschule] (ISS 19.5) than in patients with qualification for university admission [Abitur] (ISS 19.4). The direct costs of treating trauma patients at the hospital appear to be lower in patients with a higher level of education than in the comparison group with a lower educational level. Because of missing data, the calculated indirect costs can merely represent a general trend, so that the

Evolution of association between renal and liver functions while awaiting heart transplant: An application using a bivariate multiphase nonlinear mixed effects model.

PubMed

Rajeswaran, Jeevanantham; Blackstone, Eugene H; Barnard, John

2018-07-01

In many longitudinal follow-up studies, we observe more than one longitudinal outcome. Impaired renal and liver functions are indicators of poor clinical outcomes for patients who are on mechanical circulatory support and awaiting heart transplant. Hence, monitoring organ functions while waiting for heart transplant is an integral part of patient management. Longitudinal measurements of bilirubin can be used as a marker for liver function and glomerular filtration rate for renal function. We derive an approximation to evolution of association between these two organ functions using a bivariate nonlinear mixed effects model for continuous longitudinal measurements, where the two submodels are linked by a common distribution of time-dependent latent variables and a common distribution of measurement errors.

Flood risk analysis for flood control and sediment transportation in sandy regions: A case study in the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Guo, Aijun; Chang, Jianxia; Wang, Yimin; Huang, Qiang; Zhou, Shuai

2018-05-01

Traditional flood risk analysis focuses on the probability of flood events exceeding the design flood of downstream hydraulic structures while neglecting the influence of sedimentation in river channels on regional flood control systems. This work advances traditional flood risk analysis by proposing a univariate and copula-based bivariate hydrological risk framework which incorporates both flood control and sediment transport. In developing the framework, the conditional probabilities of different flood events under various extreme precipitation scenarios are estimated by exploiting the copula-based model. Moreover, a Monte Carlo-based algorithm is designed to quantify the sampling uncertainty associated with univariate and bivariate hydrological risk analyses. Two catchments located on the Loess plateau are selected as study regions: the upper catchments of the Xianyang and Huaxian stations (denoted as UCX and UCH, respectively). The univariate and bivariate return periods, risk and reliability in the context of uncertainty for the purposes of flood control and sediment transport are assessed for the study regions. The results indicate that sedimentation triggers higher risks of damaging the safety of local flood control systems compared with the event that AMF exceeds the design flood of downstream hydraulic structures in the UCX and UCH. Moreover, there is considerable sampling uncertainty affecting the univariate and bivariate hydrologic risk evaluation, which greatly challenges measures of future flood mitigation. In addition, results also confirm that the developed framework can estimate conditional probabilities associated with different flood events under various extreme precipitation scenarios aiming for flood control and sediment transport. The proposed hydrological risk framework offers a promising technical reference for flood risk analysis in sandy regions worldwide.

Direct, indirect, and intangible costs after severe trauma up to occupational reintegration – an empirical analysis of 113 seriously injured patients

PubMed Central

Anders, Benjamin; Ommen, Oliver; Pfaff, Holger; Lüngen, Markus; Lefering, Rolf; Thüm, Sonja; Janssen, Christian

2013-01-01

Aim: Although seriously injured patients account for a high medical as well as socioeconomic burden of disease in the German health care system, there are only very few data describing the costs that arise between the days of accident and occupational reintegration. With this study, a comprehensive cost model is developed that describes the direct, indirect and intangible costs of an accident and their relationship with socioeconomic background of the patients. Methods: This study included 113 patients who each had at least two injuries and a total Abbreviated Injury Scale (AIS) greater than or equal to five. We calculated the direct, indirect and intangible costs that arose between the day of the accident and occupational reintegration. Direct costs were the treatment costs at hospitals and rehabilitation centers. Indirect costs were calculated using the human capital approach on the basis of the work days lost due to injury, including sickness allowance benefits. Intangible costs were assessed using the Short Form Survey (SF-36) and represented in non-monetary form. Following univariate analysis, a bivariate analysis of the above costs and the patients’ sociodemographic and socioeconomic characteristics was performed. Results: At an average Injury Severity Score (ISS) of 19.2, the average direct cost per patient were €35,661. An average of 185.2 work days were lost, resulting in indirect costs of €17,205. The resulting total costs per patient were €50,431. A bivariate analysis showed that the costs for hospital treatment were 58% higher in patients who graduated from lower secondary school [Hauptschule] (ISS 19.5) than in patients with qualification for university admission [Abitur] (ISS 19.4). Conclusions: The direct costs of treating trauma patients at the hospital appear to be lower in patients with a higher level of education than in the comparison group with a lower educational level. Because of missing data, the calculated indirect costs can merely

Deeper Insights into the Circumgalactic Medium using Multivariate Analysis Methods

NASA Astrophysics Data System (ADS)

Lewis, James; Churchill, Christopher W.; Nielsen, Nikole M.; Kacprzak, Glenn

2017-01-01

Drawing from a database of galaxies whose surrounding gas has absorption from MgII, called the MgII-Absorbing Galaxy Catalog (MAGIICAT, Neilsen et al 2013), we studied the circumgalactic medium (CGM) for a sample of 47 galaxies. Using multivariate analysis, in particular the k-means clustering algorithm, we determined that simultaneously examining column density (N), rest-frame B-K color, virial mass, and azimuthal angle (the projected angle between the galaxy major axis and the quasar line of sight) yields two distinct populations: (1) bluer, lower mass galaxies with higher column density along the minor axis, and (2) redder, higher mass galaxies with lower column density along the major axis. We support this grouping by running (i) two-sample, two-dimensional Kolmogorov-Smirnov (KS) tests on each of the six bivariate planes and (ii) two-sample KS tests on each of the four variables to show that the galaxies significantly cluster into two independent populations. To account for the fact that 16 of our 47 galaxies have upper limits on N, we performed Monte-Carlo tests whereby we replaced upper limits with random deviates drawn from a Schechter distribution fit, f(N). These tests strengthen the results of the KS tests. We examined the behavior of the MgII λ2796 absorption line equivalent width and velocity width for each galaxy population. We find that equivalent width and velocity width do not show similar characteristic distinctions between the two galaxy populations. We discuss the k-means clustering algorithm for optimizing the analysis of populations within datasets as opposed to using arbitrary bivariate subsample cuts. We also discuss the power of the k-means clustering algorithm in extracting deeper physical insight into the CGM in relationship to host galaxies.

Assessment of cardio-respiratory interactions in preterm infants by bivariate autoregressive modeling and surrogate data analysis.

PubMed

Indic, Premananda; Bloch-Salisbury, Elisabeth; Bednarek, Frank; Brown, Emery N; Paydarfar, David; Barbieri, Riccardo

2011-07-01

Cardio-respiratory interactions are weak at the earliest stages of human development, suggesting that assessment of their presence and integrity may be an important indicator of development in infants. Despite the valuable research devoted to infant development, there is still a need for specifically targeted standards and methods to assess cardiopulmonary functions in the early stages of life. We present a new methodological framework for the analysis of cardiovascular variables in preterm infants. Our approach is based on a set of mathematical tools that have been successful in quantifying important cardiovascular control mechanisms in adult humans, here specifically adapted to reflect the physiology of the developing cardiovascular system. We applied our methodology in a study of cardio-respiratory responses for 11 preterm infants. We quantified cardio-respiratory interactions using specifically tailored multivariate autoregressive analysis and calculated the coherence as well as gain using causal approaches. The significance of the interactions in each subject was determined by surrogate data analysis. The method was tested in control conditions as well as in two different experimental conditions; with and without use of mild mechanosensory intervention. Our multivariate analysis revealed a significantly higher coherence, as confirmed by surrogate data analysis, in the frequency range associated with eupneic breathing compared to the other ranges. Our analysis validates the models behind our new approaches, and our results confirm the presence of cardio-respiratory coupling in early stages of development, particularly during periods of mild mechanosensory intervention, thus encouraging further application of our approach. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Impacts of rising health care costs on families with employment-based private insurance: a national analysis with state fixed effects.

PubMed

Yu, Hao; Dick, Andrew W

2012-10-01

Given the rapid growth of health care costs, some experts were concerned with erosion of employment-based private insurance (EBPI). This empirical analysis aims to quantify the concern. Using the National Health Account, we generated a cost index to represent state-level annual cost growth. We merged it with the 1996-2003 Medical Expenditure Panel Survey. The unit of analysis is the family. We conducted both bivariate and multivariate logistic analyses. The bivariate analysis found a significant inverse association between the cost index and the proportion of families receiving an offer of EBPI. The multivariate analysis showed that the cost index was significantly negatively associated with the likelihood of receiving an EBPI offer for the entire sample and for families in the first, second, and third quartiles of income distribution. The cost index was also significantly negatively associated with the proportion of families with EBPI for the entire year for each family member (EBPI-EYEM). The multivariate analysis confirmed significance of the relationship for the entire sample, and for families in the second and third quartiles of income distribution. Among the families with EBPI-EYEM, there was a positive relationship between the cost index and this group's likelihood of having out-of-pocket expenditures exceeding 10 percent of family income. The multivariate analysis confirmed significance of the relationship for the entire group and for families in the second and third quartiles of income distribution. Rising health costs reduce EBPI availability and enrollment, and the financial protection provided by it, especially for middle-class families. © Health Research and Educational Trust.

Impacts of Rising Health Care Costs on Families with Employment-Based Private Insurance: A National Analysis with State Fixed Effects

PubMed Central

Yu, Hao; Dick, Andrew W

2012-01-01

Background Given the rapid growth of health care costs, some experts were concerned with erosion of employment-based private insurance (EBPI). This empirical analysis aims to quantify the concern. Methods Using the National Health Account, we generated a cost index to represent state-level annual cost growth. We merged it with the 1996–2003 Medical Expenditure Panel Survey. The unit of analysis is the family. We conducted both bivariate and multivariate logistic analyses. Results The bivariate analysis found a significant inverse association between the cost index and the proportion of families receiving an offer of EBPI. The multivariate analysis showed that the cost index was significantly negatively associated with the likelihood of receiving an EBPI offer for the entire sample and for families in the first, second, and third quartiles of income distribution. The cost index was also significantly negatively associated with the proportion of families with EBPI for the entire year for each family member (EBPI-EYEM). The multivariate analysis confirmed significance of the relationship for the entire sample, and for families in the second and third quartiles of income distribution. Among the families with EBPI-EYEM, there was a positive relationship between the cost index and this group's likelihood of having out-of-pocket expenditures exceeding 10 percent of family income. The multivariate analysis confirmed significance of the relationship for the entire group and for families in the second and third quartiles of income distribution. Conclusions Rising health costs reduce EBPI availability and enrollment, and the financial protection provided by it, especially for middle-class families. PMID:22417314

A new correlation coefficient for bivariate time-series data

NASA Astrophysics Data System (ADS)

Erdem, Orhan; Ceyhan, Elvan; Varli, Yusuf

2014-11-01

The correlation in time series has received considerable attention in the literature. Its use has attained an important role in the social sciences and finance. For example, pair trading in finance is concerned with the correlation between stock prices, returns, etc. In general, Pearson’s correlation coefficient is employed in these areas although it has many underlying assumptions which restrict its use. Here, we introduce a new correlation coefficient which takes into account the lag difference of data points. We investigate the properties of this new correlation coefficient. We demonstrate that it is more appropriate for showing the direction of the covariation of the two variables over time. We also compare the performance of the new correlation coefficient with Pearson’s correlation coefficient and Detrended Cross-Correlation Analysis (DCCA) via simulated examples.

A Meta-Analysis of Social Capital and Health: A Case for Needed Research

PubMed Central

Gilbert, Keon L.; Quinn, Sandra C.; Goodman, Robert M.; Butler, James; Wallace, John

2014-01-01

Background Social capital refers to various levels of social relationships formed through social networks. Measurement differences have lead to imprecise measurement. Methods A meta-analysis of eligible studies assessing the bivariate association between social capital and self-reported health and all-cause mortality. Results Thirty-nine studies met inclusion criteria, showing social capital increased odds of good health by 27% (95% confidence intervals [CI] =21%, 34%). Social capital variables, reciprocity increased odds of good health by 39% (95% CI = 21%, 60%), trust by 32% (95% CI =19%, 46%). Future research suggests operationalizing measures by assessing differences by race/ethnicity, gender and socioeconomic status. PMID:23548810

Evaluating Dynamic Bivariate Correlations in Resting-state fMRI: A comparison study and a new approach

PubMed Central

Lindquist, Martin A.; Xu, Yuting; Nebel, Mary Beth; Caffo, Brain S.

2014-01-01

To date, most functional Magnetic Resonance Imaging (fMRI) studies have assumed that the functional connectivity (FC) between time series from distinct brain regions is constant across time. However, recently, there has been increased interest in quantifying possible dynamic changes in FC during fMRI experiments, as it is thought this may provide insight into the fundamental workings of brain networks. In this work we focus on the specific problem of estimating the dynamic behavior of pair-wise correlations between time courses extracted from two different regions of the brain. We critique the commonly used sliding-windows technique, and discuss some alternative methods used to model volatility in the finance literature that could also prove useful in the neuroimaging setting. In particular, we focus on the Dynamic Conditional Correlation (DCC) model, which provides a model-based approach towards estimating dynamic correlations. We investigate the properties of several techniques in a series of simulation studies and find that DCC achieves the best overall balance between sensitivity and specificity in detecting dynamic changes in correlations. We also investigate its scalability beyond the bivariate case to demonstrate its utility for studying dynamic correlations between more than two brain regions. Finally, we illustrate its performance in an application to test-retest resting state fMRI data. PMID:24993894

Design and analysis of mixed cropping experiments for indigenous Pacific Islands

Treesearch

Mareko P. Tofinga

1993-01-01

Mixed cropping (including agroforestry) often gives yield advan-tages as opposed to monocropping. Many criteria have been used to assess yield advantage in crop mixtures. Some of these are presented. In addition, the relative merits of replacement, additive and bivariate factorial designs are discussed. The concepts of analysis of mixed cropping are applied to an...

Disability in physical education textbooks: an analysis of image content.

PubMed

Táboas-Pais, María Inés; Rey-Cao, Ana

2012-10-01

The aim of this paper is to show how images of disability are portrayed in physical education textbooks for secondary schools in Spain. The sample was composed of 3,316 images published in 36 textbooks by 10 publishing houses. A content analysis was carried out using a coding scheme based on categories employed in other similar studies and adapted to the requirements of this study with additional categories. The variables were camera angle, gender, type of physical activity, field of practice, space, and level. Univariate and bivariate descriptive analyses were also carried out. The Pearson chi-square statistic was used to identify associations between the variables. Results showed a noticeable imbalance between people with disabilities and people without disabilities, and women with disabilities were less frequently represented than men with disabilities. People with disabilities were depicted as participating in a very limited variety of segregated, competitive, and elite sports activities.

Bivariate quadratic method in quantifying the differential capacitance and energy capacity of supercapacitors under high current operation

NASA Astrophysics Data System (ADS)

Goh, Chin-Teng; Cruden, Andrew

2014-11-01

Capacitance and resistance are the fundamental electrical parameters used to evaluate the electrical characteristics of a supercapacitor, namely the dynamic voltage response, energy capacity, state of charge and health condition. In the British Standards EN62391 and EN62576, the constant capacitance method can be further improved with a differential capacitance that more accurately describes the dynamic voltage response of supercapacitors. This paper presents a novel bivariate quadratic based method to model the dynamic voltage response of supercapacitors under high current charge-discharge cycling, and to enable the derivation of the differential capacitance and energy capacity directly from terminal measurements, i.e. voltage and current, rather than from multiple pulsed-current or excitation signal tests across different bias levels. The estimation results the author achieves are in close agreement with experimental measurements, within a relative error of 0.2%, at various high current levels (25-200 A), more accurate than the constant capacitance method (4-7%). The archival value of this paper is the introduction of an improved quantification method for the electrical characteristics of supercapacitors, and the disclosure of the distinct properties of supercapacitors: the nonlinear capacitance-voltage characteristic, capacitance variation between charging and discharging, and distribution of energy capacity across the operating voltage window.

Mixture models in diagnostic meta-analyses--clustering summary receiver operating characteristic curves accounted for heterogeneity and correlation.

PubMed

Schlattmann, Peter; Verba, Maryna; Dewey, Marc; Walther, Mario

2015-01-01

Bivariate linear and generalized linear random effects are frequently used to perform a diagnostic meta-analysis. The objective of this article was to apply a finite mixture model of bivariate normal distributions that can be used for the construction of componentwise summary receiver operating characteristic (sROC) curves. Bivariate linear random effects and a bivariate finite mixture model are used. The latter model is developed as an extension of a univariate finite mixture model. Two examples, computed tomography (CT) angiography for ruling out coronary artery disease and procalcitonin as a diagnostic marker for sepsis, are used to estimate mean sensitivity and mean specificity and to construct sROC curves. The suggested approach of a bivariate finite mixture model identifies two latent classes of diagnostic accuracy for the CT angiography example. Both classes show high sensitivity but mainly two different levels of specificity. For the procalcitonin example, this approach identifies three latent classes of diagnostic accuracy. Here, sensitivities and specificities are quite different as such that sensitivity increases with decreasing specificity. Additionally, the model is used to construct componentwise sROC curves and to classify individual studies. The proposed method offers an alternative approach to model between-study heterogeneity in a diagnostic meta-analysis. Furthermore, it is possible to construct sROC curves even if a positive correlation between sensitivity and specificity is present. Copyright © 2015 Elsevier Inc. All rights reserved.

A rank test for bivariate time-to-event outcomes when one event is a surrogate

PubMed Central

Shaw, Pamela A.; Fay, Michael P.

2016-01-01

In many clinical settings, improving patient survival is of interest but a practical surrogate, such as time to disease progression, is instead used as a clinical trial’s primary endpoint. A time-to-first endpoint (e.g. death or disease progression) is commonly analyzed but may not be adequate to summarize patient outcomes if a subsequent event contains important additional information. We consider a surrogate outcome very generally, as one correlated with the true endpoint of interest. Settings of interest include those where the surrogate indicates a beneficial outcome so that the usual time-to-first endpoint of death or surrogate event is nonsensical. We present a new two-sample test for bivariate, interval-censored time-to-event data, where one endpoint is a surrogate for the second, less frequently observed endpoint of true interest. This test examines whether patient groups have equal clinical severity. If the true endpoint rarely occurs, the proposed test acts like a weighted logrank test on the surrogate; if it occurs for most individuals, then our test acts like a weighted logrank test on the true endpoint. If the surrogate is a useful statistical surrogate, our test can have better power than tests based on the surrogate that naively handle the true endpoint. In settings where the surrogate is not valid (treatment affects the surrogate but not the true endpoint), our test incorporates the information regarding the lack of treatment effect from the observed true endpoints and hence is expected to have a dampened treatment effect compared to tests based on the surrogate alone. PMID:27059817

Underrepresentation of Women in the Academic Profession: A Comparative Analysis of the North American Region

ERIC Educational Resources Information Center

Metcalfe, Amy Scott; Gonzalez, Laura Padilla

2013-01-01

The present study addresses women's underrepresentation in the academic profession, as well as the need for policies and practices aimed at this issue. It compares underrepresentation of academic women in North American countries, and explores, throughout a bivariate analysis, personal, professional, as well as institutional variables related to…

Diaphragm and Lung Ultrasound to Predict Weaning Outcome: Systematic Review and Meta-Analysis.

PubMed

Llamas-Álvarez, Ana M; Tenza-Lozano, Eva M; Latour-Pérez, Jaime

2017-12-01

Deciding the optimal timing for extubation in patients who are mechanically ventilated can be challenging, and traditional weaning predictor tools are not very accurate. The aim of this systematic review and meta-analysis was to assess the accuracy of lung and diaphragm ultrasound for predicting weaning outcomes in critically ill adults. MEDLINE, the Cochrane Library, Web of Science, Scopus, LILACS, Teseo, Tesis Doctorales en Red, and OpenGrey were searched, and the bibliographies of relevant studies were reviewed. Two researchers independently selected studies that met the inclusion criteria and assessed study quality in accordance with the Quality Assessment of Diagnostic Accuracy Studies-2 tool. The summary receiver-operating characteristic curve and pooled diagnostic OR (DOR) were estimated by using a bivariate random effects analysis. Sources of heterogeneity were explored by using predefined subgroup analyses and bivariate meta-regression. Nineteen studies involving 1,071 people were included in the study. For diaphragm thickening fraction, the area under the summary receiver-operating characteristic curve was 0.87, and DOR was 21 (95% CI, 11-40). Regarding diaphragmatic excursion, pooled sensitivity was 75% (95% CI, 65-85); pooled specificity, 75% (95% CI, 60-85); and DOR, 10 (95% CI, 4-24). For lung ultrasound, the area under the summary receiver-operating characteristic curve was 0.77, and DOR was 38 (95% CI, 7-198). Based on bivariate meta-regression analysis, a significantly higher specificity for diaphragm thickening fraction and higher sensitivity for diaphragmatic excursion was detected in studies with applicability concerns. Lung and diaphragm ultrasound can help predict weaning outcome, but its accuracy may vary depending on the patient subpopulation. Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

A Preliminary Comparison of the Effectiveness of Cluster Analysis Weighting Procedures for Within-Group Covariance Structure.

ERIC Educational Resources Information Center

Donoghue, John R.

A Monte Carlo study compared the usefulness of six variable weighting methods for cluster analysis. Data were 100 bivariate observations from 2 subgroups, generated according to a finite normal mixture model. Subgroup size, within-group correlation, within-group variance, and distance between subgroup centroids were manipulated. Of the clustering…

A method of using cluster analysis to study statistical dependence in multivariate data

NASA Technical Reports Server (NTRS)

Borucki, W. J.; Card, D. H.; Lyle, G. C.

1975-01-01

A technique is presented that uses both cluster analysis and a Monte Carlo significance test of clusters to discover associations between variables in multidimensional data. The method is applied to an example of a noisy function in three-dimensional space, to a sample from a mixture of three bivariate normal distributions, and to the well-known Fisher's Iris data.

Multivariate hydrological frequency analysis for extreme events using Archimedean copula. Case study: Lower Tunjuelo River basin (Colombia)

NASA Astrophysics Data System (ADS)

Gómez, Wilmar

2017-04-01

By analyzing the spatial and temporal variability of extreme precipitation events we can prevent or reduce the threat and risk. Many water resources projects require joint probability distributions of random variables such as precipitation intensity and duration, which can not be independent with each other. The problem of defining a probability model for observations of several dependent variables is greatly simplified by the joint distribution in terms of their marginal by taking copulas. This document presents a general framework set frequency analysis bivariate and multivariate using Archimedean copulas for extreme events of hydroclimatological nature such as severe storms. This analysis was conducted in the lower Tunjuelo River basin in Colombia for precipitation events. The results obtained show that for a joint study of the intensity-duration-frequency, IDF curves can be obtained through copulas and thus establish more accurate and reliable information from design storms and associated risks. It shows how the use of copulas greatly simplifies the study of multivariate distributions that introduce the concept of joint return period used to represent the needs of hydrological designs properly in frequency analysis.

Bivariate and multivariate analyses of the influence of blood variables of patients submitted to Roux-en-Y gastric bypass on the stability of erythrocyte membrane against the chaotropic action of ethanol.

PubMed

de Arvelos, Leticia Ramos; Rocha, Vanessa Custódio Afonso; Felix, Gabriela Pereira; da Cunha, Cleine Chagas; Bernardino Neto, Morun; da Silva Garrote Filho, Mario; de Fátima Pinheiro, Conceição; Resende, Elmiro Santos; Penha-Silva, Nilson

2013-03-01

The stability of the erythrocyte membrane, which is essential for the maintenance of cell functions, occurs in a critical region of fluidity, which depends largely on its composition and the composition and characteristics of the medium. As the composition of the erythrocyte membrane is influenced by several blood variables, the stability of the erythrocyte membrane must have relations with them. The present study aimed to evaluate, by bivariate and multivariate statistical analyses, the correlations and causal relationships between hematologic and biochemical variables and the stability of the erythrocyte membrane against the chaotropic action of ethanol. The validity of this type of analysis depends on the homogeneity of the population and on the variability of the studied parameters, conditions that can be filled by patients who undergo bariatric surgery by the technique of Roux-en-Y gastric bypass since they will suffer feeding restrictions that have great impact on their blood composition. Pathway analysis revealed that an increase in hemoglobin leads to decreased stability of the cell, probably through a process mediated by an increase in mean corpuscular volume. Furthermore, an increase in the mean corpuscular hemoglobin (MCH) leads to an increase in erythrocyte membrane stability, probably because higher values of MCH are associated with smaller quantities of red blood cells and a larger contact area between the cell membrane and ethanol present in the medium.

Sex determination from the mandibular ramus flexure of Koreans by discrimination function analysis using three-dimensional mandible models.

PubMed

Lin, Chenghe; Jiao, Benzheng; Liu, Shanshan; Guan, Feng; Chung, Nak-Eun; Han, Seung-Ho; Lee, U-Young

2014-03-01

It has been known that mandible ramus flexure is an important morphologic trait for sex determination. However, it will be unavailable when mandible is incomplete or fragmented. Therefore, the anthropometric analysis on incomplete or fragmented mandible becomes more important. The aim of this study is to investigate the sex-discriminant potential of mandible ramus flexure on the Korean three-dimensional (3D) mandible models with anthropometric analysis. The sample consists of 240 three dimensional mandibular models obtained from Korean population (M:F; 120:120, mean age 46.2 y), collected by The Catholic Institute for Applied Anatomy, The Catholic University of Korea. Anthropometric information about 11 metric was taken with Mimics, anthropometry libraries toolkit. These parameters were subjected to different discriminant function analyses using SPSS 17.0. Univariate analyses showed that the resubstitution accuracies for sex determination range from 50.4 to 77.1%. Mandibular flexure upper border (MFUB), maximum ramus vertical height (MRVH), and upper ramus vertical height (URVH) expressed the greatest dimorphism, 72.1 to 77.1%. Bivariate analyses indicated that the combination of MFUB and MRVH hold even higher resubstitution accuracy of 81.7%. Furthermore, the direct and stepwise discriminant analyses with the variables on the upper ramus above flexure could predict sex in 83.3 and 85.0%, respectively. When all variables of mandibular ramus flexure were input in stepwise discriminant analysis, the resubstitution accuracy arrived as high as 88.8%. Therefore, we concluded that the upper ramus above flexure hold the larger potentials than the mandibular ramus flexure itself to predict sexes, and that the equations in bivariate and multivariate analysis from our study will be helpful for sex determination on Korean population in forensic science and law. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Structural Analysis of Women’s Heptathlon

PubMed Central

Gassmann, Freya; Fröhlich, Michael; Emrich, Eike

2016-01-01

The heptathlon comprises the results of seven single disciplines, assuming an equal influence from each discipline, depending on the measured performance. Data analysis was based on the data recorded for the individual performances of the 10 winning heptathletes in the World Athletics Championships from 1987 to 2013 and the Olympic Games from 1988 to 2012. In addition to descriptive analysis methods, correlations, bivariate and multivariate linear regressions, and panel data regressions were used. The transformation of the performances from seconds, centimeters, and meters into points showed that the individual disciplines do not equally affect the overall competition result. The currently valid conversion formula for the run, jump, and throw disciplines prefers the sprint and jump disciplines but penalizes the athletes performing in the 800 m run, javelin throw, and shotput disciplines. Furthermore, 21% to 48% of the variance of the sum of points can be attributed to the performances in the disciplines of long jump, 200 m sprint, 100 m hurdles, and high jump. To balance the effects of the single disciplines in the heptathlon, the formula to calculate points should be reevaluated. PMID:29910260

Genome-wide analysis of disease progression in age-related macular degeneration.

PubMed

Yan, Qi; Ding, Ying; Liu, Yi; Sun, Tao; Fritsche, Lars G; Clemons, Traci; Ratnapriya, Rinki; Klein, Michael L; Cook, Richard J; Liu, Yu; Fan, Ruzong; Wei, Lai; Abecasis, Gonçalo R; Swaroop, Anand; Chew, Emily Y; Weeks, Daniel E; Chen, Wei

2018-03-01

Family- and population-based genetic studies have successfully identified multiple disease-susceptibility loci for Age-related macular degeneration (AMD), one of the first batch and most successful examples of genome-wide association study. However, most genetic studies to date have focused on case-control studies of late AMD (choroidal neovascularization or geographic atrophy). The genetic influences on disease progression are largely unexplored. We assembled unique resources to perform a genome-wide bivariate time-to-event analysis to test for association of time-to-late-AMD with ∼9 million variants on 2721 Caucasians from a large multi-center randomized clinical trial, the Age-Related Eye Disease Study. To our knowledge, this is the first genome-wide association study of disease progression (bivariate survival outcome) in AMD genetic studies, thus providing novel insights to AMD genetics. We used a robust Cox proportional hazards model to appropriately account for between-eye correlation when analyzing the progression time in the two eyes of each participant. We identified four previously reported susceptibility loci showing genome-wide significant association with AMD progression: ARMS2-HTRA1 (P = 8.1 × 10-43), CFH (P = 3.5 × 10-37), C2-CFB-SKIV2L (P = 8.1 × 10-10) and C3 (P = 1.2 × 10-9). Furthermore, we detected association of rs58978565 near TNR (P = 2.3 × 10-8), rs28368872 near ATF7IP2 (P = 2.9 × 10-8) and rs142450006 near MMP9 (P = 0.0006) with progression to choroidal neovascularization but not geographic atrophy. Secondary analysis limited to 34 reported risk variants revealed that LIPC and CTRB2-CTRB1 were also associated with AMD progression (P < 0.0015). Our genome-wide analysis thus expands the genetics in both development and progression of AMD and should assist in early identification of high risk individuals.

Unsupervised Outlier Profile Analysis

PubMed Central

Ghosh, Debashis; Li, Song

2014-01-01

In much of the analysis of high-throughput genomic data, “interesting” genes have been selected based on assessment of differential expression between two groups or generalizations thereof. Most of the literature focuses on changes in mean expression or the entire distribution. In this article, we explore the use of C(α) tests, which have been applied in other genomic data settings. Their use for the outlier expression problem, in particular with continuous data, is problematic but nevertheless motivates new statistics that give an unsupervised analog to previously developed outlier profile analysis approaches. Some simulation studies are used to evaluate the proposal. A bivariate extension is described that can accommodate data from two platforms on matched samples. The proposed methods are applied to data from a prostate cancer study. PMID:25452686

A new method for correlation analysis of compositional (environmental) data - a worked example.

PubMed

Reimann, C; Filzmoser, P; Hron, K; Kynčlová, P; Garrett, R G

2017-12-31

Most data in environmental sciences and geochemistry are compositional. Already the unit used to report the data (e.g., μg/l, mg/kg, wt%) implies that the analytical results for each element are not free to vary independently of the other measured variables. This is often neglected in statistical analysis, where a simple log-transformation of the single variables is insufficient to put the data into an acceptable geometry. This is also important for bivariate data analysis and for correlation analysis, for which the data need to be appropriately log-ratio transformed. A new approach based on the isometric log-ratio (ilr) transformation, leading to so-called symmetric coordinates, is presented here. Summarizing the correlations in a heat-map gives a powerful tool for bivariate data analysis. Here an application of the new method using a data set from a regional geochemical mapping project based on soil O and C horizon samples is demonstrated. Differences to 'classical' correlation analysis based on log-transformed data are highlighted. The fact that some expected strong positive correlations appear and remain unchanged even following a log-ratio transformation has probably led to the misconception that the special nature of compositional data can be ignored when working with trace elements. The example dataset is employed to demonstrate that using 'classical' correlation analysis and plotting XY diagrams, scatterplots, based on the original or simply log-transformed data can easily lead to severe misinterpretations of the relationships between elements. Copyright © 2017 Elsevier B.V. All rights reserved.

Simultaneous Analysis of the Behavioural Phenotype, Physical Factors, and Parenting Stress in People with Cornelia De Lange Syndrome

ERIC Educational Resources Information Center

Wulffaert, J.; van Berckelaer-Onnes, I.; Kroonenberg, P.; Scholte, E.; Bhuiyan, Z.; Hennekam, R.

2009-01-01

Background: Studies into the phenotype of rare genetic syndromes largely rely on bivariate analysis. The aim of this study was to describe the phenotype of Cornelia de Lange syndrome (CdLS) in depth by examining a large number of variables with varying measurement levels. Virtually the only suitable multivariate technique for this is categorical…

Cross-platform single cell analysis of kidney development shows stromal cells express Gdnf.

PubMed

Magella, Bliss; Adam, Mike; Potter, Andrew S; Venkatasubramanian, Meenakshi; Chetal, Kashish; Hay, Stuart B; Salomonis, Nathan; Potter, S Steven

2018-02-01

The developing kidney provides a useful model for study of the principles of organogenesis. In this report we use three independent platforms, Drop-Seq, Chromium 10x Genomics and Fluidigm C1, to carry out single cell RNA-Seq (scRNA-Seq) analysis of the E14.5 mouse kidney. Using the software AltAnalyze, in conjunction with the unsupervised approach ICGS, we were unable to identify and confirm the presence of 16 distinct cell populations during this stage of active nephrogenesis. Using a novel integrative supervised computational strategy, we were able to successfully harmonize and compare the cell profiles across all three technological platforms. Analysis of possible cross compartment receptor/ligand interactions identified the nephrogenic zone stroma as a source of GDNF. This was unexpected because the cap mesenchyme nephron progenitors had been thought to be the sole source of GDNF, which is a key driver of branching morphogenesis of the collecting duct system. The expression of Gdnf by stromal cells was validated in several ways, including Gdnf in situ hybridization combined with immunohistochemistry for SIX2, and marker of nephron progenitors, and MEIS1, a marker of stromal cells. Finally, the single cell gene expression profiles generated in this study confirmed and extended previous work showing the presence of multilineage priming during kidney development. Nephron progenitors showed stochastic expression of genes associated with multiple potential differentiation lineages. Copyright © 2017 Elsevier Inc. All rights reserved.

Meta-analysis of the relationships between Kerr and Jermier's substitutes for leadership and employee job attitudes, role perceptions, and performance.

PubMed

Podsakoff, P M; MacKenzie, S B; Bommer, W H

1996-08-01

A meta-analysis was conducted to estimate more accurately the bivariate relationships between leadership behaviors, substitutes for leadership, and subordinate attitudes, and role perceptions and performance, and to examine the relative strengths of the relationships between these variables. Estimates of 435 relationships were obtained from 22 studies containing 36 independent samples. The findings showed that the combination of the substitutes variables and leader behaviors account for a majority of the variance in employee attitudes and role perceptions and a substantial proportion of the variance in in-role and extra-role performance; on average, the substitutes for leadership uniquely accounted for more of the variance in the criterion variables than did leader behaviors.

Accuracy of mucocutaneous leishmaniasis diagnosis using polymerase chain reaction: systematic literature review and meta-analysis

PubMed Central

Gomes, Ciro Martins; Mazin, Suleimy Cristina; dos Santos, Elisa Raphael; Cesetti, Mariana Vicente; Bächtold, Guilherme Albergaria Brízida; Cordeiro, João Henrique de Freitas; Theodoro, Fabrício Claudino Estrela Terra; Damasco, Fabiana dos Santos; Carranza, Sebastián Andrés Vernal; Santos, Adriana de Oliveira; Roselino, Ana Maria; Sampaio, Raimunda Nonata Ribeiro

2015-01-01

The diagnosis of mucocutaneous leishmaniasis (MCL) is hampered by the absence of a gold standard. An accurate diagnosis is essential because of the high toxicity of the medications for the disease. This study aimed to assess the ability of polymerase chain reaction (PCR) to identify MCL and to compare these results with clinical research recently published by the authors. A systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA Statement was performed using comprehensive search criteria and communication with the authors. A meta-analysis considering the estimates of the univariate and bivariate models was performed. Specificity near 100% was common among the papers. The primary reason for accuracy differences was sensitivity. The meta-analysis, which was only possible for PCR samples of lesion fragments, revealed a sensitivity of 71% [95% confidence interval (CI) = 0.59; 0.81] and a specificity of 93% (95% CI = 0.83; 0.98) in the bivariate model. The search for measures that could increase the sensitivity of PCR should be encouraged. The quality of the collected material and the optimisation of the amplification of genetic material should be prioritised. PMID:25946238

Sexual Harassment Retaliation Climate DEOCS 4.1 Construct Validity Summary

DTIC Science & Technology

2017-08-01

exploratory factor analysis, and bivariate correlations (sample 1) 2) To determine the factor structure of the remaining (final) questions via...statistics, reliability analysis, exploratory factor analysis, and bivariate correlations of the prospective Sexual Harassment Retaliation Climate...reported by the survey requester). For information regarding the composition of sample, refer to Table 1. Table 1. Sample 1 Demographics n

Bivariate least squares linear regression: Towards a unified analytic formalism. I. Functional models

NASA Astrophysics Data System (ADS)

Caimmi, R.

2011-08-01

Concerning bivariate least squares linear regression, the classical approach pursued for functional models in earlier attempts ( York, 1966, 1969) is reviewed using a new formalism in terms of deviation (matrix) traces which, for unweighted data, reduce to usual quantities leaving aside an unessential (but dimensional) multiplicative factor. Within the framework of classical error models, the dependent variable relates to the independent variable according to the usual additive model. The classes of linear models considered are regression lines in the general case of correlated errors in X and in Y for weighted data, and in the opposite limiting situations of (i) uncorrelated errors in X and in Y, and (ii) completely correlated errors in X and in Y. The special case of (C) generalized orthogonal regression is considered in detail together with well known subcases, namely: (Y) errors in X negligible (ideally null) with respect to errors in Y; (X) errors in Y negligible (ideally null) with respect to errors in X; (O) genuine orthogonal regression; (R) reduced major-axis regression. In the limit of unweighted data, the results determined for functional models are compared with their counterparts related to extreme structural models i.e. the instrumental scatter is negligible (ideally null) with respect to the intrinsic scatter ( Isobe et al., 1990; Feigelson and Babu, 1992). While regression line slope and intercept estimators for functional and structural models necessarily coincide, the contrary holds for related variance estimators even if the residuals obey a Gaussian distribution, with the exception of Y models. An example of astronomical application is considered, concerning the [O/H]-[Fe/H] empirical relations deduced from five samples related to different stars and/or different methods of oxygen abundance determination. For selected samples and assigned methods, different regression models yield consistent results within the errors (∓ σ) for both

Nonlinear Analysis of Motor Activity Shows Differences between Schizophrenia and Depression: A Study Using Fourier Analysis and Sample Entropy

PubMed Central

Hauge, Erik R.; Berle, Jan Øystein; Oedegaard, Ketil J.; Holsten, Fred; Fasmer, Ole Bernt

2011-01-01

The purpose of this study has been to describe motor activity data obtained by using wrist-worn actigraphs in patients with schizophrenia and major depression by the use of linear and non-linear methods of analysis. Different time frames were investigated, i.e., activity counts measured every minute for up to five hours and activity counts made hourly for up to two weeks. The results show that motor activity was lower in the schizophrenic patients and in patients with major depression, compared to controls. Using one minute intervals the depressed patients had a higher standard deviation (SD) compared to both the schizophrenic patients and the controls. The ratio between the root mean square successive differences (RMSSD) and SD was higher in the schizophrenic patients compared to controls. The Fourier analysis of the activity counts measured every minute showed that the relation between variance in the low and the high frequency range was lower in the schizophrenic patients compared to the controls. The sample entropy was higher in the schizophrenic patients compared to controls in the time series from the activity counts made every minute. The main conclusions of the study are that schizophrenic and depressive patients have distinctly different profiles of motor activity and that the results differ according to period length analysed. PMID:21297977

Price-volume multifractal analysis of the Moroccan stock market

NASA Astrophysics Data System (ADS)

El Alaoui, Marwane

2017-11-01

In this paper, we analyzed price-volume multifractal cross-correlations of Moroccan Stock Exchange. We chose the period from January 1st 2000 to January 20th 2017 to investigate the multifractal behavior of price change and volume change series. Then, we used multifractal detrended cross-correlations analysis method (MF-DCCA) and multifractal detrended fluctuation analysis (MF-DFA) to analyze the series. We computed bivariate generalized Hurst exponent, Rényi exponent and spectrum of singularity for each pair of indices to measure quantitatively cross-correlations. Furthermore, we used detrended cross-correlations coefficient (DCCA) and cross-correlation test (Q(m)) to analyze cross-correlation quantitatively and qualitatively. By analyzing results, we found existence of price-volume multifractal cross-correlations. The spectrum width has a strong multifractal cross-correlation. We remarked that volume change series is anti-persistent when we analyzed the generalized Hurst exponent for all moments q. The cross-correlation test showed the presence of a significant cross-correlation. However, DCCA coefficient had a small positive value, which means that the level of correlation is not very significant. Finally, we analyzed sources of multifractality and their degree of contribution in the series.

Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces

NASA Astrophysics Data System (ADS)

Qian, Xi-Yuan; Liu, Ya-Min; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

2015-06-01

When common factors strongly influence two power-law cross-correlated time series recorded in complex natural or social systems, using detrended cross-correlation analysis (DCCA) without considering these common factors will bias the results. We use detrended partial cross-correlation analysis (DPXA) to uncover the intrinsic power-law cross correlations between two simultaneously recorded time series in the presence of nonstationarity after removing the effects of other time series acting as common forces. The DPXA method is a generalization of the detrended cross-correlation analysis that takes into account partial correlation analysis. We demonstrate the method by using bivariate fractional Brownian motions contaminated with a fractional Brownian motion. We find that the DPXA is able to recover the analytical cross Hurst indices, and thus the multiscale DPXA coefficients are a viable alternative to the conventional cross-correlation coefficient. We demonstrate the advantage of the DPXA coefficients over the DCCA coefficients by analyzing contaminated bivariate fractional Brownian motions. We calculate the DPXA coefficients and use them to extract the intrinsic cross correlation between crude oil and gold futures by taking into consideration the impact of the U.S. dollar index. We develop the multifractal DPXA (MF-DPXA) method in order to generalize the DPXA method and investigate multifractal time series. We analyze multifractal binomial measures masked with strong white noises and find that the MF-DPXA method quantifies the hidden multifractal nature while the multifractal DCCA method fails.

Statistical modeling of space shuttle environmental data

NASA Technical Reports Server (NTRS)

Tubbs, J. D.; Brewer, D. W.

1983-01-01

Statistical models which use a class of bivariate gamma distribution are examined. Topics discussed include: (1) the ratio of positively correlated gamma varieties; (2) a method to determine if unequal shape parameters are necessary in bivariate gamma distribution; (3) differential equations for modal location of a family of bivariate gamma distribution; and (4) analysis of some wind gust data using the analytical results developed for modeling application.

Statistical analysis of multivariate atmospheric variables. [cloud cover

NASA Technical Reports Server (NTRS)

Tubbs, J. D.

1979-01-01

Topics covered include: (1) estimation in discrete multivariate distributions; (2) a procedure to predict cloud cover frequencies in the bivariate case; (3) a program to compute conditional bivariate normal parameters; (4) the transformation of nonnormal multivariate to near-normal; (5) test of fit for the extreme value distribution based upon the generalized minimum chi-square; (6) test of fit for continuous distributions based upon the generalized minimum chi-square; (7) effect of correlated observations on confidence sets based upon chi-square statistics; and (8) generation of random variates from specified distributions.

Examining the Impact of Psychiatric Diagnosis and Comorbidity on the Medical Lethality of Adolescent "Suicide Attempts"

ERIC Educational Resources Information Center

Mc Manama O'Brien, Kimberly H.; Berzin, Stephanie C.

2012-01-01

Specific psychiatric diagnoses and comorbidity patterns were examined to determine if they were related to the medical lethality of "suicide attempts" among adolescents presenting to an urban general hospital (N = 375). Bivariate analysis showed that attempters with substance abuse disorders had higher levels of lethality than attempters without…

Temporal and spatial characteristics of extreme precipitation events in the Midwest of Jilin Province based on multifractal detrended fluctuation analysis method and copula functions

NASA Astrophysics Data System (ADS)

Guo, Enliang; Zhang, Jiquan; Si, Ha; Dong, Zhenhua; Cao, Tiehua; Lan, Wu

2017-10-01

Environmental changes have brought about significant changes and challenges to water resources and management in the world; these include increasing climate variability, land use change, intensive agriculture, and rapid urbanization and industrial development, especially much more frequency extreme precipitation events. All of which greatly affect water resource and the development of social economy. In this study, we take extreme precipitation events in the Midwest of Jilin Province as an example; daily precipitation data during 1960-2014 are used. The threshold of extreme precipitation events is defined by multifractal detrended fluctuation analysis (MF-DFA) method. Extreme precipitation (EP), extreme precipitation ratio (EPR), and intensity of extreme precipitation (EPI) are selected as the extreme precipitation indicators, and then the Kolmogorov-Smirnov (K-S) test is employed to determine the optimal probability distribution function of extreme precipitation indicators. On this basis, copulas connect nonparametric estimation method and the Akaike Information Criterion (AIC) method is adopted to determine the bivariate copula function. Finally, we analyze the characteristics of single variable extremum and bivariate joint probability distribution of the extreme precipitation events. The results show that the threshold of extreme precipitation events in semi-arid areas is far less than that in subhumid areas. The extreme precipitation frequency shows a significant decline while the extreme precipitation intensity shows a trend of growth; there are significant differences in spatiotemporal of extreme precipitation events. The spatial variation trend of the joint return period gets shorter from the west to the east. The spatial distribution of co-occurrence return period takes on contrary changes and it is longer than the joint return period.

Toward the improvement in fetal monitoring during labor with the inclusion of maternal heart rate analysis.

PubMed

Gonçalves, Hernâni; Pinto, Paula; Silva, Manuela; Ayres-de-Campos, Diogo; Bernardes, João

2016-04-01

Fetal heart rate (FHR) monitoring is used routinely in labor, but conventional methods have a limited capacity to detect fetal hypoxia/acidosis. An exploratory study was performed on the simultaneous assessment of maternal heart rate (MHR) and FHR variability, to evaluate their evolution during labor and their capacity to detect newborn acidemia. MHR and FHR were simultaneously recorded in 51 singleton term pregnancies during the last two hours of labor and compared with newborn umbilical artery blood (UAB) pH. Linear/nonlinear indices were computed separately for MHR and FHR. Interaction between MHR and FHR was quantified through the same indices on FHR-MHR and through their correlation and cross-entropy. Univariate and bivariate statistical analysis included nonparametric confidence intervals and statistical tests, receiver operating characteristic curves and linear discriminant analysis. Progression of labor was associated with a significant increase in most MHR and FHR linear indices, whereas entropy indices decreased. FHR alone and in combination with MHR as FHR-MHR evidenced the highest auROC values for prediction of fetal acidemia, with 0.76 and 0.88 for the UAB pH thresholds 7.20 and 7.15, respectively. The inclusion of MHR on bivariate analysis achieved sensitivity and specificity values of nearly 100 and 89.1%, respectively. These results suggest that simultaneous analysis of MHR and FHR may improve the identification of fetal acidemia compared with FHR alone, namely during the last hour of labor.

A vine copula mixed effect model for trivariate meta-analysis of diagnostic test accuracy studies accounting for disease prevalence.

PubMed

Nikoloulopoulos, Aristidis K

2017-10-01

A bivariate copula mixed model has been recently proposed to synthesize diagnostic test accuracy studies and it has been shown that it is superior to the standard generalized linear mixed model in this context. Here, we call trivariate vine copulas to extend the bivariate meta-analysis of diagnostic test accuracy studies by accounting for disease prevalence. Our vine copula mixed model includes the trivariate generalized linear mixed model as a special case and can also operate on the original scale of sensitivity, specificity, and disease prevalence. Our general methodology is illustrated by re-analyzing the data of two published meta-analyses. Our study suggests that there can be an improvement on trivariate generalized linear mixed model in fit to data and makes the argument for moving to vine copula random effects models especially because of their richness, including reflection asymmetric tail dependence, and computational feasibility despite their three dimensionality.

Influence of geomagnetic activity and atmospheric pressure in hypertensive adults.

PubMed

Azcárate, T; Mendoza, B

2017-09-01

We performed a study of the systolic and diastolic arterial blood pressure behavior under natural variables such as the atmospheric pressure and the horizontal geomagnetic field component. We worked with a group of eight adult hypertensive volunteers, four men and four women, with ages between 18 and 27 years in Mexico City during a geomagnetic storm in 2014. The data was divided by gender, age, and day/night cycle. We studied the time series using three methods: correlations, bivariate analysis, and superposed epoch (within a window of 2 days around the day of occurrence of a geomagnetic storm) analysis, between the systolic and diastolic blood pressure and the natural variables. The correlation analysis indicated a correlation between the systolic and diastolic blood pressure and the atmospheric pressure and the horizontal geomagnetic field component, being the largest during the night. Furthermore, the correlation and bivariate analyses showed that the largest correlations are between the systolic and diastolic blood pressure and the horizontal geomagnetic field component. Finally, the superposed epoch analysis showed that the largest number of significant changes in the blood pressure under the influence of geomagnetic field occurred in the systolic blood pressure for men.

Influence of geomagnetic activity and atmospheric pressure in hypertensive adults

NASA Astrophysics Data System (ADS)

Azcárate, T.; Mendoza, B.

2017-09-01

We performed a study of the systolic and diastolic arterial blood pressure behavior under natural variables such as the atmospheric pressure and the horizontal geomagnetic field component. We worked with a group of eight adult hypertensive volunteers, four men and four women, with ages between 18 and 27 years in Mexico City during a geomagnetic storm in 2014. The data was divided by gender, age, and day/night cycle. We studied the time series using three methods: correlations, bivariate analysis, and superposed epoch (within a window of 2 days around the day of occurrence of a geomagnetic storm) analysis, between the systolic and diastolic blood pressure and the natural variables. The correlation analysis indicated a correlation between the systolic and diastolic blood pressure and the atmospheric pressure and the horizontal geomagnetic field component, being the largest during the night. Furthermore, the correlation and bivariate analyses showed that the largest correlations are between the systolic and diastolic blood pressure and the horizontal geomagnetic field component. Finally, the superposed epoch analysis showed that the largest number of significant changes in the blood pressure under the influence of geomagnetic field occurred in the systolic blood pressure for men.

Authenticity and TV Shows: A Multidimensional Analysis Perspective

ERIC Educational Resources Information Center

Al-Surmi, Mansoor

2012-01-01

Television shows, especially soap operas and sitcoms, are usually considered by English as a second language practitioners as a source of authentic spoken conversational materials presumably because they reflect the linguistic features of natural conversation. However, practitioners are faced with the dilemma of how to assess whether such…

[Height deficit in school aged children: a multivariate analysis of possible risk factors, Pernambuco-1997].

PubMed

Laurentino, G E C; Arruda, I K G; Raposo, M C F; Batista Filho, M

2005-06-01

The nutritional status and some risk factors in 894 school children (ages 6 to 12) in the State of Pernambuco, Brazil, were analyzed based on the data collected by the Second State Research on Nourishment, Health and Nutrition carried out in 1997. The cutoff point used in the nutritional evaluation was the limit referring to -2 score-Z, being the NCHS the reference standard. The prevalence of stunting in the state was of 16.9%. Rural areas were more affected, reaching 27.1%. Bivariate analysis showed that the low socioeconomic level of the children and their families is associated with the occurrence of stunting. The logistic regression model pointed the variables: residence location, gender, access to treated potable water, low education, and per-capita income as the main determinants in stunting. The conjunct analysis of all the factors that explain the malnutrition found among the school children studied showed that the probability of a school-aged child to present height deficit varied from 1.5 to 60.3% depending on the risk factors taken into account, therefore showing different epidemiological "scenarios." The study also concluded that in the State of Pernambuco the height deficit constitutes a public health problem especially for school children in rural areas, showing two very different epidemiologic realities between urban and rural areas.

Systematic Review and Meta-Analysis of Studies Evaluating Diagnostic Test Accuracy: A Practical Review for Clinical Researchers-Part II. Statistical Methods of Meta-Analysis

PubMed Central

Lee, Juneyoung; Kim, Kyung Won; Choi, Sang Hyun; Huh, Jimi

2015-01-01

Meta-analysis of diagnostic test accuracy studies differs from the usual meta-analysis of therapeutic/interventional studies in that, it is required to simultaneously analyze a pair of two outcome measures such as sensitivity and specificity, instead of a single outcome. Since sensitivity and specificity are generally inversely correlated and could be affected by a threshold effect, more sophisticated statistical methods are required for the meta-analysis of diagnostic test accuracy. Hierarchical models including the bivariate model and the hierarchical summary receiver operating characteristic model are increasingly being accepted as standard methods for meta-analysis of diagnostic test accuracy studies. We provide a conceptual review of statistical methods currently used and recommended for meta-analysis of diagnostic test accuracy studies. This article could serve as a methodological reference for those who perform systematic review and meta-analysis of diagnostic test accuracy studies. PMID:26576107

Landslide susceptibility assessment in Lianhua County (China): A comparison between a random forest data mining technique and bivariate and multivariate statistical models

NASA Astrophysics Data System (ADS)

Hong, Haoyuan; Pourghasemi, Hamid Reza; Pourtaghi, Zohre Sadat

2016-04-01

Landslides are an important natural hazard that causes a great amount of damage around the world every year, especially during the rainy season. The Lianhua area is located in the middle of China's southern mountainous area, west of Jiangxi Province, and is known to be an area prone to landslides. The aim of this study was to evaluate and compare landslide susceptibility maps produced using the random forest (RF) data mining technique with those produced by bivariate (evidential belief function and frequency ratio) and multivariate (logistic regression) statistical models for Lianhua County, China. First, a landslide inventory map was prepared using aerial photograph interpretation, satellite images, and extensive field surveys. In total, 163 landslide events were recognized in the study area, with 114 landslides (70%) used for training and 49 landslides (30%) used for validation. Next, the landslide conditioning factors-including the slope angle, altitude, slope aspect, topographic wetness index (TWI), slope-length (LS), plan curvature, profile curvature, distance to rivers, distance to faults, distance to roads, annual precipitation, land use, normalized difference vegetation index (NDVI), and lithology-were derived from the spatial database. Finally, the landslide susceptibility maps of Lianhua County were generated in ArcGIS 10.1 based on the random forest (RF), evidential belief function (EBF), frequency ratio (FR), and logistic regression (LR) approaches and were validated using a receiver operating characteristic (ROC) curve. The ROC plot assessment results showed that for landslide susceptibility maps produced using the EBF, FR, LR, and RF models, the area under the curve (AUC) values were 0.8122, 0.8134, 0.7751, and 0.7172, respectively. Therefore, we can conclude that all four models have an AUC of more than 0.70 and can be used in landslide susceptibility mapping in the study area; meanwhile, the EBF and FR models had the best performance for Lianhua

Meta-analysis of diagnostic accuracy studies in mental health

PubMed Central

Takwoingi, Yemisi; Riley, Richard D; Deeks, Jonathan J

2015-01-01

Objectives To explain methods for data synthesis of evidence from diagnostic test accuracy (DTA) studies, and to illustrate different types of analyses that may be performed in a DTA systematic review. Methods We described properties of meta-analytic methods for quantitative synthesis of evidence. We used a DTA review comparing the accuracy of three screening questionnaires for bipolar disorder to illustrate application of the methods for each type of analysis. Results The discriminatory ability of a test is commonly expressed in terms of sensitivity (proportion of those with the condition who test positive) and specificity (proportion of those without the condition who test negative). There is a trade-off between sensitivity and specificity, as an increasing threshold for defining test positivity will decrease sensitivity and increase specificity. Methods recommended for meta-analysis of DTA studies --such as the bivariate or hierarchical summary receiver operating characteristic (HSROC) model --jointly summarise sensitivity and specificity while taking into account this threshold effect, as well as allowing for between study differences in test performance beyond what would be expected by chance. The bivariate model focuses on estimation of a summary sensitivity and specificity at a common threshold while the HSROC model focuses on the estimation of a summary curve from studies that have used different thresholds. Conclusions Meta-analyses of diagnostic accuracy studies can provide answers to important clinical questions. We hope this article will provide clinicians with sufficient understanding of the terminology and methods to aid interpretation of systematic reviews and facilitate better patient care. PMID:26446042

The Effect of Frequency and Type of Internet Use on Perceived Social Support and Sense of Well-Being in Individuals with Spinal Cord Injury

ERIC Educational Resources Information Center

Miller, Susan M.

2008-01-01

This article examines the effect of frequency and type of Internet use on perceived social support and sense of well-being in persons with spinal cord injury. The results show that Internet use is not significantly related to perceived social support. Bivariate analysis indicates that there is a significant negative association between total…

Improving wavelet denoising based on an in-depth analysis of the camera color processing

NASA Astrophysics Data System (ADS)

Seybold, Tamara; Plichta, Mathias; Stechele, Walter

2015-02-01

While Denoising is an extensively studied task in signal processing research, most denoising methods are designed and evaluated using readily processed image data, e.g. the well-known Kodak data set. The noise model is usually additive white Gaussian noise (AWGN). This kind of test data does not correspond to nowadays real-world image data taken with a digital camera. Using such unrealistic data to test, optimize and compare denoising algorithms may lead to incorrect parameter tuning or suboptimal choices in research on real-time camera denoising algorithms. In this paper we derive a precise analysis of the noise characteristics for the different steps in the color processing. Based on real camera noise measurements and simulation of the processing steps, we obtain a good approximation for the noise characteristics. We further show how this approximation can be used in standard wavelet denoising methods. We improve the wavelet hard thresholding and bivariate thresholding based on our noise analysis results. Both the visual quality and objective quality metrics show the advantage of the proposed method. As the method is implemented using look-up-tables that are calculated before the denoising step, our method can be implemented with very low computational complexity and can process HD video sequences real-time in an FPGA.

Comparison of connectivity analyses for resting state EEG data

NASA Astrophysics Data System (ADS)

Olejarczyk, Elzbieta; Marzetti, Laura; Pizzella, Vittorio; Zappasodi, Filippo

2017-06-01

Objective. In the present work, a nonlinear measure (transfer entropy, TE) was used in a multivariate approach for the analysis of effective connectivity in high density resting state EEG data in eyes open and eyes closed. Advantages of the multivariate approach in comparison to the bivariate one were tested. Moreover, the multivariate TE was compared to an effective linear measure, i.e. directed transfer function (DTF). Finally, the existence of a relationship between the information transfer and the level of brain synchronization as measured by phase synchronization value (PLV) was investigated. Approach. The comparison between the connectivity measures, i.e. bivariate versus multivariate TE, TE versus DTF, TE versus PLV, was performed by means of statistical analysis of indexes based on graph theory. Main results. The multivariate approach is less sensitive to false indirect connections with respect to the bivariate estimates. The multivariate TE differentiated better between eyes closed and eyes open conditions compared to DTF. Moreover, the multivariate TE evidenced non-linear phenomena in information transfer, which are not evidenced by the use of DTF. We also showed that the target of information flow, in particular the frontal region, is an area of greater brain synchronization. Significance. Comparison of different connectivity analysis methods pointed to the advantages of nonlinear methods, and indicated a relationship existing between the flow of information and the level of synchronization of the brain.

Moving Average Models with Bivariate Exponential and Geometric Distributions.

DTIC Science & Technology

1985-03-01

ordinary time series and of point processes. Developments in Statistics, Vol. 1, P.R. Krishnaiah , ed. Academic Press, New York. [9] Esary, J.D. and...valued and discrete - valued time series with ARMA correlation structure. Multivariate Analysis V, P.R. Krishnaiah , ed. North-Holland. 151-166. [28

Discrete bivariate population balance modelling of heteroaggregation processes.

PubMed

Rollié, Sascha; Briesen, Heiko; Sundmacher, Kai

2009-08-15

Heteroaggregation in binary particle mixtures was simulated with a discrete population balance model in terms of two internal coordinates describing the particle properties. The considered particle species are of different size and zeta-potential. Property space is reduced with a semi-heuristic approach to enable an efficient solution. Aggregation rates are based on deterministic models for Brownian motion and stability, under consideration of DLVO interaction potentials. A charge-balance kernel is presented, relating the electrostatic surface potential to the property space by a simple charge balance. Parameter sensitivity with respect to the fractal dimension, aggregate size, hydrodynamic correction, ionic strength and absolute particle concentration was assessed. Results were compared to simulations with the literature kernel based on geometric coverage effects for clusters with heterogeneous surface properties. In both cases electrostatic phenomena, which dominate the aggregation process, show identical trends: impeded cluster-cluster aggregation at low particle mixing ratio (1:1), restabilisation at high mixing ratios (100:1) and formation of complex clusters for intermediate ratios (10:1). The particle mixing ratio controls the surface coverage extent of the larger particle species. Simulation results are compared to experimental flow cytometric data and show very satisfactory agreement.

Modelling the vicious circle between obesity and physical activity in children and adolescents using a bivariate probit model with endogenous regressors.

PubMed

Yeh, C-Y; Chen, L-J; Ku, P-W; Chen, C-M

2015-01-01

The increasing prevalence of obesity in children and adolescents has become one of the most important public health issues around the world. Lack of physical activity is a risk factor for obesity, while being obese could reduce the likelihood of participating in physical activity. Failing to account for the endogeneity between obesity and physical activity would result in biased estimation. This study investigates the relationship between overweight and physical activity by taking endogeneity into consideration. It develops an endogenous bivariate probit model estimated by the maximum likelihood method. The data included 4008 boys and 4197 girls in the 5th-9th grades in Taiwan in 2007-2008. The relationship between overweight and physical activity is significantly negative in the endogenous model, but insignificant in the comparative exogenous model. This endogenous relationship presents a vicious circle in which lower levels of physical activity lead to overweight, while those who are already overweight engage in less physical activity. The results not only reveal the importance of endogenous treatment, but also demonstrate the robust negative relationship between these two factors. An emphasis should be put on overweight and obese children and adolescents in order to break the vicious circle. Promotion of physical activity by appropriate counselling programmes and peer support could be effective in reducing the prevalence of obesity in children and adolescents.

Role of Surgical Services in Profitability of Hospitals in California: An Analysis of Office of Statewide Health Planning and Development Annual Financial Data.

PubMed

Moazzez, Ashkan; de Virgilio, Christian

2016-10-01

With constant changes in health-care laws and payment methods, profitability, and financial sustainability of hospitals are of utmost importance. The purpose of this study is to determine the relationship between surgical services and hospital profitability. The Office of Statewide Health Planning and Development annual financial databases for the years 2009 to 2011 were used for this study. The hospitals' characteristics and income statement elements were extracted for statistical analysis using bivariate and multivariate linear regression. A total of 989 financial records of 339 hospitals were included. On bivariate analysis, the number of inpatient and ambulatory operating rooms (ORs), the number of cases done both as inpatient and outpatient in each OR, and the average minutes used in inpatient ORs were significantly related with the net income of the hospital. On multivariate regression analysis, when controlling for hospitals' payer mix and the study year, only the number of inpatient cases done in the inpatient ORs (β = 832, P = 0.037), and the number of ambulatory ORs (β = 1,485, 466, P = 0.001) were significantly related with the net income of the hospital. These findings suggest that hospitals can maximize their profitability by diverting and allocating outpatient surgeries to ambulatory ORs, to allow for more inpatient surgeries.

Cooperative Genome-Wide Analysis Shows Increased Homozygosity in Early Onset Parkinson's Disease

PubMed Central

Nalls, Michael A.; Martinez, Maria; Schulte, Claudia; Holmans, Peter; Gasser, Thomas; Hardy, John; Singleton, Andrew B.; Wood, Nicholas W.; Brice, Alexis; Heutink, Peter; Williams, Nigel; Morris, Huw R.

2012-01-01

Parkinson's disease (PD) occurs in both familial and sporadic forms, and both monogenic and complex genetic factors have been identified. Early onset PD (EOPD) is particularly associated with autosomal recessive (AR) mutations, and three genes, PARK2, PARK7 and PINK1, have been found to carry mutations leading to AR disease. Since mutations in these genes account for less than 10% of EOPD patients, we hypothesized that further recessive genetic factors are involved in this disorder, which may appear in extended runs of homozygosity. We carried out genome wide SNP genotyping to look for extended runs of homozygosity (ROHs) in 1,445 EOPD cases and 6,987 controls. Logistic regression analyses showed an increased level of genomic homozygosity in EOPD cases compared to controls. These differences are larger for ROH of 9 Mb and above, where there is a more than three-fold increase in the proportion of cases carrying a ROH. These differences are not explained by occult recessive mutations at existing loci. Controlling for genome wide homozygosity in logistic regression analyses increased the differences between cases and controls, indicating that in EOPD cases ROHs do not simply relate to genome wide measures of inbreeding. Homozygosity at a locus on chromosome19p13.3 was identified as being more common in EOPD cases as compared to controls. Sequencing analysis of genes and predicted transcripts within this locus failed to identify a novel mutation causing EOPD in our cohort. There is an increased rate of genome wide homozygosity in EOPD, as measured by an increase in ROHs. These ROHs are a signature of inbreeding and do not necessarily harbour disease-causing genetic variants. Although there might be other regions of interest apart from chromosome 19p13.3, we lack the power to detect them with this analysis. PMID:22427796

Parsimonious nonstationary flood frequency analysis

NASA Astrophysics Data System (ADS)

Serago, Jake M.; Vogel, Richard M.

2018-02-01

There is now widespread awareness of the impact of anthropogenic influences on extreme floods (and droughts) and thus an increasing need for methods to account for such influences when estimating a frequency distribution. We introduce a parsimonious approach to nonstationary flood frequency analysis (NFFA) based on a bivariate regression equation which describes the relationship between annual maximum floods, x, and an exogenous variable which may explain the nonstationary behavior of x. The conditional mean, variance and skewness of both x and y = ln (x) are derived, and combined with numerous common probability distributions including the lognormal, generalized extreme value and log Pearson type III models, resulting in a very simple and general approach to NFFA. Our approach offers several advantages over existing approaches including: parsimony, ease of use, graphical display, prediction intervals, and opportunities for uncertainty analysis. We introduce nonstationary probability plots and document how such plots can be used to assess the improved goodness of fit associated with a NFFA.

Multifractal detrending moving-average cross-correlation analysis

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Zhou, Wei-Xing

2011-07-01

There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross correlations. The multifractal detrended cross-correlation analysis (MFDCCA) approaches can be used to quantify such cross correlations, such as the MFDCCA based on the detrended fluctuation analysis (MFXDFA) method. We develop in this work a class of MFDCCA algorithms based on the detrending moving-average analysis, called MFXDMA. The performances of the proposed MFXDMA algorithms are compared with the MFXDFA method by extensive numerical experiments on pairs of time series generated from bivariate fractional Brownian motions, two-component autoregressive fractionally integrated moving-average processes, and binomial measures, which have theoretical expressions of the multifractal nature. In all cases, the scaling exponents hxy extracted from the MFXDMA and MFXDFA algorithms are very close to the theoretical values. For bivariate fractional Brownian motions, the scaling exponent of the cross correlation is independent of the cross-correlation coefficient between two time series, and the MFXDFA and centered MFXDMA algorithms have comparative performances, which outperform the forward and backward MFXDMA algorithms. For two-component autoregressive fractionally integrated moving-average processes, we also find that the MFXDFA and centered MFXDMA algorithms have comparative performances, while the forward and backward MFXDMA algorithms perform slightly worse. For binomial measures, the forward MFXDMA algorithm exhibits the best performance, the centered MFXDMA algorithms performs worst, and the backward MFXDMA algorithm outperforms the MFXDFA algorithm when the moment order q<0 and underperforms when q>0. We apply these algorithms to the return time series of two stock market indexes and to their volatilities. For the returns, the centered MFXDMA algorithm gives the best estimates of hxy(q) since its hxy(2) is closest to 0

Word Reading Fluency: Role of Genome-Wide Single-Nucleotide Polymorphisms in Developmental Stability and Correlations with Print Exposure

ERIC Educational Resources Information Center

Harlaar, Nicole; Trzaskowski, Maciej; Dale, Philip S.; Plomin, Robert

2014-01-01

The genetic effects on individual differences in reading development were examined using genome-wide complex trait analysis (GCTA) in a twin sample. In unrelated individuals (one twin per pair, n = 2,942), the GCTA-based heritability of reading fluency was ~20%-29% at ages 7 and 12. GCTA bivariate results showed that the phenotypic stability of…

Virtual Assessment of Sex: Linear and Angular Traits of the Mandibular Ramus Using Three-Dimensional Computed Tomography.

PubMed

Inci, Ercan; Ekizoglu, Oguzhan; Turkay, Rustu; Aksoy, Sema; Can, Ismail Ozgur; Solmaz, Dilek; Sayin, Ibrahim

2016-10-01

Morphometric analysis of the mandibular ramus (MR) provides highly accurate data to discriminate sex. The objective of this study was to demonstrate the utility and accuracy of MR morphometric analysis for sex identification in a Turkish population.Four hundred fifteen Turkish patients (18-60 y; 201 male and 214 female) who had previously had multidetector computed tomography scans of the cranium were included in the study. Multidetector computed tomography images were obtained using three-dimensional reconstructions and a volume-rendering technique, and 8 linear and 3 angular values were measured. Univariate, bivariate, and multivariate discriminant analyses were performed, and the accuracy rates for determining sex were calculated.Mandibular ramus values produced high accuracy rates of 51% to 95.6%. Upper ramus vertical height had the highest rate at 95.6%, and bivariate analysis showed 89.7% to 98.6% accuracy rates with the highest ratios of mandibular flexure upper border and maximum ramus breadth. Stepwise discrimination analysis gave a 99% accuracy rate for all MR variables.Our study showed that the MR, in particular morphometric measures of the upper part of the ramus, can provide valuable data to determine sex in a Turkish population. The method combines both anthropological and radiologic studies.

Assessment of Coastal and Urban Flooding Hazards Applying Extreme Value Analysis and Multivariate Statistical Techniques: A Case Study in Elwood, Australia

NASA Astrophysics Data System (ADS)

Guimarães Nobre, Gabriela; Arnbjerg-Nielsen, Karsten; Rosbjerg, Dan; Madsen, Henrik

2016-04-01

Traditionally, flood risk assessment studies have been carried out from a univariate frequency analysis perspective. However, statistical dependence between hydrological variables, such as extreme rainfall and extreme sea surge, is plausible to exist, since both variables to some extent are driven by common meteorological conditions. Aiming to overcome this limitation, multivariate statistical techniques has the potential to combine different sources of flooding in the investigation. The aim of this study was to apply a range of statistical methodologies for analyzing combined extreme hydrological variables that can lead to coastal and urban flooding. The study area is the Elwood Catchment, which is a highly urbanized catchment located in the city of Port Phillip, Melbourne, Australia. The first part of the investigation dealt with the marginal extreme value distributions. Two approaches to extract extreme value series were applied (Annual Maximum and Partial Duration Series), and different probability distribution functions were fit to the observed sample. Results obtained by using the Generalized Pareto distribution demonstrate the ability of the Pareto family to model the extreme events. Advancing into multivariate extreme value analysis, first an investigation regarding the asymptotic properties of extremal dependence was carried out. As a weak positive asymptotic dependence between the bivariate extreme pairs was found, the Conditional method proposed by Heffernan and Tawn (2004) was chosen. This approach is suitable to model bivariate extreme values, which are relatively unlikely to occur together. The results show that the probability of an extreme sea surge occurring during a one-hour intensity extreme precipitation event (or vice versa) can be twice as great as what would occur when assuming independent events. Therefore, presuming independence between these two variables would result in severe underestimation of the flooding risk in the study area.

Grain size statistics and depositional pattern of the Ecca Group sandstones, Karoo Supergroup in the Eastern Cape Province, South Africa

NASA Astrophysics Data System (ADS)

Baiyegunhi, Christopher; Liu, Kuiwu; Gwavava, Oswald

2017-11-01

Grain size analysis is a vital sedimentological tool used to unravel the hydrodynamic conditions, mode of transportation and deposition of detrital sediments. In this study, detailed grain-size analysis was carried out on thirty-five sandstone samples from the Ecca Group in the Eastern Cape Province of South Africa. Grain-size statistical parameters, bivariate analysis, linear discriminate functions, Passega diagrams and log-probability curves were used to reveal the depositional processes, sedimentation mechanisms, hydrodynamic energy conditions and to discriminate different depositional environments. The grain-size parameters show that most of the sandstones are very fine to fine grained, moderately well sorted, mostly near-symmetrical and mesokurtic in nature. The abundance of very fine to fine grained sandstones indicate the dominance of low energy environment. The bivariate plots show that the samples are mostly grouped, except for the Prince Albert samples that show scattered trend, which is due to the either mixture of two modes in equal proportion in bimodal sediments or good sorting in unimodal sediments. The linear discriminant function analysis is dominantly indicative of turbidity current deposits under shallow marine environments for samples from the Prince Albert, Collingham and Ripon Formations, while those samples from the Fort Brown Formation are lacustrine or deltaic deposits. The C-M plots indicated that the sediments were deposited mainly by suspension and saltation, and graded suspension. Visher diagrams show that saltation is the major process of transportation, followed by suspension.

An Exploratory Data Analysis System for Support in Medical Decision-Making

PubMed Central

Copeland, J. A.; Hamel, B.; Bourne, J. R.

1979-01-01

An experimental system was developed to allow retrieval and analysis of data collected during a study of neurobehavioral correlates of renal disease. After retrieving data organized in a relational data base, simple bivariate statistics of parametric and nonparametric nature could be conducted. An “exploratory” mode in which the system provided guidance in selection of appropriate statistical analyses was also available to the user. The system traversed a decision tree using the inherent qualities of the data (e.g., the identity and number of patients, tests, and time epochs) to search for the appropriate analyses to employ.

Regional and National Grid Integration Studies Consistently Show Higher

Science.gov Websites

Levels of Renewables Are Possible | Energy Analysis | NREL Regional and National Grid Integration Studies Consistently Show Higher Levels of Renewables Are Possible Regional and National Grid Integration Studies Consistently Show Higher Levels of Renewables Are Possible Analysis Insights: April 2015

Multifractal Cross Wavelet Analysis

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Gao, Xing-Lu; Zhou, Wei-Xing; Stanley, H. Eugene

Complex systems are composed of mutually interacting components and the output values of these components usually exhibit long-range cross-correlations. Using wavelet analysis, we propose a method of characterizing the joint multifractal nature of these long-range cross correlations, a method we call multifractal cross wavelet analysis (MFXWT). We assess the performance of the MFXWT method by performing extensive numerical experiments on the dual binomial measures with multifractal cross correlations and the bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. For binomial multifractal measures, we find the empirical joint multifractality of MFXWT to be in approximate agreement with the theoretical formula. For bFBMs, MFXWT may provide spurious multifractality because of the wide spanning range of the multifractal spectrum. We also apply the MFXWT method to stock market indices, and in pairs of index returns and volatilities we find an intriguing joint multifractal behavior. The tests on surrogate series also reveal that the cross correlation behavior, particularly the cross correlation with zero lag, is the main origin of cross multifractality.

Predictors of unsafe sexual behavior among people living with human immunodeficiency virus/AIDS attending antiretroviral therapy center in Western India.

PubMed

Mehta, Kedar G; Baxi, Rajendra; Chavda, Parag; Patel, Sangita; Mazumdar, Vihang

2016-01-01

As more and more people with human immunodeficiency virus (HIV) live longer and healthier lives because of antiretroviral therapy (ART), an increasing number of sexual transmissions of HIV may arise from these people living with HIV/AIDS (PLWHA). Hence, this study is conducted to assess the predictors of unsafe sexual behavior among PLWHA on ART in Western India. The current cross-sectional study was carried out among 175 PLWHAs attending ART center of a Tertiary Care Hospital in Western India. Unsafe sex was defined as inconsistent and/or incorrect condom use. A total of 39 variables from four domains viz., sociodemographic, relationship-related, medical and psycho-social factors were studied for their relationship to unsafe sexual behavior. The variables found to be significantly associated with unsafe sex practices in bivariate analysis were explored by multivariate analysis using multiple logistic regression in SPSS 17.0 version. Fifty-eight percentage of PLWHAs were practicing unsafe sex. 15 out of total 39 variables showed significant association in bivariate analysis. Finally, 11 of them showed significant association in multivariate analysis. Young age group, illiteracy, lack of counseling, misbeliefs about condom use, nondisclosure to spouse and lack of partner communication were the major factors found to be independently associated with unsafe sex in multivariate analysis. Appropriate interventions like need-based counseling are required to address risk factors associated with unsafe sex.

Grain size analysis and depositional environment of shallow marine to basin floor, Kelantan River Delta

NASA Astrophysics Data System (ADS)

Afifah, M. R. Nurul; Aziz, A. Che; Roslan, M. Kamal

2015-09-01

Sediment samples were collected from the shallow marine from Kuala Besar, Kelantan outwards to the basin floor of South China Sea which consisted of quaternary bottom sediments. Sixty five samples were analysed for their grain size distribution and statistical relationships. Basic statistical analysis like mean, standard deviation, skewness and kurtosis were calculated and used to differentiate the depositional environment of the sediments and to derive the uniformity of depositional environment either from the beach or river environment. The sediments of all areas were varied in their sorting ranging from very well sorted to poorly sorted, strongly negative skewed to strongly positive skewed, and extremely leptokurtic to very platykurtic in nature. Bivariate plots between the grain-size parameters were then interpreted and the Coarsest-Median (CM) pattern showed the trend suggesting relationships between sediments influenced by three ongoing hydrodynamic factors namely turbidity current, littoral drift and waves dynamic, which functioned to control the sediments distribution pattern in various ways.

Ultrasound for Distal Forearm Fracture: A Systematic Review and Diagnostic Meta-Analysis

PubMed Central

Douma-den Hamer, Djoke; Blanker, Marco H.; Edens, Mireille A.; Buijteweg, Lonneke N.; Boomsma, Martijn F.; van Helden, Sven H.; Mauritz, Gert-Jan

2016-01-01

Study Objective To determine the diagnostic accuracy of ultrasound for detecting distal forearm fractures. Methods A systematic review and diagnostic meta-analysis was performed according to the PRISMA statement. We searched MEDLINE, Web of Science and the Cochrane Library from inception to September 2015. All prospective studies of the diagnostic accuracy of ultrasound versus radiography as the reference standard were included. We excluded studies with a retrospective design and those with evidence of verification bias. We assessed the methodological quality of the included studies with the QUADAS-2 tool. We performed a meta-analysis of studies evaluating ultrasound to calculate the pooled sensitivity and specificity with 95% confidence intervals (CI95%) using a bivariate model with random effects. Subgroup and sensitivity analysis were used to examine the effect of methodological differences and other study characteristics. Results Out of 867 publications we included 16 studies with 1,204 patients and 641 fractures. The pooled test characteristics for ultrasound were: sensitivity 97% (CI95% 93–99%), specificity 95% (CI95% 89–98%), positive likelihood ratio (LR) 20.0 (8.5–47.2) and negative LR 0.03 (0.01–0.08). The corresponding pooled diagnostic odds ratio (DOR) was 667 (142–3,133). Apparent differences were shown for method of viewing, with the 6-view method showing higher specificity, positive LR, and DOR, compared to the 4-view method. Conclusion The present meta-analysis showed that ultrasound has a high accuracy for the diagnosis of distal forearm fractures in children when used by proper viewing method. Based on this, ultrasound should be considered a reliable alternative, which has the advantages of being radiation free. PMID:27196439

A Large-Scale Initiative Inviting Patients to Share Personal Fitness Tracker Data with Their Providers: Initial Results

PubMed Central

Pevnick, Joshua M.; Fuller, Garth; Duncan, Ray; Spiegel, Brennan M. R.

2016-01-01

Background Personal fitness trackers (PFT) have substantial potential to improve healthcare. Objective To quantify and characterize early adopters who shared their PFT data with providers. Methods We used bivariate statistics and logistic regression to compare patients who shared any PFT data vs. patients who did not. Results A patient portal was used to invite 79,953 registered portal users to share their data. Of 66,105 users included in our analysis, 499 (0.8%) uploaded data during an initial 37-day study period. Bivariate and regression analysis showed that early adopters were more likely than non-adopters to be younger, male, white, health system employees, and to have higher BMIs. Neither comorbidities nor utilization predicted adoption. Conclusion Our results demonstrate that patients had little intrinsic desire to share PFT data with their providers, and suggest that patients most at risk for poor health outcomes are least likely to share PFT data. Marketing, incentives, and/or cultural change may be needed to induce such data-sharing. PMID:27846287

#13ReasonsWhy Health Professionals and Educators are Tweeting: A Systematic Analysis of Uses and Perceptions of Show Content and Learning Outcomes.

PubMed

Walker, Kimberly K; Burns, Kelli

2018-04-27

This study is a content analysis of health professionals' and educators' tweets about a popular Netflix show that depicts teen suicide: 13 Reasons Why. A content analysis of 740 tweets was conducted to determine the main themes associated with professionals' and educators' tweets about the show, as well as the valence of the tweets. Additionally, a thematic analysis of linked content in tweets (n = 178) was conducted to explore additional content shared about the show and modeling outcomes. Results indicated the largest percentage of tweets was related to social learning, particularly about outcomes that could occur from viewing the show. The valence of the tweets about outcomes was more positive than negative. However, linked materials commonly circulated in tweets signified greater concern with unintended learning outcomes. Some of the linked content included media guidelines for reporting on suicide with recommendations that entertainment producers follow the guidelines. This study emphasizes the importance of including social learning objectives in future typologies of Twitter uses and demonstrates the importance of examining linked content in Twitter studies.

[Spatial point pattern analysis of main trees and flowering Fargesia qinlingensis in Abies fargesii forests in Mt Taibai of the Qinling Mountains, China].

PubMed

Li, Guo Chun; Song, Hua Dong; Li, Qi; Bu, Shu Hai

2017-11-01

In Abies fargesii forests of the giant panda's habitats in Mt. Taibai, the spatial distribution patterns and interspecific associations of main tree species and their spatial associations with the understory flowering Fargesia qinlingensis were analyzed at multiple scales by univariate and bivaria-te O-ring function in point pattern analysis. The results showed that in the A. fargesii forest, the number of A. fargesii was largest but its population structure was in decline. The population of Betula platyphylla was relatively young, with a stable population structure, while the population of B. albo-sinensis declined. The three populations showed aggregated distributions at small scales and gradually showed random distributions with increasing spatial scales. Spatial associations among tree species were mainly showed at small scales and gradually became not spatially associated with increasing scale. A. fargesii and B. platyphylla were positively associated with flowering F. qinlingensis at large and medium scales, whereas B. albo-sinensis showed negatively associated with flowering F. qinlingensis at large and medium scales. The interaction between trees and F. qinlingensis in the habitats of giant panda promoted the dynamic succession and development of forests, which changed the environment of giant panda's habitats in Qinling.

Male and female child murderers: an empirical analysis of U.S. arrest data.

PubMed

Sellers, Brian G; Heide, Kathleen M

2012-08-01

Recent U.S. cases of murders by children below age 11 have captured national headlines. A review of the literature reveals that little is known about this population of juvenile homicide offenders (JHOs). Most studies on juvenile murderers have used small clinical samples, focused on adolescents, and concentrated on male offenders. Studies that have used Supplementary Homicide Report (SHR) data have found significant gender differences among juveniles below 18 years arrested for murder. This study investigated gender differences among 226 juvenile murderers ages 6 through 10 involved in single-victim incidents using bivariate and multivariate statistical techniques. Consistent with previous research, bivariate analyses revealed gender differences with respect to the type of weapon used, age of the victim, relationship to the victim, and circumstances of the crime. Logistic regression analysis identified female JHOs as more likely to use a knife, kill a family member, and kill a victim below age 5, when compared with male JHOs. From these findings, profiles of young male and female JHOs can be drawn. The article concludes with a discussion of the study's implications for prevention and treatment. The authors recommend that future research in gender differences among young children focus on examining psychological, neurological, and sociological variables not included in the SHR data set.

Genomic analysis of codon usage shows influence of mutation pressure, natural selection, and host features on Marburg virus evolution.

PubMed

Nasrullah, Izza; Butt, Azeem M; Tahir, Shifa; Idrees, Muhammad; Tong, Yigang

2015-08-26

The Marburg virus (MARV) has a negative-sense single-stranded RNA genome, belongs to the family Filoviridae, and is responsible for several outbreaks of highly fatal hemorrhagic fever. Codon usage patterns of viruses reflect a series of evolutionary changes that enable viruses to shape their survival rates and fitness toward the external environment and, most importantly, their hosts. To understand the evolution of MARV at the codon level, we report a comprehensive analysis of synonymous codon usage patterns in MARV genomes. Multiple codon analysis approaches and statistical methods were performed to determine overall codon usage patterns, biases in codon usage, and influence of various factors, including mutation pressure, natural selection, and its two hosts, Homo sapiens and Rousettus aegyptiacus. Nucleotide composition and relative synonymous codon usage (RSCU) analysis revealed that MARV shows mutation bias and prefers U- and A-ended codons to code amino acids. Effective number of codons analysis indicated that overall codon usage among MARV genomes is slightly biased. The Parity Rule 2 plot analysis showed that GC and AU nucleotides were not used proportionally which accounts for the presence of natural selection. Codon usage patterns of MARV were also found to be influenced by its hosts. This indicates that MARV have evolved codon usage patterns that are specific to both of its hosts. Moreover, selection pressure from R. aegyptiacus on the MARV RSCU patterns was found to be dominant compared with that from H. sapiens. Overall, mutation pressure was found to be the most important and dominant force that shapes codon usage patterns in MARV. To our knowledge, this is the first detailed codon usage analysis of MARV and extends our understanding of the mechanisms that contribute to codon usage and evolution of MARV.

Multifractal detrended cross-correlation analysis in the MENA area

NASA Astrophysics Data System (ADS)

El Alaoui, Marwane; Benbachir, Saâd

2013-12-01

In this paper, we investigated multifractal cross-correlations qualitatively and quantitatively using a cross-correlation test and the Multifractal detrended cross-correlation analysis method (MF-DCCA) for markets in the MENA area. We used cross-correlation coefficients to measure the level of this correlation. The analysis concerns four stock market indices of Morocco, Tunisia, Egypt and Jordan. The countries chosen are signatory of the Agadir agreement concerning the establishment of a free trade area comprising Arab Mediterranean countries. We computed the bivariate generalized Hurst exponent, Rényi exponent and spectrum of singularity for each pair of indices to measure quantitatively the cross-correlations. By analyzing the results, we found the existence of multifractal cross-correlations between all of these markets. We compared the spectrum width of these indices; we also found which pair of indices has a strong multifractal cross-correlation.

SU-C-BRC-04: Efficient Dose Calculation Algorithm for FFF IMRT with a Simplified Bivariate Gaussian Source Model

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

Li, F; Park, J; Barraclough, B

2016-06-15

Purpose: To develop an efficient and accurate independent dose calculation algorithm with a simplified analytical source model for the quality assurance and safe delivery of Flattening Filter Free (FFF)-IMRT on an Elekta Versa HD. Methods: The source model consisted of a point source and a 2D bivariate Gaussian source, respectively modeling the primary photons and the combined effect of head scatter, monitor chamber backscatter and collimator exchange effect. The in-air fluence was firstly calculated by back-projecting the edges of beam defining devices onto the source plane and integrating the visible source distribution. The effect of the rounded MLC leaf end,more » tongue-and-groove and interleaf transmission was taken into account in the back-projection. The in-air fluence was then modified with a fourth degree polynomial modeling the cone-shaped dose distribution of FFF beams. Planar dose distribution was obtained by convolving the in-air fluence with a dose deposition kernel (DDK) consisting of the sum of three 2D Gaussian functions. The parameters of the source model and the DDK were commissioned using measured in-air output factors (Sc) and cross beam profiles, respectively. A novel method was used to eliminate the volume averaging effect of ion chambers in determining the DDK. Planar dose distributions of five head-and-neck FFF-IMRT plans were calculated and compared against measurements performed with a 2D diode array (MapCHECK™) to validate the accuracy of the algorithm. Results: The proposed source model predicted Sc for both 6MV and 10MV with an accuracy better than 0.1%. With a stringent gamma criterion (2%/2mm/local difference), the passing rate of the FFF-IMRT dose calculation was 97.2±2.6%. Conclusion: The removal of the flattening filter represents a simplification of the head structure which allows the use of a simpler source model for very accurate dose calculation. The proposed algorithm offers an effective way to ensure the safe delivery

Factor analysis shows association between family activity environment and children's health behaviour.

PubMed

Hendrie, Gilly A; Coveney, John; Cox, David N

2011-12-01

To characterise the family activity environment in a questionnaire format, assess the questionnaire's reliability and describe its predictive ability by examining the relationships between the family activity environment and children's health behaviours - physical activity, screen time and fruit and vegetable intake. This paper describes the creation of a tool, based on previously validated scales, adapted from the food domain. Data are from 106 children and their parents (Adelaide, South Australia). Factor analysis was used to characterise factors within the family activity environment. Pearson-Product Moment correlations between the family environment and child outcomes, controlling for demographic variation, were examined. Three factors described the family activity environment - parental activity involvement, opportunity for role modelling and parental support for physical activity - and explained 37.6% of the variance. Controlling for demographic factors, the scale was significantly correlated with children's health behaviour - physical activity (r=0.27), screen time (r=-0.24) and fruit and vegetable intake (r=0.34). The family activity environment questionnaire shows high internal consistency and moderate predictive ability. This study has built on previous research by taking a more comprehensive approach to measuring the family activity environment. This research suggests the family activity environment should be considered in family-based health promotion interventions. © 2011 The Authors. ANZJPH © 2011 Public Health Association of Australia.

A Study of Effects of MultiCollinearity in the Multivariable Analysis

PubMed Central

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

2015-01-01

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

A Study of Effects of MultiCollinearity in the Multivariable Analysis.

PubMed

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

2014-10-01

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

HIV-1 Phylogenetic analysis shows HIV-1 transits through the meninges to brain and peripheral tissues

PubMed Central

Lamers, Susanna L.; Gray, Rebecca R.; Salemi, Marco; Huysentruyt, Leanne C.; McGrath, Michael

2010-01-01

Brain infection by the human immunodeficiency virus type 1 (HIV-1) has been investigated in many reports with a variety of conclusions concerning the time of entry and degree of viral compartmentalization. To address these diverse findings, we sequenced HIV-1 gp120 clones from a wide range of brain, peripheral and meningeal tissues from five patients who died from several HIV-1 associated disease pathologies. High-resolution phylogenetic analysis confirmed previous studies that showed a significant degree of compartmentalization in brain and peripheral tissue subpopulations. Some intermixing between the HIV-1 subpopulations was evident, especially in patients that died from pathologies other than HIV-associated dementia. Interestingly, the major tissue harboring virus from both the brain and peripheral tissues was the meninges. These results show that 1) HIV-1 is clearly capable of migrating out of the brain, 2) the meninges are the most likely primary transport tissues, and 3) infected brain macrophages comprise an important HIV reservoir during highly active antiretroviral therapy. PMID:21055482

MULTIVARIATE ANALYSIS OF DRINKING BEHAVIOUR IN A RURAL POPULATION

PubMed Central

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

1997-01-01

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

Predicting sun-protective intentions and behaviours using the theory of planned behaviour: a systematic review and meta-analysis.

PubMed

Starfelt Sutton, Louise C; White, Katherine M

2016-11-01

To synthesise theory of planned behaviour (TPB) relationships, using meta-analysis, and test the predictive utility of the model for sun protection behaviour. Thirty-eight samples were identified via database/manual searches and academic society posts based on the criteria: measuring sun-protective intentions and/or prospective behaviour; using the TPB/theory of reasoned action as a basis of measurement; and providing bivariate correlations for at least one relevant TPB association. Sun-protective intentions and behaviours. The sample-weighted average effects were moderate-to-strong with attitudes showing the strongest association with intention (r+ = 0.494), followed by perceived behavioural control (PBC; r+ = 0.451), and subjective norm (r+ = 0.419). Intentions showed a stronger association with prospective behaviour (r+ = 0.486) compared to PBC (r+ = 0.314). A total of 39% of variance in intentions and 25% of variance in behaviour were explained. Publication bias was not evident. Moderator analyses showed that TPB associations were stronger when measures specified the Target, Action, Context and Time; in non-student samples; and when follow-up exceeded two weeks. Despite recent criticism, this review shows that the TPB explains a large amount of variance in sun protection and that TPB associations are robust across different populations.

From root to fruit: RNA-Seq analysis shows that arbuscular mycorrhizal symbiosis may affect tomato fruit metabolism.

PubMed

Zouari, Inès; Salvioli, Alessandra; Chialva, Matteo; Novero, Mara; Miozzi, Laura; Tenore, Gian Carlo; Bagnaresi, Paolo; Bonfante, Paola

2014-03-21

Tomato (Solanum lycopersicum) establishes a beneficial symbiosis with arbuscular mycorrhizal (AM) fungi. The formation of the mycorrhizal association in the roots leads to plant-wide modulation of gene expression. To understand the systemic effect of the fungal symbiosis on the tomato fruit, we used RNA-Seq to perform global transcriptome profiling on Moneymaker tomato fruits at the turning ripening stage. Fruits were collected at 55 days after flowering, from plants colonized with Funneliformis mosseae and from control plants, which were fertilized to avoid responses related to nutrient deficiency. Transcriptome analysis identified 712 genes that are differentially expressed in fruits from mycorrhizal and control plants. Gene Ontology (GO) enrichment analysis of these genes showed 81 overrepresented functional GO classes. Up-regulated GO classes include photosynthesis, stress response, transport, amino acid synthesis and carbohydrate metabolism functions, suggesting a general impact of fungal symbiosis on primary metabolisms and, particularly, on mineral nutrition. Down-regulated GO classes include cell wall, metabolism and ethylene response pathways. Quantitative RT-PCR validated the RNA-Seq results for 12 genes out of 14 when tested at three fruit ripening stages, mature green, breaker and turning. Quantification of fruit nutraceutical and mineral contents produced values consistent with the expression changes observed by RNA-Seq analysis. This RNA-Seq profiling produced a novel data set that explores the intersection of mycorrhization and fruit development. We found that the fruits of mycorrhizal plants show two transcriptomic "signatures": genes characteristic of a climacteric fleshy fruit, and genes characteristic of mycorrhizal status, like phosphate and sulphate transporters. Moreover, mycorrhizal plants under low nutrient conditions produce fruits with a nutrient content similar to those from non-mycorrhizal plants under high nutrient conditions

Recruitment Methods and Show Rates to a Prostate Cancer Early Detection Program for High-Risk Men: A Comprehensive Analysis

PubMed Central

Giri, Veda N.; Coups, Elliot J.; Ruth, Karen; Goplerud, Julia; Raysor, Susan; Kim, Taylor Y.; Bagden, Loretta; Mastalski, Kathleen; Zakrzewski, Debra; Leimkuhler, Suzanne; Watkins-Bruner, Deborah

2009-01-01

Purpose Men with a family history (FH) of prostate cancer (PCA) and African American (AA) men are at higher risk for PCA. Recruitment and retention of these high-risk men into early detection programs has been challenging. We report a comprehensive analysis on recruitment methods, show rates, and participant factors from the Prostate Cancer Risk Assessment Program (PRAP), which is a prospective, longitudinal PCA screening study. Materials and Methods Men 35–69 years are eligible if they have a FH of PCA, are AA, or have a BRCA1/2 mutation. Recruitment methods were analyzed with respect to participant demographics and show to the first PRAP appointment using standard statistical methods Results Out of 707 men recruited, 64.9% showed to the initial PRAP appointment. More individuals were recruited via radio than from referral or other methods (χ2 = 298.13, p < .0001). Men recruited via radio were more likely to be AA (p<0.001), less educated (p=0.003), not married or partnered (p=0.007), and have no FH of PCA (p<0.001). Men recruited via referrals had higher incomes (p=0.007). Men recruited via referral were more likely to attend their initial PRAP visit than those recruited by radio or other methods (χ2 = 27.08, p < .0001). Conclusions This comprehensive analysis finds that radio leads to higher recruitment of AA men with lower socioeconomic status. However, these are the high-risk men that have lower show rates for PCA screening. Targeted motivational measures need to be studied to improve show rates for PCA risk assessment for these high-risk men. PMID:19758657

Cement Leakage in Percutaneous Vertebral Augmentation for Osteoporotic Vertebral Compression Fractures: Analysis of Risk Factors.

PubMed

Xie, Weixing; Jin, Daxiang; Ma, Hui; Ding, Jinyong; Xu, Jixi; Zhang, Shuncong; Liang, De

2016-05-01

The risk factors for cement leakage were retrospectively reviewed in 192 patients who underwent percutaneous vertebral augmentation (PVA). To discuss the factors related to the cement leakage in PVA procedure for the treatment of osteoporotic vertebral compression fractures. PVA is widely applied for the treatment of osteoporotic vertebral fractures. Cement leakage is a major complication of this procedure. The risk factors for cement leakage were controversial. A retrospective review of 192 patients who underwent PVA was conducted. The following data were recorded: age, sex, bone density, number of fractured vertebrae before surgery, number of treated vertebrae, severity of the treated vertebrae, operative approach, volume of injected bone cement, preoperative vertebral compression ratio, preoperative local kyphosis angle, intraosseous clefts, preoperative vertebral cortical bone defect, and ratio and type of cement leakage. To study the correlation between each factor and cement leakage ratio, bivariate regression analysis was employed to perform univariate analysis, whereas multivariate linear regression analysis was employed to perform multivariate analysis. The study included 192 patients (282 treated vertebrae), and cement leakage occurred in 100 vertebrae (35.46%). The vertebrae with preoperative cortical bone defects generally exhibited higher cement leakage ratio, and the leakage is typically type C. Vertebrae with intact cortical bones before the procedure tend to experience type S leakage. Univariate analysis showed that patient age, bone density, number of fractured vertebrae before surgery, and vertebral cortical bone were associated with cement leakage ratio (P<0.05). Multivariate analysis showed that the main factors influencing bone cement leakage are bone density and vertebral cortical bone defect, with standardized partial regression coefficients of -0.085 and 0.144, respectively. High bone density and vertebral cortical bone defect are

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.

Business cycles and fertility dynamics in the United States: a vector autoregressive model.

PubMed

Mocan, N H

1990-01-01

"Using vector-autoregressions...this paper shows that fertility moves countercyclically over the business cycle....[It] shows that the United States fertility is not governed by a deterministic trend as was assumed by previous studies. Rather, fertility evolves around a stochastic trend. It is shown that a bivariate analysis between fertility and unemployment yields a procyclical picture of fertility. However, when one considers the effects on fertility of early marriages and the divorce behavior as well as economic activity, fertility moves countercyclically." excerpt

Statistical power of intervention analyses: simulation and empirical application to treated lumber prices

Treesearch

Jeffrey P. Prestemon

2009-01-01

Timber product markets are subject to large shocks deriving from natural disturbances and policy shifts. Statistical modeling of shocks is often done to assess their economic importance. In this article, I simulate the statistical power of univariate and bivariate methods of shock detection using time series intervention models. Simulations show that bivariate methods...

Gene-based interaction analysis shows GABAergic genes interacting with parenting in adolescent depressive symptoms.

PubMed

Van Assche, Evelien; Moons, Tim; Cinar, Ozan; Viechtbauer, Wolfgang; Oldehinkel, Albertine J; Van Leeuwen, Karla; Verschueren, Karine; Colpin, Hilde; Lambrechts, Diether; Van den Noortgate, Wim; Goossens, Luc; Claes, Stephan; van Winkel, Ruud

2017-12-01

Most gene-environment interaction studies (G × E) have focused on single candidate genes. This approach is criticized for its expectations of large effect sizes and occurrence of spurious results. We describe an approach that accounts for the polygenic nature of most psychiatric phenotypes and reduces the risk of false-positive findings. We apply this method focusing on the role of perceived parental support, psychological control, and harsh punishment in depressive symptoms in adolescence. Analyses were conducted on 982 adolescents of Caucasian origin (M age (SD) = 13.78 (.94) years) genotyped for 4,947 SNPs in 263 genes, selected based on a literature survey. The Leuven Adolescent Perceived Parenting Scale (LAPPS) and the Parental Behavior Scale (PBS) were used to assess perceived parental psychological control, harsh punishment, and support. The Center for Epidemiologic Studies Depression Scale (CES-D) was the outcome. We used gene-based testing taking into account linkage disequilibrium to identify genes containing SNPs exhibiting an interaction with environmental factors yielding a p-value per single gene. Significant results at the corrected p-value of p < 1.90 × 10 -4 were examined in an independent replication sample of Dutch adolescents (N = 1354). Two genes showed evidence for interaction with perceived support: GABRR1 (p = 4.62 × 10 -5 ) and GABRR2 (p = 9.05 × 10 -6 ). No genes interacted significantly with psychological control or harsh punishment. Gene-based analysis was unable to confirm the interaction of GABRR1 or GABRR2 with support in the replication sample. However, for GABRR2, but not GABRR1, the correlation of the estimates between the two datasets was significant (r (46) = .32; p = .027) and a gene-based analysis of the combined datasets supported GABRR2 × support interaction (p = 1.63 × 10 -4 ). We present a gene-based method for gene-environment interactions in a polygenic context and show that genes

HIV-1 phylogenetic analysis shows HIV-1 transits through the meninges to brain and peripheral tissues.

PubMed

Lamers, Susanna L; Gray, Rebecca R; Salemi, Marco; Huysentruyt, Leanne C; McGrath, Michael S

2011-01-01

Brain infection by the human immunodeficiency virus type 1 (HIV-1) has been investigated in many reports with a variety of conclusions concerning the time of entry and degree of viral compartmentalization. To address these diverse findings, we sequenced HIV-1 gp120 clones from a wide range of brain, peripheral and meningeal tissues from five patients who died from several HIV-1 associated disease pathologies. High-resolution phylogenetic analysis confirmed previous studies that showed a significant degree of compartmentalization in brain and peripheral tissue subpopulations. Some intermixing between the HIV-1 subpopulations was evident, especially in patients that died from pathologies other than HIV-associated dementia. Interestingly, the major tissue harboring virus from both the brain and peripheral tissues was the meninges. These results show that (1) HIV-1 is clearly capable of migrating out of the brain, (2) the meninges are the most likely primary transport tissues, and (3) infected brain macrophages comprise an important HIV reservoir during highly active antiretroviral therapy. Copyright © 2010 Elsevier B.V. All rights reserved.

Bivariate threshold models for genetic evaluation of susceptibility to and ability to recover from mastitis in Danish Holstein cows.

PubMed

Welderufael, B G; Janss, L L G; de Koning, D J; Sørensen, L P; Løvendahl, P; Fikse, W F

2017-06-01

Mastitis in dairy cows is an unavoidable problem and genetic variation in recovery from mastitis, in addition to susceptibility, is therefore of interest. Genetic parameters for susceptibility to and recovery from mastitis were estimated for Danish Holstein-Friesian cows using data from automatic milking systems equipped with online somatic cell count measuring units. The somatic cell count measurements were converted to elevated mastitis risk, a continuous variable [on a (0-1) scale] indicating the risk of mastitis. Risk values >0.6 were assumed to indicate that a cow had mastitis. For each cow and lactation, the sequence of health states (mastitic or healthy) was converted to a weekly transition: 0 if the cow stayed within the same state and 1 if the cow changed state. The result was 2 series of transitions: one for healthy to diseased (HD, to model mastitis susceptibility) and the other for diseased to healthy (DH, to model recovery ability). The 2 series of transitions were analyzed with bivariate threshold models, including several systematic effects and a function of time. The model included effects of herd, parity, herd-test-week, permanent environment (to account for the repetitive nature of transition records from a cow) plus two time-varying effects (lactation stage and time within episode). In early lactation, there was an increased risk of getting mastitis but the risk remained stable afterwards. Mean recovery rate was 45% per lactation. Heritabilities were 0.07 [posterior mean of standard deviations (PSD) = 0.03] for HD and 0.08 (PSD = 0.03) for DH. The genetic correlation between HD and DH has a posterior mean of -0.83 (PSD = 0.13). Although susceptibility and recovery from mastitis are strongly negatively correlated, recovery can be considered as a new trait for selection. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under

Molecular Analysis of Mixed Endometrial Carcinomas Shows Clonality in Most Cases.

PubMed

Köbel, Martin; Meng, Bo; Hoang, Lien N; Almadani, Noorah; Li, Xiaodong; Soslow, Robert A; Gilks, C Blake; Lee, Cheng-Han

2016-02-01

Mixed endometrial carcinoma refers to a tumor that comprises 2 or more distinct histotypes. We studied 18 mixed-type endometrial carcinomas-11 mixed serous and low-grade endometrioid carcinomas (SC/EC), 5 mixed clear cell and low-grade ECs (CCC/EC), and 2 mixed CCC and SCs (CCC/SC), using targeted next-generation sequencing and immunohistochemistry to compare the molecular profiles of the different histotypes present in each case. In 16 of 18 cases there was molecular evidence that both components shared a clonal origin. Eight cases (6 EC/SC, 1 EC/CCC, and 1 SC/CCC) showed an SC molecular profile that was the same in both components. Five cases (3 CCC/EC and 2 SC/EC) showed a shared endometrioid molecular profile and identical mismatch-repair protein deficiency in both components. A single SC/EC case harbored the same POLE exonuclease domain mutation in both components. One SC/CCC and 1 EC/CCC case showed both shared and unique molecular features in the 2 histotype components, suggesting early molecular divergence from a common clonal origin. In 2 cases, there were no shared molecular features, and these appear to be biologically unrelated synchronous tumors. Overall, these results show that the different histologic components in mixed endometrial carcinomas typically share the same molecular aberrations. Mixed endometrial carcinomas most commonly occur through morphologic mimicry, whereby tumors with serous-type molecular profile show morphologic features of EC or CCC, or through underlying deficiency in DNA nucleotide repair, with resulting rapid accrual of mutations and intratumoral phenotypic heterogeneity. Less commonly, mixed endometrial carcinomas are the result of early molecular divergence from a common progenitor clone or are synchronous biologically unrelated tumors (collision tumors).

Molecular analysis of mixed endometrial carcinomas shows clonality in most cases

PubMed Central

Hoang, Lien N.; Almadani, Noorah; Li, Xiaodong; Soslow, Robert A; Gilks, C. Blake; Lee, Cheng-Han

2016-01-01

Mixed endometrial carcinoma refers to a tumor that is comprised of two or more distinct histotypes. We studied 18 mixed-type endometrial carcinomas - 11 mixed serous and low-grade endometrioid carcinomas (SC/EC), 5 mixed clear cell and low-grade endometrioid carcinomas (CCC/EC), and 2 mixed clear cell and serous carcinoma (CCC/SC), using targeted next generation sequencing and immunohistochemistry to compare the molecular profiles of the different histotypes present in each case. In 16 of 18 cases there was molecular evidence that both components shared a clonal origin. Eight cases (6 EC/SC, 1 EC/CCC and 1 SC/CCC) showed a serous carcinoma molecular profile that was the same in both components. Five cases (3 CCC/EC and 2 SC/EC) showed a shared endometrioid molecular profile and identical mismatch repair protein (MMR) deficiency in both components. A single SC/EC case harbored the same POLE exonuclease domain mutation in both components. One SC/CCC and one EC/CCC case showed both shared and unique molecular features in the two histotype components, suggesting early molecular divergence from a common clonal origin. In two cases, there were no shared molecular features and these appear to be biologically unrelated synchronous tumors. Overall, these results show that the different histologic components in mixed endometrial carcinomas typically share the same molecular aberrations. Mixed endometrial carcinomas most commonly occur through morphological mimicry, whereby tumors with serous-type molecular profile show morphological features of endometrioid or clear cell carcinoma, or through underlying deficiency in DNA nucleotide repair, with resulting rapid accrual of mutations and intratumoral phenotypic heterogeneity. Less commonly, mixed endometrial carcinomas are the result of early molecular divergence from a common progenitor clone or are synchronous biologically unrelated tumors (collision tumors). PMID:26492180

Alcohol outlet density and violence: a geospatial analysis.

PubMed

Zhu, L; Gorman, D M; Horel, S

2004-01-01

To examine the relationship between alcohol outlet density and violent crime controlling for neighbourhood sociostructural characteristics and the effects of spatially autocorrelated error. The sample for this ecologic study comprised 188 census tracts from the City of Austin, Texas and 263 tracts from the City of San Antonio, Texas. Data pertaining to neighbourhood social structure, alcohol density and violent crime were collected from archival sources, and analysed using bivariate, multivariate and geospatial analyses. Using ordinary least squares analysis, the neighbourhood sociostructural covariates explained close to 59% of the variability in violent crime rates in Austin and close to 39% in San Antonio. Adding alcohol outlet density in the target and adjacent census tracts improved the explanatory power of both models. Alcohol outlet density in the target census tract remained a significant predictor of violent crime rates in both cities when the effects of autocorrelated error were controlled for. In Austin, the effects of alcohol outlet density in the adjacent census tracts also remained significant. The final model explains 71% of the variance in violent crime in Austin and 56% in San Antonio. The findings show a clear association between alcohol outlet density and violence, and suggest that the issues of alcohol availability and access are fundamental to the prevention of alcohol-related problems within communities.

Minia, Egypt: Principal Component Analysis

PubMed

Abdelrehim, Marwa G; Mahfouz, Eman M; Ewis, Ashraf A; Seedhom, Amany E; Afifi, Hassan M; Shebl, Fatma M

2018-02-26

Background: Pancreatic cancer (PC) is a serious and rapidly progressing malignancy. Identifying risk factors including dietary elements is important to develop preventive strategies. This study focused on possible links between diet and PC. Methods: We conducted a case-control study including all PC patients diagnosed at Minia Cancer Center and controls from general population from June 2014 to December 2015. Dietary data were collected directly through personal interviews. Principal component analysis (PCA) was performed to identify dietary groups. The data were analyzed using crude odds ratios (ORs) and multivariable logistic regression with adjusted ORs and 95% confidence intervals (CIs). Results: A total of 75 cases and 149 controls were included in the study. PCA identified six dietary groups, labeled as cereals and grains, vegetables, proteins, dairy products, fruits, and sugars. Bivariate analysis showed that consumption of vegetables, fruits, sugars, and total energy intake were associated with change in PC risk. In multivariable-adjusted models comparing highest versus lowest levels of intake, we observed significant lower odds of PC in association with vegetable intake (OR 0.24; 95% CI, 0.07-0.85, P=0.012) and a higher likelihood with the total energy intake (OR 9.88; 95% CI, 2.56-38.09, P<0.0001). There was also a suggested link between high fruit consumption and reduced odds of PC. Conclusions: The study supports the association between dietary factors and the odds of PC development in Egypt. It was found that higher energy intake is associated with an increase in likelihood of PC, while increased vegetable consumption is associated with a lower odds ratio. Creative Commons Attribution License

Exploring High-D Spaces with Multiform Matrices and Small Multiples

PubMed Central

MacEachren, Alan; Dai, Xiping; Hardisty, Frank; Guo, Diansheng; Lengerich, Gene

2011-01-01

We introduce an approach to visual analysis of multivariate data that integrates several methods from information visualization, exploratory data analysis (EDA), and geovisualization. The approach leverages the component-based architecture implemented in GeoVISTA Studio to construct a flexible, multiview, tightly (but generically) coordinated, EDA toolkit. This toolkit builds upon traditional ideas behind both small multiples and scatterplot matrices in three fundamental ways. First, we develop a general, MultiForm, Bivariate Matrix and a complementary MultiForm, Bivariate Small Multiple plot in which different bivariate representation forms can be used in combination. We demonstrate the flexibility of this approach with matrices and small multiples that depict multivariate data through combinations of: scatterplots, bivariate maps, and space-filling displays. Second, we apply a measure of conditional entropy to (a) identify variables from a high-dimensional data set that are likely to display interesting relationships and (b) generate a default order of these variables in the matrix or small multiple display. Third, we add conditioning, a kind of dynamic query/filtering in which supplementary (undisplayed) variables are used to constrain the view onto variables that are displayed. Conditioning allows the effects of one or more well understood variables to be removed from the analysis, making relationships among remaining variables easier to explore. We illustrate the individual and combined functionality enabled by this approach through application to analysis of cancer diagnosis and mortality data and their associated covariates and risk factors. PMID:21947129

Texture analysis of apparent diffusion coefficient maps for treatment response assessment in prostate cancer bone metastases-A pilot study.

PubMed

Reischauer, Carolin; Patzwahl, René; Koh, Dow-Mu; Froehlich, Johannes M; Gutzeit, Andreas

2018-04-01

To evaluate whole-lesion volumetric texture analysis of apparent diffusion coefficient (ADC) maps for assessing treatment response in prostate cancer bone metastases. Texture analysis is performed in 12 treatment-naïve patients with 34 metastases before treatment and at one, two, and three months after the initiation of androgen deprivation therapy. Four first-order and 19 second-order statistical texture features are computed on the ADC maps in each lesion at every time point. Repeatability, inter-patient variability, and changes in the feature values under therapy are investigated. Spearman rank's correlation coefficients are calculated across time to demonstrate the relationship between the texture features and the serum prostate specific antigen (PSA) levels. With few exceptions, the texture features exhibited moderate to high precision. At the same time, Friedman's tests revealed that all first-order and second-order statistical texture features changed significantly in response to therapy. Thereby, the majority of texture features showed significant changes in their values at all post-treatment time points relative to baseline. Bivariate analysis detected significant correlations between the great majority of texture features and the serum PSA levels. Thereby, three first-order and six second-order statistical features showed strong correlations with the serum PSA levels across time. The findings in the present work indicate that whole-tumor volumetric texture analysis may be utilized for response assessment in prostate cancer bone metastases. The approach may be used as a complementary measure for treatment monitoring in conjunction with averaged ADC values. Copyright © 2018 Elsevier B.V. All rights reserved.

A survey of variable selection methods in two Chinese epidemiology journals

PubMed Central

2010-01-01

Background Although much has been written on developing better procedures for variable selection, there is little research on how it is practiced in actual studies. This review surveys the variable selection methods reported in two high-ranking Chinese epidemiology journals. Methods Articles published in 2004, 2006, and 2008 in the Chinese Journal of Epidemiology and the Chinese Journal of Preventive Medicine were reviewed. Five categories of methods were identified whereby variables were selected using: A - bivariate analyses; B - multivariable analysis; e.g. stepwise or individual significance testing of model coefficients; C - first bivariate analyses, followed by multivariable analysis; D - bivariate analyses or multivariable analysis; and E - other criteria like prior knowledge or personal judgment. Results Among the 287 articles that reported using variable selection methods, 6%, 26%, 30%, 21%, and 17% were in categories A through E, respectively. One hundred sixty-three studies selected variables using bivariate analyses, 80% (130/163) via multiple significance testing at the 5% alpha-level. Of the 219 multivariable analyses, 97 (44%) used stepwise procedures, 89 (41%) tested individual regression coefficients, but 33 (15%) did not mention how variables were selected. Sixty percent (58/97) of the stepwise routines also did not specify the algorithm and/or significance levels. Conclusions The variable selection methods reported in the two journals were limited in variety, and details were often missing. Many studies still relied on problematic techniques like stepwise procedures and/or multiple testing of bivariate associations at the 0.05 alpha-level. These deficiencies should be rectified to safeguard the scientific validity of articles published in Chinese epidemiology journals. PMID:20920252

Creating Realistic Data Sets with Specified Properties via Simulation

ERIC Educational Resources Information Center

Goldman, Robert N.; McKenzie, John D. Jr.

2009-01-01

We explain how to simulate both univariate and bivariate raw data sets having specified values for common summary statistics. The first example illustrates how to "construct" a data set having prescribed values for the mean and the standard deviation--for a one-sample t test with a specified outcome. The second shows how to create a bivariate data…

Does Child Maltreatment Predict Adult Crime? Reexamining the Question in a Prospective Study of Gender Differences, Education, and Marital Status.

PubMed

Jung, Hyunzee; Herrenkohl, Todd I; Klika, J Bart; Lee, Jungeun Olivia; Brown, Eric C

2015-08-01

Bivariate analyses of adult crime and child maltreatment showed that individuals who had been maltreated as children, according to child welfare reports, subsequently committed more crime than others who had not been maltreated. Analyses of crimes by category-property, person, and society-provided further evidence of a link between child maltreatment and crime at the bivariate level. Tests of gender differences showed that crime generally is more prevalent among males, although females with a history of maltreatment were more likely than those in a no-maltreatment (comparison) group to report having had some prior involvement in crime. Surprisingly, multivariate analyses controlling for childhood socioeconomic status, gender, minority racial status, marital status, and education level showed that, with one exception (crimes against society), the significant association between child maltreatment and crime observed in bivariate tests was not maintained. Implications for future research are discussed. © The Author(s) 2014.

Determination of volatile compounds in wine by gas chromatography-flame ionization detection: comparison between the U.S. Environmental Protection Agency 3sigma approach and Hubaux-Vos calculation of detection limits using ordinary and bivariate least squares.

PubMed

Caruso, Rosario; Scordino, Monica; Traulo, Pasqualino; Gagliano, Giacomo

2012-01-01

A capillary GC-flame ionization detection (FID) method to determine volatile compounds (ethyl acetate, 1,1-diethoxyethane, methyl alcohol, 1-propanol, 2-methyl-1-propanol, 2-methyl-1-butanol, 3-methyl-1-butanol, 1-butanol, and 2-butanol) in wine was investigated in terms of calculation of detection limits and calibration method. The main objectives were: (1) calculation of regression coefficient parameters by ordinary least-squares (OLS) and bivariate least-squares (BLS) regression models, taking into account errors in both axes; (2) estimation of linear dynamic range (LDR) according to International Conference on Harmonization recommendations; (3) performance evaluation of a method by using three different internal standards (ISs) such as acetonitrile, acetone, and 1-pentanol; (4) evaluation of LODs according to the U.S. Environmental Protection Agency (EPA) 3sigma approach and the Hubaux-Vos (H-V) method; (5) application of H-V theory to a gas chromatographic analytical method and to a food matrix; and (6) accuracy assessment of the method relative to methyl alcohol content through a Unione Italiana Vini (UIV) interlaboratory proficiency test. Calibration curves calculated via BLS and OLS show similar slopes, while intercepts are closer to zero in the first case, independent of the chosen IS. The studied ISs show a substantially equivalent behavior, even though the IS closer to the analyte retention time seems to be more appropriate in terms of LDR and LOD. Results indicate an underestimation of LODs using the EPA 3sigma approach instead of the more realistic H-V method, both with OLS and BLS regression models. Methanol contents compared with UIV average values indicate recovery between 90 and 110%.

To Identify the Important Soil Properties Affecting Dinoseb Adsorption with Statistical Analysis

PubMed Central

Guan, Yiqing; Wei, Jianhui; Zhang, Danrong; Zu, Mingjuan; Zhang, Liru

2013-01-01

Investigating the influences of soil characteristic factors on dinoseb adsorption parameter with different statistical methods would be valuable to explicitly figure out the extent of these influences. The correlation coefficients and the direct, indirect effects of soil characteristic factors on dinoseb adsorption parameter were analyzed through bivariate correlation analysis, and path analysis. With stepwise regression analysis the factors which had little influence on the adsorption parameter were excluded. Results indicate that pH and CEC had moderate relationship and lower direct effect on dinoseb adsorption parameter due to the multicollinearity with other soil factors, and organic carbon and clay contents were found to be the most significant soil factors which affect the dinoseb adsorption process. A regression is thereby set up to explore the relationship between the dinoseb adsorption parameter and the two soil factors: the soil organic carbon and clay contents. A 92% of the variation of dinoseb sorption coefficient could be attributed to the variation of the soil organic carbon and clay contents. PMID:23737715

Genome-wide analysis of adolescent psychotic-like experiences shows genetic overlap with psychiatric disorders.

PubMed

Pain, Oliver; Dudbridge, Frank; Cardno, Alastair G; Freeman, Daniel; Lu, Yi; Lundstrom, Sebastian; Lichtenstein, Paul; Ronald, Angelica

2018-03-31

This study aimed to test for overlap in genetic influences between psychotic-like experience traits shown by adolescents in the community, and clinically-recognized psychiatric disorders in adulthood, specifically schizophrenia, bipolar disorder, and major depression. The full spectra of psychotic-like experience domains, both in terms of their severity and type (positive, cognitive, and negative), were assessed using self- and parent-ratings in three European community samples aged 15-19 years (Final N incl. siblings = 6,297-10,098). A mega-genome-wide association study (mega-GWAS) for each psychotic-like experience domain was performed. Single nucleotide polymorphism (SNP)-heritability of each psychotic-like experience domain was estimated using genomic-relatedness-based restricted maximum-likelihood (GREML) and linkage disequilibrium- (LD-) score regression. Genetic overlap between specific psychotic-like experience domains and schizophrenia, bipolar disorder, and major depression was assessed using polygenic risk score (PRS) and LD-score regression. GREML returned SNP-heritability estimates of 3-9% for psychotic-like experience trait domains, with higher estimates for less skewed traits (Anhedonia, Cognitive Disorganization) than for more skewed traits (Paranoia and Hallucinations, Parent-rated Negative Symptoms). Mega-GWAS analysis identified one genome-wide significant association for Anhedonia within IDO2 but which did not replicate in an independent sample. PRS analysis revealed that the schizophrenia PRS significantly predicted all adolescent psychotic-like experience trait domains (Paranoia and Hallucinations only in non-zero scorers). The major depression PRS significantly predicted Anhedonia and Parent-rated Negative Symptoms in adolescence. Psychotic-like experiences during adolescence in the community show additive genetic effects and partly share genetic influences with clinically-recognized psychiatric disorders, specifically schizophrenia and

Santa Clara Strength of Religious Faith Questionnaire: Psychometric analysis in older adults

PubMed Central

Cummings, Jeremy P.; Carson, Cody S.; Shrestha, Srijana; Kunik, Mark E.; Armento, Maria E.; Stanley, Melinda A.; Amspoker, Amber B.

2014-01-01

Objectives To assist researchers and clinicians considering using the Santa Clara Strength of Religious Faith Questionnaire (SCSRFQ) with older-adult samples, the current study analyzed the psychometrics of SCSRFQ scores in two older-adult samples. Method Adults age 55 or older who had formerly participated in studies of cognitive-behavioral therapy for anxiety and/or depression were recruited to complete questionnaires. In Study 1 (N = 66), the authors assessed the relations between the SCSRFQ and other measures of religiousness/spirituality, mental health, and demographic variables, using bivariate correlations and nonparametric tests. In Study 2 (N = 223), the authors also conducted confirmatory and exploratory factor analyses of the SCSRFQ, as well as an Item Response Theory analysis. Results The SCSRFQ was moderately to highly positively correlated with all measures of religiousness/spirituality. Relations with mental health were weak and differed across samples. Ethnic minorities scored higher than White participants on the SCSRFQ, but only in Study 2. Factor analyses showed that a single-factor model fit the SCSRFQ best. According to Item Response Theory analysis, SCSRFQ items discriminated well between participants with low-to-moderate levels of the construct but provided little information at higher levels. Conclusion Although the SCSRFQ scores had adequate psychometric characteristics, the measure’s usefulness may be limited in samples of older adults. PMID:24892461

Joint multifractal analysis based on the partition function approach: analytical analysis, numerical simulation and empirical application

NASA Astrophysics Data System (ADS)

Xie, Wen-Jie; Jiang, Zhi-Qiang; Gu, Gao-Feng; Xiong, Xiong; Zhou, Wei-Xing

2015-10-01

Many complex systems generate multifractal time series which are long-range cross-correlated. Numerous methods have been proposed to characterize the multifractal nature of these long-range cross correlations. However, several important issues about these methods are not well understood and most methods consider only one moment order. We study the joint multifractal analysis based on partition function with two moment orders, which was initially invented to investigate fluid fields, and derive analytically several important properties. We apply the method numerically to binomial measures with multifractal cross correlations and bivariate fractional Brownian motions without multifractal cross correlations. For binomial multifractal measures, the explicit expressions of mass function, singularity strength and multifractal spectrum of the cross correlations are derived, which agree excellently with the numerical results. We also apply the method to stock market indexes and unveil intriguing multifractality in the cross correlations of index volatilities.

Systems Level Analysis of Systemic Sclerosis Shows a Network of Immune and Profibrotic Pathways Connected with Genetic Polymorphisms

PubMed Central

Mahoney, J. Matthew; Taroni, Jaclyn; Martyanov, Viktor; Wood, Tammara A.; Greene, Casey S.; Pioli, Patricia A.; Hinchcliff, Monique E.; Whitfield, Michael L.

2015-01-01

Systemic sclerosis (SSc) is a rare systemic autoimmune disease characterized by skin and organ fibrosis. The pathogenesis of SSc and its progression are poorly understood. The SSc intrinsic gene expression subsets (inflammatory, fibroproliferative, normal-like, and limited) are observed in multiple clinical cohorts of patients with SSc. Analysis of longitudinal skin biopsies suggests that a patient's subset assignment is stable over 6–12 months. Genetically, SSc is multi-factorial with many genetic risk loci for SSc generally and for specific clinical manifestations. Here we identify the genes consistently associated with the intrinsic subsets across three independent cohorts, show the relationship between these genes using a gene-gene interaction network, and place the genetic risk loci in the context of the intrinsic subsets. To identify gene expression modules common to three independent datasets from three different clinical centers, we developed a consensus clustering procedure based on mutual information of partitions, an information theory concept, and performed a meta-analysis of these genome-wide gene expression datasets. We created a gene-gene interaction network of the conserved molecular features across the intrinsic subsets and analyzed their connections with SSc-associated genetic polymorphisms. The network is composed of distinct, but interconnected, components related to interferon activation, M2 macrophages, adaptive immunity, extracellular matrix remodeling, and cell proliferation. The network shows extensive connections between the inflammatory- and fibroproliferative-specific genes. The network also shows connections between these subset-specific genes and 30 SSc-associated polymorphic genes including STAT4, BLK, IRF7, NOTCH4, PLAUR, CSK, IRAK1, and several human leukocyte antigen (HLA) genes. Our analyses suggest that the gene expression changes underlying the SSc subsets may be long-lived, but mechanistically interconnected and related to a

Joint multifractal analysis based on wavelet leaders

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Yang, Yan-Hong; Wang, Gang-Jin; Zhou, Wei-Xing

2017-12-01

Mutually interacting components form complex systems and these components usually have long-range cross-correlated outputs. Using wavelet leaders, we propose a method for characterizing the joint multifractal nature of these long-range cross correlations; we call this method joint multifractal analysis based on wavelet leaders (MF-X-WL). We test the validity of the MF-X-WL method by performing extensive numerical experiments on dual binomial measures with multifractal cross correlations and bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. Both experiments indicate that MF-X-WL is capable of detecting cross correlations in synthetic data with acceptable estimating errors. We also apply the MF-X-WL method to pairs of series from financial markets (returns and volatilities) and online worlds (online numbers of different genders and different societies) and determine intriguing joint multifractal behavior.

Urine proteome analysis in Dent's disease shows high selective changes potentially involved in chronic renal damage.

PubMed

Santucci, Laura; Candiano, Giovanni; Anglani, Franca; Bruschi, Maurizio; Tosetto, Enrica; Cremasco, Daniela; Murer, Luisa; D'Ambrosio, Chiara; Scaloni, Andrea; Petretto, Andrea; Caridi, Gianluca; Rossi, Roberta; Bonanni, Alice; Ghiggeri, Gian Marco

2016-01-01

Definition of the urinary protein composition would represent a potential tool for diagnosis in many clinical conditions. The use of new proteomic technologies allows detection of genetic and post-trasductional variants that increase sensitivity of the approach but complicates comparison within a heterogeneous patient population. Overall, this limits research of urinary biomarkers. Studying monogenic diseases are useful models to address this issue since genetic variability is reduced among first- and second-degree relatives of the same family. We applied this concept to Dent's disease, a monogenic condition characterised by low-molecular-weight proteinuria that is inherited following an X-linked trait. Results are presented here on a combined proteomic approach (LC-mass spectrometry, Western blot and zymograms for proteases and inhibitors) to characterise urine proteins in a large family (18 members, 6 hemizygous patients, 6 carrier females, and 6 normals) with Dent's diseases due to the 1070G>T mutation of the CLCN5. Gene ontology analysis on more than 1000 proteins showed that several clusters of proteins characterised urine of affected patients compared to carrier females and normal subjects: proteins involved in extracellular matrix remodelling were the major group. Specific analysis on metalloproteases and their inhibitors underscored unexpected mechanisms potentially involved in renal fibrosis. Studying with new-generation techniques for proteomic analysis of the members of a large family with Dent's disease sharing the same molecular defect allowed highly repetitive results that justify conclusions. Identification in urine of proteins actively involved in interstitial matrix remodelling poses the question of active anti-fibrotic drugs in Dent's patients. Copyright © 2015 Elsevier B.V. All rights reserved.

Radiogenomic analysis of lower grade glioma: a pilot multi-institutional study shows an association between quantitative image features and tumor genomics

NASA Astrophysics Data System (ADS)

Mazurowski, Maciej A.; Clark, Kal; Czarnek, Nicholas M.; Shamsesfandabadi, Parisa; Peters, Katherine B.; Saha, Ashirbani

2017-03-01

Recent studies showed that genomic analysis of lower grade gliomas can be very effective for stratification of patients into groups with different prognosis and proposed specific genomic classifications. In this study, we explore the association of one of those genomic classifications with imaging parameters to determine whether imaging could serve a similar role to genomics in cancer patient treatment. Specifically, we analyzed imaging and genomics data for 110 patients from 5 institutions from The Cancer Genome Atlas and The Cancer Imaging Archive datasets. The analyzed imaging data contained preoperative FLAIR sequence for each patient. The images were analyzed using the in-house algorithms which quantify 2D and 3D aspects of the tumor shape. Genomic data consisted of a cluster of clusters classification proposed in a very recent and leading publication in the field of lower grade glioma genomics. Our statistical analysis showed that there is a strong association between the tumor cluster-of-clusters subtype and two imaging features: bounding ellipsoid volume ratio and angular standard deviation. This result shows high promise for the potential use of imaging as a surrogate measure for genomics in the decision process regarding treatment of lower grade glioma patients.

Guidance for deriving and presenting percentage study weights in meta-analysis of test accuracy studies.

PubMed

Burke, Danielle L; Ensor, Joie; Snell, Kym I E; van der Windt, Danielle; Riley, Richard D

2018-06-01

Percentage study weights in meta-analysis reveal the contribution of each study toward the overall summary results and are especially important when some studies are considered outliers or at high risk of bias. In meta-analyses of test accuracy reviews, such as a bivariate meta-analysis of sensitivity and specificity, the percentage study weights are not currently derived. Rather, the focus is on representing the precision of study estimates on receiver operating characteristic plots by scaling the points relative to the study sample size or to their standard error. In this article, we recommend that researchers should also provide the percentage study weights directly, and we propose a method to derive them based on a decomposition of Fisher information matrix. This method also generalises to a bivariate meta-regression so that percentage study weights can also be derived for estimates of study-level modifiers of test accuracy. Application is made to two meta-analyses examining test accuracy: one of ear temperature for diagnosis of fever in children and the other of positron emission tomography for diagnosis of Alzheimer's disease. These highlight that the percentage study weights provide important information that is otherwise hidden if the presentation only focuses on precision based on sample size or standard errors. Software code is provided for Stata, and we suggest that our proposed percentage weights should be routinely added on forest and receiver operating characteristic plots for sensitivity and specificity, to provide transparency of the contribution of each study toward the results. This has implications for the PRISMA-diagnostic test accuracy guidelines that are currently being produced. Copyright © 2017 John Wiley & Sons, Ltd.

Statistical Development of Flood Frequency and Magnitude Equations for the Cosumnes and Mokelumne River Drainage Basins, Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Burns, R. G.; Meyer, R. W.; Cornwell, K.

2003-12-01

In-basin statistical relations allow for development of regional flood frequency and magnitude equations in the Cosumnes River and Mokelumne River drainage basins. Current equations were derived from data collected through 1975, and do not reflect newer data with some significant flooding. Physical basin characteristics (area, mean basin elevation, slope of longest reach, and mean annual precipitation) were correlated against predicted flood discharges for each of the 5, 10, 25, 50, 100, 200, and 500-year recurrence intervals in a multivariate analysis. Predicted maximum instantaneous flood discharges were determined using the PEAKFQ program with default settings, for 24 stream gages within the study area presumed not affected by flow management practices. For numerical comparisons, GIS-based methods using Spatial Analyst and the Arc Hydro Tools extension were applied to derive physical basin characteristics as predictor variables from a 30m digital elevation model (DEM) and a mean annual precipitation raster (PRISM). In a bivariate analysis, examination of Pearson correlation coefficients, F-statistic, and t & p thresholds show good correlation between area and flood discharges. Similar analyses show poor correlation for mean basin elevation, slope and precipitation, with flood discharge. Bivariate analysis suggests slope may not be an appropriate predictor term for use in the multivariate analysis. Precipitation and elevation correlate very well, demonstrating possible orographic effects. From the multivariate analysis, less than 6% of the variability in the correlation is not explained for flood recurrences up to 25 years. Longer term predictions up to 500 years accrue greater uncertainty with as much as 15% of the variability in the correlation left unexplained.

Statistical Modeling of Bivariate Data.

DTIC Science & Technology

1982-08-01

Technical S. PERFORMING ORG. REPORT NUMBER 7. AUTNOR(a) S. CONTRACT OR GRANT NUMBER(e) Terry Joe Woodfield DAAG29-80-C-0070 S. PERFORMING ORGANIZATION NAME...proaramming has caused it to be a widely practiced form of program construction. The idea behind this approach is to carefully organize a program so that it...flows smoothly from one computation to the next without haphazard placement of loops and branches. There are , J a variety of ways to organize a program

Analysis of vector wind change with respect to time for Cape Kennedy, Florida

NASA Technical Reports Server (NTRS)

Adelfang, S. I.

1978-01-01

Multivariate analysis was used to determine the joint distribution of the four variables represented by the components of the wind vector at an initial time and after a specified elapsed time is hypothesized to be quadravariate normal; the fourteen statistics of this distribution, calculated from 15 years of twice-daily rawinsonde data are presented by monthly reference periods for each month from 0 to 27 km. The hypotheses that the wind component changes with respect to time is univariate normal, that the joint distribution of wind component change with respect to time is univariate normal, that the joint distribution of wind component changes is bivariate normal, and that the modulus of vector wind change is Rayleigh are tested by comparison with observed distributions. Statistics of the conditional bivariate normal distributions of vector wind at a future time given the vector wind at an initial time are derived. Wind changes over time periods from 1 to 5 hours, calculated from Jimsphere data, are presented. Extension of the theoretical prediction (based on rawinsonde data) of wind component change standard deviation to time periods of 1 to 5 hours falls (with a few exceptions) within the 95 percentile confidence band of the population estimate obtained from the Jimsphere sample data. The joint distributions of wind change components, conditional wind components, and 1 km vector wind shear change components are illustrated by probability ellipses at the 95 percentile level.

Retrospective Analysis of Patient Presentations at the Sydney (Australia) Royal Easter Show from 2012 to 2014.

PubMed

Crabtree, Nathan; Mo, Shirley; Ong, Leon; Jegathees, Thuvarahan; Wei, Daniel; Fahey, David; Liu, Jia Jenny

2017-04-01

Introduction Comprehensive studies on the relationship between patient demographics and subsequent treatment and disposition at a single mass-gathering event are lacking. The Sydney Royal Easter Show (SRES; Sydney Olympic Park, New South Wales, Australia) is an annual, 14-day, agricultural mass-gathering event occurring around the Easter weekend, attracting more than 800,000 patrons per year. In this study, patient records from the SRES were analyzed to examine relationships between weather, crowd size, day of week, and demographics on treatment and disposition. This information would help to predict factors affecting patient treatment and disposition to guide ongoing training of first responders and to evaluate the appropriateness of staffing skills mix at future events. Hypothesis Patient demographics, environmental factors, and attendance would influence the nature and severity of presentations at the SRES, which would influence staffing requirements. A retrospective analysis of 4,141 patient record forms was performed for patients who presented to St John Ambulance (Australian Capital Territory, Australia) at the SRES between 2012 and 2014 inclusive. Presentation type was classified using a previously published minimum data set. Data on weather and crowd size were obtained from the Australian Bureau of Meteorology (Melbourne, Victoria, Australia) and the SRES, respectively. Statistical analyses were performed using SPSS v22 (IBM; Armonk, New York USA). Between 2012 to 2014, over 2.5 million people attended the SRES with 4,141 patients treated onsite. As expected, the majority of presentations were injuries (49%) and illnesses (46%). Although patient demographics and presentation types did not change over time, the duration of treatment increased. A higher proportion of patients were discharged to hospital or home compared to the proportion of patients discharged back to the event. Patients from rural/regional locations (accounting for 15% of all patients) were

The diagnostic performance of shear wave elastography for malignant cervical lymph nodes: A systematic review and meta-analysis.

PubMed

Suh, Chong Hyun; Choi, Young Jun; Baek, Jung Hwan; Lee, Jeong Hyun

2017-01-01

To evaluate the diagnostic performance of shear wave elastography for malignant cervical lymph nodes. We searched the Ovid-MEDLINE and EMBASE databases for published studies regarding the use of shear wave elastography for diagnosing malignant cervical lymph nodes. The diagnostic performance of shear wave elastography was assessed using bivariate modelling and hierarchical summary receiver operating characteristic modelling. Meta-regression analysis and subgroup analysis according to acoustic radiation force impulse imaging (ARFI) and Supersonic shear imaging (SSI) were also performed. Eight eligible studies which included a total sample size of 481 patients with 647 cervical lymph nodes, were included. Shear wave elastography showed a summary sensitivity of 81 % (95 % CI: 72-88 %) and specificity of 85 % (95 % CI: 70-93 %). The results of meta-regression analysis revealed that the prevalence of malignant lymph nodes was a significant factor affecting study heterogeneity (p < .01). According to the subgroup analysis, the summary estimates of the sensitivity and specificity did not differ between ARFI and SSI (p = .93). Shear wave elastography is an acceptable imaging modality for diagnosing malignant cervical lymph nodes. We believe that both ARFI and SSI may have a complementary role for diagnosing malignant cervical lymph nodes. • Shear wave elastography is acceptable modality for diagnosing malignant cervical lymph nodes. • Shear wave elastography demonstrated summary sensitivity of 81 % and specificity of 85 %. • ARFI and SSI have complementary roles for diagnosing malignant cervical lymph nodes.

The role of failure modes and effects analysis in showing the benefits of automation in the blood bank.

PubMed

Han, Tae Hee; Kim, Moon Jung; Kim, Shinyoung; Kim, Hyun Ok; Lee, Mi Ae; Choi, Ji Seon; Hur, Mina; St John, Andrew

2013-05-01

Failure modes and effects analysis (FMEA) is a risk management tool used by the manufacturing industry but now being applied in laboratories. Teams from six South Korean blood banks used this tool to map their manual and automated blood grouping processes and determine the risk priority numbers (RPNs) as a total measure of error risk. The RPNs determined by each of the teams consistently showed that the use of automation dramatically reduced the RPN compared to manual processes. In addition, FMEA showed where the major risks occur in each of the manual processes and where attention should be prioritized to improve the process. Despite no previous experience with FMEA, the teams found the technique relatively easy to use and the subjectivity associated with assigning risk numbers did not affect the validity of the data. FMEA should become a routine technique for improving processes in laboratories. © 2012 American Association of Blood Banks.

Study designs, use of statistical tests, and statistical analysis software choice in 2015: Results from two Pakistani monthly Medline indexed journals.

PubMed

Shaikh, Masood Ali

2017-09-01

Assessment of research articles in terms of study designs used, statistical tests applied and the use of statistical analysis programmes help determine research activity profile and trends in the country. In this descriptive study, all original articles published by Journal of Pakistan Medical Association (JPMA) and Journal of the College of Physicians and Surgeons Pakistan (JCPSP), in the year 2015 were reviewed in terms of study designs used, application of statistical tests, and the use of statistical analysis programmes. JPMA and JCPSP published 192 and 128 original articles, respectively, in the year 2015. Results of this study indicate that cross-sectional study design, bivariate inferential statistical analysis entailing comparison between two variables/groups, and use of statistical software programme SPSS to be the most common study design, inferential statistical analysis, and statistical analysis software programmes, respectively. These results echo previously published assessment of these two journals for the year 2014.

Maternal Complications Associated with Stillbirth Delivery: a Cross-Sectional Analysis

PubMed Central

Gold, Katherine J.; Mozurkewich, Ellen L.; Puder, Karoline S.; Treadwell, Marjorie C.

2016-01-01

This study sought to identify delivery complications associated with stillbirth labor and delivery. We conducted a retrospective chart review evaluating stillbirth demographics, pregnancy and maternal risk factors, and complications of labor and delivery. We performed bivariable analysis and multivariable logistic regression to evaluate factors associated with medical complications and variations by race. Our cohort included 543 mothers with stillbirth, of which two-thirds were African-American. We noted high rates of shoulder dystocia, clinical chorioamnionitis, postpartum hemorrhage, and retained placenta in women with stillbirths. 33 women (6%) experienced at least one serious maternal complication. Complication rates did not vary by maternal race. Providers who perform obstetrical care should be alert to the high rate of maternal medical complications associated with labor and delivery of a stillbirth fetus. PMID:26479679

Maternal complications associated with stillbirth delivery: A cross-sectional analysis.

PubMed

Gold, K J; Mozurkewich, E L; Puder, K S; Treadwell, M C

2016-01-01

This study sought to identify delivery complications associated with stillbirth labour and delivery. We conducted a retrospective chart review evaluating stillbirth demographics, pregnancy and maternal risk factors, and complications of labour and delivery. We performed bivariable analysis and multivariable logistic regression to evaluate factors associated with medical complications and variations by race. Our cohort included 543 mothers with stillbirth, of which two-thirds were African-American. We noted high rates of shoulder dystocia, clinical chorioamnionitis, postpartum haemorrhage and retained placenta in women with stillbirths. Thirty-three women (6%) experienced at least one serious maternal complication. Complication rates did not vary by maternal race. Providers who perform obstetrical care should be alert to the high rate of maternal medical complications associated with labour and delivery of a stillbirth foetus.

Multivariate longitudinal data analysis with mixed effects hidden Markov models.

PubMed

Raffa, Jesse D; Dubin, Joel A

2015-09-01

Multiple longitudinal responses are often collected as a means to capture relevant features of the true outcome of interest, which is often hidden and not directly measurable. We outline an approach which models these multivariate longitudinal responses as generated from a hidden disease process. We propose a class of models which uses a hidden Markov model with separate but correlated random effects between multiple longitudinal responses. This approach was motivated by a smoking cessation clinical trial, where a bivariate longitudinal response involving both a continuous and a binomial response was collected for each participant to monitor smoking behavior. A Bayesian method using Markov chain Monte Carlo is used. Comparison of separate univariate response models to the bivariate response models was undertaken. Our methods are demonstrated on the smoking cessation clinical trial dataset, and properties of our approach are examined through extensive simulation studies. © 2015, The International Biometric Society.

Dental Workforce Availability and Dental Services Utilization in Appalachia: A Geospatial Analysis

PubMed Central

Feng, Xue; Sambamoorthi, Usha; Wiener, R. Constance

2016-01-01

Objectives There is considerable variation in dental services utilization across Appalachian counties, and a plausible explanation is that individuals in some geographical areas do not utilize dental care due to dental workforce shortage. We conducted an ecological study on dental workforce availability and dental services utilization in Appalachia. Methods We derived county-level (n = 364) data on demographic, socio-economic characteristics and dental services utilization in Appalachia from the 2010 Behavioral Risk Factor Surveillance System (BRFSS) using person-level data. We obtained county-level dental workforce availability and physician-to-population ratio estimates from Area Health Resource File, and linked them to the county-level BRFSS data. The dependent variable was the proportion using dental services within the last year in each county (ranging from 16.6% to 91.0%). We described the association between dental workforce availability and dental services utilization using ordinary least squares regression and spatial regression techniques. Spatial analyses consisted of bivariate Local Indicators of Spatial Association (LISA) and geographically weighted regression (GWR). Results Bivariate LISA showed that counties in the central and southern Appalachian regions had significant (p < .05) low-low spatial clusters (low dental workforce availability, low percent dental services utilization). GWR revealed considerable local variations in the association between dental utilization and dental workforce availability. In the multivariate GWR models, 8.5% (t-statistics >1.96) and 13.45% (t-statistics >1.96) of counties showed positive and statistically significant relationships between the dental services utilization and workforce availability of dentists and dental hygienists, respectively. Conclusions Dental workforce availability was associated with dental services utilization in the Appalachian region; however, this association was not statistically significant

Quantitative analysis of intra-Golgi transport shows intercisternal exchange for all cargo

PubMed Central

Dmitrieff, Serge; Rao, Madan; Sens, Pierre

2013-01-01

The mechanisms controlling the transport of proteins through the Golgi stack of mammalian and plant cells is the subject of intense debate, with two models, cisternal progression and intercisternal exchange, emerging as major contenders. A variety of transport experiments have claimed support for each of these models. We reevaluate these experiments using a single quantitative coarse-grained framework of intra-Golgi transport that accounts for both transport models and their many variants. Our analysis makes a definitive case for the existence of intercisternal exchange both for small membrane proteins and large protein complexes––this implies that membrane structures larger than the typical protein-coated vesicles must be involved in transport. Notwithstanding, we find that current observations on protein transport cannot rule out cisternal progression as contributing significantly to the transport process. To discriminate between the different models of intra-Golgi transport, we suggest experiments and an analysis based on our extended theoretical framework that compare the dynamics of transiting and resident proteins. PMID:24019488

Probabilistic Fracture Mechanics Analysis of the Orbiter's LH2 Feedline Flowliner

NASA Technical Reports Server (NTRS)

Bonacuse, Peter J. (Technical Monitor); Hudak, Stephen J., Jr.; Huyse, Luc; Chell, Graham; Lee, Yi-Der; Riha, David S.; Thacker, Ben; McClung, Craig; Gardner, Brian; Leverant, Gerald R.;

Systematic Review and Meta-Analysis of CT Features for Differentiating Complicated and Uncomplicated Appendicitis.

PubMed

Kim, Hae Young; Park, Ji Hoon; Lee, Yoon Jin; Lee, Sung Soo; Jeon, Jong-June; Lee, Kyoung Ho

2018-04-01

Purpose To perform a systematic review and meta-analysis to identify computed tomographic (CT) features for differentiating complicated appendicitis in patients suspected of having appendicitis and to summarize their diagnostic accuracy. Materials and Methods Studies on diagnostic accuracy of CT features for differentiating complicated appendicitis (perforated or gangrenous appendicitis) in patients suspected of having appendicitis were searched in Ovid-MEDLINE, EMBASE, and the Cochrane Library. Overlapping descriptors used in different studies to denote the same image finding were subsumed under a single CT feature. Pooled diagnostic accuracy of the CT features was calculated by using a bivariate random effects model. CT features with pooled diagnostic odds ratios with 95% confidence intervals not including 1 were considered as informative. Results Twenty-three studies were included, and 184 overlapping descriptors for various CT findings were subsumed under 14 features. Of these, 10 features were informative for complicated appendicitis. There was a general tendency for these features to show relatively high specificity but low sensitivity. Extraluminal appendicolith, abscess, appendiceal wall enhancement defect, extraluminal air, ileus, periappendiceal fluid collection, ascites, intraluminal air, and intraluminal appendicolith showed pooled specificity greater than 70% (range, 74%-100%), but sensitivity was limited (range, 14%-59%). Periappendiceal fat stranding was the only feature that showed high sensitivity (94%; 95% confidence interval: 86%, 98%) but low specificity (40%; 95% confidence interval, 23%, 60%). Conclusion Ten informative CT features for differentiating complicated appendicitis were identified in this study, nine of which showed high specificity, but low sensitivity. © RSNA, 2017 Online supplemental material is available for this article.

LC-MS Analysis of Phenolic Compounds in Tubers Showing Zebra Chip Symptoms

USDA-ARS?s Scientific Manuscript database

A new potato disorder called zebra chip (ZC) has been identified in the United States and has been especially problematic in Texas where substantial economic losses have been incurred. Upon frying, ZC tubers develop a dark “zebra chip” pattern of discoloration. LC-MS analysis of symptomatic tubers...

MOST light-curve analysis of the γ Doradus pulsator HR 8799, showing resonances and amplitude variations

NASA Astrophysics Data System (ADS)

Sódor, Á.; Chené, A.-N.; De Cat, P.; Bognár, Zs.; Wright, D. J.; Marois, C.; Walker, G. A. H.; Matthews, J. M.; Kallinger, T.; Rowe, J. F.; Kuschnig, R.; Guenther, D. B.; Moffat, A. F. J.; Rucinski, S. M.; Sasselov, D.; Weiss, W. W.

2014-08-01

Context. The central star of the HR 8799 system is a γ Doradus-type pulsator. The system harbours four planetary-mass companions detected by direct imaging, and is a good solar system analogue. The masses of the companions are not accurately known because the estimation depends greatly on the age of the system, which is also not known with sufficient accuracy. Asteroseismic studies of the star might help to better constrain the age of HR 8799. We organized an extensive photometric and multi-site spectroscopic observing campaign to study the pulsations of the central star. Aims: The aim of the present study is to investigate the pulsation properties of HR 8799 in detail via the ultra-precise 47 d nearly continuous photometry obtained with the Microvariability and Oscillations in STars (MOST) space telescope, and to find as many independent pulsation modes as possible, which is the prerequisite for an asteroseismic age determination. Methods: We carried out Fourier analysis of the wide-band photometric time series. Results: We find that resonance and sudden amplitude changes characterize the pulsation of HR 8799. The dominant frequency is always at f1 = 1.978 d-1.Many multiples of one-ninth of the dominant frequency appear in the Fourier spectrum of the MOST data: n/9 f1, where n = {1,2,3,4,5,6,7,8,9,10,13,14,17,18}. Our analysis also reveals that many of these peaks show strong amplitude decrease and phase variations even on the 47 d time scale. The dependencies between the pulsation frequencies of HR 8799 make the planned subsequent asteroseismic analysis rather difficult. We point out some resemblance between the light curve of HR 8799 and the modulated pulsation light curves of Blazhko RR Lyrae stars. Based on data from the MOST satellite, a Canadian Space Agency mission, jointly operated by Dynacon Inc., the University of Toronto Institute for Aerospace Studies and the University of British Columbia, with the assistance of the University of Vienna.

Use of Multivariate Linkage Analysis for Dissection of a Complex Cognitive Trait

PubMed Central

Marlow, Angela J.; Fisher, Simon E.; Francks, Clyde; MacPhie, I. Laurence; Cherny, Stacey S.; Richardson, Alex J.; Talcott, Joel B.; Stein, John F.; Monaco, Anthony P.; Cardon, Lon R.

2003-01-01

Replication of linkage results for complex traits has been exceedingly difficult, owing in part to the inability to measure the precise underlying phenotype, small sample sizes, genetic heterogeneity, and statistical methods employed in analysis. Often, in any particular study, multiple correlated traits have been collected, yet these have been analyzed independently or, at most, in bivariate analyses. Theoretical arguments suggest that full multivariate analysis of all available traits should offer more power to detect linkage; however, this has not yet been evaluated on a genomewide scale. Here, we conduct multivariate genomewide analyses of quantitative-trait loci that influence reading- and language-related measures in families affected with developmental dyslexia. The results of these analyses are substantially clearer than those of previous univariate analyses of the same data set, helping to resolve a number of key issues. These outcomes highlight the relevance of multivariate analysis for complex disorders for dissection of linkage results in correlated traits. The approach employed here may aid positional cloning of susceptibility genes in a wide spectrum of complex traits. PMID:12587094

A preliminary analysis of quantifying computer security vulnerability data in "the wild"

NASA Astrophysics Data System (ADS)

Farris, Katheryn A.; McNamara, Sean R.; Goldstein, Adam; Cybenko, George

2016-05-01

A system of computers, networks and software has some level of vulnerability exposure that puts it at risk to criminal hackers. Presently, most vulnerability research uses data from software vendors, and the National Vulnerability Database (NVD). We propose an alternative path forward through grounding our analysis in data from the operational information security community, i.e. vulnerability data from "the wild". In this paper, we propose a vulnerability data parsing algorithm and an in-depth univariate and multivariate analysis of the vulnerability arrival and deletion process (also referred to as the vulnerability birth-death process). We find that vulnerability arrivals are best characterized by the log-normal distribution and vulnerability deletions are best characterized by the exponential distribution. These distributions can serve as prior probabilities for future Bayesian analysis. We also find that over 22% of the deleted vulnerability data have a rate of zero, and that the arrival vulnerability data is always greater than zero. Finally, we quantify and visualize the dependencies between vulnerability arrivals and deletions through a bivariate scatterplot and statistical observations.

Analysis of quantitative data obtained from toxicity studies showing non-normal distribution.

PubMed

Kobayashi, Katsumi

2005-05-01

The data obtained from toxicity studies are examined for homogeneity of variance, but, usually, they are not examined for normal distribution. In this study I examined the measured items of a carcinogenicity/chronic toxicity study with rats for both homogeneity of variance and normal distribution. It was observed that a lot of hematology and biochemistry items showed non-normal distribution. For testing normal distribution of the data obtained from toxicity studies, the data of the concurrent control group may be examined, and for the data that show a non-normal distribution, non-parametric tests with robustness may be applied.

Identifying Ant-Mirid Spatial Interactions to Improve Biological Control in Cacao-Based Agroforestry System.

PubMed

Bagny Beilhe, Leïla; Piou, Cyril; Tadu, Zéphirin; Babin, Régis

2018-06-06

The use of ants for biological control of insect pests was the first reported case of conservation biological control. Direct and indirect community interactions between ants and pests lead to differential spatial pattern. We investigated spatial interactions between mirids, the major cocoa pest in West Africa and numerically dominant ant species, using bivariate point pattern analysis to identify potential biological control agents. We assume that potential biological control agents should display negative spatial interactions with mirids considering their niche overlap. The mirid/ant data were collected in complex cacao-based agroforestry systems sampled in three agroecological areas over a forest-savannah gradient in Cameroon. Three species, Crematogaster striatula Emery (Hymenoptera: Formicidae), Crematogaster clariventris Mayr (Hymenoptera: Formicidae), and Oecophylla longinoda Latreille (Hymenoptera: Formicidae) with high predator and aggressive behaviors were identified as dominant and showed negative spatial relationships with mirids. The weaver ant, O. longinoda was identified as the only potential biological control agent, considering its ubiquity in the plots, the similarity in niche requirements, and the spatial segregation with mirids resulting probably from exclusion mechanisms. Combining bivariate point pattern analysis to good knowledge of insect ecology was an effective method to identify a potentially good biological control agent.

Association between work, income and quality of life of kidney transplant recipient the municipality of Teresina, PI, Brazil.

PubMed

Costa, Joelma Maria; Nogueira, Lidya Tolstenko

2014-01-01

Evaluate the quality of life of kidney transplant recipients has been a way to determine the impact of transplantation in health care and subsequent treatment of chronic character. To analyze the association between income, work and quality of life of kidney transplant recipients. The sample consisted of 147 people, with an average of 74.3 months of realization of the transplantation. Data was collected using the following methods: socioeconomic assessment tool and the Medical Outcome Study 36 - Item Short - Form Health Survey, validated for use in Brazil. A bivariate analysis was performed using the Mann-Whitney's U test. The average quality of life related to health for the physical component was 63.8 (SD = 29.4), and for the mental component, 65.6 (SD = 29.2). The bivariate analysis showed that the exercise of labor activity and family income higher than three minimum wages were significantly associated with a better quality of life. Labor activities are significant for kidney transplant recipients and special attention must be given by the multidisciplinary team in the search for strategies that promote and encourage their maintenance and reintegration into the labor market.

The analysis of ensembles of moderately saturated interstellar lines

NASA Technical Reports Server (NTRS)

Jenkins, E. B.

1986-01-01

It is shown that the combined equivalent widths for a large population of Gaussian-like interstellar line components, each with different central optical depths tau(0) and velocity dispersions b, exhibit a curve of growth (COG) which closely mimics that of a single, pure Gaussian distribution in velocity. Two parametric distributions functions for the line populations are considered: a bivariate Gaussian for tau(0) and b and a power law distribution for tau(0) combined with a Gaussian dispersion for b. First, COGs for populations having an extremely large number of nonoverlapping components are derived, and the implications are shown by focusing on the doublet-ratio analysis for a pair of lines whose f-values differ by a factor of two. The consequences of having, instead of an almost infinite number of lines, a relatively small collection of components added together for each member of a doublet are examined. The theory of how the equivalent widths grow for populations of overlapping Gaussian profiles is developed. Examples of the composite COG analysis applied to existing collections of high-resolution interstellar line data are presented.

Global morphological analysis of marine viruses shows minimal regional variation and dominance of non-tailed viruses.

PubMed

Brum, Jennifer R; Schenck, Ryan O; Sullivan, Matthew B

2013-09-01

Viruses influence oceanic ecosystems by causing mortality of microorganisms, altering nutrient and organic matter flux via lysis and auxiliary metabolic gene expression and changing the trajectory of microbial evolution through horizontal gene transfer. Limited host range and differing genetic potential of individual virus types mean that investigations into the types of viruses that exist in the ocean and their spatial distribution throughout the world's oceans are critical to understanding the global impacts of marine viruses. Here we evaluate viral morphological characteristics (morphotype, capsid diameter and tail length) using a quantitative transmission electron microscopy (qTEM) method across six of the world's oceans and seas sampled through the Tara Oceans Expedition. Extensive experimental validation of the qTEM method shows that neither sample preservation nor preparation significantly alters natural viral morphological characteristics. The global sampling analysis demonstrated that morphological characteristics did not vary consistently with depth (surface versus deep chlorophyll maximum waters) or oceanic region. Instead, temperature, salinity and oxygen concentration, but not chlorophyll a concentration, were more explanatory in evaluating differences in viral assemblage morphological characteristics. Surprisingly, given that the majority of cultivated bacterial viruses are tailed, non-tailed viruses appear to numerically dominate the upper oceans as they comprised 51-92% of the viral particles observed. Together, these results document global marine viral morphological characteristics, show that their minimal variability is more explained by environmental conditions than geography and suggest that non-tailed viruses might represent the most ecologically important targets for future research.

Diagnostic accuracy of magnetic resonance imaging techniques for treatment response evaluation in patients with high-grade glioma, a systematic review and meta-analysis.

PubMed

van Dijken, Bart R J; van Laar, Peter Jan; Holtman, Gea A; van der Hoorn, Anouk

2017-10-01

Treatment response assessment in high-grade gliomas uses contrast enhanced T1-weighted MRI, but is unreliable. Novel advanced MRI techniques have been studied, but the accuracy is not well known. Therefore, we performed a systematic meta-analysis to assess the diagnostic accuracy of anatomical and advanced MRI for treatment response in high-grade gliomas. Databases were searched systematically. Study selection and data extraction were done by two authors independently. Meta-analysis was performed using a bivariate random effects model when ≥5 studies were included. Anatomical MRI (five studies, 166 patients) showed a pooled sensitivity and specificity of 68% (95%CI 51-81) and 77% (45-93), respectively. Pooled apparent diffusion coefficients (seven studies, 204 patients) demonstrated a sensitivity of 71% (60-80) and specificity of 87% (77-93). DSC-perfusion (18 studies, 708 patients) sensitivity was 87% (82-91) with a specificity of 86% (77-91). DCE-perfusion (five studies, 207 patients) sensitivity was 92% (73-98) and specificity was 85% (76-92). The sensitivity of spectroscopy (nine studies, 203 patients) was 91% (79-97) and specificity was 95% (65-99). Advanced techniques showed higher diagnostic accuracy than anatomical MRI, the highest for spectroscopy, supporting the use in treatment response assessment in high-grade gliomas. • Treatment response assessment in high-grade gliomas with anatomical MRI is unreliable • Novel advanced MRI techniques have been studied, but diagnostic accuracy is unknown • Meta-analysis demonstrates that advanced MRI showed higher diagnostic accuracy than anatomical MRI • Highest diagnostic accuracy for spectroscopy and perfusion MRI • Supports the incorporation of advanced MRI in high-grade glioma treatment response assessment.

Dental erosion and its association with diet in Libyan schoolchildren.

PubMed

Huew, R; Waterhouse, P J; Moynihan, P J; Kometa, S; Maguire, A

2011-10-01

To investigate any association between dental erosion and its potential dietary risk factors in a group of schoolchildren in Benghazi, Libya. A cross-sectional observational study. A random sample of 12-year-old schoolchildren in 36 randomly selected schools completed a questionnaire to provide dietary data and underwent dental examination. Dental erosion was assessed using UK National Diet and Nutrition Survey (2000) criteria. Associations between erosion and dietary variables under study were investigated through processes of bivariate and multivariate analyses. Of 791 schoolchildren dentally examined, 40.8% had dental erosion; erosion into enamel affecting 32.5%, into dentine affecting 8% and into pulp affecting 0.3% of subjects. Bivariate analysis showed frequency of fruit-based sugary drink intake was statistically significantly and positively associated with erosion (p=0.006, Odds Ratio; 1.498, 95% CI; 1.124, 1.996) as was the length of time taken to consume acidic drinks (p≠0.005, Odds Ratio; 1.593, 95%CI; 1.161, 2.186). Additionally, multivariate analysis showed frequency of consumption of fruit other than bananas, sugared tea with milk and flavoured milk to also be positively associated with erosion (p=<0.05). In this group of Libyan 12-year-olds, frequency of consumption of fruit-based sugary drinks and length of time taken to consume acidic drinks were the primary statistically significant positive risk factors for dental erosion.

Accuracy of Presurgical Functional MR Imaging for Language Mapping of Brain Tumors: A Systematic Review and Meta-Analysis.

PubMed

Weng, Hsu-Huei; Noll, Kyle R; Johnson, Jason M; Prabhu, Sujit S; Tsai, Yuan-Hsiung; Chang, Sheng-Wei; Huang, Yen-Chu; Lee, Jiann-Der; Yang, Jen-Tsung; Yang, Cheng-Ta; Tsai, Ying-Huang; Yang, Chun-Yuh; Hazle, John D; Schomer, Donald F; Liu, Ho-Ling

2018-02-01

Purpose To compare functional magnetic resonance (MR) imaging for language mapping (hereafter, language functional MR imaging) with direct cortical stimulation (DCS) in patients with brain tumors and to assess factors associated with its accuracy. Materials and Methods PubMed/MEDLINE and related databases were searched for research articles published between January 2000 and September 2016. Findings were pooled by using bivariate random-effects and hierarchic summary receiver operating characteristic curve models. Meta-regression and subgroup analyses were performed to evaluate whether publication year, functional MR imaging paradigm, magnetic field strength, statistical threshold, and analysis software affected classification accuracy. Results Ten articles with a total of 214 patients were included in the analysis. On a per-patient basis, the pooled sensitivity and specificity of functional MR imaging was 44% (95% confidence interval [CI]: 14%, 78%) and 80% (95% CI: 54%, 93%), respectively. On a per-tag basis (ie, each DCS stimulation site or "tag" was considered a separate data point across all patients), the pooled sensitivity and specificity were 67% (95% CI: 51%, 80%) and 55% (95% CI: 25%, 82%), respectively. The per-tag analysis showed significantly higher sensitivity for studies with shorter functional MR imaging session times (P = .03) and relaxed statistical threshold (P = .05). Significantly higher specificity was found when expressive language task (P = .02), longer functional MR imaging session times (P < .01), visual presentation of stimuli (P = .04), and stringent statistical threshold (P = .01) were used. Conclusion Results of this study showed moderate accuracy of language functional MR imaging when compared with intraoperative DCS, and the included studies displayed significant methodologic heterogeneity. © RSNA, 2017 Online supplemental material is available for this article.

Analysis of Factors Affecting Women of Childbearing Age to Screen Using Visual Inspection with Acetic Acid.

PubMed

Sidabutar, Sondang; Martini, Santi; Wahyuni, Chatarina Umbul

2017-02-01

The purpose of this study was to evaluate patient factors such as knowledge, attitude, motivation, perception, socio-economic status and travel time to health facilities and assess how these factors affected patients' decision to pursue cervical cancer screening with visual inspection with acetic acid (VIA). A total of 80 women of childbearing age who visited Kenjeran and Balongsari Public Health Centers for health assessments were involved in this study. Patients who agreed to participate in the study underwent a verbal questionnaire to evaluate various factors. Bivariate analysis concluded that knowledge, attitude, motivation, perception, socioeconomic status, and travel time to health facilities were significantly different between women who received VIA screening and women who did not receive VIA screening ( p < 0.05). The factors of knowledge, attitudes, motivation, perception, socio-economic status, and the travel time to health facilities accounted for 2.920-fold, 2.043-fold, 3.704-fold, 2.965-fold, 3.198-fold and 2.386-fold possibility, respectively, of patients to pursue cervical cancer screening with VIA. Multivariate analysis showed that perception, socio-economic status, and travel time to health facilities were the most important factors influencing whether or not women pursued VIA screening. Knowledge, attitude, motivation, perception, socio-economic status, and travel time to health facilities appears to affect women's' decision to pursue cervical cancer screening with VIA, with the largest intake being the motivational factor.

New QCT analysis approach shows the importance of fall orientation on femoral neck strength.

PubMed

Carpenter, R Dana; Beaupré, Gary S; Lang, Thomas F; Orwoll, Eric S; Carter, Dennis R

2005-09-01

The influence of fall orientation on femur strength has important implications for understanding hip fracture risk. A new image analysis technique showed that the strength of the femoral neck in 37 males varied significantly along the neck axis and that bending strength varied by a factor of up to 2.8 for different loading directions. Osteoporosis is associated with decreased BMD and increased hip fracture risk, but it is unclear whether specific osteoporotic changes in the proximal femur lead to a more vulnerable overall structure. Nonhomogeneous beam theory, which is used to determine the mechanical response of composite structures to applied loads, can be used along with QCT to estimate the resistance of the femoral neck to axial forces and bending moments. The bending moment [My(theta)] sufficient to induce yielding within femoral neck sections was estimated for a range of bending orientations (theta) using in vivo QCT images of 37 male (mean age, 73 years; range, 65-87 years) femora. Volumetric BMD, axial stiffness, average moment at yield (M(y,avg)), maximum and minimum moment at yield (M(y,max) and M(y,min)), bone strength index (BSI), stress-strain index (SSI), and density-weighted moments of resistance (Rx and Ry) were also computed. Differences among the proximal, mid-, and distal neck regions were detected using ANOVA. My(theta) was found to vary by as much as a factor of 2.8 for different bending directions. Axial stiffness, M(y,avg), M(y,max), M(y,min), BSI, and Rx differed significantly between all femoral neck regions, with an overall trend of increasing axial stiffness and bending strength when moving from the proximal neck to the distal neck. Mean axial stiffness increased 62% between the proximal and distal neck, and mean M(y,avg) increased 53% between the proximal and distal neck. The results of this study show that femoral neck strength strongly depends on both fall orientation and location along the neck axis. Compressive yielding in the

Psychological risk and protective factors for disability in chronic low back pain - a longitudinal analysis in primary care.

PubMed

Jegan, Nikita Roman A; Brugger, Markus; Viniol, Annika; Strauch, Konstantin; Barth, Jürgen; Baum, Erika; Leonhardt, Corinna; Becker, Annette

2017-03-20

Utilizing psychological resources when dealing with chronic low back pain might aid the prevention of disability. The observational study at hand examined the longitudinal impact of resilience and coping resources on disability in addition to established risk factors. Four hundred eighty four patients with chronic low back pain (>3 months) were recruited in primary care practices and followed up for one year. Resilience, coping, depression, somatization, pain and demographic variables were measured at baseline. At follow-up (participation rate 89%), data on disability was collected. We first calculated bivariate correlations of all the predictors with each other and with follow-up disability. We then used a multiple regression to evaluate the impact of all the predictors on disability together. More than half of the followed up sample showed a high degree of disability at baseline (53.7%) and had suffered for more than 10 years from pain (50.4%). Besides gender all of the predictors were bivariately associated with follow-up disability. However in the main analysis (multiple regression), disability at follow up was only predicted by baseline disability, age and somatization. There was no relationship between resilience and disability, nor between coping resources and disability. Although it is known that there are cross-sectional relationships between resilience/coping resources and disability we were not able to replicate it in the multiple regression. This can have several reasons: a) the majority of patients in our sample were much more disabled and suffered for a longer time than in other studies. Therefore our results might be limited to this specific population and resilience and coping resources might still have a protective influence in acute or subacute populations. b) We used a rather broad operationalization of resilience. There is emerging evidence that focusing on more concrete sub facets like (pain) self-efficacy and acceptance might be more

Bivariate autoregressive state-space modeling of psychophysiological time series data.

PubMed

Smith, Daniel M; Abtahi, Mohammadreza; Amiri, Amir Mohammad; Mankodiya, Kunal

2016-08-01

Heart rate (HR) and electrodermal activity (EDA) are often used as physiological measures of psychological arousal in various neuropsychology experiments. In this exploratory study, we analyze HR and EDA data collected from four participants, each with a history of suicidal tendencies, during a cognitive task known as the Paced Auditory Serial Addition Test (PASAT). A central aim of this investigation is to guide future research by assessing heterogeneity in the population of individuals with suicidal tendencies. Using a state-space modeling approach to time series analysis, we evaluate the effect of an exogenous input, i.e., the stimulus presentation rate which was increased systematically during the experimental task. Participants differed in several parameters characterizing the way in which psychological arousal was experienced during the task. Increasing the stimulus presentation rate was associated with an increase in EDA in participants 2 and 4. The effect on HR was positive for participant 2 and negative for participants 3 and 4. We discuss future directions in light of the heterogeneity in the population indicated by these findings.

DBH Prediction Using Allometry Described by Bivariate Copula Distribution

NASA Astrophysics Data System (ADS)

Xu, Q.; Hou, Z.; Li, B.; Greenberg, J. A.

2017-12-01

Forest biomass mapping based on single tree detection from the airborne laser scanning (ALS) usually depends on an allometric equation that relates diameter at breast height (DBH) with per-tree aboveground biomass. The incapability of the ALS technology in directly measuring DBH leads to the need to predict DBH with other ALS-measured tree-level structural parameters. A copula-based method is proposed in the study to predict DBH with the ALS-measured tree height and crown diameter using a dataset measured in the Lassen National Forest in California. Instead of exploring an explicit mathematical equation that explains the underlying relationship between DBH and other structural parameters, the copula-based prediction method utilizes the dependency between cumulative distributions of these variables, and solves the DBH based on an assumption that for a single tree, the cumulative probability of each structural parameter is identical. Results show that compared with the bench-marking least-square linear regression and the k-MSN imputation, the copula-based method obtains better accuracy in the DBH for the Lassen National Forest. To assess the generalization of the proposed method, prediction uncertainty is quantified using bootstrapping techniques that examine the variability of the RMSE of the predicted DBH. We find that the copula distribution is reliable in describing the allometric relationship between tree-level structural parameters, and it contributes to the reduction of prediction uncertainty.

Global morphological analysis of marine viruses shows minimal regional variation and dominance of non-tailed viruses

PubMed Central

Brum, Jennifer R; Schenck, Ryan O; Sullivan, Matthew B

2013-01-01

Viruses influence oceanic ecosystems by causing mortality of microorganisms, altering nutrient and organic matter flux via lysis and auxiliary metabolic gene expression and changing the trajectory of microbial evolution through horizontal gene transfer. Limited host range and differing genetic potential of individual virus types mean that investigations into the types of viruses that exist in the ocean and their spatial distribution throughout the world's oceans are critical to understanding the global impacts of marine viruses. Here we evaluate viral morphological characteristics (morphotype, capsid diameter and tail length) using a quantitative transmission electron microscopy (qTEM) method across six of the world's oceans and seas sampled through the Tara Oceans Expedition. Extensive experimental validation of the qTEM method shows that neither sample preservation nor preparation significantly alters natural viral morphological characteristics. The global sampling analysis demonstrated that morphological characteristics did not vary consistently with depth (surface versus deep chlorophyll maximum waters) or oceanic region. Instead, temperature, salinity and oxygen concentration, but not chlorophyll a concentration, were more explanatory in evaluating differences in viral assemblage morphological characteristics. Surprisingly, given that the majority of cultivated bacterial viruses are tailed, non-tailed viruses appear to numerically dominate the upper oceans as they comprised 51–92% of the viral particles observed. Together, these results document global marine viral morphological characteristics, show that their minimal variability is more explained by environmental conditions than geography and suggest that non-tailed viruses might represent the most ecologically important targets for future research. PMID:23635867

Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations

NASA Astrophysics Data System (ADS)

Kwapień, Jarosław; Oświecimka, Paweł; DroŻdŻ, Stanisław

2015-11-01

The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρDCCA works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρDCCA that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρq not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρq works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q -dependent counterpart of the correlation matrices and then to the network representation.

Metabolic control analysis of developing oilseed rape (Brassica napus cv Westar) embryos shows that lipid assembly exerts significant control over oil accumulation.

PubMed

Tang, Mingguo; Guschina, Irina A; O'Hara, Paul; Slabas, Antoni R; Quant, Patti A; Fawcett, Tony; Harwood, John L

2012-10-01

Metabolic control analysis allows the study of metabolic regulation. We applied both single- and double-manipulation top-down control analysis to examine the control of lipid accumulation in developing oilseed rape (Brassica napus) embryos. The biosynthetic pathway was conceptually divided into two blocks of reactions (fatty acid biosynthesis (Block A), lipid assembly (Block B)) connected by a single system intermediate, the acyl-coenzyme A (acyl-CoA) pool. Single manipulation used exogenous oleate. Triclosan was used to inhibit specifically Block A, whereas diazepam selectively manipulated flux through Block B. Exogenous oleate inhibited the radiolabelling of fatty acids from [1-(14)C]acetate, but stimulated that from [U-14C]glycerol into acyl lipids. The calculation of group flux control coefficients showed that c. 70% of the metabolic control was in the lipid assembly block of reactions. Monte Carlo simulations gave an estimation of the error of the resulting group flux control coefficients as 0.27±0.06 for Block A and 0.73±0.06 for Block B. The two methods of control analysis gave very similar results and showed that Block B reactions were more important under our conditions. This contrasts notably with data from oil palm or olive fruit cultures and is important for efforts to increase oilseed rape lipid yields. © 2012 The Authors. New Phytologist © 2012 New Phytologist Trust.

Nurses' attitudes and knowledge regarding organ and tissue donation and transplantation in a provincial hospital: A descriptive and multivariate analysis.

PubMed

Lomero, Maria Del Mar; Jiménez-Herrera, María F; Rasero, Maria José; Sandiumenge, Alberto

2017-09-01

The attitudes and knowledge of nursing personnel regarding organ and tissue donation can influence the decision to donate. This study aimed to determine these two factors among nurses at a district hospital in Barcelona, Spain. A survey was carried out using a 35 item questionnaire. Results were subjected to descriptive and comparative statistical analyses using bivariate and multivariate analyses to examine the relation between demographic data and attitudes toward donation. The completion rate was 68.2%, with 98.6% of those responding stating that they were in favor of organ donation. The respondents were unsure as to whether the criteria for inclusion in transplant waiting lists were appropriate (57.5%), whereas 72.2% agreed that brain death is equivalent to death. The bivariate analysis revealed a significant association between a positive attitude toward donation and working on permanent night shift no religious beliefs. Attitudes toward donation among nurses were generally positive; a negative attitude, although attitudes towards donation among the nurses participating in the study were generally positive, it should be pointed out that when a negative attitude does exist this affects significant aspects such as belief in the diagnosis of brain death or the criteria for inclusion on the waiting list, amongst others, which reflects that specific training in donation focused on nurses continues to be needed. © 2017 John Wiley & Sons Australia, Ltd.

Describing the genetic architecture of epilepsy through heritability analysis.

PubMed

Speed, Doug; O'Brien, Terence J; Palotie, Aarno; Shkura, Kirill; Marson, Anthony G; Balding, David J; Johnson, Michael R

2014-10-01

Epilepsy is a disease with substantial missing heritability; despite its high genetic component, genetic association studies have had limited success detecting common variants which influence susceptibility. In this paper, we reassess the role of common variants on epilepsy using extensions of heritability analysis. Our data set consists of 1258 UK patients with epilepsy, of which 958 have focal epilepsy, and 5129 population control subjects, with genotypes recorded for over 4 million common single nucleotide polymorphisms. Firstly, we show that on the liability scale, common variants collectively explain at least 26% (standard deviation 5%) of phenotypic variation for all epilepsy and 27% (standard deviation 5%) for focal epilepsy. Secondly we provide a new method for estimating the number of causal variants for complex traits; when applied to epilepsy, our most optimistic estimate suggests that at least 400 variants influence disease susceptibility, with potentially many thousands. Thirdly, we use bivariate analysis to assess how similar the genetic architecture of focal epilepsy is to that of non-focal epilepsy; we demonstrate both significant differences (P = 0.004) and significant similarities (P = 0.01) between the two subtypes, indicating that although the clinical definition of focal epilepsy does identify a genetically distinct epilepsy subtype, there is also scope to improve the classification of epilepsy by incorporating genotypic information. Lastly, we investigate the potential value in using genetic data to diagnose epilepsy following a single epileptic seizure; we find that a prediction model explaining 10% of phenotypic variation could have clinical utility for deciding which single-seizure individuals are likely to benefit from immediate anti-epileptic drug therapy. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain.

Lungworm Infections in German Dairy Cattle Herds — Seroprevalence and GIS-Supported Risk Factor Analysis

PubMed Central

Schunn, Anne-Marie; Conraths, Franz J.; Staubach, Christoph; Fröhlich, Andreas; Forbes, Andrew; Strube, Christina

2013-01-01

In November 2008, a total of 19,910 bulk tank milk (BTM) samples were obtained from dairy farms from all over Germany, corresponding to about 20% of all German dairy herds, and analysed for antibodies against the bovine lungworm Dictyocaulus viviparus by use of the recombinant MSP-ELISA. A total number of 3,397 (17.1%; n = 19,910) BTM samples tested seropositive. The prevalences in individual German federal states varied between 0.0% and 31.2% positive herds. A geospatial map was drawn to show the distribution of seropositive and seronegative herds per postal code area. ELISA results were further analysed for associations with land-use and climate data. Bivariate statistical analysis was used to identify potential spatial risk factors for dictyocaulosis. Statistically significant positive associations were found between lungworm seropositive herds and the proportion of water bodies and grassed area per postal code area. Variables that showed a statistically significant association with a positive BTM test were included in a logistic regression model, which was further refined by controlled stepwise selection of variables. The low Pseudo R2 values (0.08 for the full model and 0.06 for the final model) and further evaluation of the model by ROC analysis indicate that additional, unrecorded factors (e.g. management factors) or random effects may substantially contribute to lungworm infections in dairy cows. Veterinarians should include lungworms in the differential diagnosis of respiratory disease in dairy cattle, particularly those at pasture. Monitoring of herds through BTM screening for antibodies can help farmers and veterinarians plan and implement appropriate control measures. PMID:24040243

Modeling hardwood crown radii using circular data analysis

Treesearch

Paul F. Doruska; Hal O. Liechty; Douglas J. Marshall

2003-01-01

Cylindrical data are bivariate data composed of a linear and an angular component. One can use uniform, first-order (one maximum and one minimum) or second-order (two maxima and two minima) models to relate the linear component to the angular component. Crown radii can be treated as cylindrical data when the azimuths at which the radii are measured are also recorded....

Can Automated Facial Expression Analysis Show Differences Between Autism and Typical Functioning?

PubMed

Borsos, Zsófia; Gyori, Miklos

2017-01-01

Exploratory analyses of emotional expressions using a commercially available facial expression recognition software are reported, from the context of a serious game for screening purposes. Our results are based on a comparative analysis of two matched groups of kindergarten-age children (high-functioning children with autism spectrum condition: n=13; typically developing children: n=13). Results indicate that this technology has the potential to identify autism-specific emotion expression features, and may play a role in affective diagnostic and assistive technologies.

10. INTERIOR VIEW SHOWING MOUNTINGS FROM TUNING DEVICE. VIEW SHOWS ...

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

10. INTERIOR VIEW SHOWING MOUNTINGS FROM TUNING DEVICE. VIEW SHOWS COPPER SHEETING ON WALLS. - Chollas Heights Naval Radio Transmitting Facility, Helix House, 6410 Zero Road, San Diego, San Diego County, CA

What factors are associated with unplanned return following transurethral resection of bladder tumor? An analysis of a large single institution's experience.

PubMed

Ghali, Fady; Moses, Rachel A; Raffin, Eric; Hyams, Elias S

2016-10-01

This study sought to evaluate factors associated with unplanned hospital return (UR) following transurethral resection of bladder tumor (TURBT), the largest source of readmission among ambulatory urological procedures. A retrospective review of TURBTs at a single academic institution between April 2011 and August 2014 was performed. Demographics, comorbidities, length of stay, tumor size and multiple other factors were recorded. UR was recorded within 30 days of surgery. Bivariate and multivariable analyses were performed to determine factors associated with UR. Among 708 patients undergoing TURBT, 23.9% were female with a mean age of 70 years. The rate of UR was 10.9%. The most common cause of UR was gross hematuria, accounting for 70%. On bivariate analysis, Foley catheter placement in the operating room, non-aspirin anticoagulation and index length of stay longer than 24 h were associated with hematuria-related UR (p < 0.05). Preoperative antibiotics, female gender and aspirin therapy were associated with lower rates of hematuria-related UR (p < 0.05), while tumor size, distance of residence to the hospital, and Foley on hospital discharge (rather than from the operating room) had no association (p > 0.05). On multivariable analysis, only Foley placement in the operating room remained associated with higher rates of hematuria-related UR, while preoperative antibiotics, female gender and aspirin therapy remained associated with a lower likelihood of this event. UR following TURBT is common and typically results from gross hematuria. Patients with postoperative Foley catheterization in the operating room may require additional counseling or supervision before discharge, and should be considered for discharge with a Foley rather than having a prompt voiding trial.

The diagnostic performance of shear-wave elastography for liver fibrosis in children and adolescents: A systematic review and diagnostic meta-analysis.

PubMed

Kim, Jeong Rye; Suh, Chong Hyun; Yoon, Hee Mang; Lee, Jin Seong; Cho, Young Ah; Jung, Ah Young

2018-03-01

To assess the diagnostic performance of shear-wave elastography for determining the severity of liver fibrosis in children and adolescents. An electronic literature search of PubMed and EMBASE was conducted. Bivariate modelling and hierarchical summary receiver-operating-characteristic modelling were performed to evaluate the diagnostic performance of shear-wave elastography. Meta-regression and subgroup analyses according to the modality of shear-wave imaging and the degree of liver fibrosis were also performed. Twelve eligible studies with 550 patients were included. Shear-wave elastography showed a summary sensitivity of 81 % (95 % CI: 71-88) and a specificity of 91 % (95 % CI: 83-96) for the prediction of significant liver fibrosis. The number of measurements of shear-wave elastography performed was a significant factor influencing study heterogeneity. Subgroup analysis revealed shear-wave elastography to have an excellent diagnostic performance according to each degree of liver fibrosis. Supersonic shear imaging (SSI) had a higher sensitivity (p<.01) and specificity (p<.01) than acoustic radiation force impulse imaging (ARFI). Shear-wave elastography is an excellent modality for the evaluation of the severity of liver fibrosis in children and adolescents. Compared with ARFI, SSI showed better diagnostic performance for prediction of significant liver fibrosis. • Shear-wave elastography is beneficial for determining liver fibrosis severity in children. • Shear-wave elastography showed summary sensitivity of 81 %, specificity of 91 %. • SSI showed better diagnostic performance than ARFI for significant liver fibrosis.

Systematic analysis of DEMETER-like DNA glycosylase genes shows lineage-specific Smi-miR7972 involved in SmDML1 regulation in Salvia miltiorrhiza.

PubMed

Li, Jiang; Li, Caili; Lu, Shanfa

2018-05-08

DEMETER-like DNA glycosylases (DMLs) initiate the base excision repair-dependent DNA demethylation to regulate a wide range of biological processes in plants. Six putative SmDML genes, termed SmDML1-SmDML6, were identified from the genome of S. miltiorrhiza, an emerging model plant for Traditional Chinese Medicine (TCM) studies. Integrated analysis of gene structures, sequence features, conserved domains and motifs, phylogenetic analysis and differential expression showed the conservation and divergence of SmDMLs. SmDML1, SmDML2 and SmDML4 were significantly down-regulated by the treatment of 5Aza-dC, a general DNA methylation inhibitor, suggesting involvement of SmDMLs in genome DNA methylation change. SmDML1 was predicted and experimentally validated to be target of Smi-miR7972. Computational analysis of forty whole genome sequences and almost all of RNA-seq data from Lamiids revealed that MIR7972s were only distributed in some plants of the three orders, including Lamiales, Solanales and Boraginales, and the number of MIR7972 genes varied among species. It suggests that MIR7972 genes underwent expansion and loss during the evolution of some Lamiids species. Phylogenetic analysis of MIR7972s showed closer evolutionary relationships between MIR7972s in Boraginales and Solanales in comparison with Lamiales. These results provide a valuable resource for elucidating DNA demethylation mechanism in S. miltiorrhiza.

Statistical analysis of the calibration procedure for personnel radiation measurement instruments

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

Bush, W.J.; Bengston, S.J.; Kalbeitzer, F.L.

1980-11-01

Thermoluminescent analyzer (TLA) calibration procedures were used to estimate personnel radiation exposure levels at the Idaho National Engineering Laboratory (INEL). A statistical analysis is presented herein based on data collected over a six month period in 1979 on four TLA's located in the Department of Energy (DOE) Radiological and Environmental Sciences Laboratory at the INEL. The data were collected according to the day-to-day procedure in effect at that time. Both gamma and beta radiation models are developed. Observed TLA readings of thermoluminescent dosimeters are correlated with known radiation levels. This correlation is then used to predict unknown radiation doses frommore » future analyzer readings of personnel thermoluminescent dosimeters. The statistical techniques applied in this analysis include weighted linear regression, estimation of systematic and random error variances, prediction interval estimation using Scheffe's theory of calibration, the estimation of the ratio of the means of two normal bivariate distributed random variables and their corresponding confidence limits according to Kendall and Stuart, tests of normality, experimental design, a comparison between instruments, and quality control.« less

Bivariate and Multivariate Associations between Trait Listening Goals and Trait Communicator Preferences

ERIC Educational Resources Information Center

Keaton, Shaughan A.; Keteyian, Robert V.; Bodie, Graham D.

2014-01-01

This article provides validity evidence for a measure of listening goals by showing theoretically consistent relationships with an existing communication preference questionnaire. Participants (N = 257) were administered trait measures for listening goals and communicator preferences. The four listening goals--relational, task-oriented,…

Showing "F = BIL" Using Video Analysis

ERIC Educational Resources Information Center

Smith, Leon; Parker, David; Brown, Carl; Ireson, Gren

2011-01-01

The force on a current-carrying conductor in a magnetic field is a common aspect of post-16 physics courses. Many textbooks approach this topic via a current balance, e.g. Hutchins (1990) through to Duncan (2000), with websites such as "Practical Physics" giving a qualitative version. This article takes the approach of equating "F = BIL"sin[theta]…

How Important Are Health Care Expenditures for Life Expectancy? A Comparative, European Analysis.

PubMed

van den Heuvel, Wim J A; Olaroiu, Marinela

2017-03-01

The relationship between health care expenditures and health care outcomes, such as life expectancy and mortality, is complex. Research outcomes show different and contradictory results on this relationship. How and why health care expenditures affect health outcomes is not clear. A causal link between the two is not proven. Without such knowledge, effects of increase/decrease in health care expenses on health outcomes may be overestimated/underestimated. This study analyzes the relationship between life expectancy at birth and expenditures on health care, taking into account expenditures of social production and education, as well as the quantity and quality of health care provisions and lifestyles. This is a cross-sectional study, analyzing national data of 31 European countries. First, the bivariate correlation between the dependent variable and independent variables are calculated and described. Next a forward linear regression analysis is applied. The data are derived from standardized, comparative data bases as available in the Organisation for Economic Co-operation and Development and Eurostat. Health care expenditures are assessed as a percentage of the Gross Domestic Product (GDP). Health care expenditures are not the main determinant of life expectancy at birth, but social protection expenditures are. The regression analysis shows that in countries that spend a high percentage of their GDP on social protection, that have fewer curative beds and low infant mortality, whose citizens report fewer unmet health care needs and drink less alcohol, citizens have a significant longer life expectancy. To realize high life expectancy of citizens, policy measures have to be directed on investment in social protection expenditures, on improving quality of care, and on promoting a healthy life style. Copyright © 2016 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Meta-analysis: identification of low birthweight by other anthropometric measurements at birth in developing countries.

PubMed

Goto, Eita

2011-01-01

Low birthweight should be identified early, even in developing countries where birthweight cannot be easily measured due to the absence of scales and trained staff. This meta-analysis evaluated and compared the use of other anthropometric measurements at birth to predict low birthweight. All studies of medium to high quality (Quality Assessment of Diagnostic Accuracy Studies score ≥8) published in English were included. Bivariate random-effects meta-analysis and hierarchical summary receiver operating characteristic curves were used. A total of 69 studies evaluated foot length or the circumference of the chest, (mid-upper) arm, or thigh (n = 8, 25, 30, and 6, respectively). Chest circumference and arm circumference had areas under the curve >0.9 (0.95 for both), pooled positive likelihood ratios >5 (8.7 and 10.3, respectively), and negative likelihood ratios <0.2 (0.13 and 0.17, respectively); thigh circumference and foot length were less accurate. There was no substantial difference between chest and arm circumference with respect to pooled sensitivity (0.88 vs. 0.84, P = 0.505), specificity (0.90 vs. 0.92, P = 0.565), or diagnostic odds ratio (67 vs. 60, P = 0.552). However, as compared with arm circumference, chest circumference showed greater clustering of observations on the hierarchical summary receiver operating characteristic curve and narrower 95% confidence and prediction regions. Chest circumference and arm circumference have similarly high, although not confirmative, accuracy in predicting low birthweight; however, chest circumference appears to be more precise.

Drought Analysis for Kuwait Using Standardized Precipitation Index

PubMed Central

2014-01-01

Implementation of adequate measures to assess and monitor droughts is recognized as a major matter challenging researchers involved in water resources management. The objective of this study is to assess the hydrologic drought characteristics from the historical rainfall records of Kuwait with arid environment by employing the criterion of Standardized Precipitation Index (SPI). A wide range of monthly total precipitation data from January 1967 to December 2009 is used for the assessment. The computation of the SPI series is performed for intermediate- and long-time scales of 3, 6, 12, and 24 months. The drought severity and duration are also estimated. The bivariate probability distribution for these two drought characteristics is constructed by using Clayton copula. It has been shown that the drought SPI series for the time scales examined have no systematic trend component but a seasonal pattern related to rainfall data. The results are used to perform univariate and bivariate frequency analyses for the drought events. The study will help evaluating the risk of future droughts in the region, assessing their consequences on economy, environment, and society, and adopting measures for mitigating the effect of droughts. PMID:25386598

Factors associated with school-aged children's body mass index in Korean American families.

PubMed

Jang, Myoungock; Grey, Margaret; Sadler, Lois; Jeon, Sangchoon; Nam, Soohyun; Song, Hee-Jung; Whittemore, Robin

2017-08-01

To examine factors associated with children's body mass index and obesity-risk behaviours in Korean American families. Limited data are available about family factors related to overweight and obesity in Korean American children. A cross-sectional study. Convenient sampling was employed to recruit Korean American families in the Northeast of the United States between August 2014 and January 2015. Child, family and societal/demographic/community factors were measured with self-report questionnaires completed by mothers and children. Height and weight were measured to calculate body mass index. Data were analyzed using mixed effects models incorporating within-group correlation in siblings. The sample included 170 Korean American children and 137 mothers. In bivariate analyses, more child screen time, number of children in the household, greater parental underestimation of child's weight and children's participation in the school lunch program were significantly associated with higher child body mass index. In multivariate analyses that included variables showing significant bivariate relationship, no variable was associated with child body mass index. There were no child, family and societal/demographic/community factors related to child body mass index in Korean American families in the multivariate analysis, which is contrary to research in other racial/ethnic groups. In bivariate analyses, there is evidence that some factors were significantly related to child body mass index. Further research is needed to understand the unique behavioural, social and cultural features that contribute to childhood obesity in Korean American families. © 2017 John Wiley & Sons Ltd.

Analysis of a large dataset of mycorrhiza inoculation field trials on potato shows highly significant increases in yield.

PubMed

Hijri, Mohamed

2016-04-01

An increasing human population requires more food production in nutrient-efficient systems in order to simultaneously meet global food needs while reducing the environmental footprint of agriculture. Arbuscular mycorrhizal fungi (AMF) have the potential to enhance crop yield, but their efficiency has yet to be demonstrated in large-scale crop production systems. This study reports an analysis of a dataset consisting of 231 field trials in which the same AMF inoculant (Rhizophagus irregularis DAOM 197198) was applied to potato over a 4-year period in North America and Europe under authentic field conditions. The inoculation was performed using a liquid suspension of AMF spores that was sprayed onto potato seed pieces, yielding a calculated 71 spores per seed piece. Statistical analysis showed a highly significant increase in marketable potato yield (ANOVA, P < 0.0001) for inoculated fields (42.2 tons/ha) compared with non-inoculated controls (38.3 tons/ha), irrespective of trial year. The average yield increase was 3.9 tons/ha, representing 9.5 % of total crop yield. Inoculation was profitable with a 0.67-tons/ha increase in yield, a threshold reached in almost 79 % of all trials. This finding clearly demonstrates the benefits of mycorrhizal-based inoculation on crop yield, using potato as a case study. Further improvements of these beneficial inoculants will help compensate for crop production deficits, both now and in the future.

Working with Noise in Bivariate Data

ERIC Educational Resources Information Center

Groth, Randall E.; Jones, Matthew; Knaub, Mary

2017-01-01

The authors asked a group of students during a classroom research study to analyze data sets containing different amounts of noise. The authors use the word "noise" to refer to statistical variability. The four students in the group were finishing seventh grade and participating in summer mathematics instruction. The authors carefully…

Influence of geomagnetic activity and atmospheric pressure on human arterial pressure during the solar cycle 24

NASA Astrophysics Data System (ADS)

Azcárate, T.; Mendoza, B.; Levi, J. R.

2016-11-01

We performed a study of the systolic (SBP) and diastolic (DBP) arterial blood pressure behavior under natural variables such as the atmospheric pressure (AtmP) and the horizontal geomagnetic field component (H). We worked with a sample of 304 healthy normotense volunteers, 152 men and 152 women, with ages between 18 and 84 years in Mexico City during the period 2008-2014, corresponding to the minimum, ascending and maximum phases of the solar cycle 24. The data was divided by gender, age and day/night cycle. We studied the time series using three methods: Correlations, bivariate and superposed epochs (within a window of three days around the day of occurrence of a geomagnetic storm) analysis, between the SBP and DBP and the natural variables (AtmP and H). The correlation analysis indicated correlation between the SBP and DBP and AtmP and H, being the largest during the night. Furthermore, the correlation and bivariate analysis showed that the largest correlations are between the SBP and DBP and the AtmP. The superposed epoch analysis found that the largest number of significant SBP and DBP changes occurred for women. Finally, the blood pressure changes are larger during the solar minimum and ascending solar cycle phases than during the solar maximum; the storms of the minimum were more intense than those of the maximum and this could be the reason of behavior of the blood pressure changes along the solar cycle.

Why Do Some First Nations Communities Have Safe Water and Others Not? Socioeconomic Determinants of Drinking Water Risk

PubMed Central

Brown, Brandon; Wachowiak-Smolíková, Renata; Spence, Nicholas D.; Wachowiak, Mark P.; Walters, Dan F.

2016-01-01

Securing safe and adequate drinking water is an ongoing issue for many Canadian First Nations communities despite nearly 15 years of reports, studies, policy changes, financial commitments, and regulations. The federal drinking water evaluation scheme is narrowly scoped, ignoring community level social factors, which may play a role in access to safe water in First Nations. This research used the 2006 Aboriginal Affairs and Northern Development Canada First Nations Drinking Water System Risk Survey data and the Community Well-Being Index, including labour force, education, housing, and income, from the 2006 Census. Bivariate analysis was conducted using the Spearman’s correlation, Kendall’s tau correlation, and Pearson’s correlation. Multivariable analysis was conducted using an ordinal (proportional or cumulative odds) regression model. Results showed that the regression model was significant. Community socioeconomic indicators had no relationship with drinking water risk characterization in both the bivariate and multivariable models, with the sole exception of labour force, which had a significantly positive effect on drinking water risk rankings. Socioeconomic factors were not important in explaining access to safe drinking water in First Nations communities. Improvements in the quality of safe water data as well as an examination of other community processes are required to address this pressing policy issue. PMID:27157172

Why Do Some First Nations Communities Have Safe Water and Others Not? Socioeconomic Determinants of Drinking Water Risk.

PubMed

Brown, Brandon; Wachowiak-Smolíková, Renata; Spence, Nicholas D; Wachowiak, Mark P; Walters, Dan F

2016-09-01

Securing safe and adequate drinking water is an ongoing issue for many Canadian First Nations communities despite nearly 15 years of reports, studies, policy changes, financial commitments, and regulations. The federal drinking water evaluation scheme is narrowly scoped, ignoring community level social factors, which may play a role in access to safe water in First Nations. This research used the 2006 Aboriginal Affairs and Northern Development Canada First Nations Drinking Water System Risk Survey data and the Community Well-Being Index, including labour force, education, housing, and income, from the 2006 Census. Bivariate analysis was conducted using the Spearman's correlation, Kendall's tau correlation, and Pearson's correlation. Multivariable analysis was conducted using an ordinal (proportional or cumulative odds) regression model. Results showed that the regression model was significant. Community socioeconomic indicators had no relationship with drinking water risk characterization in both the bivariate and multivariable models, with the sole exception of labour force, which had a significantly positive effect on drinking water risk rankings. Socioeconomic factors were not important in explaining access to safe drinking water in First Nations communities. Improvements in the quality of safe water data as well as an examination of other community processes are required to address this pressing policy issue.

Loneliness in Men 60 Years and Over: The Association With Purpose in Life.

PubMed

Neville, Stephen; Adams, Jeffery; Montayre, Jed; Larmer, Peter; Garrett, Nick; Stephens, Christine; Alpass, Fiona

2018-07-01

Loneliness as a consequence of getting older negatively impacts on the health and well-being of men as they age. Having a purpose in life may mitigate loneliness and therefore positively impact on health and well-being. Limited research into loneliness and purpose in life has been undertaken in older men. This study seeks to understand the relationship between loneliness and purpose in life in a group of older men. Using data from a cross-sectional survey of 614 men aged 60 years and over living in New Zealand, bivariate and multivariate analyses were undertaken to examine the relationship between loneliness and purpose in life using a range of demographic, health, and social connection variables. Bivariate analysis revealed that being unpartnered and having low socioeconomic status, limited social networks, low levels of participation, and mental health issues were associated with loneliness. Multivariate analysis showed that having poor mental health and lower purpose in life were indicators of loneliness. Consequently, improving mental health and purpose in life are likely to reduce loneliness in at-risk older men. As older men are a heterogeneous group from a variety of sociocultural and ethnic backgrounds, a multidimensional approach to any intervention initiatives needs to occur.

Dental services utilization by women of childbearing age by socioeconomic status.

PubMed

Kaylor, Mary B; Polivka, Barbara J; Chaudry, Rosemary; Salsberry, Pamela; Wee, Alvin G

2010-04-01

For women of childbearing age, oral health not only affects their physical and psychological well-being but also that of their children. This study used the 2003-2004 Ohio Family Health Survey (N = 9,819) to examine dental need and utilization by women in Ohio. Predisposing, enabling, and need variables were examined as they effect dental health service utilization by women of childbearing age at different socioeconomic status (SES) levels. The proportion of women in the low SES group self reporting a dental need (18%) was 3 times that of the proportion of women in the higher SES group with a self reported need (6%). Results of bivariate analysis showed that having a dental visit in the past year varied significantly by SES, race, insurance status, provider density, and need. A racial disparity in dental service utilization was noted in the bivariate analysis of the middle SES group. While dental need and type of dental coverage varied by SES, both were significantly associated with utilization of dental services within all 3 SES categories in the logistic regressions. These results suggest that measures need to be implemented to meet the goal of increasing access and utilization of dental health services by low-income populations.

Association between periodontal flap surgery for periodontitis and vasculogenic erectile dysfunction in Koreans.

PubMed

Lee, Jae-Hong; Choi, Jung-Kyu; Kim, Sang-Hyun; Cho, Kyung-Hyun; Kim, Young-Taek; Choi, Seong-Ho; Jung, Ui-Won

2017-04-01

The National Health Insurance Service-National Sample Cohort and medical checkup data from 2002 to 2013 were used to evaluate the association between periodontal surgery for the treatment of periodontitis (PSTP) and vasculogenic erectile dysfunction (VED). Bivariate and multivariate logistic regression analyses were applied to a longitudinal retrospective database to assess the association between PSTP and VED while adjusting for the potential confounding effects of sociodemographic factors (age, household income, insurance status, health status, residence area, and smoking status) and comorbidities (diabetes mellitus, angina pectoris, cerebral infarction, and myocardial infarction). Among the 7,148 PSTP within the 268,296 recruited subjects, the overall prevalence of VED in PSTP was 1.43% (n=102). The bivariate analysis showed that VED was significantly related to PSTP (odds ratio [OR], 1.99; 95% confidence interval [CI], 1.38-2.06; P <0.001), and this was confirmed in the multivariate analysis after adjusting for sociodemographic factors and comorbidities (OR, 1.29; 95% CI, 1.06-1.58; P =0.002). Subjects with a history of periodontal flap surgery had a significantly higher risk of VED, after adjusting for potential confounding factors. Further studies are required to identify the key mechanisms underlying the association between severe periodontal disease and VED.

Association between periodontal flap surgery for periodontitis and vasculogenic erectile dysfunction in Koreans

PubMed Central

2017-01-01

Purpose The National Health Insurance Service-National Sample Cohort and medical checkup data from 2002 to 2013 were used to evaluate the association between periodontal surgery for the treatment of periodontitis (PSTP) and vasculogenic erectile dysfunction (VED). Methods Bivariate and multivariate logistic regression analyses were applied to a longitudinal retrospective database to assess the association between PSTP and VED while adjusting for the potential confounding effects of sociodemographic factors (age, household income, insurance status, health status, residence area, and smoking status) and comorbidities (diabetes mellitus, angina pectoris, cerebral infarction, and myocardial infarction). Results Among the 7,148 PSTP within the 268,296 recruited subjects, the overall prevalence of VED in PSTP was 1.43% (n=102). The bivariate analysis showed that VED was significantly related to PSTP (odds ratio [OR], 1.99; 95% confidence interval [CI], 1.38–2.06; P<0.001), and this was confirmed in the multivariate analysis after adjusting for sociodemographic factors and comorbidities (OR, 1.29; 95% CI, 1.06–1.58; P=0.002). Conclusions Subjects with a history of periodontal flap surgery had a significantly higher risk of VED, after adjusting for potential confounding factors. Further studies are required to identify the key mechanisms underlying the association between severe periodontal disease and VED. PMID:28462008

Compounding effects of sea level rise and fluvial flooding.

PubMed

Moftakhari, Hamed R; Salvadori, Gianfausto; AghaKouchak, Amir; Sanders, Brett F; Matthew, Richard A

2017-09-12

Sea level rise (SLR), a well-documented and urgent aspect of anthropogenic global warming, threatens population and assets located in low-lying coastal regions all around the world. Common flood hazard assessment practices typically account for one driver at a time (e.g., either fluvial flooding only or ocean flooding only), whereas coastal cities vulnerable to SLR are at risk for flooding from multiple drivers (e.g., extreme coastal high tide, storm surge, and river flow). Here, we propose a bivariate flood hazard assessment approach that accounts for compound flooding from river flow and coastal water level, and we show that a univariate approach may not appropriately characterize the flood hazard if there are compounding effects. Using copulas and bivariate dependence analysis, we also quantify the increases in failure probabilities for 2030 and 2050 caused by SLR under representative concentration pathways 4.5 and 8.5. Additionally, the increase in failure probability is shown to be strongly affected by compounding effects. The proposed failure probability method offers an innovative tool for assessing compounding flood hazards in a warming climate.

Testing for the Endogenous Nature between Women's Empowerment and Antenatal Health Care Utilization: Evidence from a Cross-Sectional Study in Egypt

PubMed Central

Hussein, Mohamed Ali

2014-01-01

Women's relative lack of decision-making power and their unequal access to employment, finances, education, basic health care, and other resources are considered to be the root causes of their ill-health and that of their children. The main purpose of this paper is to examine the interactive relation between women's empowerment and the use of maternal health care. Two model specifications are tested. One assumes no correlation between empowerment and antenatal care while the second specification allows for correlation. Both the univariate and the recursive bivariate probit models are tested. The data used in this study is EDHS 2008. Factor Analysis Technique is also used to construct some of the explanatory variables such as the availability and quality of health services indicators. The findings show that women's empowerment and receiving regular antenatal care are simultaneously determined and the recursive bivariate probit is a better approximation to the relationship between them. Women's empowerment has significant and positive impact on receiving regular antenatal care. The availability and quality of health services do significantly increase the likelihood of receiving regular antenatal care. PMID:25140310

28. MAP SHOWING LOCATION OF ARVFS FACILITY AS BUILT. SHOWS ...

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

28. MAP SHOWING LOCATION OF ARVFS FACILITY AS BUILT. SHOWS LINCOLN BOULEVARD, BIG LOST RIVER, AND NAVAL REACTORS FACILITY. F.C. TORKELSON DRAWING NUMBER 842-ARVFS-101-2. DATED OCTOBER 12, 1965. INEL INDEX CODE NUMBER: 075 0101 851 151969. - Idaho National Engineering Laboratory, Advanced Reentry Vehicle Fusing System, Scoville, Butte County, ID

Time-frequency wavelet analysis of the interrelationship between the global macro assets and the fear indexes

NASA Astrophysics Data System (ADS)

Abid, Fathi; Kaffel, Bilel

2018-01-01

Understanding the interrelationships of the global macro assets is crucial for global macro investing. This paper investigates the local variance and the interconnection between the stock, gold, oil, Forex and the implied volatility markets in the time/frequency domains using the wavelet methodology, including the wavelet power spectrum, the wavelet squared coherence and phase difference, the wavelet multiple correlation and cross-correlation. The univariate analysis reveals that, in some crisis periods, underlying asset markets present the same pattern in terms of the wavelet power spectrum indicating high volatility for the medium scale, and that for the other market stress periods, volatility behaves differently. Moreover, unlike the underlying asset markets, the implied volatility markets are characterized by high power regions across the entire period, even in the absence of economic events. Bivariate results show a bidirectional relationship between the underlying assets and their corresponding implied volatility indexes, and a steady co-movement between the stock index and its corresponding fear index. Multiple correlation analysis indicates a strong correlation between markets at high scales with evidence of a nearly perfect integration for a period longer than a year. In addition, the hedging strategies based on the volatility index lead to an increase in portfolio correlation. On the other hand, the results from multiple cross-correlations reveal that the lead-lag effect starts from the medium scale and that the VIX (stock market volatility index) index is the potential leader or follower of the other markets.

Groundwater source contamination mechanisms: Physicochemical profile clustering, risk factor analysis and multivariate modelling

NASA Astrophysics Data System (ADS)

Hynds, Paul; Misstear, Bruce D.; Gill, Laurence W.; Murphy, Heather M.

2014-04-01

An integrated domestic well sampling and "susceptibility assessment" programme was undertaken in the Republic of Ireland from April 2008 to November 2010. Overall, 211 domestic wells were sampled, assessed and collated with local climate data. Based upon groundwater physicochemical profile, three clusters have been identified and characterised by source type (borehole or hand-dug well) and local geological setting. Statistical analysis indicates that cluster membership is significantly associated with the prevalence of bacteria (p = 0.001), with mean Escherichia coli presence within clusters ranging from 15.4% (Cluster-1) to 47.6% (Cluster-3). Bivariate risk factor analysis shows that on-site septic tank presence was the only risk factor significantly associated (p < 0.05) with bacterial presence within all clusters. Point agriculture adjacency was significantly associated with both borehole-related clusters. Well design criteria were associated with hand-dug wells and boreholes in areas characterised by high permeability subsoils, while local geological setting was significant for hand-dug wells and boreholes in areas dominated by low/moderate permeability subsoils. Multivariate susceptibility models were developed for all clusters, with predictive accuracies of 84% (Cluster-1) to 91% (Cluster-2) achieved. Septic tank setback was a common variable within all multivariate models, while agricultural sources were also significant, albeit to a lesser degree. Furthermore, well liner clearance was a significant factor in all models, indicating that direct surface ingress is a significant well contamination mechanism. Identification and elucidation of cluster-specific contamination mechanisms may be used to develop improved overall risk management and wellhead protection strategies, while also informing future remediation and maintenance efforts.

Using SPSS to Analyze Book Collection Data.

ERIC Educational Resources Information Center

Townley, Charles T.

1981-01-01

Describes and illustrates Statistical Package for the Social Sciences (SPSS) procedures appropriate for book collection data analysis. Several different procedures for univariate, bivariate, and multivariate analysis are discussed, and applications of procedures for book collection studies are presented. Included are 24 tables illustrating output…

Comparative genomic analysis shows that Streptococcus suis meningitis isolate SC070731 contains a unique 105K genomic island.

PubMed

Wu, Zongfu; Wang, Weixue; Tang, Min; Shao, Jing; Dai, Chen; Zhang, Wei; Fan, Hongjie; Yao, Huochun; Zong, Jie; Chen, Dai; Wang, Junning; Lu, Chengping

2014-02-10

Streptococcus suis (SS) is an important swine pathogen worldwide that occasionally causes serious infections in humans. SS infection may result in meningitis in pigs and humans. The pathogenic mechanisms of SS are poorly understood. Here, we provide the complete genome sequence of S. suis serotype 2 (SS2) strain SC070731 isolated from a pig with meningitis. The chromosome is 2,138,568bp in length. There are 1933 predicted protein coding sequences and 96.7% (57/59) of the known virulence-associated genes are present in the genome. Strain SC070731 showed similar virulence with SS2 virulent strains HA9801 and ZY05719, but was more virulent than SS2 virulent strain P1/7 in the zebrafish infection model. Comparative genomic analysis revealed a unique 105K genomic island in strain SC070731 that is absent in seven other sequenced SS2 strains. Further analysis of the 105K genomic island indicated that it contained a complete nisin locus similar to the nisin U locus in S. uberis strain 42, a prophage similar to S. oralis phage PH10 and several antibiotic resistance genes. Several proteins in the 105K genomic island, including nisin and RelBE toxin-antitoxin system, contribute to the bacterial fitness and virulence in other pathogenic bacteria. Further investigation of newly identified gene products, including four putative new virulence-associated surface proteins, will improve our understanding of SS pathogenesis. Copyright © 2013 Elsevier B.V. All rights reserved.

A Content Analysis of Physical Activity in TV Shows Popular Among Adolescents

PubMed Central

Gietzen, Megan S.; Gollust, Sarah E.; Linde, Jennifer A.; Neumark-Sztainer, Dianne; Eisenberg, Marla E.

2017-01-01

Purpose Previous research demonstrates that television has the potential to influence youth behaviors, but little evidence exists on how television depicts physical activity (PA), an important public health priority for youth. This mixed-methods study investigates depictions of television characters’ participation in PA in the top 25 favorite shows ranked by a diverse sample of 2,793 adolescents. Method Randomly selected episodes from each show were content analyzed for PA incidents, reasons and context, and in relation to the gender and weight status of participating characters. Results A total of 374 incidents of PA were coded across 75 episodes, with an average of 5.0 incidents per episode. Although male and female characters were equally likely to engage in at least one incident of PA, male characters were involved in a statistically significantly larger proportion of PA incidents than female characters and were more likely to engage in PA for competitive sport. There was no statistically significant difference in engagement in PA or the proportion of PA incidents for characters coded as overweight compared to non-overweight characters. Conclusions Although female characters tended to be underrepresented in PA, this study reveals positive messages for how gender and weight are portrayed in relation to PA on TV. PMID:28151062

Intrapersonal self-transcendence, meaning-in-life and nurse-patient interaction: powerful assets for quality of life in cognitively intact nursing-home patients.

PubMed

Haugan, Gørill; Moksnes, Unni Karin; Løhre, Audhild

2016-12-01

Spirituality has demonstrated a significant impact on quality of life in nursing-home patients. Likewise, as essential aspects of spirituality, hope, self-transcendence, and meaning are found to be vital resources to nursing-home patients' global well-being. Further, nurse-patient interaction has demonstrated a powerful influence on patient's hope, self-transcendence, and meaning-in-life, as well as on anxiety and depression. The present study investigated the associations of hope, self-transcendence, meaning, and perceived nurse-patient interaction with quality of life. In a cross-sectional design, a sample of 202 cognitively intact nursing-home patients in Mid-Norway responded to the Herth Hope Index, the Self-Transcendence scale, the Purpose-in-Life test, the Nurse-Patient Interaction scale, and a one-item overall measure on quality of life. Using SPSS ordinal regression, bivariate and multivariate analyses were conducted with quality of life as dependent variable. Controlling for gender, age, and residential time, all the scales were significantly related to quality of life in the bivariate analyses. Intrapersonal self-transcendence showed an exceptional position presenting a very high odds ratio in the bivariate analysis, and also the strongest association with quality of life in multivariate analyses. Meaning and nurse-patient interaction also showed independent and significant associations with quality of life. The associations found encourage the idea that intrapersonal self-transcendence, meaning-in-life, and nurse-patient interaction are powerful health-promoting factors that significantly influence on nursing-home patients' quality of life. Therefore, pedagogical approaches for advancing caregivers' presence and confidence in health-promoting interaction should be upgraded and matured. Proper educational programs for developing interacting skills including assessing and supporting patients' intrapersonal self-transcendence and meaning-in-life should be

Severe weather as a spectacle: the Meteo-Show

NASA Astrophysics Data System (ADS)

Orbe, Iñaki; Gaztelumendi, Santiago

2017-06-01

In this work we focus on perhaps one of the worst journalist practice when dealing with severe weather, the Meteo-Show or the extended practice, especially in TV, for using weather and meteorology for spectacle. Journalism today has found weather information in a real goldmine in terms of audience due to the growing public interest in this matter. However, as it happens with other content, sensationalism and exaggeration have also reached weather information, primarily when episodes of adverse nature (snow, heavy rain, floods, etc.) are addressed. In this paper we look to identify the worst practices in weather communication through analysis of examples from real journalist work. We present some keys to understand this trend, highlighting the ingredients that are present in the worst Meteo-show.

An Analysis of the Relationship between Phonological and Nonphonological Language and Early Reading Development

ERIC Educational Resources Information Center

Batson-Magnuson, LuAnn

2017-01-01

This study explores the relationship between preschool phonological and nonphonological language performance and first-grade reading performance. Data were gathered from the files of 149 students who had completed a universal kindergarten screening program in the spring prior to enrollment. Bivariate correlation analyses, Steiger's Z comparisons,…

Spousal Caregiver Burden and Its Relation with Disability in Schizophrenia

PubMed Central

Arun, R.; Inbakamal, S.; Tharyan, Anna; Premkumar, Prasanna S.

2018-01-01

Background: Schizophrenia, a chronic psychiatric disorder, can affect one's productivity and psychosocial functioning. In Indian context, the responsibility of caring persons with schizophrenia is increasingly on their spouses. Spousal caregiver experience and its relation with disability in schizophrenia need to be studied. Materials and Methods: We conducted a cross-sectional study among 52 outpatients with schizophrenia and their spouses attending a tertiary psychiatric center. The objectives were: (a) to explore spousal caregiver burden in schizophrenia and (b) to assess the relation between disability and spousal caregiver burden. The study adopted recommended ethical principles. Scales such as Burden Assessment Schedule, Indian Disability Evaluation and Assessment Scale (IDEAS), and Positive and Negative Syndrome Scale were used to collect appropriate data. Descriptive analysis, bivariate analysis, and multivariate analysis were done in SPSS software version 16.0. Results: The mean spousal caregiver burden score was 73.5 (standard deviation: 14.0). In bivariate analysis, disability, duration of schizophrenia, severity of schizophrenia, place of residence, and socioeconomic status had statistically significant relation with spousal caregiver burden. Adjusted for spouses’ age, gender, and other significant factors in bivariate analysis, the IDEAS global disability score (2.6, [confidence interval 0.5–3.8, P = 0.013]) retained statistically significant association with spousal caregiver burden. Conclusion: Spouses of persons with schizophrenia experience significant caregiver burden. Disability was found to be the most powerful determinant of spousal caregiver burden in the sample. Focus on disability alleviation in the management of schizophrenia may help reduce spousal caregiver burden. PMID:29403125

The maternal and neonatal outcomes for an urban Indigenous population compared with their non-Indigenous counterparts and a trend analysis over four triennia.

PubMed

Kildea, Sue; Stapleton, Helen; Murphy, Rebecca; Kosiak, Machellee; Gibbons, Kristen

2013-08-30

Indigenous Australians experience significantly disproportionate poorer health outcomes compared to their non-Indigenous counterparts. Despite the recognised importance of maternal infant health (MIH), there is surprisingly little empirical research to guide service redesign that successfully addresses the disparities. This paper reports on a service evaluation that also compared key MIH indicators for Indigenous and non-Indigenous mothers and babies over a 12-year period 1998-2009. Trend analysis with logistic regression, using the independent variables of ethnicity and triennia, explored changes over time (1998-2009) between two cohorts: 1,523 births to Indigenous mothers and 43,693 births to non-Indigenous mothers. We included bivariate and multivariate analysis on key indicators (e.g. teenage births, preterm birth, low birth weight, smoking) and report odds ratios (ORs), 95% CIs and logistic regression adjusting for important confounders. We excluded transfers in from other areas which are identified within the database. Bivariate analysis revealed Indigenous women were statistically more likely to have spontaneous onset of labour and a non-instrumental vaginal birth. They were less likely to take epidurals for pain relief in labour, have assisted births, caesarean sections or perineal trauma. Despite better labour outcomes, Indigenous babies were more likely to be born preterm (< 37 weeks) and be low birth weight (< 2500 g); these differences remained significant in multivariate analysis. The trend analysis revealed relatively stable rates for teenage pregnancy, small for gestational age, low birth weight babies, and perinatal mortality for both cohorts, with the gap between cohorts consistent over time. A statistical widening of the gap in preterm birth and smoking rates was found with preterm birth demonstrating a relative increase of 51% over this period. The comprehensive database from a large urban hospital allowed a thorough examination of outcomes and

FUNSTAT and statistical image representations

NASA Technical Reports Server (NTRS)

Parzen, E.

1983-01-01

General ideas of functional statistical inference analysis of one sample and two samples, univariate and bivariate are outlined. ONESAM program is applied to analyze the univariate probability distributions of multi-spectral image data.

Alteration mapping at Goldfield, Nevada, by cluster and discriminant analysis of LANDSAT digital data

NASA Technical Reports Server (NTRS)

Ballew, G.

1977-01-01

The ability of Landsat multispectral digital data to differentiate among 62 combinations of rock and alteration types at the Goldfield mining district of Western Nevada was investigated by using statistical techniques of cluster and discriminant analysis. Multivariate discriminant analysis was not effective in classifying each of the 62 groups, with classification results essentially the same whether data of four channels alone or combined with six ratios of channels were used. Bivariate plots of group means revealed a cluster of three groups including mill tailings, basalt and all other rock and alteration types. Automatic hierarchical clustering based on the fourth dimensional Mahalanobis distance between group means of 30 groups having five or more samples was performed. The results of the cluster analysis revealed hierarchies of mill tailings vs. natural materials, basalt vs. non-basalt, highly reflectant rocks vs. other rocks and exclusively unaltered rocks vs. predominantly altered rocks. The hierarchies were used to determine the order in which sets of multiple discriminant analyses were to be performed and the resulting discriminant functions were used to produce a map of geology and alteration which has an overall accuracy of 70 percent for discriminating exclusively altered rocks from predominantly altered rocks.

Quantification of the Water-Energy Nexus in Beijing City Based on Copula Analysis

NASA Astrophysics Data System (ADS)

Cai, J.; Cai, Y.

2017-12-01

Water resource and energy resource are intimately and highly interwoven, called ``water-energy nexus", which poses challenges for the sustainable management of water resource and energy resource. In this research, the Copula analysis method is first proposed to be applied in "water-energy nexus" field to clarify the internal relationship of water resource and energy resource, which is a favorable tool to explore the relevance among random variables. Beijing City, the capital of China, is chosen as a case study. The marginal distribution functions of water resource and energy resource are analyzed first. Then the Binary Copula function is employed to construct the joint distribution function of "water-energy nexus" to quantify the inherent relationship between water resource and energy resource. The results show that it is more appropriate to apply Lognormal distribution to establish the marginal distribution function of water resource. Meanwhile, Weibull distribution is more feasible to describe the marginal distribution function of energy resource. Furthermore, it is more suitable to adopt the Bivariate Normal Copula function to construct the joint distribution function of "water-energy nexus" in Beijing City. The findings can help to identify and quantify the "water-energy nexus". In addition, our findings can provide reasonable policy recommendations on the sustainable management of water resource and energy resource to promote regional coordinated development.

Risk factors identified associated with tuberculosis in cattle at 11 livestock experiment stations of Punjab Pakistan.

PubMed

Javed, M Tariq; Irfan, M; Ali, Imtiaz; Farooqi, Farooq A; Wasiq, M; Cagiola, Monica

2011-02-01

The study was carried out in cattle kept at 11 livestock experiment stations of Punjab by using single comparative cervical intradermal tuberculin (SCCIT) test. Sahiwal was the main breed kept at these farms. Sixty three percent of animals were between four and 10 years of age. Seventy-six percent of animals weighed between 300 and 400 kg and 66% produced 5-10l of milk/day. Animals other than cattle were present at about 64% of these farms. The positive SCCIT test was recorded in 7.6% of animals at the 11 farms. However, the prevalence of tuberculosis varied from 2.0% to 19.3% at these farms. Bivariate frequency analysis showed that the chances of a positive SCCIT test were higher in older animals, in cattle with higher number of calving and those produced up to 1800l of milk. However, the chances of positive SCCIT test decreases with further increase in milk production. Results of bivariate and/or multivariate logistic regression analysis after controlling for the farm showed a significant association of age of cattle, numbers of calving, total milk produced, per day milk, lactation length, presence of sheep at the farm and total numbers of animals at the farm with a positive SCCIT test. It can be concluded from the study that herd prevalence of tuberculosis was 100%, while animal prevalence was about 8% at these farms. The stronger risk factors identified by logistic analysis were the age of cattle, numbers of calving, total milk produced and lactation length, while the presence of sheep at the farm has protective effect. 2010 Elsevier B.V. All rights reserved.

[Long-term HRV analysis shows stress reduction by magnesium intake].

PubMed

Wienecke, Elmar; Nolden, Claudia

2016-12-01

Mental pressure and stress represent an ever-increasing socio-political challenge. The heart rate variability (HRV) measurement, which has its origin in the cardiac function diagnosis, gives information on the neurovegetative activity. A low HRV shows an imbalance of the sympathetic and parasympathetic efferents and thus is an indicator of stress. A randomized, controlled, two-armed parallel study with 100 participants and a period of 90 days was performed. Main object of investigation was to what extent the mineral magnesium, which is also a high-quality natural calcium antagonist in cardiology, can influence the sympathovagal balance, when given in combination with a strength-endurance training. The effect on intracellular magnesium concentration was investigated as an additional parameter. In the group with daily supplementation of 400 mg of magnesium, HRV parameters clearly increased: pNN50 - an indicator of parasympathetic activity - increased. LF-HF ratio as well as stress index - low values for each represent a good balance of the vegetative nervous system - decreased. In the control group no positive changes in HRV parameters could be shown. Vagus activity, and thus the adaptive and regenerative capacity of the body, veritably increased by magnesium supplementation. No effect on the intracellular magnesium concentration could be shown in the study. The results of this study point out that persons with mental and physical stress can benefit from a daily intake of magnesium. This might lead to an improved physiological regulation of the sympathetic and parasympathetic efferents and, furthermore, prevent magnesium deficiency and diseases such as, for example, restlessness, irritability, lack of concentration, sleep disorder or depression.

A general framework for the use of logistic regression models in meta-analysis.

PubMed

Simmonds, Mark C; Higgins, Julian Pt

2016-12-01

Where individual participant data are available for every randomised trial in a meta-analysis of dichotomous event outcomes, "one-stage" random-effects logistic regression models have been proposed as a way to analyse these data. Such models can also be used even when individual participant data are not available and we have only summary contingency table data. One benefit of this one-stage regression model over conventional meta-analysis methods is that it maximises the correct binomial likelihood for the data and so does not require the common assumption that effect estimates are normally distributed. A second benefit of using this model is that it may be applied, with only minor modification, in a range of meta-analytic scenarios, including meta-regression, network meta-analyses and meta-analyses of diagnostic test accuracy. This single model can potentially replace the variety of often complex methods used in these areas. This paper considers, with a range of meta-analysis examples, how random-effects logistic regression models may be used in a number of different types of meta-analyses. This one-stage approach is compared with widely used meta-analysis methods including Bayesian network meta-analysis and the bivariate and hierarchical summary receiver operating characteristic (ROC) models for meta-analyses of diagnostic test accuracy. © The Author(s) 2014.

Analysis of the impact of crude oil price fluctuations on China's stock market in different periods-Based on time series network model

NASA Astrophysics Data System (ADS)

An, Yang; Sun, Mei; Gao, Cuixia; Han, Dun; Li, Xiuming

2018-02-01

This paper studies the influence of Brent oil price fluctuations on the stock prices of China's two distinct blocks, namely, the petrochemical block and the electric equipment and new energy block, applying the Shannon entropy of information theory. The co-movement trend of crude oil price and stock prices is divided into different fluctuation patterns with the coarse-graining method. Then, the bivariate time series network model is established for the two blocks stock in five different periods. By joint analysis of the network-oriented metrics, the key modes and underlying evolutionary mechanisms were identified. The results show that the both networks have different fluctuation characteristics in different periods. Their co-movement patterns are clustered in some key modes and conversion intermediaries. The study not only reveals the lag effect of crude oil price fluctuations on the stock in Chinese industry blocks but also verifies the necessity of research on special periods, and suggests that the government should use different energy policies to stabilize market volatility in different periods. A new way is provided to study the unidirectional influence between multiple variables or complex time series.

Correlation between quantitative traits and correlation between corresponding LOD scores: detection of pleiotropic effects.

PubMed

Ulgen, Ayse; Han, Zhihua; Li, Wentian

2003-12-31

We address the question of whether statistical correlations among quantitative traits lead to correlation of linkage results of these traits. Five measured quantitative traits (total cholesterol, fasting glucose, HDL cholesterol, blood pressure, and triglycerides), and one derived quantitative trait (total cholesterol divided by the HDL cholesterol) are used for phenotype correlation studies. Four of them are used for linkage analysis. We show that although correlation among phenotypes partially reflects the correlation among linkage analysis results, the LOD-score correlations are on average low. The most significant peaks found by using different traits do not often overlap. Studying covariances at specific locations in LOD scores may provide clues for further bivariate linkage analyses.

Complex time series analysis of PM10 and PM2.5 for a coastal site using artificial neural network modelling and k-means clustering

NASA Astrophysics Data System (ADS)

Elangasinghe, M. A.; Singhal, N.; Dirks, K. N.; Salmond, J. A.; Samarasinghe, S.

2014-09-01

This paper uses artificial neural networks (ANN), combined with k-means clustering, to understand the complex time series of PM10 and PM2.5 concentrations at a coastal location of New Zealand based on data from a single site. Out of available meteorological parameters from the network (wind speed, wind direction, solar radiation, temperature, relative humidity), key factors governing the pattern of the time series concentrations were identified through input sensitivity analysis performed on the trained neural network model. The transport pathways of particulate matter under these key meteorological parameters were further analysed through bivariate concentration polar plots and k-means clustering techniques. The analysis shows that the external sources such as marine aerosols and local sources such as traffic and biomass burning contribute equally to the particulate matter concentrations at the study site. These results are in agreement with the results of receptor modelling by the Auckland Council based on Positive Matrix Factorization (PMF). Our findings also show that contrasting concentration-wind speed relationships exist between marine aerosols and local traffic sources resulting in very noisy and seemingly large random PM10 concentrations. The inclusion of cluster rankings as an input parameter to the ANN model showed a statistically significant (p < 0.005) improvement in the performance of the ANN time series model and also showed better performance in picking up high concentrations. For the presented case study, the correlation coefficient between observed and predicted concentrations improved from 0.77 to 0.79 for PM2.5 and from 0.63 to 0.69 for PM10 and reduced the root mean squared error (RMSE) from 5.00 to 4.74 for PM2.5 and from 6.77 to 6.34 for PM10. The techniques presented here enable the user to obtain an understanding of potential sources and their transport characteristics prior to the implementation of costly chemical analysis techniques or

A multivariate model exploring the predictive value of demographic, adolescent, and family factors on glycemic control in adolescents with type 1 diabetes.

PubMed

Agarwal, Shivani; Jawad, Abbas F; Miller, Victoria A

2016-11-01

The current study examined how a comprehensive set of variables from multiple domains, including at the adolescent and family level, were predictive of glycemic control in adolescents with type 1 diabetes (T1D). Participants included 100 adolescents with T1D ages 10-16 yrs and their parents. Participants were enrolled in a longitudinal study about youth decision-making involvement in chronic illness management of which the baseline data were available for analysis. Bivariate associations with glycemic control (HbA1C) were tested. Hierarchical linear regression was implemented to inform the predictive model. In bivariate analyses, race, family structure, household income, insulin regimen, adolescent-reported adherence to diabetes self-management, cognitive development, adolescent responsibility for T1D management, and parent behavior during the illness management discussion were associated with HbA1c. In the multivariate model, the only significant predictors of HbA1c were race and insulin regimen, accounting for 17% of the variance. Caucasians had better glycemic control than other racial groups. Participants using pre-mixed insulin therapy and basal-bolus insulin had worse glycemic control than those on insulin pumps. This study shows that despite associations of adolescent and family-level variables with glycemic control at the bivariate level, only race and insulin regimen are predictive of glycemic control in hierarchical multivariate analyses. This model offers an alternative way to examine the relationship of demographic and psychosocial factors on glycemic control in adolescents with T1D. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Eat, sleep, work, play: associations of weight status and health-related behaviors among young adult college students.

PubMed

Quick, Virginia; Byrd-Bredbenner, Carol; White, Adrienne A; Brown, Onikia; Colby, Sarah; Shoff, Suzanne; Lohse, Barbara; Horacek, Tanya; Kidd, Tanda; Greene, Geoffrey

2014-01-01

To examine relationships of sleep, eating, and exercise behaviors; work time pressures; and sociodemographic characteristics by weight status (healthy weight [body mass index or BMI < 25] vs. overweight [BMI ≥ 25]) of young adults. Cross-sectional. Nine U.S. universities. Enrolled college students (N = 1252; 18-24 years; 80% white; 59% female). Survey included the Pittsburgh Sleep Quality Index (PSQI), Three-Factor Eating Questionnaire (TFEQ), Satter Eating Competence Inventory (ecSI), National Cancer Institute Fruit/Vegetable Screener, International Physical Activity Questionnaire, Work Time Pressure items, and sociodemographic characteristics. Chi-square and t-tests determined significant bivariate associations of sociodemographics, sleep behaviors, eating behaviors, physical activity behavior, and work time pressures with weight status (i.e., healthy vs. overweight/obese). Statistically significant bivariate associations with weight status were then entered into a multivariate logistic regression model that estimated associations with being overweight/obese. Sex (female), race (nonwhite), older age, higher Global PSQI score, lower ecSI total score, and higher TFEQ Emotional Eating Scale score were significantly (p < .05) associated with overweight/obesity in bivariate analyses. Multivariate logistic regression analysis showed that sex (female; odds ratio [OR] = 2.05, confidence interval [CI] = 1.54-2.74), older age (OR = 1.35, CI = 1.21-1.50), higher Global PSQI score (OR = 1.07, CI = 1.01-1.13), and lower ecSI score (OR = .96, CI = .94-.98), were significantly (p < .05) associated with overweight/obesity. Findings suggest that obesity prevention interventions for college students should include an education component to emphasize the importance of overall sleep quality and improving eating competence.

The fading affect bias shows positive outcomes at the general but not the individual level of analysis in the context of social media.

PubMed

Gibbons, Jeffrey A; Horowitz, Kyle A; Dunlap, Spencer M

2017-08-01

Unpleasant affect fades faster than pleasant affect (e.g., Walker, Vogl, & Thompson, 1997); this effect is referred to as the Fading Affect Bias (FAB; Walker, Skowronski, Gibbons, Vogl, & Thompson, 2003a). Research shows that the FAB is consistently related to positive/healthy outcomes at a general but not at a specific level of analysis based on event types and individual differences (e.g., Gibbons et al., 2013). Based on the positive outcomes for FAB and negative outcomes for social media (Bolton et al., 2013; Huang, 2010), the current study examined FAB in the context of social media events along with related individual differences. General positive outcomes were shown in the form of robust FAB effects across social media and non-social media events, a larger FAB for non-social media events than for social media events, negative correlations of FAB with depression, anxiety, and stress as well as a positive correlation of FAB with self-esteem. However, the lack of a negative correlation between FAB and anxiety for social media events in a 3-way interaction did not show positive outcomes at a specific level of analysis. Rehearsal ratings mediated the 3-way interaction. Implications are discussed. Copyright © 2017 Elsevier Inc. All rights reserved.

Pedagogical Techniques Employed by the Television Show "MythBusters"

NASA Astrophysics Data System (ADS)

Zavrel, Erik

2016-11-01

"MythBusters," the long-running though recently discontinued Discovery Channel science entertainment television program, has proven itself to be far more than just a highly rated show. While its focus is on entertainment, the show employs an array of pedagogical techniques to communicate scientific concepts to its audience. These techniques include: achieving active learning, avoiding jargon, employing repetition to ensure comprehension, using captivating demonstrations, cultivating an enthusiastic disposition, and increasing intrinsic motivation to learn. In this content analysis, episodes from the show's 10-year history were examined for these techniques. "MythBusters" represents an untapped source of pedagogical techniques, which science educators may consider availing themselves of in their tireless effort to better reach their students. Physics educators in particular may look to "MythBusters" for inspiration and guidance in how to incorporate these techniques into their own teaching and help their students in the learning process.

Point pattern analysis applied to flood and landslide damage events in Switzerland (1972-2009)

NASA Astrophysics Data System (ADS)

Barbería, Laura; Schulte, Lothar; Carvalho, Filipe; Peña, Juan Carlos

2017-04-01

Damage caused by meteorological and hydrological extreme events depends on many factors, not only on hazard, but also on exposure and vulnerability. In order to reach a better understanding of the relation of these complex factors, their spatial pattern and underlying processes, the spatial dependency between values of damage recorded at sites of different distances can be investigated by point pattern analysis. For the Swiss flood and landslide damage database (1972-2009) first steps of point pattern analysis have been carried out. The most severe events have been selected (severe, very severe and catastrophic, according to GEES classification, a total number of 784 damage points) and Ripley's K-test and L-test have been performed, amongst others. For this purpose, R's library spatstat has been used. The results confirm that the damage points present a statistically significant clustered pattern, which could be connected to prevalence of damages near watercourses and also to rainfall distribution of each event, together with other factors. On the other hand, bivariate analysis shows there is no segregated pattern depending on process type: flood/debris flow vs landslide. This close relation points to a coupling between slope and fluvial processes, connectivity between small-size and middle-size catchments and the influence of spatial distribution of precipitation, temperature (snow melt and snow line) and other predisposing factors such as soil moisture, land-cover and environmental conditions. Therefore, further studies will investigate the relationship between the spatial pattern and one or more covariates, such as elevation, distance from watercourse or land use. The final goal will be to perform a regression model to the data, so that the adjusted model predicts the intensity of the point process as a function of the above mentioned covariates.

Central depression in nucleonic densities: Trend analysis in the nuclear density functional theory approach

NASA Astrophysics Data System (ADS)

Schuetrumpf, B.; Nazarewicz, W.; Reinhard, P.-G.

2017-08-01

Background: The central depression of nucleonic density, i.e., a reduction of density in the nuclear interior, has been attributed to many factors. For instance, bubble structures in superheavy nuclei are believed to be due to the electrostatic repulsion. In light nuclei, the mechanism behind the density reduction in the interior has been discussed in terms of shell effects associated with occupations of s orbits. Purpose: The main objective of this work is to reveal mechanisms behind the formation of central depression in nucleonic densities in light and heavy nuclei. To this end, we introduce several measures of the internal nucleonic density. Through the statistical analysis, we study the information content of these measures with respect to nuclear matter properties. Method: We apply nuclear density functional theory with Skyrme functionals. Using the statistical tools of linear least square regression, we inspect correlations between various measures of central depression and model parameters, including nuclear matter properties. We study bivariate correlations with selected quantities as well as multiple correlations with groups of parameters. Detailed correlation analysis is carried out for 34Si for which a bubble structure has been reported recently, 48Ca, and N =82 , 126, and 184 isotonic chains. Results: We show that the central depression in medium-mass nuclei is very sensitive to shell effects, whereas for superheavy systems it is firmly driven by the electrostatic repulsion. An appreciable semibubble structure in proton density is predicted for 294Og, which is currently the heaviest nucleus known experimentally. Conclusion: Our correlation analysis reveals that the central density indicators in nuclei below 208Pb carry little information on parameters of nuclear matter; they are predominantly driven by shell structure. On the other hand, in the superheavy nuclei there exists a clear relationship between the central nucleonic density and symmetry energy.

Parametric analysis for matched pair survival data.

PubMed

Manatunga, A K; Oakes, D

1999-12-01

Hougaard's (1986) bivariate Weibull distribution with positive stable frailties is applied to matched pairs survival data when either or both components of the pair may be censored and covariate vectors may be of arbitrary fixed length. When there is no censoring, we quantify the corresponding gain in Fisher information over a fixed-effects analysis. With the appropriate parameterization, the results take a simple algebraic form. An alternative marginal ("independence working model") approach to estimation is also considered. This method ignores the correlation between the two survival times in the derivation of the estimator, but provides a valid estimate of standard error. It is shown that when both the correlation between the two survival times is high, and the ratio of the within-pair variability to the between-pair variability of the covariates is high, the fixed-effects analysis captures most of the information about the regression coefficient but the independence working model does badly. When the correlation is low, and/or most of the variability of the covariates occurs between pairs, the reverse is true. The random effects model is applied to data on skin grafts, and on loss of visual acuity among diabetics. In conclusion some extensions of the methods are indicated and they are placed in a wider context of Generalized Estimation Equation methodology.

PAX1 Methylation Hallmarks Promising Accuracy for Cervical Cancer Screening in Asians: Results from a Meta-Analysis.

PubMed

Kong, Ling-Ying; Du, Wei; Wang, Li; Yang, Zhi; Zhang, Hong-Sheng

2015-01-01

DNA methylation has been proposed as a potential biomarker for cervical cancer detection. This study aimed to evaluate the diagnostic role of paired boxed gene 1 (PAX1) methylation for cervical cancer screening in Asians. Eligible studies were retrieved by searching the electronic databases, and the quality of the enrolled studies was assessed via the quality assessment for studies of diagnostic accuracy (QUADAS) tool. The bivariate meta-analysis model was employed to generate the summary receiver operator characteristic (SROC) curve using Stata 12.0 software. Cochran's Q test and I2 statistics were applied to assess heterogeneity among studies. Publication bias was evaluated by the Deeks' funnel plot asymmetry test. A total of 9 articles containing 15 individual studies were included. The SROC analysis showed that single PAX1 methylation allowed for the discrimination between cancer/high-grade squamous intraepithelial lesion (HSIL) patients and normal individuals with a sensitivity (95% confidence interval) of 0.80 (0.70 - 0.87) and specificity of 0.89 (0.86 - 0.92), corresponding to an area under curve (AUC) of 0.92. Notably, our subgroup analysis suggested that combing parallel testing of PAX1 methylation and HPV DNA (AUC, sensitivity, and specificity of 0.90, 0.82, and 0.84, respectively) seemed to harbor higher accuracy than single HPV DNA testing (AUC, sensitivity, and specificity of 0.81, 0.86, and 0.67, respectively). PAX1 methylation hallmarks a potential diagnostic value for cervical cancer screening in Asians, and parallel testing of PAX1 methylation and HPV in cervical scrapings confers an improved accuracy than single HPV DNA testing.

Genome-Wide Gene Expression Analysis Shows AKAP13-Mediated PKD1 Signaling Regulates the Transcriptional Response to Cardiac Hypertrophy.

PubMed

Johnson, Keven R; Nicodemus-Johnson, Jessie; Spindler, Mathew J; Carnegie, Graeme K

2015-01-01

In the heart, scaffolding proteins such as A-Kinase Anchoring Proteins (AKAPs) play a crucial role in normal cellular function by serving as a signaling hub for multiple protein kinases including protein kinase D1 (PKD1). Under cardiac hypertrophic conditions AKAP13 anchored PKD1 activates the transcription factor MEF2 leading to subsequent fetal gene activation and hypertrophic response. We used an expression microarray to identify the global transcriptional response in the hearts of wild-type mice expressing the native form of AKAP13 compared to a gene-trap mouse model expressing a truncated form of AKAP13 that is unable to bind PKD1 (AKAP13-ΔPKD1). Microarray analysis showed that AKAP13-ΔPKD1 mice broadly failed to exhibit the transcriptional profile normally associated with compensatory cardiac hypertrophy following trans-aortic constriction (TAC). The identified differentially expressed genes in WT and AKAP13-ΔPKD1 hearts are vital for the compensatory hypertrophic response to pressure-overload and include myofilament, apoptotic, and cell growth/differentiation genes in addition to genes not previously identified as affected by AKAP13-anchored PKD1. Our results show that AKAP13-PKD1 signaling is critical for transcriptional regulation of key contractile, cell death, and metabolic pathways during the development of compensatory hypertrophy in vivo.

Genome-Wide Gene Expression Analysis Shows AKAP13-Mediated PKD1 Signaling Regulates the Transcriptional Response to Cardiac Hypertrophy

PubMed Central

Johnson, Keven R.; Nicodemus-Johnson, Jessie; Spindler, Mathew J.

2015-01-01

In the heart, scaffolding proteins such as A-Kinase Anchoring Proteins (AKAPs) play a crucial role in normal cellular function by serving as a signaling hub for multiple protein kinases including protein kinase D1 (PKD1). Under cardiac hypertrophic conditions AKAP13 anchored PKD1 activates the transcription factor MEF2 leading to subsequent fetal gene activation and hypertrophic response. We used an expression microarray to identify the global transcriptional response in the hearts of wild-type mice expressing the native form of AKAP13 compared to a gene-trap mouse model expressing a truncated form of AKAP13 that is unable to bind PKD1 (AKAP13-ΔPKD1). Microarray analysis showed that AKAP13-ΔPKD1 mice broadly failed to exhibit the transcriptional profile normally associated with compensatory cardiac hypertrophy following trans-aortic constriction (TAC). The identified differentially expressed genes in WT and AKAP13-ΔPKD1 hearts are vital for the compensatory hypertrophic response to pressure-overload and include myofilament, apoptotic, and cell growth/differentiation genes in addition to genes not previously identified as affected by AKAP13-anchored PKD1. Our results show that AKAP13-PKD1 signaling is critical for transcriptional regulation of key contractile, cell death, and metabolic pathways during the development of compensatory hypertrophy in vivo. PMID:26192751

Characterization of small-to-medium head-and-face dimensions for developing respirator fit test panels and evaluating fit of filtering facepiece respirators with different faceseal design

PubMed Central

Lin, Yi-Chun

2017-01-01

A respirator fit test panel (RFTP) with facial size distribution representative of intended users is essential to the evaluation of respirator fit for new models of respirators. In this study an anthropometric survey was conducted among youths representing respirator users in mid-Taiwan to characterize head-and-face dimensions key to RFTPs for application to small-to-medium facial features. The participants were fit-tested for three N95 masks of different facepiece design and the results compared to facial size distribution specified in the RFTPs of bivariate and principal component analysis design developed in this study to realize the influence of facial characteristics to respirator fit in relation to facepiece design. Nineteen dimensions were measured for 206 participants. In fit testing the qualitative fit test (QLFT) procedures prescribed by the U.S. Occupational Safety and Health Administration were adopted. As the results show, the bizygomatic breadth of the male and female participants were 90.1 and 90.8% of their counterparts reported for the U.S. youths (P < 0.001), respectively. Compared to the bivariate distribution, the PCA design better accommodated variation in facial contours among different respirator user groups or populations, with the RFTPs reported in this study and from literature consistently covering over 92% of the participants. Overall, the facial fit of filtering facepieces increased with increasing facial dimensions. The total percentages of the tests wherein the final maneuver being completed was “Moving head up-and-down”, “Talking” or “Bending over” in bivariate and PCA RFTPs were 13.3–61.9% and 22.9–52.8%, respectively. The respirators with a three-panel flat fold structured in the facepiece provided greater fit, particularly when the users moved heads. When the facial size distribution in a bivariate RFTP did not sufficiently represent petite facial size, the fit testing was inclined to overestimate the general fit

Characterization of small-to-medium head-and-face dimensions for developing respirator fit test panels and evaluating fit of filtering facepiece respirators with different faceseal design.

PubMed

Lin, Yi-Chun; Chen, Chen-Peng

2017-01-01

A respirator fit test panel (RFTP) with facial size distribution representative of intended users is essential to the evaluation of respirator fit for new models of respirators. In this study an anthropometric survey was conducted among youths representing respirator users in mid-Taiwan to characterize head-and-face dimensions key to RFTPs for application to small-to-medium facial features. The participants were fit-tested for three N95 masks of different facepiece design and the results compared to facial size distribution specified in the RFTPs of bivariate and principal component analysis design developed in this study to realize the influence of facial characteristics to respirator fit in relation to facepiece design. Nineteen dimensions were measured for 206 participants. In fit testing the qualitative fit test (QLFT) procedures prescribed by the U.S. Occupational Safety and Health Administration were adopted. As the results show, the bizygomatic breadth of the male and female participants were 90.1 and 90.8% of their counterparts reported for the U.S. youths (P < 0.001), respectively. Compared to the bivariate distribution, the PCA design better accommodated variation in facial contours among different respirator user groups or populations, with the RFTPs reported in this study and from literature consistently covering over 92% of the participants. Overall, the facial fit of filtering facepieces increased with increasing facial dimensions. The total percentages of the tests wherein the final maneuver being completed was "Moving head up-and-down", "Talking" or "Bending over" in bivariate and PCA RFTPs were 13.3-61.9% and 22.9-52.8%, respectively. The respirators with a three-panel flat fold structured in the facepiece provided greater fit, particularly when the users moved heads. When the facial size distribution in a bivariate RFTP did not sufficiently represent petite facial size, the fit testing was inclined to overestimate the general fit, thus for small

Genetic and Environmental Basis in Phenotype Correlation Between Physical Function and Cognition in Aging Chinese Twins.

PubMed

Xu, Chunsheng; Zhang, Dongfeng; Tian, Xiaocao; Wu, Yili; Pang, Zengchang; Li, Shuxia; Tan, Qihua

2017-02-01

Although the correlation between cognition and physical function has been well studied in the general population, the genetic and environmental nature of the correlation has been rarely investigated. We conducted a classical twin analysis on cognitive and physical function, including forced expiratory volume in one second (FEV1), forced vital capacity (FVC), handgrip strength, five-times-sit-to-stand test (FTSST), near visual acuity, and number of teeth lost in 379 complete twin pairs. Bivariate twin models were fitted to estimate the genetic and environmental correlation between physical and cognitive function. Bivariate analysis showed mildly positively genetic correlations between cognition and FEV1, r G = 0.23 [95% CI: 0.03, 0.62], as well as FVC, r G = 0.35 [95% CI: 0.06, 1.00]. We found that FTSST and cognition presented very high common environmental correlation, r C = -1.00 [95% CI: -1.00, -0.57], and low but significant unique environmental correlation, r E = -0.11 [95% CI: -0.22, -0.01], all in the negative direction. Meanwhile, near visual acuity and cognition also showed unique environmental correlation, r E = 0.16 [95% CI: 0.03, 0.27]. We found no significantly genetic correlation for cognition with handgrip strength, FTSST, near visual acuity, and number of teeth lost. Cognitive function was genetically related to pulmonary function. The FTSST and cognition shared almost the same common environmental factors but only part of the unique environmental factors, both with negative correlation. In contrast, near visual acuity and cognition may positively share part of the unique environmental factors.

Genome-wide microarray analysis of tomato roots showed defined responses to iron deficiency

PubMed Central

2012-01-01

Background Plants react to iron deficiency stress adopting different kind of adaptive responses. Tomato, a Strategy I plant, improves iron uptake through acidification of rhizosphere, reduction of Fe3+ to Fe2+ and transport of Fe2+ into the cells. Large-scale transcriptional analyses of roots under iron deficiency are only available for a very limited number of plant species with particular emphasis for Arabidopsis thaliana. Regarding tomato, an interesting model species for Strategy I plants and an economically important crop, physiological responses to Fe-deficiency have been thoroughly described and molecular analyses have provided evidence for genes involved in iron uptake mechanisms and their regulation. However, no detailed transcriptome analysis has been described so far. Results A genome-wide transcriptional analysis, performed with a chip that allows to monitor the expression of more than 25,000 tomato transcripts, identified 97 differentially expressed transcripts by comparing roots of Fe-deficient and Fe-sufficient tomato plants. These transcripts are related to the physiological responses of tomato roots to the nutrient stress resulting in an improved iron uptake, including regulatory aspects, translocation, root morphological modification and adaptation in primary metabolic pathways, such as glycolysis and TCA cycle. Other genes play a role in flavonoid biosynthesis and hormonal metabolism. Conclusions The transcriptional characterization confirmed the presence of the previously described mechanisms to adapt to iron starvation in tomato, but also allowed to identify other genes potentially playing a role in this process, thus opening new research perspectives to improve the knowledge on the tomato root response to the nutrient deficiency. PMID:22433273

Comparative shotgun proteomic analysis of wild and domesticated Opuntia spp. species shows a metabolic adaptation through domestication.

PubMed

Pichereaux, Carole; Hernández-Domínguez, Eric E; Santos-Diaz, Maria Del Socorro; Reyes-Agüero, Antonio; Astello-García, Marizel; Guéraud, Françoise; Negre-Salvayre, Anne; Schiltz, Odile; Rossignol, Michel; Barba de la Rosa, Ana Paulina

2016-06-30

The Opuntia genus is widely distributed in America, but the highest richness of wild species are found in Mexico, as well as the most domesticated Opuntia ficus-indica, which is the most domesticated species and an important crop in agricultural economies of arid and semiarid areas worldwide. During domestication process, the Opuntia morphological characteristics were favored, such as less and smaller spines in cladodes and less seeds in fruits, but changes at molecular level are almost unknown. To obtain more insights about the Opuntia molecular changes through domestication, a shotgun proteomic analysis and database-dependent searches by homology was carried out. >1000 protein species were identified and by using a label-free quantitation method, the Opuntia proteomes were compared in order to identify differentially accumulated proteins among wild and domesticated species. Most of the changes were observed in glucose, secondary, and 1C metabolism, which correlate with the observed protein, fiber and phenolic compounds accumulation in Opuntia cladodes. Regulatory proteins, ribosomal proteins, and proteins related with response to stress were also observed in differential accumulation. These results provide new valuable data that will help to the understanding of the molecular changes of Opuntia species through domestication. Opuntia species are well adapted to dry and warm conditions in arid and semiarid regions worldwide, and they are highly productive plants showing considerable promises as an alternative food source. However, there is a gap regarding Opuntia molecular mechanisms that enable them to grow in extreme environmental conditions and how the domestication processes has changed them. In the present study, a shotgun analysis was carried out to characterize the proteomes of five Opuntia species selected by its domestication degree. Our results will help to a better understanding of proteomic features underlying the selection and specialization under

Factors Influencing the Likelihood of Overeducation: A Bivariate Probit with Sample Selection Framework

ERIC Educational Resources Information Center

Rubb, Stephen

2014-01-01

Contrary to expectations, the likelihood of overeducation is shown to be inversely related to unemployment rates when not control for selectivity. Furthermore, incidence data show that overeducation is more common among men than women and among Whites than Blacks. At issue is selectivity: employment must be selected for overeducation to occur.…

An analysis of spatial and socio-economic determinants of tuberculosis in Hermosillo, Mexico, 2000-2006.

PubMed

Alvarez-Hernández, G; Lara-Valencia, F; Reyes-Castro, P A; Rascón-Pacheco, R A

2010-06-01

The city of Hermosillo, in Northwest Mexico, has a higher incidence of tuberculosis (TB) than the national average. However, the intra-urban TB distribution, which could limit the effectiveness of preventive strategies and control, is unknown. Using geographic information systems (GIS) and spatial analysis, we characterized the geographical distribution of TB by basic geostatistical area (BGA), and compared it with a social deprivation index. Univariate and bivariate techniques were used to detect risk areas. Globally, TB in the city of Hermosillo is not spatially auto-correlated, but local clusters with high incidence and mortality rates were identified in the northwest, central-east and southwest sections of the city. BGAs with high social deprivation had an excess risk of TB. GIS and spatial analysis are useful tools to detect high TB risk areas in the city of Hermosillo. Such areas may be vulnerable due to low socio-economic status. The study of small geographical areas in urban settings similar to Hermosillo could indicate the best course of action to be taken for TB prevention and control.

Maternal nutritional knowledge and child nutritional status in the Volta region of Ghana.

PubMed

Appoh, Lily Yaa; Krekling, Sturla

2005-04-01

The relationship between mother's nutritional knowledge, maternal education, and child nutritional status (weight-for-age) was the subject of investigation in this study. The data were collected in Ghana on 55 well nourished and 55 malnourished mother-child pairs. A questionnaire designed to collect data on mother's knowledge and practices related to child care and nutrition was administered to the mothers. Data on mother's demographic and socio-economic characteristics as well as child anthropometric data were also collected. A nutrition knowledge score was calculated based on mother's responses to the nutrition related items. Bivariate analysis gave significant associations between child nutritional status and the following variables: time of initiating of breastfeeding, mother's knowledge of importance of colostrum and whether colostrum was given to child, age of introduction of supplementary food, and mother's knowledge about causes of kwashiorkor. The two groups also showed significant differences in their nutrition knowledge scores. Maternal formal education, and marital status were also found to be associated with child nutritional status in bivariate analyses. Further analysis with logistic regression revealed that maternal nutrition knowledge was independently associated with nutritional status after the effects of other significant variables were controlled for. Maternal education on the other hand was not found to be independently associated with nutritional status. These results imply that mother's practical knowledge about nutrition may be more important than formal maternal education for child nutrition outcome.

"The Show"

ERIC Educational Resources Information Center

Gehring, John

2004-01-01

For the past 16 years, the blue-collar city of Huntington, West Virginia, has rolled out the red carpet to welcome young wrestlers and their families as old friends. They have come to town chasing the same dream for a spot in what many of them call "The Show". For three days, under the lights of an arena packed with 5,000 fans, the…

Comprehensive Morpho-Electrotonic Analysis Shows 2 Distinct Classes of L2 and L3 Pyramidal Neurons in Human Temporal Cortex

PubMed Central

Deitcher, Yair; Eyal, Guy; Kanari, Lida; Verhoog, Matthijs B; Atenekeng Kahou, Guy Antoine; Mansvelder, Huibert D; de Kock, Christiaan P J; Segev, Idan

2017-01-01

Abstract There have been few quantitative characterizations of the morphological, biophysical, and cable properties of neurons in the human neocortex. We employed feature-based statistical methods on a rare data set of 60 3D reconstructed pyramidal neurons from L2 and L3 in the human temporal cortex (HL2/L3 PCs) removed after brain surgery. Of these cells, 25 neurons were also characterized physiologically. Thirty-two morphological features were analyzed (e.g., dendritic surface area, 36 333 ± 18 157 μm2; number of basal trees, 5.55 ± 1.47; dendritic diameter, 0.76 ± 0.28 μm). Eighteen features showed a significant gradual increase with depth from the pia (e.g., dendritic length and soma radius). The other features showed weak or no correlation with depth (e.g., dendritic diameter). The basal dendritic terminals in HL2/L3 PCs are particularly elongated, enabling multiple nonlinear processing units in these dendrites. Unlike the morphological features, the active biophysical features (e.g., spike shapes and rates) and passive/cable features (e.g., somatic input resistance, 47.68 ± 15.26 MΩ, membrane time constant, 12.03 ± 1.79 ms, average dendritic cable length, 0.99 ± 0.24) were depth-independent. A novel descriptor for apical dendritic topology yielded 2 distinct classes, termed hereby as “slim-tufted” and “profuse-tufted” HL2/L3 PCs; the latter class tends to fire at higher rates. Thus, our morpho-electrotonic analysis shows 2 distinct classes of HL2/L3 PCs. PMID:28968789

Access to Care and Satisfaction Among Health Center Patients With Chronic Conditions.

PubMed

Shi, Leiyu; Lee, De-Chih; Haile, Geraldine Pierre; Liang, Hailun; Chung, Michelle; Sripipatana, Alek

This study examined access to care and satisfaction among health center patients with chronic conditions. Data for this study were obtained from the 2009 Health Center Patient Survey. Dependent variables of interest included 5 measures of access to and satisfaction with care, whereas the main independent variable was number of chronic conditions. Results of bivariate analysis and multiple logistic regressions showed that patients with chronic conditions had significantly higher odds of reporting access barriers than those without chronic conditions. Our results suggested that additional efforts and resources are necessary to address the needs of health center patients with chronic conditions.

Probabilistic modelling of drought events in China via 2-dimensional joint copula

NASA Astrophysics Data System (ADS)

Ayantobo, Olusola O.; Li, Yi; Song, Songbai; Javed, Tehseen; Yao, Ning

2018-04-01

Probabilistic modelling of drought events is a significant aspect of water resources management and planning. In this study, popularly applied and several relatively new bivariate Archimedean copulas were employed to derive regional and spatial based copula models to appraise drought risk in mainland China over 1961-2013. Drought duration (Dd), severity (Ds), and peak (Dp), as indicated by Standardized Precipitation Evapotranspiration Index (SPEI), were extracted according to the run theory and fitted with suitable marginal distributions. The maximum likelihood estimation (MLE) and curve fitting method (CFM) were used to estimate the copula parameters of nineteen bivariate Archimedean copulas. Drought probabilities and return periods were analysed based on appropriate bivariate copula in sub-region I-VII and entire mainland China. The goodness-of-fit tests as indicated by the CFM showed that copula NN19 in sub-regions III, IV, V, VI and mainland China, NN20 in sub-region I and NN13 in sub-region VII are the best for modeling drought variables. Bivariate drought probability across mainland China is relatively high, and the highest drought probabilities are found mainly in the Northwestern and Southwestern China. Besides, the result also showed that different sub-regions might suffer varying drought risks. The drought risks as observed in Sub-region III, VI and VII, are significantly greater than other sub-regions. Higher probability of droughts of longer durations in the sub-regions also corresponds to shorter return periods with greater drought severity. These results may imply tremendous challenges for the water resources management in different sub-regions, particularly the Northwestern and Southwestern China.

Local fluctuations of the signed traded volumes and the dependencies of demands: a copula analysis

NASA Astrophysics Data System (ADS)

Wang, Shanshan; Guhr, Thomas

2018-03-01

We investigate how the local fluctuations of the signed traded volumes affect the dependence of demands between stocks. We analyze the empirical dependence of demands using copulas and show that they are well described by a bivariate K copula density function. We find that large local fluctuations strongly increase the positive dependence but lower slightly the negative one in the copula density. This interesting feature is due to cross-correlations of volume imbalances between stocks. Also, we explore the asymmetries of tail dependencies of the copula density, which are moderate for the negative dependencies but strong for the positive ones. For the latter, we reveal that large local fluctuations of the signed traded volumes trigger stronger dependencies of demands than of supplies, probably indicating a bull market with persistent raising of prices.

Critical determinants of the epilepsy treatment gap: a cross-national analysis in resource-limited settings

PubMed Central

Meyer, Ana-Claire L.; Dua, Tarun; Boscardin, John; Escarce, José J.; Saxena, Shekhar; Birbeck, Gretchen L.

2013-01-01

Purpose Epilepsy is one of the most common serious neurological disorders worldwide. Our objective was to determine which economic, healthcare, neurology and epilepsy specific resources were associated with untreated epilepsy in resource-constrained settings. Methods A systematic review of the literature identified community-based studies in resource-constrained settings that calculated the epilepsy treatment gap, the proportion with untreated epilepsy, from prevalent active epilepsy cases. Economic, healthcare, neurology and epilepsy specific resources were taken from existing datasets. Poisson regression models with jackknifed standard errors were used to create bivariate and multivariate models comparing the association between treatment status and economic and health resource indicators. Relative risks were reported. Key Findings Forty-seven studies of 8285 individuals from 24 countries met inclusion criteria. Bivariate analysis demonstrated that individuals residing in rural locations had significantly higher risks of untreated epilepsy [Relative Risk(RR)=1.63; 95% confidence interval(CI):1.26,2.11]. Significantly lower risks of untreated epilepsy were observed for higher physician density [RR=0.65, 95% CI:0.55,0.78], presence of a lay [RR=0.74, 95%CI:0.60,0.91] or professional association for epilepsy [RR=0.73, 95%CI:0.59,0.91], or post-graduate neurology training program [RR=0.67, 95%CI:0.55, 0.82]. In multivariate models, higher physician density maintained significant effects [RR=0.67; 95%CI:0.52,0.88]. Significance Even among resource-limited regions, people with epilepsy in countries with fewer economic, healthcare, neurology and epilepsy specific resources are more likely to have untreated epilepsy. Community-based epilepsy care programs have improved access to treatment but in order to decrease the epilepsy treatment gap, poverty and inequalities of healthcare, neurological and epilepsy resources must be dealt with at the local, national, and global

Physics Reality Show

NASA Astrophysics Data System (ADS)

Erukhimova, Tatiana

The attention span of K-12 students is very short; they are used to digesting information in short snippets through social media and TV. To get the students interested in physics, we created the Physics Reality Show: a series of staged short videos with duration no longer than a few minutes. Each video explains and illustrates one physics concept or law through a fast-paced sequence of physics demonstrations and experiments. The cast consists entirely of physics undergraduate students with artistic abilities and substantial experience in showing physics demonstrations at current outreach events run by the department: Physics Shows and Physics & Engineering Festival. Undergraduate students are of almost the same age as their high-school audience. They are in the best position to connect with kids and convey their fascination with physics. The PI and other faculty members who are involved in the outreach advise and coach the cast. They help students in staging the episodes and choosing the most exciting and relevant demonstrations. Supported by the APS mini-outreach Grant.

[Frequency of healthy eating habits measured by the 10 Steps to Healthy Eating score proposed by the Ministry of Health: Pelotas, Rio Grande do Sul State, Brazil].

PubMed

Vinholes, Daniele Botelho; Assunção, Maria Cecília Formoso; Neutzling, Marilda Borges

2009-04-01

This study aimed to measure frequency of healthy eating habits and associated factors using the 10 Steps to Healthy Eating score proposed by the Ministry of Health in the adult population in Pelotas, Rio Grande do Sul State, Brazil. A cross-sectional population-based survey was conducted on a cluster sample of 3,136 adult residents in Pelotas. The frequency of each step to healthy eating was collected with a pre-coded questionnaire. Data analysis consisted of descriptive analysis, followed by bivariate analysis using the chi-square test. Only 1.1% of the population followed all the recommended steps. The average number of steps was six. Step four, salt intake, showed the highest frequency, while step nine, physical activity, showed the lowest. Knowledge of the population's eating habits and their distribution according to demographic and socioeconomic variables is important to guide local and national strategies to promote healthy eating habits and thus improve quality of life.

Oral hygiene status in relation to sociodemographic factors of children and adults who are hearing impaired, attending a special school.

PubMed

Kumar, Santhosh; Dagli, Rushabh Jayesh; Mathur, Anmol; Jain, Manish; Duraiswamy, Prabu; Kulkarni, Suhas

2008-01-01

This study examined the oral hygiene levels and periodontal status in a group of children and adults with hearing impairment attending a special school in Udaipur, India. Oral hygiene status was assessed by the Simplified Oral Hygiene Index (OHI-S) of Greene and Vermillion and periodontal status by the Community Periodontal Index. An analysis using a bivariate analysis revealed that all the oral hygiene variables varied significantly with age, economic status, and education of the parents. A multiple regression analysis showed that the education of the mother was the single best predictor for oral hygiene status and explained 92% of the variance. These findings show that children with hearing impairment have poor oral hygiene and high levels of periodontal disease. This may be due to a lack of communication; hence, appropriate oral health education should be tailored to the needs of these students with the support of their teachers and their parents.

New MYC IHC Classifier Integrating Quantitative Architecture Parameters to Predict MYC Gene Translocation in Diffuse Large B-Cell Lymphoma

PubMed Central

Dong, Wei-Feng; Canil, Sarah; Lai, Raymond; Morel, Didier; Swanson, Paul E.; Izevbaye, Iyare

2018-01-01

A new automated MYC IHC classifier based on bivariate logistic regression is presented. The predictor relies on image analysis developed with the open-source ImageJ platform. From a histologic section immunostained for MYC protein, 2 dimensionless quantitative variables are extracted: (a) relative distance between nuclei positive for MYC IHC based on euclidean minimum spanning tree graph and (b) coefficient of variation of the MYC IHC stain intensity among MYC IHC-positive nuclei. Distance between positive nuclei is suggested to inversely correlate MYC gene rearrangement status, whereas coefficient of variation is suggested to inversely correlate physiological regulation of MYC protein expression. The bivariate classifier was compared with 2 other MYC IHC classifiers (based on percentage of MYC IHC positive nuclei), all tested on 113 lymphomas including mostly diffuse large B-cell lymphomas with known MYC fluorescent in situ hybridization (FISH) status. The bivariate classifier strongly outperformed the “percentage of MYC IHC-positive nuclei” methods to predict MYC+ FISH status with 100% sensitivity (95% confidence interval, 94-100) associated with 80% specificity. The test is rapidly performed and might at a minimum provide primary IHC screening for MYC gene rearrangement status in diffuse large B-cell lymphomas. Furthermore, as this bivariate classifier actually predicts “permanent overexpressed MYC protein status,” it might identify nontranslocation-related chromosomal anomalies missed by FISH. PMID:27093450

Analysis of suicide mortality in Brazil: spatial distribution and socioeconomic context.

PubMed

Dantas, Ana P; Azevedo, Ulicélia N de; Nunes, Aryelly D; Amador, Ana E; Marques, Marilane V; Barbosa, Isabelle R

2018-01-01

To perform a spatial analysis of suicide mortality and its correlation with socioeconomic indicators in Brazilian municipalities. This is an ecological study with Brazilian municipalities as a unit of analysis. Data on deaths from suicide and contextual variables were analyzed. The spatial distribution, intensity and significance of the clusters were analyzed with the global Moran index, MoranMap and local indicators of spatial association (LISA), seeking to identify patterns through geostatistical analysis. A total of 50,664 deaths from suicide were registered in Brazil between 2010 and 2014. The average suicide mortality rate in Brazil was 5.23/100,000 population. The Brazilian municipalities presenting the highest rates were Taipas do Tocantins, state of Tocantins (79.68 deaths per 100,000 population), Itaporã, state of Mato Grosso do Sul (75.15 deaths per 100,000 population), Mampituba, state of Rio Grande do Sul (52.98 deaths per 100,000 population), Paranhos, state of Mato Grosso do Sul (52.41 deaths per 100,000 population), and Monjolos, state of Minas Gerais (52.08 deaths per 100,000 population). Although weak spatial autocorrelation was observed for suicide mortality (I = 0.2608), there was a formation of clusters in the South. In the bivariate spatial and classical analysis, no correlation was observed between suicide mortality and contextual variables. Suicide mortality in Brazil presents a weak spatial correlation and low or no spatial relationship with socioeconomic factors.

Phylogenetic analysis shows the general diversification pattern of deep-sea notacanthiforms (Teleostei: Elopomorpha).

PubMed

Barros-García, David; Froufe, Elsa; Bañón, Rafael; Carlos Arronte, Juan; de Carlos, Alejandro

2018-07-01

The Notacanthiformes is an ancient group of deep-sea ray-finned fishes comprising 27 species in two families; Halosauridae and Notacanthidae. Although many studies have tried to reconstruct the phylogenetic relationships among the major clades of Elopomorpha, little is known about the evolutionary history of notacanthiforms. Molecular and morphological data were used to test previous hypotheses regarding the phylogenetic relationships among notacanthiform taxa, and to unravel the origin and evolution of this group. The molecular analyses of notacanthids showed similar results to those previously obtained employing osteological data, which proposed the existence of the Lipogenyinae (Lipogenys) and Notacanthinae (Notacanthus + Polyacanthonotus) subfamilies. Nevertheless, when the external morphology data is considered Lipogenys is more related to Notacanthus than Polyacanthonotus. The analyses could not fully resolve the inner relationships of the halosaurids. The time-calibrated tree of the order Notacanthiformes shows a long process of diversification spanning from the upper Cretaceous, to 50 million years after the K-Pg extinction, with the gradual emergence of all the modern families and genera of the group. This is the first specific phylogeny of the order Notacanthiformes, combining different analyses and data in order to obtain a wider perspective of the evolution and diversification of this group of fishes. Copyright © 2018 Elsevier Inc. All rights reserved.

Neuraxial blockade for external cephalic version: Cost analysis

PubMed Central

Yamasato, Kelly; Kaneshiro, Bliss; Salcedo, Jennifer

2017-01-01

Aim Neuraxial blockade (epidural or spinal anesthesia/analgesia) with external cephalic version increases the external cephalic version success rate. Hospitals and insurers may affect access to neuraxial blockade for external cephalic version, but the costs to these institutions remain largely unstudied. The objective of this study was to perform a cost analysis of neuraxial blockade use during external cephalic version from hospital and insurance payer perspectives. Secondarily, we estimated the effect of neuraxial blockade on cesarean delivery rates. Methods A decision–analysis model was developed using costs and probabilities occurring prenatally through the delivery hospital admission. Model inputs were derived from the literature, national databases, and local supply costs. Univariate and bivariate sensitivity analyses and Monte Carlo simulations were performed to assess model robustness. Results Neuraxial blockade was cost saving to both hospitals ($30 per delivery) and insurers ($539 per delivery) using baseline estimates. From both perspectives, however, the model was sensitive to multiple variables. Monte Carlo simulation indicated neuraxial blockade to be more costly in approximately 50% of scenarios. The model demonstrated that routine use of neuraxial blockade during external cephalic version, compared to no neuraxial blockade, prevented 17 cesarean deliveries for every 100 external cephalic versions attempted. Conclusions Neuraxial blockade is associated with minimal hospital and insurer cost changes in the setting of external cephalic version, while reducing the cesarean delivery rate. PMID:25771920

Impact of physical activity and cardiovascular fitness on total homocysteine concentrations in European adolescents: The HELENA study.

PubMed

Benser, Jasmin; Valtueña, Jara; Ruiz, Jonatan R; Mielgo-Ayuso, Juan; Breidenassel, Christina; Vicente-Rodriguez, German; Ferrari, Marika; Widhalm, Kurt; Manios, Yannis; Sjöström, Michael; Molnar, Denes; Gómez-Martínez, Sonia; Kafatos, Antony; Palacios, Gonzalo; Moreno, Luis A; Castillo, Manuel J; Stehle, Peter; González-Gross, Marcela

2015-01-01

We examined the association of physical activity (PA), cardiovascular fitness (CVF) and fatness with total homocysteine (tHcy) concentrations in European adolescents. The present study comprised 713 European adolescents aged 14.8 ± 1.2 y (females 55.3%) from the multicenter HELENA cross-sectional study. PA was assessed through accelerometry, CVF by the 20-m shuttle run test, and body fat by skinfold thicknesses with the Slaughter equation. Plasma folate, cobalamin, and tHcy concentrations were measured. To examine the association of tHcy with PA, CVF, and fatness after controlling for a set of confounders including age, maturity, folate, cobalamin, creatinine, smoking, supplement use, and methylenetetrahydrofolate reductase 677 genotype (CC 47%, CT 43%, TT 10%), bivariate correlations followed by multiple regression models were performed. In the bivariate correlation analysis, tHcy concentrations were slightly negatively correlated (p<0.05) with CVF in females (measured both by stages: r=-0.118 and by VO2max: r=-0.102) and positively with body mass index (r=0.100). However, daily time spent with moderate and vigorous PA showed a weak positive association with tHcy in females (p<0.05). tHcy concentrations showed a tendency to decrease with increasing CVF and increase with increasing BMI in female European adolescents. However, tHcy concentrations were positively associated with moderate and vigorous PA in female European adolescents.

Spatial Heterodyne Observation of Water (SHOW) from a high altitude aircraft

NASA Astrophysics Data System (ADS)

Bourassa, A. E.; Langille, J.; Solheim, B.; Degenstein, D. A.; Letros, D.; Lloyd, N. D.; Loewen, P.

2017-12-01

The Spatial Heterodyne Observations of Water instrument (SHOW) is limb-sounding satellite prototype that is being developed in collaboration between the University of Saskatchewan, York University, the Canadian Space Agency and ABB. The SHOW instrument combines a field-widened SHS with an imaging system to observe limb-scattered sunlight in a vibrational band of water (1363 nm - 1366 nm). Currently, the instrument has been optimized for deployment on NASA's ER-2 aircraft. Flying at an altitude of 70, 000 ft the ER-2 configuration and SHOW viewing geometry provides high spatial resolution (< 500 m) limb-measurements of water vapor in the Upper troposphere and lower stratosphere region. During an observation campaign from July 15 - July 22, the SHOW instrument performed 10 hours of observations from the ER-2. This paper describes the SHOW measurement technique and presents the preliminary analysis and results from these flights. These observations are used to validate the SHOW measurement technique and demonstrate the sampling capabilities of the instrument.

Recalibrating the spirit level: An analysis of the interaction of income inequality and poverty and its effect on health.

PubMed

Rambotti, Simone

2015-08-01

The publication of The Spirit Level (Wilkinson and Pickett, 2009) marked a paramount moment in the analysis of health and inequality, quickly attracting a remarkable degree of attention, both positive and negative, both in academic and in public discourse. Following at least 20 years of research, the book proposes a simple and powerful argument: inequality per se, more specifically income inequality, is harmful to every aspect of social life. In order to confirm this idea, the authors present a series of bivariate, cross-sectional associations showing comparisons across countries and within the United States. Despite the methodological limitations of this approach, the authors advance causal claims concerning the detrimental effects of income inequality. They also rule out poverty as a plausible alternative explanation, without directly measuring it. Meanwhile, over the last decade stratification scholars have demonstrated the nonlinear effect of economic factors, especially income, on health. The results suggest that a relative approach is best for analyzing dynamics at the top of the income distribution, whereas an absolute approach seems most appropriate for studying the bottom of the distribution. Consistent with this perspective, here I reanalyze data from The Spirit Level, adding a measure of poverty, in order to control the effect of inequality and explore its interaction with poverty. The findings show that inequality and poverty-which I contend are two interdependent but nonetheless distinct phenomena-interact across countries, such that the detrimental effects of inequality are present or stronger in countries with high poverty, and absent or weaker in countries with low poverty; poverty replaces inequality as the favored explanation of health and social ills across states. The new evidence suggests that income distributions are characterized by a complex interplay between inequality and poverty, whose interaction deserves further analysis. Copyright �

Assessing the genetic overlap between BMI and cognitive function

PubMed Central

Marioni, R E; Yang, J; Dykiert, D; Mõttus, R; Campbell, A; Ibrahim-Verbaas, Carla A; Bressler, Jan; Debette, Stephanie; Schuur, Maaike; Smith, Albert V; Davies, Gail; Bennett, David A; Deary, Ian J; Ikram, M Arfan; Launer, Lenore J; Fitzpatrick, Annette L; Seshadri, Sudha; van Duijn, Cornelia M; Mosely Jr, Thomas H; Davies, G; Hayward, C; Porteous, D J; Visscher, P M; Deary, I J

2016-01-01

Obesity and low cognitive function are associated with multiple adverse health outcomes across the life course. They have a small phenotypic correlation (r=−0.11; high body mass index (BMI)−low cognitive function), but whether they have a shared genetic aetiology is unknown. We investigated the phenotypic and genetic correlations between the traits using data from 6815 unrelated, genotyped members of Generation Scotland, an ethnically homogeneous cohort from five sites across Scotland. Genetic correlations were estimated using the following: same-sample bivariate genome-wide complex trait analysis (GCTA)–GREML; independent samples bivariate GCTA–GREML using Generation Scotland for cognitive data and four other samples (n=20 806) for BMI; and bivariate LDSC analysis using the largest genome-wide association study (GWAS) summary data on cognitive function (n=48 462) and BMI (n=339 224) to date. The GWAS summary data were also used to create polygenic scores for the two traits, with within- and cross-trait prediction taking place in the independent Generation Scotland cohort. A large genetic correlation of −0.51 (s.e. 0.15) was observed using the same-sample GCTA–GREML approach compared with −0.10 (s.e. 0.08) from the independent-samples GCTA–GREML approach and −0.22 (s.e. 0.03) from the bivariate LDSC analysis. A genetic profile score using cognition-specific genetic variants accounts for 0.08% (P=0.020) of the variance in BMI and a genetic profile score using BMI-specific variants accounts for 0.42% (P=1.9 × 10−7) of the variance in cognitive function. Seven common genetic variants are significantly associated with both traits at P<5 × 10−5, which is significantly more than expected by chance (P=0.007). All these results suggest there are shared genetic contributions to BMI and cognitive function. PMID:26857597

Access to childbirth care by adolescents and young people in the Northeastern region of Brazil

PubMed Central

Furtado, Érida Zoé Lustosa; Gomes, Keila Rejane Oliveira; da Gama, Silvana Granado Nogueira

2016-01-01

ABSTRACT OBJECTIVE To identify the factors that interfere with the access of adolescents and young people to childbirth care for in the Northeast region of Brazil. METHODS Cross-sectional study with 3,014 adolescents and young people admitted to the selected maternity wards to give birth in the Northeast region of Brazil. The sample design was probabilistic, in two stages: the first corresponded to the health establishments and the second to women who had recently given birth and their babies. The data was collected by means of interviews and consulting the hospital records, from pre-tested electronic form. Descriptive statistics were used for the univariate analysis, Pearson’s Chi-square test for the bivariate analysis and multiple logistic regressions for the multivariate analysis. Sociodemographic variables, obstetrical history, and birth care were analyzed. RESULTS Half of the adolescents and young people interviewed had not been given guidance on the location that they should go to when in labor, and among those who had, 23.5% did not give birth in the indicated health service. Furthermore, one third (33.3%) had to travel in search of assisted birth, and the majority (66.7%) of the postpartum women came to maternity by their own means. In the bivariate analysis, the variables marital status, paid work, health insurance, number of previous pregnancies, parity, city location, and type of health establishment showed a significant association (p < 0.20) with inadequate access to childbirth care. The multivariate analysis showed that married adolescents and young people (p < 0.015), with no health insurance (p < 0.002) and from the countryside (p < 0.001) were more likely to have inadequate access to childbirth care. CONCLUSIONS Adolescents and young women, married, without health insurance, and from the countryside are more likely to have inadequate access to birth care. The articulation between outpatient care and birth care can improve this access and

Estimating the net effect of progesterone elevation on the day of hCG on live birth rates after IVF: a cohort analysis of 3296 IVF cycles.

PubMed

Venetis, Christos A; Kolibianakis, Efstratios M; Bosdou, Julia K; Lainas, George T; Sfontouris, Ioannis A; Tarlatzis, Basil C; Lainas, Tryfon G

2015-03-01

What is the proper way of assessing the effect of progesterone elevation (PE) on the day of hCG on live birth in women undergoing fresh embryo transfer after in vitro fertilization (IVF) using GnRH analogues and gonadotrophins? This study indicates that a multivariable approach, where the effect of the most important confounders is controlled for, can lead to markedly different results regarding the association between PE on the day of hCG and live birth rates after IVF when compared with the bivariate analysis that has been typically used in the relevant literature up to date. PE on the day of hCG is associated with decreased pregnancy rates in fresh IVF cycles. Evidence for this comes from observational studies that mostly failed to control for potential confounders. This is a retrospective analysis of a cohort of fresh IVF/intracytoplasmic sperm injection cycles (n = 3296) performed in a single IVF centre during the period 2001-2013. Patients in whom ovarian stimulation was performed with gonadotrophins and GnRH analogues. Natural cycles and cycles where stimulation involved the administration of clomiphene were excluded. In order to reflect routine clinical practice, no other exclusion criteria were imposed on this dataset. The primary outcome measure for this study was live birth defined as the delivery of a live infant after 24 weeks of gestation. We compared the association between PE on the day of hCG (defined as P > 1.5 ng/ml) and live birth rates calculated by simple bivariate analyses with that derived from multivariable logistic regression. The multivariable analysis controlled for female age, number of oocytes retrieved, number of embryos transferred, developmental stage of embryos at transfer (cleavage versus blastocyst), whether at least one good-quality embryo was transferred, the woman's body mass index, the total dose of FSH administered during ovarian stimulation and the type of GnRH analogues used (agonists versus antagonists) during ovarian

Gene network analysis shows immune-signaling and ERK1/2 as novel genetic markers for multiple addiction phenotypes: alcohol, smoking and opioid addiction.

PubMed

Reyes-Gibby, Cielito C; Yuan, Christine; Wang, Jian; Yeung, Sai-Ching J; Shete, Sanjay

2015-06-05

Addictions to alcohol and tobacco, known risk factors for cancer, are complex heritable disorders. Addictive behaviors have a bidirectional relationship with pain. We hypothesize that the associations between alcohol, smoking, and opioid addiction observed in cancer patients have a genetic basis. Therefore, using bioinformatics tools, we explored the underlying genetic basis and identified new candidate genes and common biological pathways for smoking, alcohol, and opioid addiction. Literature search showed 56 genes associated with alcohol, smoking and opioid addiction. Using Core Analysis function in Ingenuity Pathway Analysis software, we found that ERK1/2 was strongly interconnected across all three addiction networks. Genes involved in immune signaling pathways were shown across all three networks. Connect function from IPA My Pathway toolbox showed that DRD2 is the gene common to both the list of genetic variations associated with all three addiction phenotypes and the components of the brain neuronal signaling network involved in substance addiction. The top canonical pathways associated with the 56 genes were: 1) calcium signaling, 2) GPCR signaling, 3) cAMP-mediated signaling, 4) GABA receptor signaling, and 5) G-alpha i signaling. Cancer patients are often prescribed opioids for cancer pain thus increasing their risk for opioid abuse and addiction. Our findings provide candidate genes and biological pathways underlying addiction phenotypes, which may be future targets for treatment of addiction. Further study of the variations of the candidate genes could allow physicians to make more informed decisions when treating cancer pain with opioid analgesics.

An epidemiological analysis of potential associations between C-reactive protein, inflammation, and prostate cancer in the male US population using the 2009 - 2010 National Health and Nutrition Examination Survey (NHANES) data

NASA Astrophysics Data System (ADS)

St. Hill, Catherine; Lutfiyya, M. Nawal

2015-08-01

Prostate cancer is the second leading cause of cancer-related deaths in US males, yet much remains to be learned about the role of inflammation in its etiology. We hypothesized that preexisting exposure to chronic inflammatory conditions caused by infectious agents or inflammatory diseases increase the risk of prostate cancer. Using the 2009-2010 National Health and Nutrition Examination Survey, we examined the relationships between demographic variables, inflammation, infection, circulating plasma C-reactive protein (CRP), and the risk of occurrence of prostate cancer in US men over 18 years of age. Using IBM SPSS, we performed bivariate and logistic regression analyses using high CRP values as the dependent variable and five study covariates including prostate cancer status. From 2009 - 2010, an estimated 5,448,373 men reported having prostate cancer of which the majority were Caucasian (70.1%) and were aged 40 years and older (62.7%). Bivariate analyses demonstrated that high CRP was not associated with an increased risk of prostate cancer. Greater odds of having prostate cancer were revealed for men that had inflammation related to disease (OR = 1.029, CI 1.029-1.029) and those who were not taking drugs to control inflammation (OR = 1.330, CI 1.324-1.336). Men who did not have inflammation resulting from non-infectious diseases had greater odds of not having prostate cancer (OR = 1.031, CI 1.030-1.031). Logistic regression analysis yielded that men with the highest CRP values had greater odds of having higher household incomes and lower odds of having received higher education, being aged 40 years or older, being of a race or ethnicity different from other, and of having prostate cancer. Our results show that chronic inflammation of multiple etiologies is a risk factor for prostate cancer and that CRP is not associated with this increased risk. Further research is needed to elucidate the complex interactions between inflammation and prostate cancer.

Geochemical analysis of potash mine seep oils, collapsed breccia pipe oil shows and selected crude oils, Eddy County, New Mexico

USGS Publications Warehouse

Palacas, J.G.; Snyder, R.P.; Baysinger, J.P.; Threlkeld, C.N.

1982-01-01

Oil shows, in the form of oil stains and bleeding oil, in core samples from two breccia pipes, Hills A and C, Eddy County, New Mexico, and seepage oils in a potash mine near Hill C breccia pipe are geochemically similar. The geochemical similarities strongly suggest that they belong to the same family of oils and were derived from similar sources. The oils are relatively high in sulfur (0.89 to 1.23 percent), rich in hydrocarbons (average 82 percent), relatively high in saturated hydrocarbon/aromatic hydrocarbon ratios (average 2.9), and based on analysis of seep oils alone, have a low API gravity (average 19.4?). The oils are for the most part severely biodegraded as attested by the loss of n-paraffin molecules. Geochemical comparison of seven crude oils collected in the vicinity of the breccia pipes indicates that the Yates oils are the likely source of the above family of oils. Six barrels of crude oil that were dumped into a potash exploration borehole near Hill C breccia pipe, to release stuck casing, are considered an unlikely source of the breccia pipe and mine seep oils. Volumetric and hydrodynamic constraints make it highly improbable that such a small volume of 'dumped' oil could migrate over distances ranging from about 600 feet to 2.5 miles to the sites of the oil shows.

Kickoff to Conflict: A Sequence Analysis of Intra-State Conflict-Preceding Event Structures

PubMed Central

D'Orazio, Vito; Yonamine, James E.

2015-01-01

While many studies have suggested or assumed that the periods preceding the onset of intra-state conflict are similar across time and space, few have empirically tested this proposition. Using the Integrated Crisis Early Warning System's domestic event data in Asia from 1998–2010, we subject this proposition to empirical analysis. We code the similarity of government-rebel interactions in sequences preceding the onset of intra-state conflict to those preceding further periods of peace using three different metrics: Euclidean, Levenshtein, and mutual information. These scores are then used as predictors in a bivariate logistic regression to forecast whether we are likely to observe conflict in neither, one, or both of the states. We find that our model accurately classifies cases where both sequences precede peace, but struggles to distinguish between cases in which one sequence escalates to conflict and where both sequences escalate to conflict. These findings empirically suggest that generalizable patterns exist between event sequences that precede peace. PMID:25951105

Modeling association among demographic parameters in analysis of open population capture-recapture data.

PubMed

Link, William A; Barker, Richard J

2005-03-01

We present a hierarchical extension of the Cormack-Jolly-Seber (CJS) model for open population capture-recapture data. In addition to recaptures of marked animals, we model first captures of animals and losses on capture. The parameter set includes capture probabilities, survival rates, and birth rates. The survival rates and birth rates are treated as a random sample from a bivariate distribution, thus the model explicitly incorporates correlation in these demographic rates. A key feature of the model is that the likelihood function, which includes a CJS model factor, is expressed entirely in terms of identifiable parameters; losses on capture can be factored out of the model. Since the computational complexity of classical likelihood methods is prohibitive, we use Markov chain Monte Carlo in a Bayesian analysis. We describe an efficient candidate-generation scheme for Metropolis-Hastings sampling of CJS models and extensions. The procedure is illustrated using mark-recapture data for the moth Gonodontis bidentata.

Modeling association among demographic parameters in analysis of open population capture-recapture data

USGS Publications Warehouse

Link, William A.; Barker, Richard J.

2005-01-01

We present a hierarchical extension of the Cormack–Jolly–Seber (CJS) model for open population capture–recapture data. In addition to recaptures of marked animals, we model first captures of animals and losses on capture. The parameter set includes capture probabilities, survival rates, and birth rates. The survival rates and birth rates are treated as a random sample from a bivariate distribution, thus the model explicitly incorporates correlation in these demographic rates. A key feature of the model is that the likelihood function, which includes a CJS model factor, is expressed entirely in terms of identifiable parameters; losses on capture can be factored out of the model. Since the computational complexity of classical likelihood methods is prohibitive, we use Markov chain Monte Carlo in a Bayesian analysis. We describe an efficient candidate-generation scheme for Metropolis–Hastings sampling of CJS models and extensions. The procedure is illustrated using mark-recapture data for the moth Gonodontis bidentata.

Applied Stochastic Eigen-Analysis

DTIC Science & Technology

2007-02-01

6.4. The companion miatrix C’U’v, with respect to u, of the bivariate polynomnial L,,v given by (6.32). is det(u I - CI) = Luv (u, V)/lný (V) D...for the term u2 vJ in the polynomial Lu, (u, v). Note that the indexing for i and j starts with zero. Operation: Lulv, Luv - L. v MAT’LAF Code function...diet(ui*eye(le igtlh( Cn3))-Ciu3) function LIv3 = lliui.csl2(lnvlil v2, i ) CulI = luv2Cu( luv lu); L 3v =L v X, L2v - det(uI - C ,,), where if ( luvl

Basic cardiovascular variability signals: mutual directed interactions explored in the information domain.

PubMed

Javorka, Michal; Krohova, Jana; Czippelova, Barbora; Turianikova, Zuzana; Lazarova, Zuzana; Javorka, Kamil; Faes, Luca

2017-05-01

The study of short-term cardiovascular interactions is classically performed through the bivariate analysis of the interactions between the beat-to-beat variability of heart period (RR interval from the ECG) and systolic blood pressure (SBP). Recent progress in the development of multivariate time series analysis methods is making it possible to explore how directed interactions between two signals change in the context of networks including other coupled signals. Exploiting these advances, the present study aims at assessing directional cardiovascular interactions among the basic variability signals of RR, SBP and diastolic blood pressure (DBP), using an approach which allows direct comparison between bivariate and multivariate coupling measures. To this end, we compute information-theoretic measures of the strength and delay of causal interactions between RR, SBP and DBP using both bivariate and trivariate (conditioned) formulations in a group of healthy subjects in a resting state and during stress conditions induced by head-up tilt (HUT) and mental arithmetics (MA). We find that bivariate measures better quantify the overall (direct  +  indirect) information transferred between variables, while trivariate measures better reflect the existence and delay of directed interactions. The main physiological results are: (i) the detection during supine rest of strong interactions along the pathway RR  →  DBP  →  SBP, reflecting marked Windkessel and/or Frank-Starling effects; (ii) the finding of relatively weak baroreflex effects SBP  →  RR at rest; (iii) the invariance of cardiovascular interactions during MA, and the emergence of stronger and faster SBP  →  RR interactions, as well as of weaker RR  →  DBP interactions, during HUT. These findings support the importance of investigating cardiovascular interactions from a network perspective, and suggest the usefulness of directed information measures to assess

Combined fluvial and pluvial urban flood hazard analysis: method development and application to Can Tho City, Mekong Delta, Vietnam

NASA Astrophysics Data System (ADS)

Apel, H.; Trepat, O. M.; Hung, N. N.; Chinh, D. T.; Merz, B.; Dung, N. V.

2015-08-01

Many urban areas experience both fluvial and pluvial floods, because locations next to rivers are preferred settlement areas, and the predominantly sealed urban surface prevents infiltration and facilitates surface inundation. The latter problem is enhanced in cities with insufficient or non-existent sewer systems. While there are a number of approaches to analyse either fluvial or pluvial flood hazard, studies of combined fluvial and pluvial flood hazard are hardly available. Thus this study aims at the analysis of fluvial and pluvial flood hazard individually, but also at developing a method for the analysis of combined pluvial and fluvial flood hazard. This combined fluvial-pluvial flood hazard analysis is performed taking Can Tho city, the largest city in the Vietnamese part of the Mekong Delta, as example. In this tropical environment the annual monsoon triggered floods of the Mekong River can coincide with heavy local convective precipitation events causing both fluvial and pluvial flooding at the same time. Fluvial flood hazard was estimated with a copula based bivariate extreme value statistic for the gauge Kratie at the upper boundary of the Mekong Delta and a large-scale hydrodynamic model of the Mekong Delta. This provided the boundaries for 2-dimensional hydrodynamic inundation simulation for Can Tho city. Pluvial hazard was estimated by a peak-over-threshold frequency estimation based on local rain gauge data, and a stochastic rain storm generator. Inundation was simulated by a 2-dimensional hydrodynamic model implemented on a Graphical Processor Unit (GPU) for time-efficient flood propagation modelling. All hazards - fluvial, pluvial and combined - were accompanied by an uncertainty estimation considering the natural variability of the flood events. This resulted in probabilistic flood hazard maps showing the maximum inundation depths for a selected set of probabilities of occurrence, with maps showing the expectation (median) and the uncertainty by

[Socio-demographic Characterization of Psychosexual Development and Crime in Men Convicted of Sexual Crimes Imprisoned in the Manizales Penitentiary Center].

PubMed

Rivera, Adriana Arcila; Ramírez, Mauricio Castaño; Montoya, Dulcinea Osorio; Quiroz, Germán

2013-03-01

This article introduces the socio-demographic characteristics of psychosexual development and sexual crimes in men deprived of liberty for such crimes who are doing time in a Manizales prison (Colombia) in 2011. It also describes the differences between abusers of individuals under 12 years of age or who are 12 years old, and abusers of individuals over that age. This is a descriptive, retrospective study performed by simple random sampling. It consisted of semi-structured interviews in which socio-demographic characteristics, psychosexual development, characteristics of crime, and prevalence of mental disorders were analyzed in a sample of 80 inmates convicted of sexual offenses at the Medium-security Pentientiary center in the city of Manizales. Univariate and bivariate analysis were performed using the χ(2) test and the logistic regression analysis with variables showing statistical significance in the bivariate analysis. It was found that convicted sex offenders belong to lower socioeconomic levels, have low educational levels, and did not receive any sexual education. Such findings become more relevant when the crimes in questions are committed against 12-year-olders or children under this age. The lack of sexual education, low educational levels and lower socioeconomic levels are associated factors in the case of sexual offenses. It is important for society (particularly health-care institutions) to find additional measures for the criminalization of such behaviors in order to achieve a better control of the problem. Copyright © 2013 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Evaluation of psychiatric and genetic risk factors among primary relatives of suicide completers in Delhi NCR region, India.

PubMed

Pasi, Shivani; Singh, Piyoosh Kumar; Pandey, Rajeev Kumar; Dikshit, P C; Jiloha, R C; Rao, V R

2015-10-30

Suicide as a public health problem is studied worldwide and association of psychiatric and genetic risk factors for suicidal behavior are the point of discussion in studies across different ethnic groups. The present study is aimed at evaluating psychiatric and genetic traits among primary relatives of suicide completer families in an urban Indian population. Bi-variate analysis shows significant increase in major depression (PHQ and Hamilton), stress, panic disorder, somatoform disorder and suicide attemptamong primary compared to other relatives. Sib pair correlations also reveal significant results for major depression (Hamilton), stress, suicide attempt, intensity of suicide ideation and other anxiety syndrome. 5-HTTLPR, 5-HTT (Stin2) and COMT risk alleles are higher among primary relatives, though statistically insignificant. Backward conditional logistic regression analysis show only independent variable, Depression (Hamilton) made a unique statistically significant contribution to the model in primary relatives. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Assessment of Simulated and Aquarius-Observed Sea Surface Salinity Using Salinity Measurements in Dry Tortugas National Park, Florida, U.S.A.: Application for Pseudocoral δ18O

NASA Astrophysics Data System (ADS)

Chaichitehrani, N.; DeLong, K. L.

2016-02-01

Salinity plays a critical role in ocean physics thus is a target for paleoclimatologic and paleoceanographic reconstruction. Here we assess the quality of space-borne sea surface salinity (SSS) determinations and simulated SSS versus SSS measurements from an open ocean coral reef site, Dry Tortugas National Park (DTNP). The oxygen isotopic composition of seawater (δ18Osw) is related to SSS, thus SSS can be used to understand δ18Osw variability when measurements of δ18Osw are sparse. In marine carbonates such as corals, δ18Ocoral varies with temperature and δ18Osw creating a bivariate system, which is difficult to calibrate with two variables. Accurate determinations of SSS from satellites and simulations can be substituted for local SSS, converted to δ18Osw, in bivariate forward models to estimate δ18Ocoral or pseudocoral thus improving calibrations of δ18Ocoral for locations and time intervals without in situ observations. Monthly and daily Aquarius-retrieved SSS data Level-3 (Official Version 3.0) with spatial resolution are compared with local SSS in DTNP obtained from Water Quality Monitoring Project for the Florida Keys National Marine Sanctuary and southwest Florida shelf, which includes DTNP, for the concurrent interval from 2011-2014. Our statistical analysis shows a satisfactory agreement between daily Aquarius SSS and local SSS (r2=0.68; RMSE=0.24 psu). Additional SSS data are obtained from the National Data Buoy Center DRYF1 station in DTNP. Monthly-simulated SSS (Global Ocean Physics Reanalysis GLORYS2V3) obtained from the MyOcean WebPortal compares relatively well with DRYF1 monthly SSS data (r2=0.68; RMSE=0.35 psu) for the earlier interval from 1998-2002. Our analysis indicates that Aquarius-retrieved and simulated SSS can be utilized as a substitute for local SSS in bivariate forward models to calculate pseudocoral δ18Ocoral as well as forward models other marine carbonates for locations without SSS observations.

Meta-analysis of the effect of natural frequencies on Bayesian reasoning.

PubMed

McDowell, Michelle; Jacobs, Perke

2017-12-01

The natural frequency facilitation effect describes the finding that people are better able to solve descriptive Bayesian inference tasks when represented as joint frequencies obtained through natural sampling, known as natural frequencies, than as conditional probabilities. The present meta-analysis reviews 20 years of research seeking to address when, why, and for whom natural frequency formats are most effective. We review contributions from research associated with the 2 dominant theoretical perspectives, the ecological rationality framework and nested-sets theory, and test potential moderators of the effect. A systematic review of relevant literature yielded 35 articles representing 226 performance estimates. These estimates were statistically integrated using a bivariate mixed-effects model that yields summary estimates of average performances across the 2 formats and estimates of the effects of different study characteristics on performance. These study characteristics range from moderators representing individual characteristics (e.g., numeracy, expertise), to methodological differences (e.g., use of incentives, scoring criteria) and features of problem representation (e.g., short menu format, visual aid). Short menu formats (less computationally complex representations showing joint-events) and visual aids demonstrated some of the strongest moderation effects, improving performance for both conditional probability and natural frequency formats. A number of methodological factors (e.g., exposure to both problem formats) were also found to affect performance rates, emphasizing the importance of a systematic approach. We suggest how research on Bayesian reasoning can be strengthened by broadening the definition of successful Bayesian reasoning to incorporate choice and process and by applying different research methodologies. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A Case of Loeffler Endocarditis That Showed Endomyocardial Systolic Dysfunction Detected by Layer Specific Strain Analysis.

PubMed

Jin, Xuanyi; Ma, Chunyan; Wang, Yonghuai; Yang, Jun

2017-12-12

Loeffler endocarditis is a rare comprehensive cardiac manifestation caused by eosinophilic cell infiltrations and is present in 50%-60% of patients with hypereosinophilic syndrome (HES). Left ventricle (LV) endocardial systolic dysfunction is a major cause of morbidity and mortality in HES and Loeffler endocarditis. We present a case of Loeffler endocarditis, whose left ventricular (LV) systolic dysfunction and endocardial systolic dysfunction were first neglected by conventional transthoracic echocardiography (TTE), but were later pointed out by layer-specific longitudinal strain analysis. With timely initial therapeutic management, the patient's outcome was remarkable. Thus, we strongly recommend strain analysis as a necessary supplementary test of conventional TTE in all patients with Loeffler endocarditis.

Behavioral and Molecular Genetics of Reading-Related AM and FM Detection Thresholds.

PubMed

Bruni, Matthew; Flax, Judy F; Buyske, Steven; Shindhelm, Amber D; Witton, Caroline; Brzustowicz, Linda M; Bartlett, Christopher W

2017-03-01

Auditory detection thresholds for certain frequencies of both amplitude modulated (AM) and frequency modulated (FM) dynamic auditory stimuli are associated with reading in typically developing and dyslexic readers. We present the first behavioral and molecular genetic characterization of these two auditory traits. Two extant extended family datasets were given reading tasks and psychoacoustic tasks to determine FM 2 Hz and AM 20 Hz sensitivity thresholds. Univariate heritabilities were significant for both AM (h 2  = 0.20) and FM (h 2  = 0.29). Bayesian posterior probability of linkage (PPL) analysis found loci for AM (12q, PPL = 81 %) and FM (10p, PPL = 32 %; 20q, PPL = 65 %). Bivariate heritability analyses revealed that FM is genetically correlated with reading, while AM was not. Bivariate PPL analysis indicates that FM loci (10p, 20q) are not also associated with reading.

Application of Archimedean copulas to the analysis of drought decadal variation in China

NASA Astrophysics Data System (ADS)

Zuo, Dongdong; Feng, Guolin; Zhang, Zengping; Hou, Wei

2017-12-01

Based on daily precipitation data collected from 1171 stations in China during 1961-2015, the monthly standardized precipitation index was derived and used to extract two major drought characteristics which are drought duration and severity. Next, a bivariate joint model was established based on the marginal distributions of the two variables and Archimedean copula functions. The joint probability and return period were calculated to analyze the drought characteristics and decadal variation. According to the fit analysis, the Gumbel-Hougaard copula provided the best fit to the observed data. Based on four drought duration classifications and four severity classifications, the drought events were divided into 16 drought types according to the different combinations of duration and severity classifications, and the probability and return period were analyzed for different drought types. The results showed that the occurring probability of six common drought types (0 < D ≤ 1 and 0.5 < S ≤ 1, 1 < D ≤ 3 and 0.5 < S ≤ 1, 1 < D ≤ 3 and 1 < S ≤ 1.5, 1 < D ≤ 3 and 1.5 < S ≤ 2, 1 < D ≤ 3 and 2 < S, and 3 < D ≤ 6 and 2 < S) accounted for 76% of the total probability of all types. Moreover, due to their greater variation, two drought types were particularly notable, i.e., the drought types where D ≥ 6 and S ≥ 2. Analyzing the joint probability in different decades indicated that the location of the drought center had a distinctive stage feature, which cycled from north to northeast to southwest during 1961-2015. However, southwest, north, and northeast China had a higher drought risk. In addition, the drought situation in southwest China should be noted because the joint probability values, return period, and the analysis of trends in the drought duration and severity all indicated a considerable risk in recent years.

The double-edged sword of electronic health records: implications for patient disclosure.

PubMed

Campos-Castillo, Celeste; Anthony, Denise L

2015-04-01

Electronic health record (EHR) systems are linked to improvements in quality of care, yet also privacy and security risks. Results from research studies are mixed about whether patients withhold personal information from their providers to protect against the perceived EHR privacy and security risks. This study seeks to reconcile the mixed findings by focusing on whether accounting for patients' global ratings of care reveals a relationship between EHR provider-use and patient non-disclosure. A nationally representative sample from the 2012 Health Information National Trends Survey was analyzed using bivariate and multivariable logit regressions to examine whether global ratings of care suppress the relationship between EHR provider-use and patient non-disclosure. 13% of respondents reported having ever withheld information from a provider because of privacy/security concerns. Bivariate analysis showed that withholding information was unrelated to whether respondents' providers used an EHR. Multivariable analysis showed that accounting for respondents' global ratings of care revealed a positive relationship between having a provider who uses an EHR and withholding information. After accounting for global ratings of care, findings suggest that patients may non-disclose to providers to protect against the perceived EHR privacy and security risks. Despite evidence that EHRs inhibit patient disclosure, their advantages for promoting quality of care may outweigh the drawbacks. Clinicians should leverage the EHR's value in quality of care and discuss patients' privacy concerns during clinic visits, while policy makers should consider how to address the real and perceived privacy and security risks of EHRs. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Measuring multiple spike train synchrony.

PubMed

Kreuz, Thomas; Chicharro, Daniel; Andrzejak, Ralph G; Haas, Julie S; Abarbanel, Henry D I

2009-10-15

Measures of multiple spike train synchrony are essential in order to study issues such as spike timing reliability, network synchronization, and neuronal coding. These measures can broadly be divided in multivariate measures and averages over bivariate measures. One of the most recent bivariate approaches, the ISI-distance, employs the ratio of instantaneous interspike intervals (ISIs). In this study we propose two extensions of the ISI-distance, the straightforward averaged bivariate ISI-distance and the multivariate ISI-diversity based on the coefficient of variation. Like the original measure these extensions combine many properties desirable in applications to real data. In particular, they are parameter-free, time scale independent, and easy to visualize in a time-resolved manner, as we illustrate with in vitro recordings from a cortical neuron. Using a simulated network of Hindemarsh-Rose neurons as a controlled configuration we compare the performance of our methods in distinguishing different levels of multi-neuron spike train synchrony to the performance of six other previously published measures. We show and explain why the averaged bivariate measures perform better than the multivariate ones and why the multivariate ISI-diversity is the best performer among the multivariate methods. Finally, in a comparison against standard methods that rely on moving window estimates, we use single-unit monkey data to demonstrate the advantages of the instantaneous nature of our methods.

In silico analysis of SIGMAR1 variant (rs4879809) segregating in a consanguineous Pakistani family showing amyotrophic lateral sclerosis without frontotemporal lobar dementia.

PubMed

Ullah, Muhammad Ikram; Ahmad, Arsalan; Raza, Syed Irfan; Amar, Ali; Ali, Amjad; Bhatti, Attya; John, Peter; Mohyuddin, Aisha; Ahmad, Wasim; Hassan, Muhammad Jawad

2015-10-01

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder affecting upper motor neurons in the brain and lower motor neurons in the brain stem and spinal cord, resulting in fatal paralysis. It has been found to be associated with frontotemporal lobar degeneration (FTLD). In the present study, we have described homozygosity mapping and gene sequencing in a consanguineous autosomal recessive Pakistani family showing non-juvenile ALS without signs of FTLD. Gene mapping was carried out in all recruited family members using microsatellite markers, and linkage was established with sigma non-opioid intracellular receptor 1 (SIGMAR1) gene at chromosome 9p13.2. Gene sequencing of SIGMAR1 revealed a novel 3'-UTR nucleotide variation c.672*31A>G (rs4879809) segregating with disease in this family. The C9ORF72 repeat region in intron 1, previously implicated in a related phenotype, was excluded through linkage, and further confirmation of exclusion was obtained by amplifying intron 1 of C9ORF72 with multiple primers in affected individuals and controls. In silico analysis was carried out to explore the possible role of 3'-UTR variant of SIGMAR1 in ALS. The Regulatory RNA motif and Element Finder program revealed disturbance in miRNA (hsa-miR-1205) binding site due to this variation. ESEFinder analysis showed new SRSF1 and SRSF1-IgM-BRCA1 binding sites with significant scores due to this variation. Our results indicate that the 3'-UTR SIGMAR1 variant c.672*31A>G may have a role in the pathogenesis of ALS in this family.

Bayesian Analysis of Item Response Curves. Research Report 84-1. Mathematical Sciences Technical Report No. 132.

ERIC Educational Resources Information Center

Tsutakawa, Robert K.; Lin, Hsin Ying

Item response curves for a set of binary responses are studied from a Bayesian viewpoint of estimating the item parameters. For the two-parameter logistic model with normally distributed ability, restricted bivariate beta priors are used to illustrate the computation of the posterior mode via the EM algorithm. The procedure is illustrated by data…

A Content Analysis of How Sexual Behavior and Reproductive Health are Being Portrayed on Primetime Television Shows Being Watched by Teens and Young Adults.

PubMed

Kinsler, Janni J; Glik, Deborah; de Castro Buffington, Sandra; Malan, Hannah; Nadjat-Haiem, Carsten; Wainwright, Nicole; Papp-Green, Melissa

2018-02-01

Television is a leading source of sexual education for teens and young adults, thus it is important to understand how sexual behavior and reproductive health are portrayed in popular primetime programming. This study is a media content analysis of the 19 top-rated scripted English-language primetime television shows aired between January 1, 2015 and May 31, 2015, and viewed by American youth audiences 12-24 years of age. The purpose of this study is to assess how sex/sexuality and reproductive health are being portrayed in a popular medium that reaches many adolescent and young adult audiences. Themes used for this analysis include youth pregnancy/parenting, mentoring/guidance of youth regarding sexual behavior, sex/sexuality, body image/identity, sexual violence/abuse/harassment, gender identity/sexual orientation, and reproductive health. Themes have been classified in one of the following six categories: visual cues, brief mentions, dialogue, minor storylines, major storylines, and multi-episode storylines. Our findings indicate that narratives providing educational information regarding the risks and consequences of sexual behavior were missing from the television shows we analyzed and that storylines promoting low risk sexual behavior were rare. Sexual violence and abuse, casual sex among adults, lack of contraception use, or no portrayal of consequences of risky behaviors were common. Compared to prior research, we found an emergent theme normalizing non-heterosexual gender identity and sexual orientation. Our findings have important implications as exposure to popular media shapes the perceptions and behaviors of teens and young adults. This study has the potential to shed light on the need to create stories and narratives in television shows watched by American teens and young adults with educational messages regarding the risks and consequences of sexual behavior.

Modelling world gold prices and USD foreign exchange relationship using multivariate GARCH model

NASA Astrophysics Data System (ADS)

Ping, Pung Yean; Ahmad, Maizah Hura Binti

2014-12-01

World gold price is a popular investment commodity. The series have often been modeled using univariate models. The objective of this paper is to show that there is a co-movement between gold price and USD foreign exchange rate. Using the effect of the USD foreign exchange rate on the gold price, a model that can be used to forecast future gold prices is developed. For this purpose, the current paper proposes a multivariate GARCH (Bivariate GARCH) model. Using daily prices of both series from 01.01.2000 to 05.05.2014, a causal relation between the two series understudied are found and a bivariate GARCH model is produced.

Performance of screening questionnaires for obstructive sleep apnea during pregnancy: A systematic review and meta-analysis.

PubMed

Tantrakul, Visasiri; Numthavaj, Pawin; Guilleminault, Christian; McEvoy, Mark; Panburana, Panyu; Khaing, Win; Attia, John; Thakkinstian, Ammarin

2017-12-01

This review aims to evaluate the performance of obstructive sleep apnea (OSA) screening questionnaires during pregnancy. A systematic review and meta-analysis was performed using MEDLINE Scopus, CINAHL, and the Cochrane library. A bivariate meta-analysis was applied for pooling of diagnostic parameters. Six of the total 4719 articles met the inclusion criteria. The Berlin questionnaire (BQ, N = 604) and Epworth sleepiness scale (ESS, N = 420) were the most frequently used screening tools during pregnancy. The pooled prevalence of OSA during pregnancy was 26.7% (95%CI: 16.9%, 34.4%, I 2  = 83.15%). BQ performance was poor to fair with pooled sensitivity and specificity of 0.66 (95%CI: 0.45, 0.83; I 2  = 78.65%) and 0.62 (95%CI: 0.48, 0.75; I 2  = 81.55%), respectively. BQ performance was heterogeneous depending on type of reference test and pregnancy. Sensitivity increased if diagnosis was based on polysomnography (0.90), and respiratory disturbance index (0.90). However, sensitivity decreased if screening was performed in early pregnancy (≤20 weeks gestation: 0.47), and high-risk pregnancy (0.44). Performance of ESS was poor with pooled sensitivity and specificity of 0.44 (95%CI: 0.33, 0.56; I 2  = 32.8%) and 0.62 (95%CI: 0.48, 0.75; I 2  = 81.55%), respectively. In conclusion, BQ and ESS showed poor performance during pregnancy, hence a new OSA screening questionnaire is needed. Registration: PROSPERO registration CRD42015025848. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

More than Meets the Ear: A Factor Analysis of Student Impressions of Television Talk Show Hosts.

ERIC Educational Resources Information Center

Walker, James R.

To identify the descriptors most frequently associated with four popular television talk show hosts and to isolate the fundamental dimensions of the images of those talk show hosts, a study surveyed 209 students from Memphis State University and the University of Arkansas (Little Rock) about their impressions of Johnny Carson, David Letterman,…

Phylogenomic analysis shows that ‘Bacillus vanillea’ is a later heterotypic synonym of Bacillus siamensis

USDA-ARS?s Scientific Manuscript database

‘Bacillus vanillea’ XY18T (=CGMCC 8629 T =NCCB 100507 T) was isolated from cured vanilla beans and involved in the formation of vanilla aroma compounds. A draft genome of this type strain was assembled and yielded a length of 3.72 Mbp and a GC content of 46.3%. Comparative genomic analysis with its ...

Volunteering by older adults and risk of mortality: a meta-analysis.

PubMed

Okun, Morris A; Yeung, Ellen WanHeung; Brown, Stephanie

2013-06-01

Organizational volunteering has been touted as an effective strategy for older adults to help themselves while helping others. Extending previous reviews, we carried out a meta-analysis of the relation between organizational volunteering by late-middle-aged and older adults (minimum age = 55 years old) and risk of mortality. We focused on unadjusted effect sizes (i.e., bivariate relations), adjusted effect sizes (i.e., controlling for other variables such as health), and interaction effect sizes (e.g., the joint effect of volunteering and religiosity). For unadjusted effect sizes, on average, volunteering reduced mortality risk by 47%, with a 95% confidence interval ranging from 38% to 55%. For adjusted effect sizes, on average, volunteering reduced mortality risk by 24%, with a 95% confidence interval ranging from 16% to 31%. For interaction effect sizes, we found preliminary support that as public religiosity increases, the inverse relation between volunteering and mortality risk becomes stronger. The discussion identifies several unresolved issues and directions for future research. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Review of Research Shows, Overall, Acupuncture Did Not Increase Pregnancy Rates with IVF

MedlinePlus

... X Y Z Review of Research Shows, Overall, Acupuncture Did Not Increase Pregnancy Rates With IVF Share: An analysis of research conducted on acupuncture as an adjuvant (booster) treatment to in vitro ...

ANALYZING CORRELATIONS BETWEEN STREAM AND WATERSHED ATTRIBUTES

EPA Science Inventory

Bivariate correlation analysis has been widely used to explore relationships between stream and watershed attributes that have all been measured on the same set of watersheds or sampling locations. Researchers routinely test H0: =0 for each correlation in a large table and then ...

Predictors of workplace violence among female sex workers in Tijuana, Mexico.

PubMed

Katsulis, Yasmina; Durfee, Alesha; Lopez, Vera; Robillard, Alyssa

2015-05-01

For sex workers, differences in rates of exposure to workplace violence are likely influenced by a variety of risk factors, including where one works and under what circumstances. Economic stressors, such as housing insecurity, may also increase the likelihood of exposure. Bivariate analyses demonstrate statistically significant associations between workplace violence and selected predictor variables, including age, drug use, exchanging sex for goods, soliciting clients outdoors, and experiencing housing insecurity. Multivariate regression analysis shows that after controlling for each of these variables in one model, only soliciting clients outdoors and housing insecurity emerge as statistically significant predictors for workplace violence. © The Author(s) 2014.

The role of marriage in the causal pathway from economic conditions early in life to mortality.

PubMed

van den Berg, Gerard J; Gupta, Sumedha

2015-03-01

This paper analyzes the interplay between early-life conditions and marital status, as determinants of adult mortality. We use individual data from Dutch registers (years 1815-2000), combined with business cycle conditions in childhood as indicators of early-life conditions. The empirical analysis estimates bivariate duration models of marriage and mortality, allowing for unobserved heterogeneity. Results show that conditions around birth and school going ages are important for marriage and mortality. Men typically enjoy a protective effect of marriage, whereas women suffer during childbearing ages. However, having been born under favorable economic conditions reduces female mortality during childbearing ages. Copyright © 2014 Elsevier B.V. All rights reserved.

Impact of national income and inequality on sugar and caries relationship.

PubMed

Masood, M; Masood, Y; Newton, T

2012-01-01

The aim of this study was to examine the impact that national income and income inequality in high and low income countries have on the relationship between dental caries and sugar consumption. An ecological study design was used in this study of 73 countries. The mean decayed, missing, or filled permanent teeth (DMFT) for 12-year-old children were obtained from the WHO Oral Health Country/Area Profile Programme. United Nations Food and Agricultural Organization data were used for per capita sugar consumption. Gross national incomes per capita based on purchasing power parity and the Gini coefficient were obtained from World Bank data. Bivariate and multivariate linear regression analysis was performed to estimate the associations between mean DMFT and per capita sugar consumption in different income and income inequality countries. Bivariate and multivariate regression analysis showed that countries with a high national income and low income inequality have a strong negative association between sugar consumption and caries (B = -2.80, R2 = 0.17), whereas countries with a low income and high income inequality have a strong positive relationship between DMFT and per capita sugar consumption (B = -0.89, R2 = 0.20). The relationship between per capita consumption of sugar and dental caries is modified by the absolute level of income of the country, but not by the level of income inequality within a country. Copyright © 2012 S. Karger AG, Basel.

Correlation between presumed sinusitis-induced pain and paranasal sinus computed tomographic findings.

PubMed

Mudgil, Shikha P; Wise, Scott W; Hopper, Kenneth D; Kasales, Claudia J; Mauger, David; Fornadley, John A

2002-02-01

The correlation between facial and/or head pain in patients clinically suspected of having sinusitis and actual localized findings on sinus computed tomographic (CT) imaging are poorly understood. To prospectively evaluate the relationship of paranasal sinus pain symptoms with CT imaging. Two hundred consecutive patients referred by otolaryngologists and internists for CT of the paranasal sinuses participated by completing a questionnaire immediately before undergoing CT. Three radiologists blinded to the patients' responses scored the degree of air/fluid level, mucosal thickening, bony reaction, and mucus retention cysts using a graded scale of severity (0 to 3 points). The osteomeatal complexes and nasolacrimal ducts were also evaluated for patency. Bivariate analysis was performed to evaluate the relationship between patients' localized symptoms and CT findings in the respective sinus. One hundred sixty-three patients (82%) reported having some form of facial pain or headache. The right temple/forehead was the most frequently reported region of maximal pain. On CT imaging the maxillary sinus was the most frequently involved sinus. Bivariate analysis failed to show any relationship between patient symptoms and findings on CT. Patients with a normal CT reported a mean 5.88 sites of facial or head pain versus 5.45 sites for patients with an abnormal CT. Patient-based responses of sinonasal pain symptoms fail to correlate with findings in the respective sinuses. CT should therefore be reserved for delineating the anatomy and degree of sinus disease before surgical intervention.

Effects of perceptions of care, medical advice, and hospital quality on patient satisfaction after primary total knee replacement: A cross-sectional study.

PubMed

Schaal, Tom; Schoenfelder, Tonio; Klewer, Joerg; Kugler, Joachim

2017-01-01

The increase in the number of patients presenting with osteoarthritis in the past decade has led to a 32% increase in knee replacement surgeries designed to reduce restrictions on patient movement and improve their quality of life. Patient satisfaction is becoming an increasingly important indicator of quality of care. This study was designed to identify predictors of various service components in the treatment process and hospital key performance indicators significantly associated with patient satisfaction. A multicenter cross-sectional study was conducted with 856 patients having their primary total knee replacements at 41 hospitals. Patient satisfaction was queried via a validated, multidimensional questionnaire mainly using a six-point scale. In addition to bivariate calculations, patient satisfaction was the dependent variable in a binary logistic regression model. The bivariate analysis showed a strong association between satisfaction and sex (male or female), the patients' health before admission, and the length of stay. The number of cases treated at each hospital did not reveal any impact on satisfaction. The multivariate analysis identified three predictors associated with overall satisfaction. The strongest factor was the treatment outcome and the weakest was the quality of food. It became apparent that the statutory procedure minimums were not being met. The relevant factors influencing patient satisfaction were partially the same as previous study results and allowed more detailed conclusions. The results provide suggestions across hospitals that could help health care providers better meet needs of patients after knee arthroplasties.

Mice overexpressing corticotropin-releasing factor show brain atrophy and motor dysfunctions.

PubMed

Goebel, Miriam; Fleming, Sheila M; Million, Mulugeta; Stengel, Andreas; Taché, Yvette; Wang, Lixin

2010-03-31

Chronic stress and persistently high glucocorticoid levels can induce brain atrophy. Corticotropin-releasing factor (CRF)-overexpressing (OE) mice are a genetic model of chronic stress with elevated brain CRF and plasma corticosterone levels and Cushing's syndrome. The brain structural alterations in the CRF-OE mice, however, are not well known. We found that adult male and female CRF-OE mice had significantly lower whole brain and cerebellum weights than their wild type (WT) littermates (347.7+/-3.6mg vs. 460.1+/-4.3mg and 36.3+/-0.8mg vs. 50.0+/-1.3mg, respectively) without sex-related difference. The epididymal/parametrial fat mass was significantly higher in CRF-OE mice. The brain weight was inversely correlated to epididymal/parametrial fat weight, but not to body weight. Computerized image analysis system in Nissl-stained brain sections of female mice showed that the anterior cingulate and sensorimotor cortexes of CRF-OE mice were significantly thinner, and the volumes of the hippocampus, hypothalamic paraventricular nucleus and amygdala were significantly reduced compared to WT, while the locus coeruleus showed a non-significant increase. Motor functions determined by beam crossing and gait analysis showed that CRF-OE mice took longer time and more steps to traverse a beam with more errors, and displayed reduced stride length compared to their WT littermates. These data show that CRF-OE mice display brain size reduction associated with alterations of motor coordination and an increase in visceral fat mass providing a novel animal model to study mechanisms involved in brain atrophy under conditions of sustained elevation of brain CRF and circulating glucocorticoid levels. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

Media-Constructed Anti-Intellectualism: The Portrayal of Experts in Popular US Television Talk Shows.

ERIC Educational Resources Information Center

Holderman, Lisa B.

2003-01-01

Examines the popular portrayal of intellectual expertise through a content analysis of 200 of the 10 top-rated popular US television talk shows. Shows that experts in this sample were typically brought on late in the program, allotted little speaking time, placed among non-experts, frequently interrupted, and sometimes challenged. Indicates that…

Neuraxial blockade for external cephalic version: Cost analysis.

PubMed

Yamasato, Kelly; Kaneshiro, Bliss; Salcedo, Jennifer

2015-07-01

Neuraxial blockade (epidural or spinal anesthesia/analgesia) with external cephalic version increases the external cephalic version success rate. Hospitals and insurers may affect access to neuraxial blockade for external cephalic version, but the costs to these institutions remain largely unstudied. The objective of this study was to perform a cost analysis of neuraxial blockade use during external cephalic version from hospital and insurance payer perspectives. Secondarily, we estimated the effect of neuraxial blockade on cesarean delivery rates. A decision-analysis model was developed using costs and probabilities occurring prenatally through the delivery hospital admission. Model inputs were derived from the literature, national databases, and local supply costs. Univariate and bivariate sensitivity analyses and Monte Carlo simulations were performed to assess model robustness. Neuraxial blockade was cost saving to both hospitals ($30 per delivery) and insurers ($539 per delivery) using baseline estimates. From both perspectives, however, the model was sensitive to multiple variables. Monte Carlo simulation indicated neuraxial blockade to be more costly in approximately 50% of scenarios. The model demonstrated that routine use of neuraxial blockade during external cephalic version, compared to no neuraxial blockade, prevented 17 cesarean deliveries for every 100 external cephalic versions attempted. Neuraxial blockade is associated with minimal hospital and insurer cost changes in the setting of external cephalic version, while reducing the cesarean delivery rate. © 2015 The Authors. Journal of Obstetrics and Gynaecology Research © 2015 Japan Society of Obstetrics and Gynecology.

A break-even analysis of major ear surgery.

PubMed

Wasson, J D; Phillips, J S

2015-10-01

To determine variables which affect cost and profit for major ear surgery and perform a break-even analysis. Retrospective financial analysis. UK teaching hospital. Patients who underwent major ear surgery under general anaesthesia performed by the senior author in main theatre over a 2-year period between dates of 07 September 2010 and 07 September 2012. Income, cost and profit for each major ear patient spell. Variables that affect major ear surgery profitability. Seventy-six patients met inclusion criteria. Wide variation in earnings, with a median net loss of £-1345.50 was observed. Income was relatively uniform across all patient spells; however, theatre time of major ear surgery at a cost of £953.24 per hour varied between patients and was the main determinant of cost and profit for the patient spell. Bivariate linear regression of earnings on theatre time identified 94% of variation in earnings was due to variation in theatre time (r = -0.969; P < 0.0001) and derived a break-even time for major ear surgery of 110.6 min. Theatre time was dependent on complexity of procedure and number of OPCS4 procedures performed, with a significant increase in theatre time when three or more procedures were performed during major ear surgery (P = 0.015). For major ear surgery to either break-even or return a profit, total theatre time should not exceed 110 min and 36 s. © 2015 John Wiley & Sons Ltd.

An Examination of New Paradigms for Spline Approximations.

PubMed

Witzgall, Christoph; Gilsinn, David E; McClain, Marjorie A

2006-01-01

Lavery splines are examined in the univariate and bivariate cases. In both instances relaxation based algorithms for approximate calculation of Lavery splines are proposed. Following previous work Gilsinn, et al. [7] addressing the bivariate case, a rotationally invariant functional is assumed. The version of bivariate splines proposed in this paper also aims at irregularly spaced data and uses Hseih-Clough-Tocher elements based on the triangulated irregular network (TIN) concept. In this paper, the univariate case, however, is investigated in greater detail so as to further the understanding of the bivariate case.

Social exclusion, deprivation and child health: a spatial analysis of ambulatory care sensitive conditions in children aged 0-4 years in Victoria, Australia.

PubMed

Butler, Danielle C; Thurecht, Linc; Brown, Laurie; Konings, Paul

2013-10-01

Recent Australian policy initiatives regarding primary health care focus on planning services around community needs and delivering these at the local area. As in many other countries, there has also been a growing concern over social inequities in health outcomes. The aims of the analysis presented here were firstly to describe small area variations in hospital admissions for ambulatory care sensitive conditions (ACSC) among children aged 0-4 years between 2003 and 2009 in the state of Victoria, Australia, and secondly to explore the relationship of ACSC hospitalisations with socio-economic disadvantage using a comparative analysis of the Child Social Exclusion (CSE) index and the Composite Score of Deprivation (CSD). This is a cross sectional secondary data analysis, with data sourced from 2003 to 2009 ACSC data from the Victorian State Government Department of Health; the Australian Standard Geographical Classification of remoteness; the Australian 2006 Census of Population and Housing; and AMPCo General Practitioner data from 2010. The relationship between the indexes and child health outcomes was examined through bivariate analysis and visually through a series of maps. The results show there is significant variation in the geographical distribution of the relationship between ACSCs and socio-economic disadvantage, with both indexes capturing important social gradients in child health conditions. However, measures of access, such as geographical accessibility and workforce supply, detect additional small area variation in child health outcomes. This research has important implications for future primary health care policy and planning of services, as these findings confirm that not all areas are the same in terms of health outcomes, and there may be benefit in tailoring mechanisms for identifying areas of need depending on the outcome intended to be affected. Copyright © 2013 Elsevier Ltd. All rights reserved.

Characterization and mutational analysis of a nicotinamide mononucleotide deamidase from Agrobacterium tumefaciens showing high thermal stability and catalytic efficiency

PubMed Central

Martínez-Moñino, Ana Belén; Zapata-Pérez, Rubén; García-Saura, Antonio Ginés; Gil-Ortiz, Fernando; Pérez-Gilabert, Manuela

2017-01-01

NAD+ has emerged as a crucial element in both bioenergetic and signaling pathways since it acts as a key regulator of cellular and organismal homeostasis. Among the enzymes involved in its recycling, nicotinamide mononucleotide (NMN) deamidase is one of the key players in the bacterial pyridine nucleotide cycle, where it catalyzes the conversion of NMN into nicotinic acid mononucleotide (NaMN), which is later converted to NAD+ in the Preiss-Handler pathway. The biochemical characteristics of bacterial NMN deamidases have been poorly studied, although they have been investigated in some firmicutes, gamma-proteobacteria and actinobacteria. In this study, we present the first characterization of an NMN deamidase from an alphaproteobacterium, Agrobacterium tumefaciens (AtCinA). The enzyme was active over a broad pH range, with an optimum at pH 7.5. Moreover, the enzyme was quite stable at neutral pH, maintaining 55% of its activity after 14 days. Surprisingly, AtCinA showed the highest optimal (80°C) and melting (85°C) temperatures described for an NMN deamidase. The above described characteristics, together with its high catalytic efficiency, make AtCinA a promising biocatalyst for the production of pure NaMN. In addition, six mutants (C32A, S48A, Y58F, Y58A, T105A and R145A) were designed to study their involvement in substrate binding, and two (S31A and K63A) to determine their contribution to the catalysis. However, only four mutants (C32A, S48A Y58F and T105A) showed activity, although with reduced catalytic efficiency. These results, combined with a thermal and structural analysis, reinforce the Ser/Lys catalytic dyad mechanism as the most plausible among those proposed. PMID:28388636

A meta-analysis of the differential relations of traditional and cyber-victimization with internalizing problems.

PubMed

Gini, Gianluca; Card, Noel A; Pozzoli, Tiziana

2018-03-01

This meta-analysis examined the associations between cyber-victimization and internalizing problems controlling for the occurrence of traditional victimization. Twenty independent samples with a total of 90,877 participants were included. Results confirmed the significant intercorrelation between traditional and cyber-victimization (r = .43). They both have medium-to-large bivariate correlations with internalizing problems. Traditional victimization (sr = .22) and cyber-victimization (sr = .12) were also uniquely related to internalizing problems. The difference in the relations between each type of victimization and internalizing problems was small (differential d = .06) and not statistically significant (p = .053). Moderation of these effect sizes by sample characteristics (e.g., age and proportion of girls) and study features (e.g., whether a definition of bullying was provided to participants and the time frame used as reference) was investigated. Results are discussed within the extant literature on cyber-aggression and cyber-victimization and future directions are proposed. © 2017 Wiley Periodicals, Inc.

Talk Show Science.

ERIC Educational Resources Information Center

Moore, Mitzi Ruth

1992-01-01

Proposes having students perform skits in which they play the roles of the science concepts they are trying to understand. Provides the dialog for a skit in which hot and cold gas molecules are interviewed on a talk show to study how these properties affect wind, rain, and other weather phenomena. (MDH)

Smoking and caffeine consumption: a genetic analysis of their association

PubMed Central

Taylor, Amy E.; Ware, Jennifer J.; Nivard, Michel G.; Neale, Michael C.; McMahon, George; Hottenga, Jouke‐Jan; Baselmans, Bart M. L.; Boomsma, Dorret I.; Munafò, Marcus R.; Vink, Jacqueline M.

2016-01-01

Abstract Smoking and caffeine consumption show a strong positive correlation, but the mechanism underlying this association is unclear. Explanations include shared genetic/environmental factors or causal effects. This study employed three methods to investigate the association between smoking and caffeine. First, bivariate genetic models were applied to data of 10 368 twins from the Netherlands Twin Register in order to estimate genetic and environmental correlations between smoking and caffeine use. Second, from the summary statistics of meta‐analyses of genome‐wide association studies on smoking and caffeine, the genetic correlation was calculated by LD‐score regression. Third, causal effects were tested using Mendelian randomization analysis in 6605 Netherlands Twin Register participants and 5714 women from the Avon Longitudinal Study of Parents and Children. Through twin modelling, a genetic correlation of r0.47 and an environmental correlation of r0.30 were estimated between current smoking (yes/no) and coffee use (high/low). Between current smoking and total caffeine use, this was r0.44 and r0.00, respectively. LD‐score regression also indicated sizeable genetic correlations between smoking and coffee use (r0.44 between smoking heaviness and cups of coffee per day, r0.28 between smoking initiation and coffee use and r0.25 between smoking persistence and coffee use). Consistent with the relatively high genetic correlations and lower environmental correlations, Mendelian randomization provided no evidence for causal effects of smoking on caffeine or vice versa. Genetic factors thus explain most of the association between smoking and caffeine consumption. These findings suggest that quitting smoking may be more difficult for heavy caffeine consumers, given their genetic susceptibility. PMID:27027469

Investigating CSI: portrayals of DNA testing on a forensic crime show and their potential effects.

PubMed

Ley, Barbara L; Jankowski, Natalie; Brewer, Paul R

2012-01-01

The popularity of forensic crime shows such as CSI has fueled debate about their potential social impact. This study considers CSI's potential effects on public understandings regarding DNA testing in the context of judicial processes, the policy debates surrounding crime laboratory procedures, and the forensic science profession, as well as an effect not discussed in previous accounts: namely, the show's potential impact on public understandings of DNA and genetics more generally. To develop a theoretical foundation for research on the "CSI effect," it draws on cultivation theory, social cognitive theory, and audience reception studies. It then uses content analysis and textual analysis to illuminate how the show depicts DNA testing. The results demonstrate that CSI tends to depict DNA testing as routine, swift, useful, and reliable and that it echoes broader discourses about genetics. At times, however, the show suggests more complex ways of thinking about DNA testing and genetics.

Intraperitoneal dedifferentiated liposarcoma showing MDM2 amplification: case report.

PubMed

Grifasi, Carlo; Calogero, Armando; Carlomagno, Nicola; Campione, Severo; D'Armiento, Francesco Paolo; Renda, Andrea

2013-11-26

Liposarcoma is the most common type of soft tissue sarcoma (STS). It is divided into five groups according to histological pattern: well-differentiated, myxoid, round cell, pleomorphic, and dedifferentiated. Dedifferentiated liposarcoma most commonly occurs in the retroperitoneum, while an intraperitoneal location is extremely rare. Only seven cases have been reported in literature. Many pathologists recognize that a large number of intra-abdominal poorly differentiated sarcomas are dedifferentiated liposarcomas. We report a case initially diagnosed as undifferentiated sarcoma that was reclassified as intraperitoneal dedifferentiated liposarcoma showing an amplification of the MDM2 gene. A 59-year-old woman with abdominal pain and constipation was referred to the Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy, in November 2012. On physical examination, a very large firm mass was palpable in the meso-hypogastrium. Computed tomography (CT) scan showed a heterogeneous density mass (measuring 10 × 19 cm) that was contiguous with the mesentery and compressed the third part of the duodenum and jejunum.At laparotomy, a large mass occupying the entire abdomen was found, adhering to the first jejunal loop and involving the mesentery. Surgical removal of the tumor along with a jejunal resection was performed because the first jejunal loop was firmly attached to the tumor.Macroscopic examination showed a solid, whitish, cerebroid, and myxoid mass, with variable hemorrhage and cystic degeneration, measuring 26 × 19 × 5 cm. Microscopic examination revealed two main different morphologic patterns: areas with spindle cells in a myxoid matrix and areas with pleomorphic cells. The case was initially diagnosed as undifferentiated pleomorphic sarcoma. Histological review showed areas of well-differentiated liposarcoma. Fluorescence in situ hybridization (FISH) analysis was performed and demonstrated an amplification of the MDM2 gene

Intraperitoneal dedifferentiated liposarcoma showing MDM2 amplification: case report

PubMed Central

2013-01-01

Background Liposarcoma is the most common type of soft tissue sarcoma (STS). It is divided into five groups according to histological pattern: well-differentiated, myxoid, round cell, pleomorphic, and dedifferentiated. Dedifferentiated liposarcoma most commonly occurs in the retroperitoneum, while an intraperitoneal location is extremely rare. Only seven cases have been reported in literature. Many pathologists recognize that a large number of intra-abdominal poorly differentiated sarcomas are dedifferentiated liposarcomas. We report a case initially diagnosed as undifferentiated sarcoma that was reclassified as intraperitoneal dedifferentiated liposarcoma showing an amplification of the MDM2 gene. Case presentation A 59-year-old woman with abdominal pain and constipation was referred to the Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy, in November 2012. On physical examination, a very large firm mass was palpable in the meso-hypogastrium. Computed tomography (CT) scan showed a heterogeneous density mass (measuring 10 × 19 cm) that was contiguous with the mesentery and compressed the third part of the duodenum and jejunum. At laparotomy, a large mass occupying the entire abdomen was found, adhering to the first jejunal loop and involving the mesentery. Surgical removal of the tumor along with a jejunal resection was performed because the first jejunal loop was firmly attached to the tumor. Macroscopic examination showed a solid, whitish, cerebroid, and myxoid mass, with variable hemorrhage and cystic degeneration, measuring 26 × 19 × 5 cm. Microscopic examination revealed two main different morphologic patterns: areas with spindle cells in a myxoid matrix and areas with pleomorphic cells. The case was initially diagnosed as undifferentiated pleomorphic sarcoma. Histological review showed areas of well-differentiated liposarcoma. Fluorescence in situ hybridization (FISH) analysis was performed and

Immunohistochemical analysis of metaplastic non-goblet columnar lined oesophagus shows phenotypic similarities to Barrett's oesophagus: a study in an Asian population.

PubMed

Srivastava, Supriya; Liew, Mei Shan; McKeon, Frank; Xian, Wa; Yeoh, Khay Guan; Ho, Khek Yu; Teh, Ming

2014-02-01

Barrett's oesophagus is a premalignant condition, predisposing to oesophageal adenocarcinoma. However, some adenocarcinoma may arise in columnar lined oesophagus without goblet cells. Our aim was to evaluate the biological properties of non-goblet columnar lined oesophagus only and elucidate its relationship with Barrett's oesophagus and associated neoplasia. Endoscopic biopsies from patients with Barrett's oesophagus (n=30), non-goblet columnar lined oesophagus (n=14), Barrett's oesophagus associated high grade dysplasia (n=6) and adenocarcinoma (n=4) were selected. Immunostaining for villin, claudin 3 and MUC4 was performed. Statistical analysis was performed and a p value <0.05 was considered significant. Villin and MUC4 were positive in 42%, 100% each and 50% in non-goblet columnar lined oesophagus, Barrett's oesophagus, high grade dysplasia and adenocarcinoma respectively, while claudin 3 was 100% positive in all the groups. In non-goblet columnar lined oesophagus, six cases that were villin immunopositive, showed positive expression for claudin 3 and/or MUC4 and there was no difference from the high grade dysplasia or adenocarcinoma (p>0.05). Our results indicate that a subset of non-goblet columnar lined oesophagus shows an intestinal phenotype representing an early stage of Barrett's oesophagus. This subset probably harbours the potential to change into adenocarcinoma in the long term. Copyright © 2013 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

Analyzing the Cost-Effectiveness of Instruction Expenditures towards High School Completion among Oahu's Public School Districts

ERIC Educational Resources Information Center

Ng, Larson S. W. M.

2011-01-01

The following study attempted to ascertain the instructional cost-effectiveness of public high school teachers towards high school completion through a financially based econometric analysis. Essentially, public high school instruction expenditures and completer data were collected from 2000 to 2007 and bivariate interaction analyzed through a…

Designing Interactive Online Nursing Courses

ERIC Educational Resources Information Center

Jain, Smita; Jain, Pawan

2015-01-01

This study empirically tests the relation between the instructional design elements and the overall meaningful interactions among online students. Eighteen online graduate nursing courses are analyzed using bivariate and multivariate analysis techniques. Findings suggest that the quantity of meaningful interaction among learners can be improved by…

Using meta-analysis to inform the design of subsequent studies of diagnostic test accuracy.

PubMed

Hinchliffe, Sally R; Crowther, Michael J; Phillips, Robert S; Sutton, Alex J

2013-06-01

An individual diagnostic accuracy study rarely provides enough information to make conclusive recommendations about the accuracy of a diagnostic test; particularly when the study is small. Meta-analysis methods provide a way of combining information from multiple studies, reducing uncertainty in the result and hopefully providing substantial evidence to underpin reliable clinical decision-making. Very few investigators consider any sample size calculations when designing a new diagnostic accuracy study. However, it is important to consider the number of subjects in a new study in order to achieve a precise measure of accuracy. Sutton et al. have suggested previously that when designing a new therapeutic trial, it could be more beneficial to consider the power of the updated meta-analysis including the new trial rather than of the new trial itself. The methodology involves simulating new studies for a range of sample sizes and estimating the power of the updated meta-analysis with each new study added. Plotting the power values against the range of sample sizes allows the clinician to make an informed decision about the sample size of a new trial. This paper extends this approach from the trial setting and applies it to diagnostic accuracy studies. Several meta-analytic models are considered including bivariate random effects meta-analysis that models the correlation between sensitivity and specificity. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

Aetiology of thrombosed external haemorrhoids: a questionnaire study.

PubMed

Gebbensleben, Ole; Hilger, York; Rohde, Henning

2009-10-23

It is important to better understand the aetiology of thrombosed external haemorrhoids (TEH) because recurrence rates are high, prophylaxis is unknown, and optimal therapy is highly debated. We conducted a questionnaire study of individuals with and without TEH. Aetiology was studied by comparison of answers to a questionnaire given to individuals with and without TEH concerning demography, history, and published aetiologic hypotheses. Participants were evaluated consecutively at our institution from March 2004 through August 2005.One hundred forty-eight individuals were enrolled, including 72 patients with TEH and 76 individuals without TEH but with alternative diagnoses, such as a screening colonoscopy or colonic polyps. Out of 38 possible aetiologic factors evaluated, 20 showed no significant bivariate correlation to TEH and were no longer traced, and 16 factors showed a significant bivariate relationship to TEH. By multivariate analysis, six independent variables were found to predict TEH correctly in 79.1% of cases: age of 46 years or younger, use of excessive physical effort, and use of dry toilet paper combined with wet cleaning methods after defaecation were associated with a significantly higher risk of developing TEH; use of bathtub, use of the shower, and genital cleaning before sleep at least once a week were associated with a significantly lower risk of developing TEH. Six hypotheses on the causes of TEH have a high probability of being correct and should be considered in future studies on aetiology, prophylaxis, and therapy of TEH.

Obesity in show cats.

PubMed

Corbee, R J

2014-12-01

Obesity is an important disease with a high prevalence in cats. Because obesity is related to several other diseases, it is important to identify the population at risk. Several risk factors for obesity have been described in the literature. A higher incidence of obesity in certain cat breeds has been suggested. The aim of this study was to determine whether obesity occurs more often in certain breeds. The second aim was to relate the increased prevalence of obesity in certain breeds to the official standards of that breed. To this end, 268 cats of 22 different breeds investigated by determining their body condition score (BCS) on a nine-point scale by inspection and palpation, at two different cat shows. Overall, 45.5% of the show cats had a BCS > 5, and 4.5% of the show cats had a BCS > 7. There were significant differences between breeds, which could be related to the breed standards. Most overweight and obese cats were in the neutered group. It warrants firm discussions with breeders and cat show judges to come to different interpretations of the standards in order to prevent overweight conditions in certain breeds from being the standard of beauty. Neutering predisposes for obesity and requires early nutritional intervention to prevent obese conditions. Journal of Animal Physiology and Animal Nutrition © 2014 Blackwell Verlag GmbH.

Binge drinking and marijuana use among menthol and non-menthol adolescent smokers: findings from the youth smoking survey.

PubMed

Azagba, Sunday; Sharaf, Mesbah F

2014-03-01

Research has shown that smoking menthol cigarettes induces smoking initiation and hinders cessation efforts especially among youth. The objective of this paper is to examine the association between menthol cigarette smoking and substance use among adolescent students in Canada. A nationally representative cross-sectional sample of 4466 Canadian students in grades 7 to 12 from the 2010-2011 Youth Smoking Survey is analyzed. A bivariate probit model is used jointly to examine the association of menthol smoking status with binge drinking and marijuana use. 32% of the current smokers in grades 7 to 12 smoke mentholated cigarettes, 73% are binge drinkers and 79% use marijuana. Results of the bivariate probit regression analysis, controlling for other covariates, show statistically significant differences in the likelihood of binge drinking and marijuana use between menthol and non-menthol smokers. Menthol cigarette smokers are 6% (ME=0.06, 95% CI=0.03-0.09) more likely to binge drink and 7% (ME=0.07, 95% CI=0.05-0.10) more likely to use marijuana. Smoking menthol cigarettes is associated with a higher likelihood of binge drinking and marijuana use among Canadian adolescents. Banning menthol in cigarettes may be beneficial to public health. Copyright © 2013 Elsevier Ltd. All rights reserved.

Analysis of vector wind change with respect to time for Cape Kennedy, Florida: Wind aloft profile change vs. time, phase 1

NASA Technical Reports Server (NTRS)

Adelfang, S. I.

1977-01-01

Wind vector change with respect to time at Cape Kennedy, Florida, is examined according to the theory of multivariate normality. The joint distribution of the four variables represented by the components of the wind vector at an initial time and after a specified elapsed time is hypothesized to be quadravariate normal; the fourteen statistics of this distribution, calculated from fifteen years of twice daily Rawinsonde data are presented by monthly reference periods for each month from 0 to 27 km. The hypotheses that the wind component changes with respect to time is univariate normal, the joint distribution of wind component changes is bivariate normal, and the modulus of vector wind change is Rayleigh, has been tested by comparison with observed distributions. Statistics of the conditional bivariate normal distributions of vector wind at a future time given the vector wind at an initial time are derived. Wind changes over time periods from one to five hours, calculated from Jimsphere data, are presented.

Analysis of Two-Component Systems in Group B Streptococcus Shows That RgfAC and the Novel FspSR Modulate Virulence and Bacterial Fitness

PubMed Central

Faralla, Cristina; Metruccio, Matteo M.; De Chiara, Matteo; Mu, Rong; Patras, Kathryn A.; Muzzi, Alessandro; Grandi, Guido; Margarit, Immaculada; Doran, Kelly S.

2014-01-01

ABSTRACT Group B Streptococcus (GBS), in the transition from commensal organisms to pathogens, will encounter diverse host environments and, thus, require coordinated control of the transcriptional responses to these changes. This work was aimed at better understanding the role of two-component signal transduction systems (TCS) in GBS pathophysiology through a systematic screening procedure. We first performed a complete inventory and sensory mechanism classification of all putative GBS TCS by genomic analysis. Five TCS were further investigated by the generation of knockout strains, and in vitro transcriptome analysis identified genes regulated by these systems, ranging from 0.1% to 3% of the genome. Interestingly, two sugar phosphotransferase systems appeared to be differentially regulated in the TCS-16 knockout strain (TCS loci were numbered in order of their appearance on the chromosome), suggesting an involvement in monitoring carbon source availability. High-throughput analysis of bacterial growth on different carbon sources showed that TCS-16 was necessary for the growth of GBS on fructose-6-phosphate. Additional transcriptional analysis provided further evidence for a stimulus-response circuit where extracellular fructose-6-phosphate leads to autoinduction of TCS-16, with concomitant dramatic upregulation of the adjacent operon, which encodes a phosphotransferase system. The TCS-16-deficient strain exhibited decreased persistence in a model of vaginal colonization. All mutant strains were also characterized in a murine model of systemic infection, and inactivation of TCS-17 (also known as RgfAC) resulted in hypervirulence. Our data suggest a role for the previously unknown TCS-16, here named FspSR, in bacterial fitness and carbon metabolism during host colonization, and the data also provide experimental evidence for TCS-17/RgfAC involvement in virulence. PMID:24846378

Eisosomes Are Dynamic Plasma Membrane Domains Showing Pil1-Lsp1 Heteroligomer Binding Equilibrium

PubMed Central

Olivera-Couto, Agustina; Salzman, Valentina; Mailhos, Milagros; Digman, Michelle A.; Gratton, Enrico; Aguilar, Pablo S.

2015-01-01

Eisosomes are plasma membrane domains concentrating lipids, transporters, and signaling molecules. In the budding yeast Saccharomyces cerevisiae, these domains are structured by scaffolds composed mainly by two cytoplasmic proteins Pil1 and Lsp1. Eisosomes are immobile domains, have relatively uniform size, and encompass thousands of units of the core proteins Pil1 and Lsp1. In this work we used fluorescence fluctuation analytical methods to determine the dynamics of eisosome core proteins at different subcellular locations. Using a combination of scanning techniques with autocorrelation analysis, we show that Pil1 and Lsp1 cytoplasmic pools freely diffuse whereas an eisosome-associated fraction of these proteins exhibits slow dynamics that fit with a binding-unbinding equilibrium. Number and brightness analysis shows that the eisosome-associated fraction is oligomeric, while cytoplasmic pools have lower aggregation states. Fluorescence lifetime imaging results indicate that Pil1 and Lsp1 directly interact in the cytoplasm and within the eisosomes. These results support a model where Pil1-Lsp1 heterodimers are the minimal eisosomes building blocks. Moreover, individual-eisosome fluorescence fluctuation analysis shows that eisosomes in the same cell are not equal domains: while roughly half of them are mostly static, the other half is actively exchanging core protein subunits. PMID:25863055

Changes in the proportion of facility-based deliveries and related maternal health services among the poor in rural Jhang, Pakistan: results from a demand-side financing intervention.

PubMed

Agha, Sohail

2011-11-30

Demand-side financing projects are now being implemented in many developing countries, yet evidence showing that they reach the poor is scanty. A maternal health voucher scheme provided voucher-paid services in Jhang, a predominantly rural district of Pakistan, during 2010. A pre-test/post-test quasi-experimental design was used to assess the changes in the proportion of facility-based deliveries and related maternal health services among the poor. Household interviews were conducted with randomly selected women in the intervention and control union councils, before and after the intervention.A strong outreach model was used. Voucher promoters were given basic training in identification of poor women using the Poverty Scorecard for Pakistan, in the types of problems women could face during delivery, and in the promotion of antenatal care (ANC), institutional delivery and postnatal care (PNC). Voucher booklets valued at Rs. 4,000 ($48), including three ANC visits, a PNC visit, an institutional delivery, and a postnatal family planning visit, were sold for Rs. 100 ($1.2) to low-income women targeted by project outreach workers. Women suffering from complications were referred to emergency obstetric care services.Analysis was conducted at the bivariate and the multivariate levels. At the multivariate level, logistic regression analysis was conducted to determine whether the increase in institutional delivery was greater among poor women (defined for this study as women in the fourth or fifth quintiles) relative to non-poor women (defined for this study as women in the first quintile) in the intervention union councils compared to the control union councils. Bivariate analysis showed significant increases in the institutional delivery rate among women in the fourth or fifth wealth quintiles in the intervention union councils but no significant changes in this indicator among women in the same wealth quintiles in the control union councils. Multivariate analysis showed

Plasma ghrelin levels and polymorphisms of ghrelin gene in Chinese obese children and adolescents.

PubMed

Zhu, J F; Liang, L; Zou, C C; Fu, J F

2010-09-01

To evaluate the role of fasting plasma ghrelin levels [ln(ghrelin)] and polymorphisms of ghrelin gene in Chinese obese children. Genotyping for ghrelin polymorphism was performed in 230 obese and 100 normal weight children. Among them, plasma ghrelin levels were measured in 91 obese and 23 health subjects. (1) Bivariate correlation analysis showed the ln(ghrelin) was inversely correlated with abnormality of glucose metabolism (r = -0.240, P = 0.023). Stepwise multiple regression analysis showed that abnormality of glucose metabolism was an independent determinant of plasma ghrelin levels (P = 0.023). (2) There was no difference in frequency of Leu72Met polymorphisms between obese and control groups (36.09 vs. 41.00%). Ghrelin is associated with obesity in childhood, especially associated with the glucose homeostasis. Lower ghrelin levels might be a result of obesity, but not a cause of obesity. The Leu72Met polymorphism of ghrelin gene is not associated with obesity and metabolic syndrome in Chinese children.

Showing and Telling Farming: Agricultural Shows and Re-Imaging British Agriculture

ERIC Educational Resources Information Center

Holloway, Lewis

2004-01-01

Some actors in the ''mainstream'' agricultural sector are beginning to engage in strategies of influencing public perceptions of farming, responding to public anxieties over industrialised agriculture and to a supposed separation of non-farming publics from food production. This paper focuses on agricultural shows as sites and events central to…

Empirical analysis shows reduced cost data collection may be an efficient method in economic clinical trials

PubMed Central

2012-01-01

Background Data collection for economic evaluation alongside clinical trials is burdensome and cost-intensive. Limiting both the frequency of data collection and recall periods can solve the problem. As a consequence, gaps in survey periods arise and must be filled appropriately. The aims of our study are to assess the validity of incomplete cost data collection and define suitable resource categories. Methods In the randomised KORINNA study, cost data from 234 elderly patients were collected quarterly over a 1-year period. Different strategies for incomplete data collection were compared with complete data collection. The sample size calculation was modified in response to elasticity of variance. Results Resource categories suitable for incomplete data collection were physiotherapy, ambulatory clinic in hospital, medication, consultations, outpatient nursing service and paid household help. Cost estimation from complete and incomplete data collection showed no difference when omitting information from one quarter. When omitting information from two quarters, costs were underestimated by 3.9% to 4.6%. With respect to the observed increased standard deviation, a larger sample size would be required, increased by 3%. Nevertheless, more time was saved than extra time would be required for additional patients. Conclusion Cost data can be collected efficiently by reducing the frequency of data collection. This can be achieved by incomplete data collection for shortened periods or complete data collection by extending recall windows. In our analysis, cost estimates per year for ambulatory healthcare and non-healthcare services in terms of three data collections was as valid and accurate as a four complete data collections. In contrast, data on hospitalisation, rehabilitation stays and care insurance benefits should be collected for the entire target period, using extended recall windows. When applying the method of incomplete data collection, sample size calculation has

Factors associated with interest in novel interfaces for upper limb prosthesis control

PubMed Central

Engdahl, Susannah M.; Chestek, Cynthia A.; Kelly, Brian; Davis, Alicia

2017-01-01

Background Surgically invasive interfaces for upper limb prosthesis control may allow users to operate advanced, multi-articulated devices. Given the potential medical risks of these invasive interfaces, it is important to understand what factors influence an individual’s decision to try one. Methods We conducted an anonymous online survey of individuals with upper limb loss. A total of 232 participants provided personal information (such as age, amputation level, etc.) and rated how likely they would be to try noninvasive (myoelectric) and invasive (targeted muscle reinnervation, peripheral nerve interfaces, cortical interfaces) interfaces for prosthesis control. Bivariate relationships between interest in each interface and 16 personal descriptors were examined. Significant variables from the bivariate analyses were then entered into multiple logistic regression models to predict interest in each interface. Results While many of the bivariate relationships were significant, only a few variables remained significant in the regression models. The regression models showed that participants were more likely to be interested in all interfaces if they had unilateral limb loss (p ≤ 0.001, odds ratio ≥ 2.799). Participants were more likely to be interested in the three invasive interfaces if they were younger (p < 0.001, odds ratio ≤ 0.959) and had acquired limb loss (p ≤ 0.012, odds ratio ≥ 3.287). Participants who used a myoelectric device were more likely to be interested in myoelectric control than those who did not (p = 0.003, odds ratio = 24.958). Conclusions Novel prosthesis control interfaces may be accepted most readily by individuals who are young, have unilateral limb loss, and/or have acquired limb loss However, this analysis did not include all possible factors that may have influenced participant’s opinions on the interfaces, so additional exploration is warranted. PMID:28767716

Factors associated with interest in novel interfaces for upper limb prosthesis control.

PubMed

Engdahl, Susannah M; Chestek, Cynthia A; Kelly, Brian; Davis, Alicia; Gates, Deanna H

2017-01-01

Surgically invasive interfaces for upper limb prosthesis control may allow users to operate advanced, multi-articulated devices. Given the potential medical risks of these invasive interfaces, it is important to understand what factors influence an individual's decision to try one. We conducted an anonymous online survey of individuals with upper limb loss. A total of 232 participants provided personal information (such as age, amputation level, etc.) and rated how likely they would be to try noninvasive (myoelectric) and invasive (targeted muscle reinnervation, peripheral nerve interfaces, cortical interfaces) interfaces for prosthesis control. Bivariate relationships between interest in each interface and 16 personal descriptors were examined. Significant variables from the bivariate analyses were then entered into multiple logistic regression models to predict interest in each interface. While many of the bivariate relationships were significant, only a few variables remained significant in the regression models. The regression models showed that participants were more likely to be interested in all interfaces if they had unilateral limb loss (p ≤ 0.001, odds ratio ≥ 2.799). Participants were more likely to be interested in the three invasive interfaces if they were younger (p < 0.001, odds ratio ≤ 0.959) and had acquired limb loss (p ≤ 0.012, odds ratio ≥ 3.287). Participants who used a myoelectric device were more likely to be interested in myoelectric control than those who did not (p = 0.003, odds ratio = 24.958). Novel prosthesis control interfaces may be accepted most readily by individuals who are young, have unilateral limb loss, and/or have acquired limb loss However, this analysis did not include all possible factors that may have influenced participant's opinions on the interfaces, so additional exploration is warranted.

Diagnosis of nutrient imbalances with vector analysis in agroforestry systems.

PubMed

Isaac, Marney E; Kimaro, Anthony A

2011-01-01

Agricultural intensification has had unintended environmental consequences, including increased nutrient leaching and surface runoff and other agrarian-derived pollutants. Improved diagnosis of on-farm nutrient dynamics will have the advantage of increasing yields and will diminish financial and environmental costs. To achieve this, a management support system that allows for site-specific rapid evaluation of nutrient production imbalances and subsequent management prescriptions is needed for agroecological design. Vector diagnosis, a bivariate model to depict changes in yield and nutritional response simultaneously in a single graph, facilitates identification of nutritional status such as growth dilution, deficiency, sufficiency, luxury uptake, and toxicity. Quantitative data from cocoa agroforestry systems and pigeonpea intercropping trials in Ghana and Tanzania, respectively, were re-evaluated with vector analysis. Relative to monoculture, biomass increase in cocoa ( L.) under shade (35-80%) was accompanied by a 17 to 25% decline in P concentration, the most limiting nutrient on this site. Similarly, increasing biomass with declining P concentrations was noted for pigeonpea [ (L). Millsp.] in response to soil moisture availability under intercropping. Although vector analysis depicted nutrient responses, the current vector model does not consider non-nutrient resource effects on growth, such as ameliorated light and soil moisture, which were particularly active in these systems. We revisit and develop vector analysis into a framework for diagnosing nutrient and non-nutrient interactions in agroforestry systems. Such a diagnostic technique advances management decision-making by increasing nutrient precision and reducing environmental issues associated with agrarian-derived soil contamination. American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.

Neighborhood Disorder and Paternal Involvement of Nonresident and Resident Fathers

ERIC Educational Resources Information Center

Zhang, Saijun; Fuller, Tamara

2012-01-01

Using data of 775 nonresident father families and 1,407 resident father families from the Fragile Families and Child Wellbeing Study, this study examined whether neighborhood disorder was associated with fathers' supportive involvement in child care. Bivariate analysis indicated that mothers and children of nonresident father families were more…

Understanding the Relationship of Trauma, Substance Use, and Resilience among Religiously Affiliated University Students

ERIC Educational Resources Information Center

Burnett, Harvey J.; Witzel, Kristen; Allers, Kylah; McBride, Duane C.

2016-01-01

This study examined patterns of association between experiencing 12 traumatic life events, resilience, and substance use at a conservative church-affiliated university. The authors used data (N = 278) from a Health Risk and Protective Factors Study that was conducted during the 2012 spring semester. Initial bivariate analysis indicated several…

Impact of Implantable Transvenous Device Lead Location on Severity of Tricuspid Regurgitation

PubMed Central

Addetia, Karima; Maffessanti, Francesco; Mediratta, Anuj; Yamat, Megan; Weinert, Lynn; Moss, Joshua D.; Nayak, Hemal M.; Burke, Martin C.; Patel, Amit R.; Kruse, Eric; Jeevanandam, Valluvan; Mor-Avi, Victor; Lang, Roberto M.

2015-01-01

Background Implantable device leads can cause tricuspid regurgitation (TR) when they interfere with leaflet motion. The aim of this study was to determine whether lead-leaflet interference is associated with TR severity, independent of other causative factors of functional TR. Methods A total of 100 patients who underwent transthoracic two-dimensional and three-dimensional (3D) echocardiography of the tricuspid valve before and after lead placement were studied. Lead position was classified on 3D echocardiography as leaflet-interfering or noninterfering. TR severity was estimated by vena contracta (VC) width. Logistic regression analysis was used to identify factors associated with postdevice TR, including predevice VC width, right ventricular end-diastolic and end-systolic areas, fractional area change, right atrial size, tricuspid annular diameter, TR gradient, device lead age, and presence or absence of lead interference. Odds ratios were used to describe the association with moderate (VC width ≥ 0.5 cm) or severe (VC width ≥ 0.7 cm) TR, separately, using bivariate and stepwise multivariate logistic regression analysis. Results Forty-five of 100 patients showed device lead tricuspid valve leaflet interference. The septal leaflet was the most commonly affected (23 patients). On bivariate analysis, preimplantation VC width, right atrial size, tricuspid annular diameter, and lead-leaflet interference were significantly associated with postdevice TR. On multivariate analysis, preimplantation VC width and the presence of an interfering lead were independently associated with postdevice TR. Furthermore, the presence of an interfering lead was the only factor associated with TR worsening, increasing the likelihood of developing moderate or severe TR by 15- and 11-fold, respectively. Conclusion Lead-leaflet interference as seen on 3D echocardiography is associated with TR after device lead placement, suggesting that 3D echocardiography should be used to assess for

Clients' reasons for prenatal ultrasonography in Ibadan, South West of Nigeria

PubMed Central

Enakpene, Christopher A; Morhason-Bello, Imran O; Marinho, Anthony O; Adedokun, Babatunde O; Kalejaiye, Adegoke O; Sogo, Kayode; Gbadamosi, Sikiru A; Awoyinka, Babatunde S; Enabor, Obehi O

2009-01-01

Background Prenatal ultrasonography has remained a universal tool but little is known especially from developing countries on clients' reasons for desiring it. Then aim was to determine the reasons why pregnant women will desire a prenatal ultrasound. Methods It was a cross-sectional survey of consecutive 222 women at 2 different ultrasonography facilities in Ibadan, South-west Nigeria. Results The mean age of the respondents was 30.1 ± 4.5 years. The commonest reason for requesting for prenatal ultrasound scans was to check for fetal viability in 144 women (64.7%) of the respondents, followed by fetal gender determination in 50 women (22.6%. Other reasons were to check for number of fetuses, fetal age and placental location. Factors such as younger age, artisans profession and low level of education significantly influenced the decision to check for fetal viability on bivariate analysis but all were not significant on multivariate analysis. Concerning fetal gender determination, older age, Christianity, occupation and gravidity were significant on bivariate analysis, however, only gravidity and occupation remained significant independent predictor on logistic regression model. Women with less than 3 previous pregnancies were about 4 times more likely to request for fetal sex determination than women with more than 3 previous pregnancies, (OR 3.8 95%CI 1.52 – 9.44). The professionals were 7 times more likely than the artisans to request to find out about their fetal sex, (OR 7.0 95%CI 1.47 – 333.20). Conclusion This study shows that Nigerian pregnant women desired prenatal ultrasonography mostly for fetal viability, followed by fetal gender determination. These preferences were influenced by their biosocial variables. PMID:19426518

Exponential Family Functional data analysis via a low-rank model.

PubMed

Li, Gen; Huang, Jianhua Z; Shen, Haipeng

2018-05-08

In many applications, non-Gaussian data such as binary or count are observed over a continuous domain and there exists a smooth underlying structure for describing such data. We develop a new functional data method to deal with this kind of data when the data are regularly spaced on the continuous domain. Our method, referred to as Exponential Family Functional Principal Component Analysis (EFPCA), assumes the data are generated from an exponential family distribution, and the matrix of the canonical parameters has a low-rank structure. The proposed method flexibly accommodates not only the standard one-way functional data, but also two-way (or bivariate) functional data. In addition, we introduce a new cross validation method for estimating the latent rank of a generalized data matrix. We demonstrate the efficacy of the proposed methods using a comprehensive simulation study. The proposed method is also applied to a real application of the UK mortality study, where data are binomially distributed and two-way functional across age groups and calendar years. The results offer novel insights into the underlying mortality pattern. © 2018, The International Biometric Society.

Radar Shows Evidence of Seas

NASA Image and Video Library

2007-03-13

This movie, comprised of several detailed images taken by Cassini radar instrument, shows bodies of liquid near Titan north pole. These images show that many of the features commonly associated with lakes on Earth

An Analysis of Terrestrial and Aquatic Environmental Controls of Riverine Dissolved Organic Carbon in the Conterminous United States

DOE PAGES

Yang, Qichun; Zhang, Xuesong; Xu, Xingya; ...

2017-05-29

Riverine carbon cycling is an important, but insufficiently investigated component of the global carbon cycle. Analyses of environmental controls on riverine carbon cycling are critical for improved understanding of mechanisms regulating carbon processing and storage along the terrestrial-aquatic continuum. Here, we compile and analyze riverine dissolved organic carbon (DOC) concentration data from 1402 United States Geological Survey (USGS) gauge stations to examine the spatial variability and environmental controls of DOC concentrations in the United States (U.S.) surface waters. DOC concentrations exhibit high spatial variability, with an average of 6.42 ± 6.47 mg C/ L (Mean ± Standard Deviation). In general,more » high DOC concentrations occur in the Upper Mississippi River basin and the Southeastern U.S., while low concentrations are mainly distributed in the Western U.S. Single-factor analysis indicates that slope of drainage areas, wetlands, forests, percentage of first-order streams, and instream nutrients (such as nitrogen and phosphorus) pronouncedly influence DOC concentrations, but the explanatory power of each bivariate model is lower than 35%. Analyses based on the general multi-linear regression models suggest DOC concentrations are jointly impacted by multiple factors. Soil properties mainly show positive correlations with DOC concentrations; forest and shrub lands have positive correlations with DOC concentrations, but urban area and croplands demonstrate negative impacts; total instream phosphorus and dam density correlate positively with DOC concentrations. Notably, the relative importance of these environmental controls varies substantially across major U.S. water resource regions. In addition, DOC concentrations and environmental controls also show significant variability from small streams to large rivers, which may be caused by changing carbon sources and removal rates by river orders. In sum, our results reveal that general multi

Suffering by comparison: Twitter users' reactions to the Victoria's Secret Fashion Show.

PubMed

Chrisler, Joan C; Fung, Kaitlin T; Lopez, Alexandra M; Gorman, Jennifer A

2013-09-01

Social comparison theory suggests that evaluating the self in comparison with others (e.g., peers, celebrities, models) can influence body image. Experimental studies that have tested effects of viewing idealized images in the media often show that women feel worse about themselves after seeing images that illustrate the beauty ideal. Twitter presents a naturally occurring opportunity to study viewers' reactions. An analysis was conducted of 977 tweets sent immediately before and during the 2011 Victoria's Secret Fashion Show that reference the show. Although the majority were idiosyncratic remarks, many tweets contain evidence of upward social comparisons to the fashion models. There were tweets about body image, eating disorders, weight, desires for food or alcohol, and thoughts about self-harm. The results support social comparison theory, and suggest that vulnerable viewers could experience negative affect, or even engage in harmful behaviors, during or after viewing the show or others like it. Copyright © 2013 Elsevier Ltd. All rights reserved.

Spatial Analysis of HIV Positive Injection Drug Users in San Francisco, 1987 to 2005

PubMed Central

Martinez, Alexis N.; Mobley, Lee R.; Lorvick, Jennifer; Novak, Scott P.; Lopez, Andrea M.; Kral, Alex H.

2014-01-01

Spatial analyses of HIV/AIDS related outcomes are growing in popularity as a tool to understand geographic changes in the epidemic and inform the effectiveness of community-based prevention and treatment programs. The Urban Health Study was a serial, cross-sectional epidemiological study of injection drug users (IDUs) in San Francisco between 1987 and 2005 (N = 29,914). HIV testing was conducted for every participant. Participant residence was geocoded to the level of the United States Census tract for every observation in dataset. Local indicator of spatial autocorrelation (LISA) tests were used to identify univariate and bivariate Census tract clusters of HIV positive IDUs in two time periods. We further compared three tract level characteristics (% poverty, % African Americans, and % unemployment) across areas of clustered and non-clustered tracts. We identified significant spatial clustering of high numbers of HIV positive IDUs in the early period (1987–1995) and late period (1996–2005). We found significant bivariate clusters of Census tracts where HIV positive IDUs and tract level poverty were above average compared to the surrounding areas. Our data suggest that poverty, rather than race, was an important neighborhood characteristic associated with the spatial distribution of HIV in SF and its spatial diffusion over time. PMID:24722543

Patient satisfaction with intravenous acetaminophen: a pooled analysis of five randomized, placebo-controlled studies in the acute postoperative setting.

PubMed

Apfel, Christian C; Souza, Kimberly; Portillo, Juan; Dalal, Poorvi; Bergese, Sergio D

2015-01-01

Intravenous (IV) acetaminophen has been shown to reduce postoperative pain and opioid consumption, which may lead to increased patient satisfaction. To determine the effect IV acetaminophen has on patient satisfaction, a pooled analysis from methodologically homogenous studies was conducted. We obtained patient-level data from five randomized, placebo-controlled studies in adults undergoing elective surgery in which patient satisfaction was measured using a 4-point categorical rating scale. The primary endpoint was "excellent" satisfaction and the secondary endpoint was "good" or "excellent" satisfaction at 24 hr after first study drug administration. Bivariate analyses were conducted using the chi-square test and Student's t-test and multivariable analyses were conducted using logistic regression analysis. Patients receiving IV acetaminophen were more than twice as likely as those who received placebo to report "excellent" patient satisfaction ratings (32.3% vs. 15.9%, respectively). Of all variables that remained statistically significant in the multivariable analysis (i.e., type of surgery, duration of anesthesia, last pain rating, and opioid consumption), IV acetaminophen had the strongest positive effect on "excellent" patient satisfaction with an odds ratio of 2.76 (95% CI 1.81-4.23). Results for "excellent" or "good" satisfaction were similar. When given as part of a perioperative analgesic regimen, IV acetaminophen was associated with significantly improved patient satisfaction.

Economic impact and market analysis of a special event: The Great New England Air Show

Treesearch

Rodney B. Warnick; David C. Bojanic; Atul Sheel; Apurv Mather; Deepak Ninan

2010-01-01

We conducted a post-event evaluation for the Great New England Air Show to assess its general economic impact and to refine economic estimates where possible. In addition to the standard economic impact variables, we examined travel distance, purchase decision involvement, event satisfaction, and frequency of attendance. Graphic mapping of event visitors' home ZIP...

ASURV: Astronomical SURVival Statistics

NASA Astrophysics Data System (ADS)

Feigelson, E. D.; Nelson, P. I.; Isobe, T.; LaValley, M.

2014-06-01

ASURV (Astronomical SURVival Statistics) provides astronomy survival analysis for right- and left-censored data including the maximum-likelihood Kaplan-Meier estimator and several univariate two-sample tests, bivariate correlation measures, and linear regressions. ASURV is written in FORTRAN 77, and is stand-alone and does not call any specialized libraries.

Endobronchial Ultrasound for Nodal Staging of Non-Small Cell Lung Cancer Patients with Radiologically Normal Mediastinum: A Meta-Analysis.

PubMed

El-Osta, Hazem; Jani, Pushan; Mansour, Ali; Rascoe, Philip; Jafri, Syed

2018-04-23

An accurate assessment of the mediastinal lymph nodes status is essential in the staging and treatment planning of potentially resectable non-small cell lung cancer (NSCLC). We performed this meta-analysis to evaluate the role of endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) in detecting occult mediastinal disease in NSCLC with no radiologic mediastinal involvement. The PubMed, Embase, and Cochrane libraries were searched for studies describing the role of EBUS-TBNA in lung cancer patients with radiologically negative mediastinum. The individual and pooled sensitivity, prevalence, negative predictive value (NPV), and diagnostic odds ratio (DOR) were calculated using the random effects model. Metaregression analysis, heterogeneity, and publication bias were also assessed. A total of 13 studies that met the inclusion criteria were included in the meta-analysis. The pooled effect size of the different diagnostic parameters were estimated as follows: prevalence, 12.8% (95% CI, 10.4%-15.7%); sensitivity, 49.5% (95% confidence interval [CI], 36.4%-62.6%); NPV, 93.0% (95% CI, 90.3%-95.0%); and log DOR, 5.069 (95% CI, 4.212-5.925). Significant heterogeneity was noticeable for the sensitivity, disease prevalence, and NPV, but not observed for log DOR. Publication bias was detected for sensitivity, NPV and log DOR but not for prevalence. Bivariate meta-regression analysis showed no significant association between the pooled calculated parameters and the type of anesthesia, imaging utilized to define negative mediastinum, rapid on-site test usage, and presence of bias by QUADAS-2 tool. Interestingly, we observed a greater sensitivity, NPV and log DOR for studies published prior to 2010, and for prospective multicenter studies. Among NSCLC patients with a radiologically normal mediastinum, the prevalence of mediastinal disease is 12.8% and the sensitivity of EBUS-TBNA is 49.5%. Despite the low sensitivity, the resulting NPV of 93.0% for EBUS

Glyceraldehyde-3-phosphate dehydrogenase from Chironomidae showed differential activity towards metals.

PubMed

Chong, Isaac K W; Ho, Wing S

2013-09-01

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is known to interact with different biomolecules and was implicated in many novel cellular activities including programmed cell death, nuclear RNA transport unrelated to the commonly known carbohydrate metabolism. We reported here the purification of GAPDH from Chironomidae larvae (Insecta, Diptera) that showed different biologic activity towards heavy metals. It was inhibited by copper, cobalt nickel, iron and lead but was activated by zinc. The GAPDH was purified by ammonium sulphate fractionation and Chelating Sepharose CL-6B chromatography followed by Blue Sepharose CL-6B chromatography. The 150-kDa tetrameric GAPDH showed optimal activity at pH 8.5 and 37°C. The multiple alignment of sequence of the Chironomidae GAPDH with other known species showed 78 - 88% identity to the conserved regions of the GADPH. Bioinformatic analysis unveils substantial N-terminal sequence similarity of GAPDH of Chironomidae larvae to mammalian GADPHs. However, the GADPH of Chironomidae larvae showed different biologic activities and cytotoxicity towards heavy metals. The GAPDH enzyme would undergo adaptive molecular changes through binding at the active site leading to higher tolerance to heavy metals.

The Attitudes, Needs, and Requirements at End of Life in the Republic of Georgia (Comparative Analysis of Groups of Patients With Cancer and Elders).

PubMed

Chikhladze, Nana; Tebidze, Nino; Chabukiani, Tamar; Chabukiani, Nana; Chkhartishvili, Nikoloz; Jincharadze, Memed; Kordzaia, Dimitri

2018-01-01

In developing a model of palliative care, the attitudes, needs, and requirements of its beneficiaries recognizing the limited remaining life expectancy need to be met. We aimed to map and compare these issues at the end of life in the groups of patients with advanced cancer and elderly individuals. The prospective study based on the analysis of semistructured interviews was conducted. Fifty individuals aged older than 85 and 50 incurable patients with advanced cancer were studied. Transcripts of interviews were analyzed qualitatively (the interviews were divided into logically completed themes, and the compliance of each with one of the levels of Abraham Maslow pyramid was determined) and quantitatively (data comparisons of 2 groups were tested in bivariate analysis using Pearson χ 2 or Fisher exact test. Two-sided significance tests were used; P value of <.05 was deemed significant). It was assumed that 120 themes were relevant to a certain level of Maslow pyramid. Their comparison showed small differences in the narratives of the patients with advanced cancer and elderly individuals aged 85 and older-concerning the past, present, and future terms of lives. In studied themes explicitly prevail the stories that are consistent with satisfaction of the upper levels of the hierarchy of needs and demands of Maslow: social relation (belonging), love, esteem, and transcendence. The attitudes, needs, and requirements at the end of life of the people are basically similar, regardless of what determined the sense of limitation of the remaining life-incurable disease or advanced age.

Modeling rainfall-runoff relationship using multivariate GARCH model

NASA Astrophysics Data System (ADS)

Modarres, R.; Ouarda, T. B. M. J.

2013-08-01

The traditional hydrologic time series approaches are used for modeling, simulating and forecasting conditional mean of hydrologic variables but neglect their time varying variance or the second order moment. This paper introduces the multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) modeling approach to show how the variance-covariance relationship between hydrologic variables varies in time. These approaches are also useful to estimate the dynamic conditional correlation between hydrologic variables. To illustrate the novelty and usefulness of MGARCH models in hydrology, two major types of MGARCH models, the bivariate diagonal VECH and constant conditional correlation (CCC) models are applied to show the variance-covariance structure and cdynamic correlation in a rainfall-runoff process. The bivariate diagonal VECH-GARCH(1,1) and CCC-GARCH(1,1) models indicated both short-run and long-run persistency in the conditional variance-covariance matrix of the rainfall-runoff process. The conditional variance of rainfall appears to have a stronger persistency, especially long-run persistency, than the conditional variance of streamflow which shows a short-lived drastic increasing pattern and a stronger short-run persistency. The conditional covariance and conditional correlation coefficients have different features for each bivariate rainfall-runoff process with different degrees of stationarity and dynamic nonlinearity. The spatial and temporal pattern of variance-covariance features may reflect the signature of different physical and hydrological variables such as drainage area, topography, soil moisture and ground water fluctuations on the strength, stationarity and nonlinearity of the conditional variance-covariance for a rainfall-runoff process.

Looped suture versus stapler device in pediatric laparoscopic appendectomy: a comparative outcomes and intraoperative cost analysis.

PubMed

Parikh, Punam P; Tashiro, Jun; Wagenaar, Amy E; Curbelo, Miosotys; Perez, Eduardo A; Neville, Holly L; Hogan, Anthony R; Sola, Juan E

2018-04-01

Appendiceal ligation during pediatric laparoscopic appendectomy (LA) may be performed using looped suture versus stapler. Controversy regarding the utility of either method exists. Clinical outcomes and cost analysis of LA with both methods were compared. All pediatric LA were performed from fiscal years 2013 and 2014 by two pediatric surgeons. While one surgeon used looped suture, the other used stapler exclusively. chi-Square tests were performed to analyze associations. Two hundred thirty-eight cases were analyzed where looped suture versus stapler LA was performed in 46% and 54% of patients, respectively. Operating room costs were $317.10 and $707.12/person for looped suture and stapler LA, respectively (P<0.0001). Difference in cost of $390.02/person was attributed solely to ligation type. On bivariate analysis, rate of in-hospital complications, length of stay, return-to-ER and readmission within 30 days did not significantly differ between groups. A comparative analysis of looped suture versus stapler device during LA for pediatric appendicitis revealed that postoperative complications, length of stay, ER visits and readmissions were not significantly different. Looped suture LA was significantly more cost efficient than stapler LA. In pediatric appendicitis, appendiceal ligation during LA may be performed safely and cost effectively with looped suture versus stapler. Cost effectiveness LEVEL OF EVIDENCE: III. Copyright © 2017 Elsevier Inc. All rights reserved.

A micro-epidemiological analysis of febrile malaria in Coastal Kenya showing hotspots within hotspots

PubMed Central

Bejon, Philip; Williams, Thomas N; Nyundo, Christopher; Hay, Simon I; Benz, David; Gething, Peter W; Otiende, Mark; Peshu, Judy; Bashraheil, Mahfudh; Greenhouse, Bryan; Bousema, Teun; Bauni, Evasius; Marsh, Kevin; Smith, David L; Borrmann, Steffen

2014-01-01

Malaria transmission is spatially heterogeneous. This reduces the efficacy of control strategies, but focusing control strategies on clusters or ‘hotspots’ of transmission may be highly effective. Among 1500 homesteads in coastal Kenya we calculated (a) the fraction of febrile children with positive malaria smears per homestead, and (b) the mean age of children with malaria per homestead. These two measures were inversely correlated, indicating that children in homesteads at higher transmission acquire immunity more rapidly. This inverse correlation increased gradually with increasing spatial scale of analysis, and hotspots of febrile malaria were identified at every scale. We found hotspots within hotspots, down to the level of an individual homestead. Febrile malaria hotspots were temporally unstable, but 4 km radius hotspots could be targeted for 1 month following 1 month periods of surveillance. DOI: http://dx.doi.org/10.7554/eLife.02130.001 PMID:24843017

A micro-epidemiological analysis of febrile malaria in Coastal Kenya showing hotspots within hotspots.

PubMed

Bejon, Philip; Williams, Thomas N; Nyundo, Christopher; Hay, Simon I; Benz, David; Gething, Peter W; Otiende, Mark; Peshu, Judy; Bashraheil, Mahfudh; Greenhouse, Bryan; Bousema, Teun; Bauni, Evasius; Marsh, Kevin; Smith, David L; Borrmann, Steffen

2014-04-24

Malaria transmission is spatially heterogeneous. This reduces the efficacy of control strategies, but focusing control strategies on clusters or 'hotspots' of transmission may be highly effective. Among 1500 homesteads in coastal Kenya we calculated (a) the fraction of febrile children with positive malaria smears per homestead, and (b) the mean age of children with malaria per homestead. These two measures were inversely correlated, indicating that children in homesteads at higher transmission acquire immunity more rapidly. This inverse correlation increased gradually with increasing spatial scale of analysis, and hotspots of febrile malaria were identified at every scale. We found hotspots within hotspots, down to the level of an individual homestead. Febrile malaria hotspots were temporally unstable, but 4 km radius hotspots could be targeted for 1 month following 1 month periods of surveillance.DOI: http://dx.doi.org/10.7554/eLife.02130.001. Copyright © 2014, Bejon et al.

Immunohistochemical and Image Analysis-Based Study Shows That Several Immune Checkpoints are Co-expressed in Non-Small Cell Lung Carcinoma Tumors.

PubMed

Parra, Edwin Roger; Villalobos, Pamela; Zhang, Jiexin; Behrens, Carmen; Mino, Barbara; Swisher, Stephen; Sepesi, Boris; Weissferdt, Annika; Kalhor, Neda; Heymach, John Victor; Moran, Cesar; Zhang, Jianjun; Lee, Jack; Rodriguez-Canales, Jaime; Gibbons, Don; Wistuba, Ignacio I

2018-06-01

The understanding of immune checkpoint molecules' co-expression in non-small cell lung carcinoma (NCLC) is important to potentially design combinatorial immunotherapy approaches. We studied 225 formalin-fixed, paraffin-embedded tumor tissues from stage I-III NCLCs - 142 adenocarcinomas (ADCs) and 83 squamous cell carcinomas (SCCs) - placed in tissue microarrays. Nine immune checkpoint markers were evaluated; four (programmed death ligand 1 [PD-L1], B7-H3, B7-H4, and indoleamine 2,3-dioxygenase 1 [IDO-1]) expressed predominantly in malignant cells (MCs) and five (inducible T cell costimulator, V-set immunoregulatory receptor, T-cell immunoglobulin mucin family member 3, lymphocyte activating 3, and OX40) expressed mostly in stromal tumor-associated inflammatory cells (TAICs). All markers were examined using a quantitative image analysis and correlated with clinicopathologic features, TAICs, and molecular characteristics. Using above the median value as positive expression in MCs and high density of TAICs expressing those markers, we identified higher expression of immune checkpoints in SCC than ADC. Common simultaneous expression by MCs was PD-L1 + B7-H3 + IDO-1 in ADC and PD-L1 + B7-H3, or B7-H3 + B7-H4, in SCC. TAICs expressing checkpoint were significantly higher in current smokers than in never smokers. Almost all the immune checkpoint markers showed positive correlation with TAICs expressing inflammatory cell markers. KRAS-mutant ADC specimens showed higher expression of PD-L1 in MCs and of B7-H3, T-cell immunoglobulin mucin family member 3, and IDO-1 in TAICs than wild type. Kaplan-Meier survival curves showed worse prognosis in ADC patients with higher B7-H4 expression by MCs. We found frequent immunohistochemical co-expression of immune checkpoints in surgically resected NCLC tumors and correlated with tumor histology, smoking history, tumor size, and the density of inflammatory cells and tumor mutational status. Copyright © 2018 International

Evolution Analysis of the Aux/IAA Gene Family in Plants Shows Dual Origins and Variable Nuclear Localization Signals.

PubMed

Wu, Wentao; Liu, Yaxue; Wang, Yuqian; Li, Huimin; Liu, Jiaxi; Tan, Jiaxin; He, Jiadai; Bai, Jingwen; Ma, Haoli

2017-10-08

The plant hormone auxin plays pivotal roles in many aspects of plant growth and development. The auxin/indole-3-acetic acid (Aux/IAA) gene family encodes short-lived nuclear proteins acting on auxin perception and signaling, but the evolutionary history of this gene family remains to be elucidated. In this study, the Aux/IAA gene family in 17 plant species covering all major lineages of plants is identified and analyzed by using multiple bioinformatics methods. A total of 434 Aux/IAA genes was found among these plant species, and the gene copy number ranges from three ( Physcomitrella patens ) to 63 ( Glycine max ). The phylogenetic analysis shows that the canonical Aux/IAA proteins can be generally divided into five major clades, and the origin of Aux/IAA proteins could be traced back to the common ancestor of land plants and green algae. Many truncated Aux/IAA proteins were found, and some of these truncated Aux/IAA proteins may be generated from the C-terminal truncation of auxin response factor (ARF) proteins. Our results indicate that tandem and segmental duplications play dominant roles for the expansion of the Aux/IAA gene family mainly under purifying selection. The putative nuclear localization signals (NLSs) in Aux/IAA proteins are conservative, and two kinds of new primordial bipartite NLSs in P. patens and Selaginella moellendorffii were discovered. Our findings not only give insights into the origin and expansion of the Aux/IAA gene family, but also provide a basis for understanding their functions during the course of evolution.

Evolution Analysis of the Aux/IAA Gene Family in Plants Shows Dual Origins and Variable Nuclear Localization Signals

PubMed Central

Wu, Wentao; Liu, Yaxue; Wang, Yuqian; Li, Huimin; Liu, Jiaxi; Tan, Jiaxin; He, Jiadai; Bai, Jingwen

2017-01-01

The plant hormone auxin plays pivotal roles in many aspects of plant growth and development. The auxin/indole-3-acetic acid (Aux/IAA) gene family encodes short-lived nuclear proteins acting on auxin perception and signaling, but the evolutionary history of this gene family remains to be elucidated. In this study, the Aux/IAA gene family in 17 plant species covering all major lineages of plants is identified and analyzed by using multiple bioinformatics methods. A total of 434 Aux/IAA genes was found among these plant species, and the gene copy number ranges from three (Physcomitrella patens) to 63 (Glycine max). The phylogenetic analysis shows that the canonical Aux/IAA proteins can be generally divided into five major clades, and the origin of Aux/IAA proteins could be traced back to the common ancestor of land plants and green algae. Many truncated Aux/IAA proteins were found, and some of these truncated Aux/IAA proteins may be generated from the C-terminal truncation of auxin response factor (ARF) proteins. Our results indicate that tandem and segmental duplications play dominant roles for the expansion of the Aux/IAA gene family mainly under purifying selection. The putative nuclear localization signals (NLSs) in Aux/IAA proteins are conservative, and two kinds of new primordial bipartite NLSs in P. patens and Selaginella moellendorffii were discovered. Our findings not only give insights into the origin and expansion of the Aux/IAA gene family, but also provide a basis for understanding their functions during the course of evolution. PMID:28991190

Children's Understanding of Showing Off.

ERIC Educational Resources Information Center

Bennett, Mark; Yeeles, Caroline

1990-01-01

Interviews 46 British children, ages 8 to 11, to test their understanding of showing off. Confirms prediction that younger childrens' understanding of motivation for showing off is based on psychological determinants and that 11-year-olds' understanding focuses on interpersonal determinants. Also discusses children's understanding of emotional…

Hey Teacher, Your Personality's Showing!

ERIC Educational Resources Information Center

Paulsen, James R.

1977-01-01

A study of 30 fourth, fifth, and sixth grade teachers and 300 of their students showed that a teacher's age, sex, and years of experience did not relate to students' mathematics achievement, but that more effective teachers showed greater "freedom from defensive behavior" than did less effective teachers. (DT)

Planning a Successful Tech Show

ERIC Educational Resources Information Center

Nikirk, Martin

2011-01-01

Tech shows are a great way to introduce prospective students, parents, and local business and industry to a technology and engineering or career and technical education program. In addition to showcasing instructional programs, a tech show allows students to demonstrate their professionalism and skills, practice public presentations, and interact…